COMPUTER SCIENCE HIGHLIGHTS 2020 McGregor Computer Science Center The future location of the Computer Science Department is rising from what was once a parking lot on the corner of Dartmouth Ave. and Platt Blvd. The second and third floors of the McGregor Computer Science Center will provide a much-needed new home for the rapidly growing department. The new space will expand the department’s ability to perform collaboratively not only across all departments at HMC but also with faculty and students from across the 5Cs and with industry and educational institutions across the country. Students majoring in some form of CS now outnumber engineering majors on campus. Twenty-four percent of all HMC-declared majors enrolled through the end of the spring semester were CS majors; another 21% were CS-math or math-comp-bio majors, making some variation of computer science the most popular major. (Engineering majors make up 31% of the student body.) In addition, the number of non-HMC students taking courses and majoring in CS at HMC has tripled. But the high demand for computer science classes has placed a strain on the department, limiting class registrations and causing frustration among CS majors and others. Construction of the McGregor Center will help offset this demand by creating room to grow from 16 to 25 faculty positions over time and will include faculty offices, Clinic and project studios, teaching and research laboratories and collaboration spaces. The larger space dedicated for computing will allow more contiguous CS space, bringing together previously fragmented elements, such as student project space, Clinic Program work areas and computer labs. While the College purchased its first computer in 1962 (the IBM 1620) and offered some classes in the late 1960s, it wasn’t until 1981 that the College hired Mike Erlinger
Blvd. A rendering of the McGregor Center as seen from Platt
to investigate whether the discipline of computer science should develop into an existing department or as a new administrative entity. Computer science became an academic department in 1984, Bob Keller was hired as its first chair in 1991 and, by 1992, the College graduated its first CS majors, Andrew Gray and Clifford Stein. In 1994, Jill E. Flansburg became the first woman to graduate with an HMC CS degree. Now, dozens of students graduate in CS each year and almost half of them are women. The computer science major has grown from 12% female in 2005 to nearly 50% female in 2019. According to the National Science Foundation, nationally women earned only 18% of bachelor’s degrees in computer science in 2015. Made possible by members of the HMC Board of Trustees, foundations, alumni, parents and friends—including a leadership gift from HMC Trustee Laurie J. Girand and
her husband, Scott A. McGregor—the new building will include a makerspace (a studio designed for hands-on, creative activities) and a machine shop, among other features. “The College is heading in a direction of further prioritizing inclusivity, community and preparedness for the next generation of students,” ASHMC President Kyle Grace ’21 said in a speech at the groundbreaking. “As a computer science major here at Mudd, I am excited to see our incredible computer science program become even larger.”
Watch the building’s progress at: hmc.edu/McGregor
DEPARTMENT NEWS
New to the Department Faculty members at Harvey Mudd College develop innovative pedagogies, offer opportunities for student research, engage students in experiential learning and challenge students to develop an informed world view. Meet four of the newest CS faculty members who pledge to continue this tradition. Lucas Bang earned a PhD in computer science
Xanda Schofield ’13, (computer science and
from the University of California Santa Barbara, an M.S. in computer science from the University of Nevada, Las Vegas, and a B.S. in computer science and mathematics from UNLV. His work focuses on software verification and formal methods for security.
mathematics) assistant professor, earned a PhD in computer science from Cornell University in May 2019. She has been a research intern at Microsoft Research and a lecturer and mentor at Cornell. Her specialty is designing easy-to-use tools for large-scale corpus text mining, with a focus on distributional semantic models.
George Montañez holds a PhD in machine
learning from Carnegie Mellon University, an M.S. in computer science from Baylor University and a B.S. in computer science from the University of California, Riverside. He was an NSF Graduate Research Fellow and a Ford Foundation Predoctoral Fellow. He twice served as an intern at Microsoft Research and once at Yahoo! Labs. He has worked as a software engineer and full-stack developer. His research lies at the intersection of computer science, algorithmic search and mathematics.
Erin Talvitie, associate professor, most recently
taught at Franklin & Marshall College (2010– 2019). Talvitie, who holds a PhD in computer science from the University of Michigan, applies machine learning to artificial intelligence, working to create artificial autonomous agents that can act flexibly and competently in unknown environments.
Faculty and Staff Updates Tenure and promotion to the rank of associate professor Julie Medero researches
George Montañez does
Surani Gunasena, Clinic
research that lies at the intersection of machine learning, information theory and algorithmic search.
coordinator, was hired in January 2020 to help facilitate Computer Science Clinic projects.
natural language processing, machine learning and educational applications of language technology.
CS Staff
Beth Trushkowsky specializes in database systems and human computation, also known as crowdsourcing.
Tim Buchheim ’01 (CS), systems administrator, worked as a programmer at the USC Information Sciences Institute for two years before being hired at HMC in 2003.
Approved for first twoyear reappointment Lucas Bang focuses on
software verification and formal methods for security.
Joyce Greene J.D.,
administrative assistant, worked four years in the engineering department before moving to computer science in 2001.
HARVEY MUDD COLLEGE | COMPUTER SCIENCE HIGHLIGHTS 2020
Kevin Herrera ’17 (CS), course
coordinator, has been on staff since graduating. He organizes grading sessions and maintains a system of auto graders for smooth assignment grading. Kathy Ryan, administrative assistant, was hired in 2018 after working as an admissions office coordinator at Claremont School of Theology.
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DEPARTMENT NEWS
In Memoriam: Robert (Bob) Keller
We celebrate the life of Robert (Bob) Keller, who died Sept. 13. Bob was an internationally recognized computer scientist with corporate and academic experience as a technical leader, researcher, educator and administrator. Bob joined the College’s computer science faculty and became chair of the newly formed department in 1991, following Bill Purves
and Mike Erlinger, who chaired the combined biology and CS departments prior to his arrival. The new CS department graduated its first CS majors in 1992. As a professor of computer science, Bob specialized in intelligent music software, programming languages, neural networks and genetic programming and is known for his work on formal models, verification, functional languages and distributed graph reduction architectures. A talented jazz musician who played trumpet and piano, Bob organized student performances for many years as part of his Jazz Improvisation class. He developed a music notation software program—dubbed the Improvisation Advisor, or “Impro-Visor”—that helps jazz musicians learn how to improvise jazz music. The free, open-source software was released in 2006, and Bob’s research teams continue to develop it. Impro-Visor has a growing user community of more than 7,500 around the world. In addition to jazz improvisation, Bob taught courses on artificial intelligence, neural networks, computability and logic, computational creativity, software development, parallel and real-time computing, and databases. He has served as an advisor for the Clinic Program as well as Computer Science Clinic director.
HARVEY MUDD COLLEGE | COMPUTER SCIENCE HIGHLIGHTS 2020
For many years, Bob coached students participating in the Association for Computing Machinery International Programming contest. He has the distinction of being the coach of the winning 1997 world finals team of Brian Carnes ’97, Brian Johnson ’98, Kevin Watkins ’98 and Dominic Mazzoni ’99. HMC is the only undergraduate institution—and the last U.S. institution—to have won the contest. In addition to his work in academia, Bob held a position at NASA’s Jet Propulsion Laboratory for more than 10 years. He was also a member of the technical staff at the Aerospace Corporation and vice-president of research and development at Quintus Computer Systems. Bob is survived by his wife, Noel, sons, Franz and Patrick, sister, Irma Ward, brother, Dennis Keller, and several nieces and nephews. The family requests that contributions in Bob’s honor be made to the Jazz Education Network’s Scholarship Program the American Brain Tumor Association, and the Sierra Club Foundation. ead more about Bob, and share a R remembrance at hmc.edu/in-memoriam/ bob-keller.
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DEPARTMENT NEWS
How Educational Partnerships With Industry Benefit Students and Companies: The Clinic Program In her Nov. 1, 2019 Forbes blog post, President Maria Klawe asked two Clinic sponsor liaisons, Aaron Gable, a software engineer for Google Chrome, and Edward Vander Bilt, innovation leader in information technology for Steelcase Inc., to talk about their experiences with the Computer Science Clinic Program. Maria Klawe: How did you learn about the
Harvey Mudd Clinic Program? Edward Vander Bilt: We were made aware
of the Clinic Program through computer science professor Jim Boerkoel, whom we had previously done collaboration work with while he was a postdoc researcher at MIT. Jim knew about the challenges we faced within manufacturing and thought that Clinic was a good model for helping Steelcase to explore new solutions to manufacturing challenges. Aaron Gable: I graduated from Harvey Mudd in 2012 as a joint computer science and math major. The Clinic Program was part of why I’d selected Harvey Mudd as a freshman in the first place. I ended up working on LAMMPS, a finite-element + molecular dynamics simulator, for Sandia National Lab. The experience was certainly a good one overall, despite (or perhaps because of) the usual difficulties of learning to work as a team, communicating with remote liaisons, and diving into a large and complex codebase. Klawe: What can you tell me about the Clinic project for which you were a liaison? Vander Bilt: We have been involved in four previous Clinics at Harvey Mudd, with the fifth starting last month, all related to the same topic of how to use computer vision and machine learning to enhance our quality control systems within our wood product business. Gable: The Chromium Project is the opensource project which powers the Chromium and Chrome web browsers, as well as Chrome OS, Opera, and a variety of other browsers and products. One of the difficulties that users frequently encounter is the large amount of memory (RAM) that Chrome consumes; the high memory usage of any given web page is exacerbated by the tabbed-browsing model, in which a user may have dozens of tabs open, each using a large amount of memory on its own. The project was to investigate and
prototype a system by which inactive tabs could have their entire state—web content, scroll position, partially-filled forms, JavaScript execution, and more—frozen and saved to the hard drive so that all of that memory could be freed up for use by other tabs. And, of course, the tabs would need to be able to be restored from disk as well. Klawe: What skills did you see the students gaining during the project? Vander Bilt: It seems that most of the students had not previously been exposed to manufacturing industrial systems and through Clinic learned much about how a large manufacturing operation works and the challenges that are faced. Overall, they gained real-world experience that should make them better prepared as they continue their career paths beyond Harvey Mudd. Gable: Clinic gives students opportunities to experience things that most internships don’t: leading a team, remote work and heaps of ambiguity. Not all of these are skills are required in all software engineering roles, but they are skills that are good to cultivate regardless, and good to know whether or not you naturally excel at them. Klawe: What kind of impact did the program have on your company? Vander Bilt: The work the Clinic team accomplished provided Steelcase with a significant leap forward in a new way of leveraging technology to enhance our processes. The team did a great job of quickly coming up to speed with the challenge and the nuisances of working with a natural product
HARVEY MUDD COLLEGE | COMPUTER SCIENCE HIGHLIGHTS 2020
such as wood. We knew with certainty that this team hit on something significant. Clinic has benefited Steelcase in a variety of ways. The first, of course, is the work product that the teams produced and prototypes they delivered. These have led to new production systems and processes within our quality control. This has resulted in both cost savings and waste reduction, playing right into the company’s sustainability strategy, which seeks to improve environmental, economic and social aspects of our company. Lastly, it has provided an excellent resource to challenge our own internal thinking and bring fresh outside thinking into our company. Gable: I felt that the project was very successful. The team learned about the guts of Chrome, came to understand its multiprocess model and communication, dissected its security boundaries, and built a prototype implementation of the save-and-restore feature. In the process of doing so, they discovered two key facts: restoring an entire tab from disk can be very slow, and doing so requires breaking Chrome’s security model in unacceptable ways. As a result, we decided not to incorporate the feature into Chrome itself. However, the project was a very successful demonstration of the capabilities and limits of such a system and allowed the team to make a very informed decision. For the full interview, see the Nov. 1, 2019, Forbes blog post at bit.ly/349rigc
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FEATURE
A Class in Stitches Six years of teaching Data Structures and Program Development (aka CS70) has taught Professor Julie Medero something interesting about her students. Computer science students are a little jealous of their engineering counterparts, who often have a physical artifact to show for their efforts. The end result of their hours of work is something tangible. Something more than pixels on a screen. So when Medero witnessed beginning programming students learning to code with ease using the TurtleStitch platform at a computer science education conference and leaving with a piece of embroidery, she saw a solution. TurtleStitch allows users to generate an image for a computerized embroidery machine using a simple block-based educational programming language. Students quickly learn to code, draw and stitch an image on a computer using a turtle icon, giving it commands about direction, angle and distance. Medero knew that if she could put TurtleStitch into use in CS70, her students could create an artifact and gain confidence as coders in the process.
When the call went out from The Claremont Colleges Center for Teaching and Learning for course development proposals, she requested funding for new tactile lab experiences using TurtleStitch that would “give students a
TurtleStitch assignments are engaging for all the students. “We love the fact that it plays a little bit with the gender stereotypes of what this work is,” Medero says. A number of algorithmic ideas
of our goals for CS70 is to help some of the students “ One that we think might not feel like they’re part of computer science—that feel like they don’t belong—to get the message that they do belong in computer science. “ –Professor Julie Medero
different way to interact with the algorithms and data structures they learn in class.” She was awarded money for several sewing machines. Because CS70 has a reputation for being extremely challenging, Medero and fellow CS professor Lucas Bang had been working for years to find ways to make the course less intimidating and more inclusive. And
that show up in math and computer science also appear in the patterns of crochet work, knitting and weaving. “They show up in a whole bunch of things that are traditionally not recognized as being mathematically rigorous, even though there are mathematical ideas in them.” Beyond giving students more confidence and a physical artifact, TurtleStitch teaches CONTINUED ON PAGE 5
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FEATURE
A Class in Stitches
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students valuable lessons about programming. For one thing, they learn to work in a particular order. Users must strategize about what sequence they do things in, a skill required for all coding. “If you go over the same spot 100,000 times, you get this big knot and you break the needle,” says Medero. “Because you have this physicality to it, it actually matters what order you do things in and how many times you go over the same spot. There is actually some really deep algorithms work that can be done in trying to figure out the best order to do things in, and the best path, to cut down on how many
times you go over the same spot to make the same design.” CS70 students are required to find a data set and to somehow visualize it. They bring in data related to a wide range of topics that they care about. One student project illustrates glacial melting climate data. Another plots global plastic production increasing over time. One student used data she collected from a rocket class to show acceleration, velocity and altitude. When the images are ready to be embroidered, Medero and Bang hang out with their students while their projects are being
HARVEY MUDD COLLEGE | COMPUTER SCIENCE HIGHLIGHTS 2020
stitched. “It ends up being a really cool way to get to know them,” she says. “One of our goals for CS70 is to help some of the students that we think might not feel like they’re part of computer science—that feel like they don’t belong—to get the message that they do belong in computer science,” says Medero. “If we can incorporate ways that they can bring in things that they care about—that are a part of them beyond their identity as a computer scientist—then that’s a big win for us.”
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STUDENT NEWS
CRA Awards The Computing Research Association announced its 2020 Outstanding Undergraduate Researcher Awards in December 2019, and two Harvey Mudd College students were commended. Ivy Liu ’20 was selected as a finalist, and Daniel Bashir ’20 earned an honorable mention. The prestigious program recognizes undergraduates at North American colleges and universities who demonstrate outstanding potential in an area of computing research.
Ivy Liu ’20 A joint mathematical and computational biology major, Liu is interested in developing and applying computational methods to facilitate biomedical research. “Integrating computer science with biology has allowed me to see the beauty of theoretical computer science as well as the applications of tools first-hand,” she says. Liu’s research experience includes working with biology professor Catherine McFadden to test the feasibility of using a particular gene to differentiate species within the coral genus Sinularia; working with computer science professors Ran Libeskind-Hadas and Yi-Chieh (Jessica) Wu to improve a dynamic programming algorithm for phylogenetic tree reconciliation; and using deep learning to predict DNA sequences related to the remodeling of epigenetic marks driven by a carcinogen with Dr. Cristian Coarfa and Dr. Cheryl Walker at Baylor College of Medicine. During summer 2019, Liu worked with Dr. Pavel Sumazin at Baylor College of Medicine to develop computational models to infer cell-typespecific expression from bulk tumor expression profiles. She conducted senior thesis research with biology professor Eliot Bush, developing methods to study the evolutionary history of microbes.
“Through these experiences, I have found a love for computational biology, and I look forward to continuing research on fundamental problems as well as developing tools that will aid biomedical research,” she says.
Daniel Bashir ’20 “The main purpose of my team’s research is to develop a quantitative framework for overfitting and underfitting in machine learning,” says Bashir. “Both of these pitfalls are major issues for anyone interested in using machine learning for practical purposes.” Bashir says his research, conducted with other members of computer science professor George Montañez’s AMISTAD Lab at HMC, seeks to answer the question, “given a particular learning algorithm and a particular dataset, by how much will my algorithm overfit or underfit the data?” Having a specific, quantifiable answer to this question for any learning algorithm and set of data would allow a researcher to understand whether or not a particular algorithm is appropriate for a specific task. “I became interested in this research while I was taking a class from Prof. George in machine learning, information theory and search,” says Bashir, a joint computer science and mathematics major. “There’s a fair amount of general advice on how to identify whether learning algorithms are overfitting or underfitting and how to fix those problems, but I think that a more quantified framework for answering these questions has the potential to help practitioners iterate on solutions to different problems using machine learning in a more principled way.”
Students Win Hackathon for Eco-Aware IDE A tool created by Harvey Mudd College students that helps developers consider the environmental impact of their code was the top pick of judges at the recent 2019 SD Hacks intercollegiate hackathon held at UC San Diego. EverGreen, created by Alice Chi ’21, Alfredo Gomez ’21 and Matthew Krager ’21, is an ecoaware integrated development environment (IDE) inspired by the societal issues surrounding the environmental impact of CO2 emissions. The tool captures the environmental impact that a programmer’s code will have by using various metrics, such as the carbon emitted in the average lifespan of a car. They calculated the CO2 emissions for a given piece of code and then generalized emissions for other hardware.
During the three-day event, 143 student teams were tasked with creating a technical solution to an issue related to sustainability, education or health and wellness. The HMC team chose sustainability as their category because they wanted to develop a solution that would help programmers improve the way they code. Particularly effective in evoking emotion about environmental impact were the team’s hand-drawn graphics for animations that gave “an impactful visual representation of the environmental influence of the user’s code.” For their first-place finish, the team received Apple iPads, Bose SoundLink
wireless headphones and a $200 Amazon gift card. The team looks forward to enhancing EverGreen by improving the grammar to suggest more efficient Python code. They note that they would also “like to add support for multiple languages to help all programmers be more environmentally conscious about their code.”
Alice Chi ’21, Alfredo Gomez ’21 and Matthew Krager ’21
HARVEY MUDD COLLEGE | COMPUTER SCIENCE HIGHLIGHTS 2020
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STUDENT NEWS
HMC Teams Place in ICPC Top 20 Programming problems at the 2019 Southern California Regional of the International Collegiate Programming Contest (ICPC) included creating a compact Morse-like code, devising a program to assist builders to bound the number and dimensions of stairs, and removing walls to enable escape from a maze. HMC’s three teams, coached by computer science professor Zach Dodds, all placed in the top 20. The team named List Incomprehension, the College’s highest scoring team, placed fifth (the third consecutive year an HMC team has placed fifth); this was quite a move up from their 30th-place finish last year. It also earned them an invitation to the North American Invitational Programming Contest in March 2020. Team RIP Jacky placed 11th and Team HMC 656 placed 13th out of the 98 teams competing. Each team of three students sharing one computer attempts to solve as many of the 11 complex, real-world programming problems posed within five hours as possible. Team List Incomprehension solved seven problems in just over 19 hours of total time-sincecontest-start; the winning Caltech team solved nine in 16:32:10. The contest fosters creativity, teamwork and innovation in building algorithms and programs and enables students to test their ability to perform under pressure. Team List Incomprehension: Cole Kurashige ’20,
Princewill Okoroafor ’20, Kye Shi ’21 Team RIP Jacky: Evan Johnson ’20, Radon Rosborough ’20,
Owen Gillespie ’20 Team HMC 656: Mathus Leungpathomaram ’23, Joe Santichaivekin ’21, Jarred Allen ’22
Founded in 1977, the ICPC is considered the world’s largest and most prestigious programming competition, involving more than 50,000 participants from over 100 countries. Top teams from regional competitions advance to the final round, where they have the chance to compete against the world’s top college-level coders. Since 2011, the top HMC team at each competition has reached at least ninth place. In 2010, HMC 42 seized first place in the regional competition and represented the College at the World Finals in Orlando, Florida. In 1997, HMC’s team of Brian Carnes ’97, Brian Johnson ’98, Kevin Watkins ’98 and Dominic Mazzoni ’99 won the World Finals. In fact, HMC is the only undergraduate, four-year college to have won the World Finals, joining a list that includes MIT, Caltech, Waterloo, Stanford and Harvard.
HARVEY MUDD COLLEGE | COMPUTER SCIENCE HIGHLIGHTS 2020
Julie Medero
An App for Literacy Education During summer 2018, computer science professor Julie Medero, along with Alfredo Gomez ’21, Alicia Ngo ’20 and Ali Otondo ’20 (aka The A Team), embarked on a project to develop an iOS application that would help children improve their reading skills. The resulting research paper, “Reading KiTTY: Pitch Range as an Indicator of Reading Skill,” was presented at the Widening Natural Language Processing (WiNLP) workshop, held during summer 2019 at the Association for Computational Linguistics conference in Florence, Italy. “This paper is about an analysis of the prosody of children’s oral reading,” says Medero. Prosody refers to the patterns of rhythm and sound in text, for example pitch, reading speed and emotionality. “That means we’re looking at how children of different reading levels use their voices as part of reading out loud. Our lab’s Reading KiTTY project is looking at how elementary-aged children could be guided through the creation of kinetic typography animations that visualize their reading out loud. Kinetic typography is a form of animation that uses size, color and motion of text, along with images, to represent the meaning of a text. It’s popular in music videos and is also commonly used in videos of famous speeches, but we think it has the potential for interesting applications in literacy education, too.” Researchers focus on two aspects: creating the first iteration of the app and exploring how to leverage natural language processing and speech processing in order effectively promote creativity. The paper accepted by WiNLP focuses on their work using pitch range as an indicator for reading skill as they apply machine learning and other computational linguistics techniques. The researchers hope to gauge a student’s reading comprehension through reading speed, emotionality/enthusiasm and the reader’s pause lengths between words.
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STUDENT NEWS
Deep Dive into Robotics Seth Isaacson ’21, Ginger Schmidt ’21, Diana Lin, ’22, Omari Matthews ’21, Kyle Rong ’22 and Daniel Yang ’22 founded the Harvey Mudd Robotics Team (aka MuddSub) in 2018. With support from the Shanahan Student-Directed Project Fund, they designed, built and programmed an autonomous underwater vehicle (AUV) named Alfie, which they entered in the annual RoboNation RoboSub competition in August 2019. Competing against teams representing schools from 14 countries and several U.S. states, Alfie made it to the semifinals. With a bigger team and more funding, MuddSub members hope to enter again—and win.
Daniel Yang ’22, Ginger Schmidt ’21, Seth Isaason ’21 and Kyle Rong ’22
Enrollment Policies Study Wins Best Paper Award As computer science becomes a more popular area of study, institutions have responded by enacting competitive enrollment processes. However, little is An Nguyen ’22 known about the effects of enrollment policies on students’ experiences and retention. Co-authored by computer science professor Colleen Lewis and computer science major
An Nguyen ’22, the paper “Competitive Enrollment Policies in Computing Departments Negatively Predict First-Year Students’ Sense of Belonging, Self-Efficacy, and Perception of Department” won the award for Best Paper (CS education research track) from SIGCSE 2020 Technical Symposium judges. “To identify relationships between those policies and students’ experiences, we linked survey data from 1,245 first-year students in 80 CS departments to a dataset of department policies,” says Nguyen. “We found that competitive enrollment negatively
HARVEY MUDD COLLEGE | COMPUTER SCIENCE HIGHLIGHTS 2020
predicts first-year students’ perception of the computing department as welcoming, their sense of belonging and their self-efficacy in computing. Both belonging and self-efficacy are known predictors of student retention in CS. In addition, these relationships are stronger for students without pre-college computing experience. Our classification of institutions as competitive is conservative, and false positives are likely. This biases our results and suggests that the negative relationships we found are an underestimation of the effects of competitive enrollment.”
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FACULTY NEWS
Professor Joins CRA Board Ran Libeskind-Hadas, R. Michael Shanahan Professor of Computer Science, was elected to serve a two-year term as secretary on the executive committee for the board of directors for the Computing Research Association (CRA), which includes more than 200 North American organizations active in computing research. An HMC faculty member since 1993, he previously served as co-chair on the CRA Education Committee (2011–2017), which focuses on promoting undergraduate research, providing resources to faculty to prepare talented students for research and encouraging undergraduate students to pursue graduate education and research careers in computing fields. In addition to his work with the CRA, Libeskind-Hadas has served on the Computing Community Consortium.
Outstanding Faculty Member For the eighth annual Leadership Awards, community members gathered via Zoom Meeting to celebrate students, faculty and staff for their contributions on campus and beyond. Colleen Lewis, McGregor-Girand Associate Professor of Computer Science, was lauded for being a faculty member who has gone above and beyond their job role to serve as a mentor for students and/or student organizations and embody Mudd values, such as collaboration and care for the campus community. A nominator writes, “Professor Lewis is all about community, care and collaboration. Her research, teaching, professional development, mentoring and contributions to the College and consortium consistently embody an open and inclusive vision of science and education; a clear-eyed view of the positive and negative interactions between society and science; and persistent and effective leadership of humane, just and equitable teaching and professional practices.” Spring semester 2020 was Lewis’ last at HMC. Her husband finished his PhD, and they moved to Illinois to continue their careers at the University of Illinois at Urbana– Champaign.
HARVEY MUDD COLLEGE | COMPUTER SCIENCE HIGHLIGHTS 2020
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SCHOLARLY ACTIVITIES
News from the HEATLab Jim Boerkoel directs the Human Experience & Agent Teamwork Lab (HEATLab) with the goal of developing techniques that augment humans’ own cognitive and physical abilities to create integrated human-agent teams that are more capable than their individual counterparts. Promoted to associate professor with tenure in 2019, Boerkoel received a 2017 Faculty Early Career Development (CAREER) grant from the National Science Foundation for his project on “Multiagent Scheduling Under Uncertainty.” This work will improve the robustness and reliability in applications, such as autonomous driving, automated warehousing and personal robots by addressing fundamental limitations in how current planning systems handle real-world scheduling uncertainty. Boerkoel and his students, Lindsay Popowski ’21 and Michael Gao ’20, had the paper “Dynamic Control of Probabilistic Simple Temporal Networks” accepted for publication and presentation at the 2020 AAAI Conference on Artificial Intelligence. Developed during summer 2019 in the HEATlab, the paper is an effort to describe more efficient and successful ways to schedule tasks that require coordination between agents. During summer 2019, HEATLab students celebrated the publication of three papers at the International Conference on Automated Planning and Scheduling in Berkeley, California. “Quantifying Degrees of Controllability in Temporal Networks with Uncertainty” Shyan Akmal ’19, Savana Ammons ’20 and Maggie Li ’19 launched a new student-led project that looks to deal with situations where scheduling uncertainty outstrips an agent’s ability to control for it.
HARVEY MUDD COLLEGE | COMPUTER SCIENCE HIGHLIGHTS 2020
They developed new analytical tools for assessing what they coined “the degree of controllability,” which measures the likelihood that an agent (e.g., robot) can control for the presence of scheduling uncertainty. . They received runner-up department honors for best student-authored paper. “Measuring and Optimizing Durability Against Scheduling Disturbances” Joon Lee ’20 and Viva Ojha ’19 used geometric interpretations of scheduling problems to develop new ways to quantify a schedule’s resilience to unexpected scheduling disturbances. They defined a new concept, “durability,” which characterizes a temporal plan’s resilience to disturbances. They also proposed several durability metrics, two new approaches for finding optimally durable schedules and an empirical model for simulating realistic sources of schedule uncertainty, which they used to perform a systematic empirical evaluation of proposed metrics and approaches. “Reducing the Computational and Communication Overhead of Robust Agent Rescheduling” Jordan Abrahams ’19 and co-author Jeremy Frank built on the work of the 2017–2018 NASA Ames Research’s HMC Computer Science Clinic team to explore how they could adapt uncertainty-aware, dynamic scheduling advice to be more judicious in how often rescheduling, and, by extension, communication, was required in multi-agent settings. They introduced a single streamlined algorithm that trades robustness for various forms of computational overhead, including multi-agent communication.
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SCHOLARLY ACTIVITIES
George Montañez (crouching center) with student researchers, who are members of his lab, AMISTAD.
Montañez and Machine Learning Computer science professor George Montañez and his students have turned their research of theoretical machine learning, probability, statistics and search into multiple publications and presentations. In early December 2019, Montañez, Jon Hayase ’20 and Julia Vendemiatti ’21 attended the 32nd Australasian Joint Conference on Artificial Intelligence in Australia to present their research. After winter break, Montañez and several students presented four more papers at the 12th International Conference on Agents and Artificial Intelligence (ICAART 2020) and the 11th International Conference on Bioinformatics Models, Methods and Algorithms, both in Malta. A sixth paper was published online by Business Horizon. Here is a list of the publications with links to each one.
32nd Australasian Joint Conference on Artificial Intelligence “The Futility of Bias-Free Learning and Search” George Montañez, Jon Hayase ’20, Julius Lauw ’20, Dominique Macias ’19, Akshay Trikha ’21, Julia Vendemiatti ’21 Building on the view of machine learning as search, researchers demonstrate the necessity of bias in learning, quantifying the role of bias (measured relative to a collection of possible datasets, or more generally, information resources) in increasing the probability of success. link.springer.com/chapter/10.1007/978-3-030-35288-2_23
HARVEY MUDD COLLEGE | COMPUTER SCIENCE HIGHLIGHTS 2020
ICAART 2020 “Decomposable Probability-of-Success Metrics in Algorithmic Search” Tyler Sam ’20, Jake Williams ’20, Abel Tadesse ’20, Huey Sun ’20 (POM), George Montañez Researchers define decomposable metrics as a category of success metrics for search problems which can be expressed as a linear operation on a probability distribution to solve this issue. Using an arbitrary decomposable metric to measure the success of a search, they demonstrate theorems which bound success in various ways, generalizing several existing results in the literature. arxiv.org/abs/2001.00742 “The Labeling Distribution Matrix (LDM): A Tool for Estimating Machine Learning Algorithm Capacity” Pedro Segura Sandoval ’19, Julius Lauw ’20, Daniel Bashir ’20, Kinjal Shah ’19, Sonia Sehra ’20, Dominique Macias ’19, George Montañez Researchers introduce the labeling distribution matrix as a tool for estimating the capacity of learning algorithms. The method attempts to characterize the diversity of possible outputs by an algorithm for different training datasets, using this to measure algorithm flexibility and responsiveness to data. arxiv.org/abs/1912.10597
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SCHOLARLY ACTIVITIES
Montañez
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More Papers Published by Computer Science Faculty and Students
“The Bias-Expressivity Trade-off” Julius Lauw ’20, Dominique Macias ’19, Akshay Trikha ’21, Julia Vendemiatti ’21, George Montañez “Automatically Solving Deduction Games via Symbolic This research proves a set of results showing the trade-off between Automatically Solving Deduction Games via Execution, Model Counting, and Entropy Maximization” bias and expressivity (flexibility). arxiv.org/abs/1911.04964 Symbolic Execution, Model Counting, and Entropy Maximization Mara Downing, Chris Thompson, Professor Lucas Bang The paper was accepted at the AAAI Conference on Artificial BIOINFORMATICS 2020 Mara Downing, Chris Thompson, Lucas Bang Intelligence and Interactive Digital Entertainment Strategy Game “Minimal Complexity Requirements for Proteins and Other {mdowning, cbthompson, lbang} @hmc.edu Workshop. The students designed a DSL for expressing a class of Combinatorial Recognition Systems” Harvey Mudd College puzzles called “deduction games,” implemented a symbolic execution George Montañez, Laina Sanders ’21, Howard Deshong ’21 301 Platt Blvd. engine for it using an automated theorem prover, and then wrote In this paper, researchers seek to answer the question: Can we Claremont, California 91711 and entropy maximizer that outputs the steps of game solution. use the tools of information theory to lower bound the minimum complexity of a protein needed to perform a given recognition task? Abstract cs.hmc.edu/~montanez/pdfs/montanez-2020-minimal-complexity.pdf We present a technique for automatically solving deducBusiness Horizons tion games in which a player makes repeated queries to a running implementation the of game and receives “Virtue as a Framework for the Design andofUse Artificial a game outcome, with the goal of discovering an unIntelligence” known secret value. By making multiple queries, a Mitchell Neubert, player Georgeiteratively Montañez reduces the uncertainty about the se“We describe a set cret of ethical encountered Google and until it challenges is known. We show how tobysynthesize player using static program analysis, model-counting, introduce virtue asqueries a framework for ethical decision making that can and information theory. The system we describe aube applied broadlytomatically to numerous organizations,” Montañez says. “We solves deduction games implemented in a also examine support for virtuegame in ethical decisionlanguage. making as well as Python-based specification
Source Code of Game Symbolic Execution
In this paper, we present a method of automatically synthesizing queries to solve deduction games. Our approach uses static code analysis, namely symbolic execution, to analyze the implementation of a game in order to extract a set of constraints that model the behavior of the game. These constraints are used in a process called ‘model counting’, which is leveraged to compute probability distributions relating player queries to game outcomes. The probability distribution functions determine an information gain objective function based on Shannon entropy, which, when maximized, yields the optimal play for the current game round. We implemented a domain specific language in which to write deduction games, enabling our static analysis phase. Our experiments demonstrate the effectiveness of our approach on a set of deduction games.
c 2019 for this paper by its authors. Use permitted unCopyright ○ der Creative Commons License Attribution 4.0 International (CC BY 4.0).
Model Counting # (s, q)
Knowledge About Secret k(s)
Outcome Probabilities p(o|q)
Game Outcome o Game Instance G(q * )
its power in attracting and retaining the employees who develop AI and the customers who use it.” 1 Introduction sciencedirect.com/science/article/pii/S0007681319301545
Deduction games are a form of puzzle in which a player attempts to discover a game solution using logical reason“The Futility of Bias-Free Learning and Search” ing. We consider deduction games that proceed in a series George Montañez, Jonathan ’20,a Julius of game roundsHayase in which player Lauw makes’20, a query and is proDominique Macias Trikha corresponding ’21, Julia Vendemiatti vided ’19, withAkshay an outcome to that ’21 query which Learning algorithms machines that turn dataanresources into reveals are some information about unknown secret value. The player’s goalthat is to discover the secret. Popular games predictions. Their paper shows unless algorithms do this fall into categorytheir are Mastermind (crack a secret conversion inthat a biased way, this predisposing predictions toward code using information a query is to the predetermined outcomes, they cannotabout predicthow anysimilar more accurately code) and Battleship (find the locations of ships by querying than random guessing. coordinates and learning if they are a ‘hit’ or ‘miss’).
Outcome Constraints (s, q)
Optimal Query q*
Entropy Maximization maxq H(q)
1: Overall strategy synthesis approach. Figure 1:Figure Overall strategy synthesis approach.
“Graphs Are Not Enough: Using Interactive Visual Analytics in Storage 2 Research” Automatically Solving Deduction Games Professor Geoff this paper which appeared We give an Kuenning overview co-authored of our approach, including the defi- in the nitions Usenix HotStorage 2019 It presents a visualization for our model of Workshop. deduction games, the steps of autotoolmatically that helpssolving systemadesigners and the vast game, and theexperimenters correspondingexplore algorithms. We follow with an example step.systems. number of possibilities available that whenilluminates configuringeach storage The tool makes it easy to “zero in” on the parameters that have the 2.1 Components of a Deduction Game most impact on performance in a chosen situation so that an analyst deduction G is a for tuple: a environment. secret set, a query can A quickly find thegame best settings a given
set, an outcome set, and game rules, respectively, denoted ‹S, Q, O, R›.
Secret. The goal of a deduction game is to discover a secret value s among a set of all potential secret values S. Player Queries. A player makes repeated queries q over the course of a game from among a set of possible queries Q. Outcomes. After each query, the outcome o, from among a set of possible outcomes O, of that game round is revealed. Game Rules. The outcome of a game round is made according to a deterministic game rule depending on the player query and the secret. We can think of the game rules as a function R : Q × S → O. We assume that the player knows the rules (code) of the game and the only unknown is s.
2.2
Solution Synthesis Steps and Components
We now describe our solution technique. The reader may find it helpful to refer to Figure 1 along with this discussion. Udeema Shakya ’23, Julia Puzzo ’23 and Josh Cabral ’23 at the Usenix Annual Technical Conference, summer 2019
HARVEY MUDD COLLEGE | COMPUTER SCIENCE HIGHLIGHTS 2020
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SCHOLARLY ACTIVITIES
National Science Foundation Funds Harvey Mudd CS Projects A Consortium for Cultivating Future Artificial Intelligence Researchers Jim Boerkoel has received a $45,900 federal grant from the NSF in support of his project. “The AAAI Undergraduate Consortium and Mentoring Program, hosted at the 2020 and 2021 AAAI Conferences on Artificial Intelligence, will attempt to address the challenge of building a healthy cohort of future artificial intelligence (AI) researchers that is representative of broader societal diversity,” Boerkoel says. This program seeks to fortify the research identities of future AI researchers across a diverse set of backgrounds, particularly among populations that are traditionally underrepresented in STEM. The long-term objective is to broaden the pipeline of students pursuing AI graduate education and research careers, and to do so in a way that the pedagogical tools and materials can be leveraged by researchers and educators at academic conferences across computer science and STEM disciplines. Read more about the importance of diversity in AI in President Maria Klawe’s Forbes interview with Boerkoel, bit.ly/349rigc.
Research Experience for Undergraduates George Montañez and Lucas Bang have received NSF funding for a renewal of the Research Experience for Undergraduates (REU) site at Harvey Mudd. Focusing on computer systems, with an eye toward search, artificial intelligence and data science, the REU brings the most compelling aspects of graduate school to a 10-week summer program where HMC students and faculty work as peers on stimulating research questions. Academic and recreational group activities create a strong common-cohort experience. The program develops research ability, improves presentation skills and nurtures student interest in research-related careers. In August 2019, the Computer Science Department completed its fifth three-year REU at HMC and Montañez and Bang are eager to continue the site for another three years. The program goals are to build a sense of joy and empowerment for doing computer science research and graduate study; expose students to the entire research process (literature survey, problem identification, ethical considerations, investigative work and preparation of publishable results); engage all students in developing significant research contributions; and develop excellent teamwork skills as well as oral and written communication skills. The REU site involves 10 students working with an experienced faculty mentor each summer for 10 weeks.
HARVEY MUDD COLLEGE | COMPUTER SCIENCE HIGHLIGHTS 2020
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SCHOLARLY ACTIVITIES
NSF Funds
(CONTINUED)
Phylogenetic Tree Reconciliations Ran Libeskind-Hadas, R. Michael Shanahan Professor of Computer Science, seeks to develop efficient algorithms for systematically identifying a small set of the most representative maximum parsimony reconciliations. Results will be extended to deal with the larger solution spaces induced by a range of event costs and for non-binary trees. This will allow development of new software for life scientists and the ability to generalize these results to event models beyond the duplicationtransfer-loss model. The NSF grant of $498,458 supports Libeskind-Hadas’ research and the design, analysis and empirical evaluation of algorithms leading to transformative new tools for biologists. Funding will support six research students a year for three years, beginning summer 2020, as well as travel to conferences. It will also fund the purchase of a high-performance computer to test the algorithms and perform computational experiments. Libeskind-Hadas performed precursory research for this project in a previous NSF-funded project in which he addressed some foundational problems in tree reconciliation.
Optimizing and Understanding Large Parameter Spaces in Storage Systems
Geoff Kuenning and his Stony Brook University colleagues, computer science professors Klaus Mueller and Erez Zadok, are collaborating on the project “CNS Core: III: Medium: Collaborative Research: Optimizing and Understanding Large Parameter Spaces in Storage Systems.” The team will test a combination of enhanced black boxoptimization methods, machine learning and visual analytics on information systems from cloud data centers to smartphones to embedded systems, such as wireless routers. Beyond improving storage systems, a significant improvement to the performance of storage systems worldwide will save energy costs and benefit the environment. The project’s comprehensive research agenda has the potential to make such optimization significantly simpler and far more effective, which can bring direct benefits to consumers, businesses and the U.S. government.
HARVEY MUDD COLLEGE | COMPUTER SCIENCE HIGHLIGHTS 2020
Math for America Los Angeles
In an effort to address a shortage of highly effective mathematics and computer science teachers in secondary schools in high-need school districts, mathematics professor Darryl Yong, computer science professors Colleen Lewis and Zach Dodds, and Karen Gallagher (USC) launched the project, “Math for America Los Angeles: Elevating Mathematics and Computer Science Instruction through Teacher Leadership.” A collaborative effort between USC, Harvey Mudd, school districts in the greater Los Angeles area and Math for America Los Angeles, the project includes funding for 34 master teaching fellows. They’ll create an improvement plan for their respective schools’ mathematics and/or computer science instructional needs.
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RESEARCH & CLINIC
2020 Summer Research Program Advisor: Lucas Bang Algorithms and Logic for Program and Quantitative Analysis (ALPAQA) Student: Emily Lu Path Complexity of Programs Students: Ibrahim Abughararh, Shaheen CullenBaratloo, Sofiane Dissem Automatic Search Synthesis Students: Mara Downing, Maximilian Mudd Mingst, Abtin Molavi, Laurel Newman, Maria Simon Taylor Advisor: Jim Boerkoel Creating more fluid, intuitive robot teammates Students: Maya Abo Dominguez, William La Probably-in-Ctrl Students: Hannah Davalos, Ryan Martinez, Vibha Rohilla Advisor: Chris Clark AUV Tracking and Mapping Students: Hannah Kyme, Zhuoqun Li, Kunyang Lu, Olivia Yoshiko Tuffli, Huaxiaoyue Wang Using numerical models to evaluate analogue simula Student: Eve Paulson
2019–2020 Thesis Cole Kurashige: An Introduction to Type Checking, Inference, and Row Types (CS/math) Advisors: Chris Stone and Jeff Polakow ‘98, Awake Security
2019–2020 Clinic Projects Computer Science Clinic CrowdStrike Automated Kafka Consumer Scaling Liaisons: Eric Schow, Luke Hunter ’03 Advisor: Lucas Bang Students: Ali Parker (PM), Owen Gillespie, Quinn Hirsohn, Julius Lauw, Zack Rossman EdgeConneX Project Terminator Liaisons: Lance Devin, Gary Avery Advisor: Lisa Kaczmarczyk Students: Priyanka Agarwal, Devon Frost, Lisa Hao, Julia Pinedo (PM)
Micro Glider Design and Testing Students: Ginger Schmidt, Hugo Minghong So Advisor: Zach Dodds Computing for Insight: Piloting tools + techniques Students: Henry Coxe, Malia Morgan, Deanna Oei Advisor: Geoff Kuenning Re-Animator development Students: Alex Bishka, Thuy-Linh Thanh Le, Ignacio Lista Rosales Storage System Tracing and Replay Student: Thomas Fleming National File Systems Trace Repository Students: Ki Pheng Lim, Michelle Wing Sze Ng Advisor: Colleen Lewis CSTeachingTips Students: Yim Chen, Catherine Hongzu Jang, Audra Lane, Ruth Alemu Mekonnen Summer Start-ups: “Social Alarm” and “Sustainability Competition” Students: Katherine Johnson, Zhuoqun Li, Jessica Marvin, Amy Wang Qian, Kobe Mia Rico, Anna Dupuy Singer, Shifa Maheen Somji, Sidney Taylor
Futrend Technology Inc. Cognitive Databases for Improved Large-scale Information Access Liaisons: Jerry Zhou, Jeff Zhong Advisor: Beth Trushkowsky Students: Daniel Bashir (PM), Lavon Burgo, Cienn Givens, Ethan Lewis, Sonia Sehra Google Google Education: Applied Machine Learning Intensive Clinic Liaisons: Josh McAdams, Sidnie Davis, Liza Roesch, Obasi Shaw Advisor: Zach Dodds Students: Lizzy Riffle (PM), Laurel Newman, Mara Downing, Sally Carlson, Isaiah Evans Google Google Call Center Liaisons: Kristina Nasr, Tim Laubach, Alexander Cho, Jennie Ibrahim Advisors: Neil Rhodes (F), Zach Dodds (S) Students: Henry Jacobs (PM-S), Joon Young Lee (PM-F), Hazal Su Dinç, Shifan Chen, Ben Meyer (S)
HARVEY MUDD COLLEGE | COMPUTER SCIENCE HIGHLIGHTS 2020
Advisor: Ran Libeskind-Hadas Phylogenetic tree reconciliation Students: Nathaniel Efrat-Henrici, Justin Jiang, JingYi Liu, Ross Mawhorter, Santi Santichaivekin Advisor: George Montañez Artificial Machine Intellegence: Search Targets Awaiting Discovery/AMISTAD Students: Hana Ahmed, Kevin Ginta, Cindy Lay Probability and Machine Learning Students: Jarred Allen, Nicolas Espinosa Dice, Cynthia Hiromi Hom, Megan Kaye, Amani Rune Maina-Kilaas Advisor: Xanda Schofield ’13 Text Mining for Digital Humanities Students: Theodore de Volo, Alfredo Gomez, Tatsuki Kuze Advisor: Erin Talvitie Model-Based Reinforcement Learning in Atari 2600 Students: Bowen Jiang, Xintong Wang, Siyi Zhao Advisor: Yi-Chieh (Jessica) Wu Computational Biology Students: Matthew LeMay, Julia Vendemiatti, Trenton Wesley, Qing Yang
Google Applied Computing Google Applied Computing Series Liaisons: Kiran Raskutti, Mitch McKinnon Advisor: Zach Dodds Students: Lindsey Cleary (PM), Sega Birhane, Tiffany Madruga, Celine Park, Kaitlyn Zeichick Google Irvine Google Front-end Framework Liaisons: Lindsay Erickson ’04, Nathan Tate, Scott Ellsworth ’89 Advisor: Melissa O’Neill Students: Carl Aslund (PM-S), Sascha Reynolds (PMF), Susan Xiao, Sage White, Francisco Ruiz Google Measurement Lab Discovering and Displaying Drops in Internet Performance Data Liaison: Peter Boothe ’00 Advisor: Ran Libeskind-Hadas Students: Jacqui Giese (PM), Pascal Habineza, Roman Rosenast, Amy Sorto, Rui-Jie Yew
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RESEARCH & CLINIC
Clinic Projects (CONTINUED) HMC INQ Puzzle Master 9000: The Jigsaw Puzzle-Helping App Liaison: Josh Jones ’98 Advisors: Bob Keller (F), Zach Dodds (S) Students: Adrian Garcia, Celena Chen, Djassi Julien, Mazda Moayeri, Sydney Wallace (PM) Indeed Modeling Employment-Matches for Anonymous Job Seekers Liaisons: Man Liang, Christiaan Visser, David Arpin, Jai Chakrapani Advisors: Bob Keller (F), Kathleen Breeden (S), Zach Dodds (S) Students: Kira Weiss (PM-S), Garret Conway (PM-F), Josh Cabral, Shihao Lin, NaNa Mathis Juniper Networks Optimizing Router Performance Liaison: Ron Bonica Advisor: Geoff Kuenning Students: Radon Rosborough (PM-S), Hakan Alpan, Bradley Newton (PM-F), Miles President Laserfiche A Framework for Evaluating OCR Engines’ Accuracy Liaisons: Tessa Adair ’14, Doren Lan ’18 Advisor: Xanda Schofield ’13 Students: Jocelyn Chen (PM-S), Athena ParaskevasNevius, Ian Taylor (PM-F), Andrew Lewis Lawrence Livermore National Laboratory GPU-Accelerated Visualization of High-order Physics Simulation Meshes Liaisons: Cyrus Harrison, Matt Larsen, Walt Nissen ’00, Kenny Weiss Advisor: Chris Stone Students: Ben Baral, Gabe Bessler (PM-F), Julia Read (PM-S), David Sobek Los Angeles Regional Food Bank Food Waste Analysis Through a Handheld Scanner App Liaisons: Roger Castle, Sam Ettinger ’14, Peter Felix, Scott Newton, Weldon Wu Advisor: Lisa Kaczmarczyk Students: Morgan Carothers, Shannon Collier, Sol Cruz, Kayley James (PM), Erin Jimenez Microsoft Eye Tracking to Improve Reading Experience on Screens Liaisons: Mike Bennett, Rob McKaughan ’98 Advisor: Katherine Breeden Students: Alia Curtis (PM), Huey Fields, Michael Hamlett, Julia Wang, Iris Zhou
MIT Lincoln Laboratory RACECAR Liaisons: Eyassu Shimelis ’18, Andrew Fishberg ’16, Sabina Chen Advisor: Zachary Dodds Students: Matthew Calligaro (PM), Evan Johnson, Zoe Ryan, Emiko Suzuki Paramount Animation An Asset Browser for Feature Animation Liaisons: Gene Lee, Vijoy Gaddipati Advisor: Katherine Breeden Students: Anisha Kaul (PM), Teresa Ibarra, Cody Newman, Ali Otondo, Huize Huang Pure Storage Automatic Disk-Image Conversion Liaisons: Naveen Neelakantam, Drew Bernat ’99 Advisor: Mark Kampe Students: David Trujillo (PM), Joe Brennan, Emily Cao, Giselle Serate ServiceNow Efficient Indexing of Compressed Time-series Data Liaisons: James Capaldo ’92, Magaly Drant, Thejaka Kanewala, Meg Sharkey, Vincent Seguin Advisor: Geoff Kuenning Students: Garrett Cheadle, Alanna DeMuro, Levente Papp, Neeta Rao (PM-F), Cassie Rossi (PM-S) Steelcase Facilitating the Visual Communication of Wood Veneer Liaisons: Ed Vanderbilt, Mark Schild, James Huey, Steve Merdzinski Advisor: Katherine Breeden Students: Jenna Kahn (PM-S), Matt Kanovsky (PM-F), Kevin Sasaki, Anya Wallace The Factor Programming Language Numerical Programming and an Online Platform for the Factor Programming Language Liaison: John Benediktsson ’01 Advisor: Ben Wiedermann Students: Maxwell Denning, Cameron Krimsky, Cole Kurashige, Nandeeka Nayak (PM-S), Kye Shi (PM-F) The Walter Bradley Center The Limits of Transfer Learning Liaison: Robert J. Marks Advisor: George Montañez Students: Jake Williams (PM-S), Tyler Sam (PM-F), Abel Tadesse, Huey Sun
HARVEY MUDD COLLEGE | COMPUTER SCIENCE HIGHLIGHTS 2020
Walmart Labs Expediting Grocery Pick Up – A Computer Vision Approach Liaisons: Jennifer Chen, Arun Nagarathinam, Maddy Vasantham Advisor: Erin Talvitie Students: Tony Jiang (PM-F), Walker Quinn, Dave Makhervaks (PM-S), Jason Yi Walmart Labs Voice Improving Product Relevance for Online Voice Groceries Liaisons: Ghodrat Aalipour, Venkata Nandanavanam Advisors: Colleen Lewis (F), Ran Libeskind-Hadas (S) Students: Shannon Steele (PM-S), Ka Ki Fung (PM-F), Richy Chen, Justin Gadalla Webroot Analyzing Web Usage Data to Detect Threat Patterns Liaisons: Michael Balloni ’98, Hal Lonas, Trung Tran, Brittany Wang ’19, Fred Yip Advisor: Lisa Kaczmarczyk Students: Jill Cardamon (PM), Nisha Bhatia, Riley Julianne Lin, Riley Mangan Computer Science/Biology Clinic Dassault Systèmes BIOVIA Predicting Antibody Developability From Sequence Using Machine Learning Liaisons: Ian Kerman and Dr. Reza Sadeghi Advisor: Jessica Wu and Naim Matasci Students: Emily Zhao (PM-F), Tom Dougherty (PM-S), Xingyao Chen, Rachel Schibler, Chan Hong Computer Science/Mathematics Clinic Sustainable Claremont Addressing the Effects of Traffic on Air Quality at Claremont High School Liaisons: Angela Oakley, Stuart Wood Advisors: Alfonso Castro, Julie Medero Students: Kylie Hetzel (PM), Daniel Ashcroft, Isaiah Fujii Bresnihan, Jasmine Seo Computer Science/Physics Clinic Los Alamos National Laboratory Automating the Extraction of Photon Doppler Velocimetry Data Liaison: Candace Joggerst ’04 Advisor: Peter Saeta Students: Nicholas Koskelo (PM), Max Treutelaar, Trevor Walker, Isabel Duan (S), Rikki Walters (S)
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AWARDS
2019–2020 Departmental Awards & Recognition The Class of ’94 Award
Clinic Team Awards
Computer Science Service Award
Morgan Carothers Nuo Liu Celine Park
Matthew Garrick Calligaro Morgan Carothers Xingyao Chen Shannon Kathleen Collier Sol Cruz Thomas Dowling Dougherty Owen Lockwood Gillespie Maria Teresa Maninang Ibarra Erin Marie Jimenez Evan Durston Johnson Julius Lauw Cody Tyler Newman Alessandra Siobhan Otondo Zoe Leolani Ryan Rachel Schibler Claire Emiko Suzuki YiCong Zhao
Matthew Garrick Calligaro Athena Maria Paraskevas-Nevius Giselle Sarah Serate
Don Chamberlin Computer Science Research Award
Mara Downing Julius Lauw Clinic Individual Award
Kylie Grace Hetzel Jasmine Seo Computer Science Service Award
Matthew Garrick Calligaro Athena Maria Paraskevas-Nevius Giselle Sarah Serate
Wing and Ellen Tam Award (seniors)
Matthew Garrick Calligaro Morgan Carothers Nicholas Koskelo Nandeeka Nayak Jasmine Seo Giselle Sarah Serate Anna Victoria Serbent Anya Wallace Iris X. Zhou Isaac B. Zinda
Class of 2020 Departmental Honors Carl Aslund Matthew Garrick Calligaro Morgan Carothers Shannon Kathleen Collier Mara Downing Michael Zikai Gao Owen Lockwood Gillespie Cienn Givens Jonathan Hayase Cole Kurashige Jacky Lee Joon Young Lee Tse Yang Lim Nuo Liu Mazda Moayeri
Nandeeka Nayak Laurel Aileen Newman Princewill C. Okoroafor Athena Maria Paraskevas-Nevius Celine Park Miles President Adelaide Punt Radon Rosborough Tyler Jiang Sam Giselle Sarah Serate Samuel S Tan Julia Wang Xinyu (Carrie) Yang
HARVEY MUDD COLLEGE | COMPUTER SCIENCE HIGHLIGHTS 2020
18
ALUMNI NEWS
1995 Adam Wells: After a few years of long-distance
marriage, my wife, Maria, and I and our three kids, Mateo (16), Eva (13) and DJ (5), are now happily living together in my hometown of Las Vegas. Maria is a family court attorney, and I just celebrated my 20-year anniversary with Apple, which is still a great place to work. My latest hobbies: microcontrollers and 3D printing.
1996 Darin Grant: I’m the CTO at Animal Logic which made effects for the Matrix movies as well as producing a number of animated features, including Happy Feet, The Lego Movie and Peter Rabbit. I’ve worked in this industry alongside many HMC grads since about two weeks after graduating and have loved every minute of it. I also have had the pleasure of recommending recipients of Scientific and Technical Achievement Awards for the Academy of Motion Pictures Arts and Sciences over the past 15 years. I live in Los Angeles and live on video conference while regularly traveling to Sydney and Vancouver, much to the disappointment of my 9-year-old son, Atticus.
1997 David Hamm: Crazy times on the Fortnite team
at Epic Games. We are hiring! Dallas Kashuba (formerly Bethune): I’ve
been working at my company, New Dream/ DreamHost, since graduating, and I’ve recently formed a new team to research and develop spatial computing interfaces. We are developing software that uses VR headsets to help people understand and interact with data and information systems in ways not possible on a flat screen. Human brains are adapted for 3D and current computing interfaces are holding us back! Our first early prototype generates multi-user, interactive 3D visualizations of Kubernetes clusters.
1998 Matthew Dharm:
After taking a job with Qualcomm after graduation, I did a couple of startups in embedded systems, eventually winding up
with the title CTO. I parted ways with that organization in 2017 and now work for Avnet as a subject-matter expert in all things Broadcom and spend some time consulting for other organizations which need expertise in the world where hardware meets software. I’ve also been spending some time traveling, including a trip to the northern-most city in the world (Honningsvåg, Norway—There are settlements further north, but not incorporated cities) and an upcoming trip to Alaska. The photo was taken in the mountains above Honningsvåg. Josh Jones: I live in Santa Monica and run
HMC INQ now! We fund startups with Mudd alums only. Apply today at hmcinq.com/apply, please! Michael Wolf: I am the manager of the Scalable
Algorithms Department at Sandia National Laboratories in Albuquerque. In my spare time, I enjoy hiking, traveling and eating with my wife, Amy.
1999 Andrew Bernat: Jenn and I have lived in Mountain View since 2013. I’m a principal engineer at Pure Storage, focusing on reliability and upcoming hardware. Jenn is a full-time mom and part time legal secretary, packing more work into a day than physics strictly allows. We’ve got two kids, Danny (10) and Becky (7). Life is good!
2000 Mike Hanley: I am working at Disney as a VP,
software engineering leading development for connected and embedded devices for Disney’s new streaming services Disney+ and ESPN+.
2003 Conor Sen: I’ve lived in Atlanta for nine years
now. My wife, Crystal, and I recently celebrated our sixth wedding anniversary. Our kids are 3 1/2 and 17 months, and we’re enjoying the ups and down that go along with that. Professionally, I’ve been managing money for individuals for almost seven years, and I’ve been a columnist for Bloomberg Opinion for over three. The political fluidity in Georgia, particularly the Atlanta suburbs, makes this a fascinating place to live right now. I do miss those late-night In-N-Out runs, though.
HARVEY MUDD COLLEGE | COMPUTER SCIENCE HIGHLIGHTS 2020
2003 Avani Gadani: After a brief stint in industry, I went back to academia and am currently an assistant professor in CS at Emory university. My lab (SimBioSys) looks at problems at the boundaries of systems, complexity and data science. I commute to Atlanta from San Francisco, where I live with my 21-month-old son, Agni, as well as Chris Erickson ’06 and Peter Wilson ’02.
2004 Erika and Jeff Rice Scherpelz: These
days, we are living just outside of Seattle. Erika works on Google Maps. I stay home with our two daughters who are 5 and 2. Most of our time is taken up with those things, but we did manage a kid-free trip to Japan in April 2019, and we went to our 15-year Mudd reunion. We also host a monthly board game group. If you’re in the area, you’re welcome to come!
2008 Jason Fennell: I left my role as head of engineering at Yelp late last year. I’ve been enjoying a year off playing with my two young kids and also staying involved with Mudd through the board of trustees. I’m starting to look for exec jobs again, too.
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ALUMNI NEWS
2010 Josh Swanson: I received my PhD in
mathematics from the University of Washington in summer 2018. I’m in the middle of a three-year post-doc at UC San Diego. I’ve been kept quite busy with many research projects!
2011 Audrey Lawrence: I’ve been working in the autonomous vehicle industry, and I’m based in Seattle leading mapping and infrastructure at a startup, CARMERA, that makes HD maps for AVs. Outside of work, you can catch me traveling the world, dancing to techno, running long distances and hanging out with cats.
farming and broom making in my spare time. Occasionally meeting up with other Bay Area Mudders for dumplings or pie!
2015 Priya Donti: I am a PhD student in computer science and public policy at Carnegie Mellon University, working at the intersection of machine learning, electric power systems and climate change mitigation. I recently cofounded an initiative called Climate Change AI, a group of volunteers from academia and industry that seeks to facilitate work at the intersection of climate change and machine learning. Mimee Xu: Mimee moved to NYU as a PhD student after a few years in industry (Google, Baidu SVAIL, UnifyID). She not only has more time to play around with security and machine learning, but also has time to be crushed by classes such as Gaussian Processes and Distributed Systems.
continue to work toward a PhD at University of Washington CSE, where I am in my third year studying machine learning with Kevin Jamieson.
2017 Madi Pignetti: I edited and released a book
called super / natural. It is a collection of fiction, poetry and art revolving around our relationship with the Earth. There are works from 23 different creators, and the works are united through their themes of the supernatural. As a whole, the work stands as a literary call to action, urging readers to envision and manifest the futures they seek (and to avoid some of the more dystopic possibilities). More info at https://www. perennial-press.com/super-natural-preorders.
2018 Porter Adams: Arthur Reyes ’18, Heather Wing ’20 and I founded Disappear Digital to
help protect personal data and information. I had been helping law enforcement with missing persons investigations when I realized how easy it is to find people’s information on the internet. Disappear Digital’s services include checking your social media for privacy concerns, removing phone numbers and home addresses from data broker websites and reviewing data breaches to find potentially compromised passwords. How much of your information is out there for anyone to find?
2019 Kinjal Shah: I am working as a software
engineer at Facebook, specifically on their probabilistic programming languages team.
We Love Hearing From You
2014 Miranda Parker: I just graduated with my PhD in human-centered computing from Georgia Tech! The photo is me with my advisor, Mark Guzdial, and his son, who also received his PhD in the same ceremony. Vivian Wehner: Mobile ad platform for Yahoo!
(RIP), indoor mapping at Apple, Google Translate iOS app, now a performance engineer at Facebook. Adopted two dogs, urban
2016 Jennifer Rogers Brennan: In August 2019, I married my boyfriend of nine years, Eamon Brennan. Eamon and I live in Seattle and look forward to the day that we spend enough time at home to get a dog. In the meantime, I
HARVEY MUDD COLLEGE | COMPUTER SCIENCE HIGHLIGHTS 2020
Thank you for your enthusiastic response to the Computer Science Department’s request for alumni news. We’ll be in touch each spring by email, or you can send updates at any time to chair@cs.hmc.edu.
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