Computer Science Highlights 2022, Harvey Mudd College

COMPUTER SCIENCE

HIGHLIGHTS

2022

Update from the Department Chair

2022–2023 represents a year of innovation and growth in computer science!

We are excited to have added new staff members to our team. Chelsey Calingo joins HMC CS as our new program assistant. Chelsey is an alum of UC Riverside with a bachelor’s degree in applied math in computer science and a master’s in higher education administration and policy. She leads several student programs that aim to make our student experience more equitable, just and inclusive.

Morgan McArdle is our new departmental administrative assistant. She is an alum of Syracuse University with a bachelor’s degree in illustration with a concentration in painting. Her artistic flair can be spotted at department events and can be seen adorning department displays.

We are also excited to be searching for multiple, new tenure-track faculty members, including in the area of climate and computer science, jointly held through the Hixon Center for Climate and the Environment and CS. This professor will help us establish our new, firstof-its-kind climate + CS joint major.

Professor Xanda Schofield ’13 and CS Clinic and Administrative Project Manager Surani Gunasena are leading efforts to reimagine our longstanding CS121 Software Development CS major requirement. Prof. Schofield will pilot a new CS in the Wild course that dives into the technical and professional skills necessary to plan, execute, document and present computational projects beyond a classroom.

Innovation and growth are keystones of our thriving faculty and student research program. Professors Katherine Breeden and

Calden Wloka collaborate with students on research that investigates developing better human gaze models in a new, state-of-the-art eye-tracking research lab. Professor Lucas Bang is incorporating ideas from the HMC CS curriculum into electronic artworks, including robotic hands that edit their own source code and video installations of neural networks that reprogram themselves to generate complex patterns of images.

Of course, this is only a tiny taste of the exciting growth and innovation happening within the department. We invite you to visit our newly relaunched website (hmc.edu/cs) to learn more and to be in touch. We’re always excited to learn of the growth and innovations of our distinguished alums.

Be well, be whole, be you!

Jim Boerkoel

Csilla & Walt Foley Professor and Chair, Department of Computer Science

Computing Literacy Initiatives

Prioritizing Computer Science in K–12 Schools

Harvey Mudd College joined national nonprofit organization Code.org and over 500 of the nation’s top industry, nonprofit and education leaders to issue a letter calling on state governments and education leaders to “update the K-12 curriculum in each state, for every student in every school to have the opportunity to learn computer science.”

“The middle and high school years are a crucial time to engage students in computer science and its creative possibilities, particularly for girls and students from other underrepresented groups in the field,” said President Klawe, a signatory on the letter. “These years are a time when students are forming their identities, and it’s important for them to learn skills, gain confidence and see that they can succeed in tech careers—careers that are vital to our nation’s economy and

also offer creativity, flexibility, good pay and a chance to impact the world.”

The coalition behind this effort is unprecedented in U.S. education, uniting the leaders and founders of large tech companies such as Apple, Microsoft, Alphabet and Amazon, together with CEOs of companies across sectors, including American Express, Nike, Starbucks, Delta Airlines, AT&T, UPS, Walgreens and Hasbro, as well as national education organizations such as Khan Academy, the American Federation of Teachers and the National Education Association.

Over the last decade, all 50 states have taken action to expand access to computer science, including allowing computer science to count toward core graduation requirements, funding professional learning to train more teachers and creating clear certification

pathways for computer science teachers. The United States has 700,000 currently open computing jobs, but today, only 5% of high school students study computer science per year.

“Every industry is impacted by digital technology, yet not every student has the opportunity to learn how technology works,” said Code.org CEO Hadi Partovi. “Today, computer science should be a core subject, just like basic biology or algebra …. We must ensure that standards and the curricula used across the country prioritize computer science so that all students, particularly from underrepresented backgrounds, have the opportunity to participate in our digital economy.”

Computing Literacy Initiatives

NSF Grant Supports Universal Computing Curricula

A new project to develop undergraduateuniversal computing curricula will be headquartered at Harvey Mudd College. HMC, Claremont McKenna College and Caltech are working together on ComputingAs-Literacy (CAL): Undergraduate Universal Computing, recently funded by the National Science Foundation as part of the Improving Undergraduate STEM Education: Education and Human Resources initiative.

“Computing has long been a valuable specialty and worthwhile liberal art,” says Zachary Dodds, Leonhard-Johnson-Rae Professor of Computer Science and CAL co-principal investigator at HMC, along with computer science professor Lucas Bang. “In our era, computing is also becoming a means through which other fields stage explorations and express their insights. An expressive, generative, reproducible medium, computing shares space with the venerable literacies of

Harvard Kennedy Case Study Features HMC CS

The successful effort by Harvey Mudd College to raise the percentage of women majoring in computer science is now a featured case study in the Harvard Kennedy School Case Program, the world’s largest repository of case studies for educators in government and public policy.

The case study, “Harvey Mudd College: Promoting Women in Computer Science Through Inclusive Education,” details the steps HMC faculty took to redesign the core CS introductory course, engage students and incorporate inclusive pedagogy, raising the percentage of women CS majors from 10% to over 50% in less than 10 years. The case study also includes a description of how faculty assessed the effectiveness of the redesign and pedagogical changes.

Harvey Mudd and AnitaB.org are partnering to share best practices with larger colleges and universities through the BRAID (Building Recruiting And Inclusion for Diversity) initiative.

critical reading, compelling presentation and cogent writing. Creative computing is joining that list, for many professional and personal paths.”

The goal of the project is to develop computing curricula to be offered among other universal undergraduate literacies, much like the traditional English composition class. CMC and Caltech will make computing— the intellectual and professional literacy of authoring and creatively partnering with computational artifacts—required of all their undergraduates.

“HMC has required every student to make creative computing part of their skillset since before I arrived in 1999,” says Dodds. “More and more schools are looking to adapt this kind of student support within their own mission and priorities. Partnerships among those schools help everyone.”

Students will be integral to the curriculum, its development and evolution as the new Computing 1 (Comp1) courses are piloted and assessed. Dodds believes the collaboration between HMC, CMC and Caltech will be fruitful. “These three schools certainly have distinct points of pride. Even so, all three channel their students’ ambition for broad, positive impact beyond their campus experiences. Handled thoughtfully, computing can help amplify those impacts.”

The project’s premise is that our future is personal and communal, not computational. Dodds and the project team intend CAL to replace computing as the personal and communal literacy it is. CAL’s goal is to deepen all undergraduates’ personal skillsets, both to include our era’s defining technologies—and in service to our era’s defining challenges.

Faculty and Staff Updates

Second, Two-year Appointment

Lucas Bang applies principles from combinatorics and information theory to software analysis problems. Through a recent NSF grant, Bang and computer science researchers at University of California, Santa Barbara are seeking to improve software quality assurance techniques. He is also co-director, with computer science professor George Montañez, for an NSF-funded Research Experience for Undergraduates site at HMC focusing on computer systems.

Katherine Breeden uses eye tracking to investigate the human side of computer graphics. Her other research interests include applied geometry and advanced sampling methods. She also is the administrative director of HMC’s Clinic Program.

George Montañez explores why machine learning works from a search and dependence perspective and identifies information constraints on general search processes. He leads the Artificial Machine Intelligence = Search Targets Awaiting Discovery (AMISTAD) lab, whose participants research problems in theoretical machine learning, probability, statistics and search.

Visiting Faculty

Arthi Padmanabhan, visiting assistant professor, is broadly interested in systems and networking. Her research focuses on building systems that enable scalable machine learning on real-time video data. She was a software engineer at Microsoft for three years. She received her B.A. in computer science from Pomona College in 2014 and her CS PhD from UCLA.

Blake Jackson, visiting assistant professor, teaches Natural Language Processing and Principles of Computer Science. His research area is human-robot interaction, including verbal noncompliance and clarification interactions, robot ethics, natural language generation (especially pragmatics), robot gender presentation and mental models of robot identity. He earned a PhD from Colorado School of Mines.

Papers and Presentations of the AMISTAD Lab

Research papers authored by students in Professor George Montañez’s AMISTAD Lab have been accepted to conferences, and students have gained valuable experience presenting their research to the CS community.

IEEE 2022

The IEEE 2022 International Joint Conference on Neural Networks (part of the IEEE World Congress on Computational Intelligence) accepted “Bounding Generalization Error Through Bias and Capacity,” co-authored by Montañez, Ramya Ramalingam ’21, Nico Espinosa Dice ’22 and Megan Kaye ’22. The paper was Espinosa Dice’s and Kaye’s second with the AMISTAD Lab and Ramalingam’s first. Ramalingam is a PhD student at the University of Pennsylvania, Espinosa Dice entered the CS PhD program at Cornell in the fall and Kaye has entered the workforce. Espinosa Dice and Kaye are recipients of the 2022 Don Chamberlin Research Award given by the CS department, in recognition for this and previous work.

“Identifying Bias in Data Using Two-Distribution Hypothesis Tests,” by Montañez and co-authors William Yik ’24, Limnanthes Serafini ’24, and Tim Lindsey ’23 (Biola University) was presented at the 5th AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society in Oxford, England, in August. Montañez summarizes the research:

Bounding Generalization Error Through Bias and Capacity

In supervised machine learning (i.e., classification), you are given a training dataset and you use that to produce some output (called a hypothesis) that you can use to classify future examples. While training, you have some notion on how accurate your classification hypothesis is under your training data. In the future, however, you may encounter examples you have not seen in training, so your accuracy may be different than it was in training. The degree to which you fail to generalize (properly classify) new training examples is called your generalization error. It is formally the expected difference between your error during training and your error on new examples, when you deploy your model in the real-world.

Traditional machine learning theory has developed ways of bounding how bad your generalization error can be, so that you have guarantees that your future performance won’t differ too much from your performance during training. In this paper, we develop ways of obtaining these same sorts of generalization error guarantees using geometric notions of algorithm bias and the degree to which a machine learning model can memorize training examples (e.g., its capacity). This work draws on recent results in the machine learning literature, but for the first time creates generalization bounds within the unified machine learning/AI framework called the Algorithmic Search Framework. This allows practitioners using the framework to have access to the same types of generalization guarantees previously only available within other theoretical machine learning frameworks.

Identifying Bias in Data Using Two-Distribution Hypothesis Tests

The paper presents a way of assessing whether training data is potentially too skewed (biased) to be used in training machine learning models. For example, as a hiring manager you might see that two-thirds of recent hires were male and wonder if that was a mere statistical fluke of a fair process that hires men and women in roughly equal number or if it could indicate biases within the hiring process. Before you decide to use your hiring data to train any machine learning model, the tests would alert you to the strong possibility of bias in this data. We use two-distribution statistical hypothesis tests to determine when skewed becomes too skewed to be plausibly explained as the result of a fair process. Our methods allow us to tell the user what the closest plausible explanation for their observed data is, relative to their original hypothesized explanation. A user can then determine whether or not that plausible explanation aligns with their desired notion of fairness.

Nico Espinosa Dice ’22 and Ramya Ramalingam ’21

Papers and Presentations of the AMISTAD Lab (CONTINUED)

ICAART 2022

Two papers were accepted to the 14th International Conference on Agents and Artificial Intelligence (ICAART 2022), Feb. 3–5, 2022. Both papers were accepted as full papers for oral presentation in the main conference track. “For previous iterations of ICAART, the full paper acceptance rate has been less than 20%,” says Montañez, “so getting a full paper in that track is an accomplishment. The selection for oral presentation is an additional honor.”

“Vectorization

of Bias in Machine Learning Algorithms”

This paper by Sophie Bekerman ’24, Eric Chen ’24 and Lily Lin (Biola University) concerns estimation of inductive orientation vectors, which have, until now, been a strictly theoretical quantity used for proving various bounds on algorithm performance. “This work presents methods for estimating these vectors from data, allowing us to cluster and compare black-box classification algorithms based on their output behavior alone,” Montañez says. “Since the vectors reflect underlying assumptions and biases in the algorithms, it allows us to find similarities in the inductive biases of algorithms without knowing anything about their internal structure.”

“The

Gopher Grounds: Testing the Link Between Structure and Function in Simple Machines”

This paper by Anshul Kamath ’23, Nick Grisanti ’23, Sadie Zhao ’23 (Pomona College) and Montañez builds off a 2021 paper (“The Gopher’s Gambit: Survival Advantages of Artifact-Based Intention Perception” by Montañez, Cynthia Hom ’23, Amani Maina-Kilaas ’23, Kevin Ginta ’21 [Biola University] and Cindy Lay ’22 [Claremont McKenna College]) on intention-perception in traps for artificial gophers. “In this new paper, we test and challenge some of the assumptions in the original paper (such as whether coherence is strongly or only weakly correlated with functionality) and see if producing traps using genetic algorithms changes the properties of the produced traps in terms of their coherence and functionality,” says Montañez. This paper is part of a larger body of work that includes a third paper still in development, looking specifically at applying the hypothesis tests from the Hom et al. paper to the genetic-algorithm produced traps.

Students working in computer science professor George Montañez’s AMISTAD Lab (Artificial Machine Intelligence = Search Targets Awaiting Discovery).

Amani Maina-Kilaas ’23 Recognized for Research and Scholarship

Computer science and mathematics major Amani Maina-Kilaas ’23 is a recipient of two prestigious national awards.

Maina-Kilaas received the Computing Research Association’s (CRA) 2022 Outstanding Undergraduate Researcher Award, which celebrates undergraduates at North American colleges and universities who demonstrate outstanding potential in an area of computing research. He is a member of computer science professor George Montañez’s lab AMISTAD (Artificial Machine Intelligence = Search Targets Awaiting Discovery).

“I joined the lab in the summer after my freshman year and worked with Cynthia Hom ’23, Kevin Ginta ’21 (Biola University) and Cindy Lay CMC ’22 to investigate how the ability to perceive intention can advantage virtual agents,” he says. “We created simulations to study intention perception directly through a multi-agent, prey-predator encounter and a two-player, game-theoretic adversarial situation and also indirectly through having agents analyze artifacts left behind by another. That summer resulted in three publications, two for which I was lead author and one for which I was co-lead author with Cynthia. My nomination and selection for the award is primarily based on that summer research, but I have also since continued with AMISTAD throughout the academic year, working mostly on collating past research from the lab.”

Based upon exemplary academic performance, ingenuity and unique aptitude for research, Maina-Kilaas ’23 was one of two Mudders selected by the Astronaut Scholarship Foundation to join the elite group of Astronaut Scholars for the 2022–2023 academic year.

CRA Honorable Mention

The Computing Research Association recognized computer science and mathematics major Mia Taylor ’22 with an honorable mention, given to students whose work CRA considers exemplary. She conducted research on synthesizing search algorithms with computer science professor Lucas Bang.

Offered to students pursuing degrees in STEM, the 2022 ASF Astronaut Scholarship awards scholarships up to $15,000. Other benefits include networking and mentoring opportunities with astronauts, alumni and industry leaders; participation in the Michael Collins Family Professional Development Program; and a paid trip to attend ASF’s Innovators Week, which provides an opportunity for the Astronaut Scholars to present their research at a technical conference.

Maina-Kilaas has interned as a software engineer at Stripe and tutored peers in programming languages and introductory

computer science. This summer, with University of Southern California computer science professor Muhao Chen, he researched natural language understanding (specifically, machine common sense) in the Language Understanding and Knowledge Acquisition Lab at the Information Sciences Institute.

The work of a researcher appeals to him, so Maina-Kilaas will pursue a PhD in computer science. “I would rather spend my career generating new knowledge and advancing the field as a university professor or as an industry researcher,” he says.

“As a model for search problems, we studied deduction games: those where you make guesses and learn information about some secret value from each guess,” she says. “Solving a deduction game—figuring out the correct sequence of guesses to locate a secret for each possible secret—corresponds to creating a

search algorithm. In my time with this group, I implemented an algorithm for solving deduction games, performed experiments and derived some theoretical results.” After graduation, Taylor joined Meta as a software engineer.

2022 Harvey Mudd College Leadership Awards

For the Division of Student Affairs’ 2022 Leadership Awards presentations, community members gathered via Zoom webinar for the ceremony to celebrate students, faculty and staff for their contributions on campus and beyond. Here are CS students who received awards.

Established by family and friends in memory of the HMC humanities professor, the Shirlynn Spacapan Memorial Scholarship recognizes students for their community service.

Kathleen Durkin ’23 (mathematical and computational biology) has worked in and volunteered for Mudd Residential Life. She has been a mentor for Sontag and helps facilitate Orientation, plans the First-Year Experience Programs and organizes dorm events. She spent summer 2021 living on campus, working as a resident assistant and tour guide and doing research in the Department of Biology with Professor Catherine McFadden with whom she barcode-sequenced specimens of soft coral to improve species delimitation.

Established by Dana Seaton ’06, and with support from Warren Katzenstein ’04 and Nate Yoder ’06, the Dean Chris Sundberg Prize ($500) recognizes a rising junior who demonstrates exceptional leadership and a positive impact on the College community.

Camilo Morales ’24 (CS/math) is the copresident of Society of Professional Latinos in STEM, has served as an Summer Institute mentor, will be a Chicano Latino Student Affairs sponsor, grutors for CS5 and volunteers with Uncommon Good. He mentors classmates, helping them adjust to life at Mudd and gain a sense of belonging. A nominator wrote, “As an SI mentor, he had dinner every single week with his mentees in order to provide them with a sense of community and an older student that they could count on as a friend. Camilo goes above and beyond … He encourages and inspires so many and has shown the value of helping others in your community.”

Fourth Place in Citadel Terminal Global Championship

A team of Harvey Mudd College students placed fourth in Citadel’s 2022 TERMINAL global championship, winning a $5,000 prize and beating teams of experienced players and PhDs from top universities around the world.

In November 2021, HMC students placed first and third in the TERMINAL West Coast regional event in November, and they were invited to the summer global championship. Members of the first-place team— Milo Knell ’25 (CS and math) and Alan Wu ’25 (CS and math)—joined with a member of the thirdplace team, Sahil Rane ‘25 (CS and math), to form the new team. All participated in summer research in the AMISTAD Lab (Artificial Machine Intelligence = Search Targets Awaiting Discovery) of computer science professor George Montañez.

Their experience at the West Coast competition and their work together on campus helped give the Harvey Mudd team the edge in a contest where Citadel gathers

the best players from around the world to compete, allowing the asset management firm to identify talented programmers. Competitors write code and strategize to beat other teams in TERMINAL, a tower defense game where players build a base and send units to attack the opponent. Players pick moves that are executed simultaneously. Health is lost when an enemy unit reaches the opponent’s edge, and the game ends when a player reaches 0 health.

The HMC team gave this description of its strategy: “We rewrote the pathfinding code of the official game library, to create a simulator that’s fast enough to evaluate ~50 board states per round. We made some simplifying assumptions about the game to allow us to simulate many more board states at a minimal cost of accuracy. Using this simulator, we were able to test out many different attack strategies to find out which was optimal. We came up with strategies to adapt our base to maximally exploit weaknesses in the enemy setup. In our

strategy, we do not build our base until the opponent does so we can ensure that we mirror their base. Most players have a strong side and a weak side, and by matching our strengths to their weak we are confident we can exploit their weak side more than they can ours.

“Another thing we are proud of is our smart banking, where we compute the tradeoff between sending units now and next turn versus waiting for an extra turn to get more money to send a stronger attacking force. Since saving up for several rounds is so impactful, we wrote a heuristic along with simulations to predict when the enemy would send their attack so we could counter it by sending defensive units.”

Wu says, “Part of the reason we did so well is that we sent many units to stop enemy attacks and generally had fewer times where we sent defensive units when the enemy did not attack (a waste of money).”

2022 Summer Research Program

Characterizing the Behavior of Neural Architecture Search Algorithms and Mutability of Architectures Advisor: George Montañez Students: Devon Tao, Marina Ring, Kelly Hamamoto, Joseph Lee

IOTTA Trace Repository Advisor: Geoff Kuenning Students: Marina Kazarian, Laurie Luo

Multi-Tier Caching Advisor: Geoff Kuenning Students: Julia Hsing, Lilly Lee

Deep Range to Range Regression in Model Based Reinforcement Learning Advisor: Erin Talvitie Student: Alina Hu

Scripting for All Advisor: Zachary Dodds Students: Waverly Wang, Bella Jariel, Martin Deng, Nessa Kiani

Experience-Replay Prioritization in Model-Free Reinforcement Learning Agents Advisor: Erin Talvitie Student: Ryan Butler

Exploring Randomly Wired Neural Networks for Climate Model Emulation Advisor: Sam Silva Student: William Yik

Athena Network Advisor: Zachary Dodds Students: Ayman Abdellatif, Ammar Fakih, Lucas Welch, Andrew Faber

Use Object-level Representations in Reinforcement Learning to Improve Learning Efficiency in Atari Games Advisor: Erin Talvitie Student: Zoe Shao

Embrace

Advisor: Zachary Dodds Students: Arushi Malik, Maxine Liu

GradescopeCalendar Advisor: Zachary Dodds Students: Caleb Wheeler, Arisa Cowe, Kaitlynn Gray

Comparing Spatiotemporal Attendance in Deep Convolutional Networks and Human Observers Advisor: Calden Wloka Students: Richard Chang, Malia Morgan

Profiling Compression Algorithms and Timing Methods to Determine Best Approach to Measuring the Physical Complexity of Images Advisor: Lucas Bang Student: Isabel MacGinnitie

Learning from User Behavior: A Trip-Level LabelAssist Algorithm for Longitudinal Mobility Data Collection Advisor: K. Shankari Student: Hannah Lu

Path Complexity Predicts Path Explosion in Symbolic Execution Advisor: Lucas Bang Students: Eli Pregerson, Shaheen Cullen-Baratloo

Classifying Self-Reported Intimate Partner Violence in Tweets with Multiple BERT-based Models Advisor: Akshat Gupta Students: Alec Candidato

The Search for a Search for a Search... Advisor: George Montañez Students: Carmel Pe’er, Camilo Morales, Elana Elman

Tiger Che Continuous Targets in ASF Advisor: George Montanez Students: Forrest Bicker, Milo Knell, Sahil Rane

Semantic-Syntactic Density of Regular Expressions Advisor: Lucas Bang Students: Lilian Zhu, Jenny Granados (CMC)

CS/ Math Proofcheck Project Advisor: Chris Stone Students: Henry Hammer, Nanako Noda

CS Clinic Projects

Computer Science Clinic

Alation

Federated Learning Platform for Alation Machine Learning

Liaisons: Ian Danforth, Yuhong Sun, Abhimanyu Seth, Andrea Levy ’11

Advisor: Leif Zinn-Brooks Students: Fred Qin (PM-F), Mengjun Zhao (PM-S), Jingyi Liu, Giovanni Castro, Anan Aramthanapon

California Urban Forests Council

A Mobile App to Engage Elementary-Age Students in Urban Forestry and Tree Health Liaisons: Cynthia Chavez, Christopher Crippen, Joey Crippen, Deb Etheredge, Linda Mendez, Kanami Otani, Mike Palat, Andy Trotter, Tim Womick, Advisor: Ben Wiedermann

Students: Elissa Hou, Jess Jacobs, Thuy-Linh Le (PM-S), Hilary Nelson (PM-F), Alex Nghiem, Avalon Vinella

Cradlepoint

Supporting Proof of Concept Testing Liaisons: Lynn Gates, Aaron Ebling, Alex Terrell, James Hawk, Chris LePeters

Advisor: Melissa O’Neil

Students: Jessica Kwok (PM-F), Dylan McGarvey (PM-S), Matt Tran, Natasha Wong

CrowdStrike

Autoscaling Algorithm for Managing Clients on Kubernetes Clusters

Liaisons: Luke Hunter ’03, Julius Lauw ’20, Jonathan Fuentes, Eric Schow Advisor: Lucas Bang Students: Joshua Cheung, Isabel Duan, Thomas Fleming (PM), Rachel Wander, Wayne Ying

Cubic Transportation Systems

Performance Testing for an Automated Fare Collection System Liaisons: Cheng Yeh, Kiran Uppalipatti, Galen Chui ’05 Advisor: Zachary Dodds Students: Kristen Mason (PM), James Karsten, Kari Schultz, Rose Didcock, Xander Hirsch

Esri

Bridging Geographic Information Systems and Computing Education Liaison: Kylie Donia ’03 Advisor: Geoff Kuennning Students: Lee Beckwith (PM-S), Skylar Gering (PM-F), Reymon Pedroza, Ashley Tung

Factor Programming Language

The Factor Programming Language: Game Development Liaison: John Benediktsson ’01 Advisor: Melissa O’Neil Students: Catherine Wu (PM-S), Sam Freisem-Kirov (PM-F), Jason Chen, Cher Ma, Santiago Rodriguez

Google

Helping Devices Work Better Together Liaisons: Ryan Ausanka-Cruues PZ ’05, David Samuelson, Mike Tsao Advisor: Geoff Kuenning Students: Ashkon Aghassi, Ezra Burk, Howard Deshong (PM-F), William La, Santi Santichaivekin (PM-S)

HMC INQ

A Drone System for Diverting Large Pests: Exploring the Possibility of Cloudifiers in Our Homes Liaison: Josh Jacobs ’98 Advisor: Zachary Dodds Students: Ingrid Tsang (PM-F), Cathy Chang (PM-S0, Erik Tarango, Fabrizia Mugnatto, Tristan Johnson

Los Angeles Unified School District Expanding Enrollment with a Guided School Matchmaking Tool Liaisons: Derek Chau ’97, Jodie Newbery, Michael Kessler, William Johnston Advisor: Erin Talvitie Students: Catherine Jang (PM-S), Henley Sartin (PM-F), Elizabeth Song, Jennifer Zecena, Macy Mills

Microsoft Image Similarity in PowerPoint Designer Liaisons: Michael Bentley, Jon Ko, Sarah Stein ’12 Advisor: Calden Wloka Students: Devika Chipalkatti (PM-F), Emily Lu (PM-S), Ben Lucero, Sofiane Dissem, Swamik Lamichhane, Kendah Abugharah

Proofpoint Inc.

Defending NLP Models Against Adversarial Attacks Liaisons: Cameron Malloy, Adam Starr PO ’18 Advisor: Blake Jackson Students: Meg Kaye (PM-F), Dana Teves (PM-S), Emily Chin, Skylar Litz, Keizo Morgan

Pure Storage

Data Replication for High-Performance Distributed Systems Liaisons: Andrew Bernat ’99, Dale Cieslak, Teddy Dubno ’19, Rebecca Gruver Advisor: Mark Kampe Students: Monia Yao (PM-F), Kevin Ji (PM-S), Max Mingst, Jeremy Tsai, Jacob Yoo

Quantcast

Feat: A Domain-Specific Language Liaisons: Rory Carmichael, Jackson Newhouse ’12, Scott McCoy Advisor: Christopher A. Stone Students: Theo Bayard de Volo (PM-F), Kian Chamine (PM-S) Jarred Allen, Charles Meng, Qualan Woodard

Rockerbox

Early Anomaly Detection in Marketing Data Liaisons: Kevin Hsu ’10, Mike Cen, Rick O’Toole ’10 Advisor: George Montañez

Students: Bettina Benitez, David Webber, Jacqueline Choe, Nicholas Espinosa Dice (PM), Noah Smith

Samba TV

Automatic Annotations of Media Streams Liaisons: Brian Cruz, Wayne Yang ’99 Advisor: Leif Zinn-Brooks

Students: Maya Abo Dominguez (PM-F), Aryana Villela Mugnatto, Mrjun Natarajan (PM-S), Daniel Sealand, Xintong Wang

2021–2022 CS Clinic Projects (CONTINUED)

Schmidt Academy and Cai Lab (Caltech)

webFish: Cloud-Based Spatial Genomics Visualization

Liaisons: Jonathan White, Lincoln Ombelets (F) Advisor: Kartherine Breeden Students: Ignacio Lista (PM-S), Shinn Taniya (PM-F), Alex Hadley, Michelle Lee, Adam Walker

ServiceNow

Catching Uncareful Code: Static Analysis of (Arbitrary) Data Queries

Liaisons: Kyle Barron-Kraus, Magaly Drant, Marie Harrington Advisor: Beth Trushkowsky

Students: Ria Gopu (PM-S), Tatsuki Kuze (PM-F), Dolly Efuye, Kip Lim, Josh Cordova

Shopify Inc.

Online Shopping in VR

Liaisons: Kathi Taylor, Joe Doyle, Angela Chen CMC ’21, Chris Landry, Frank Liu ’14, Daniel Beauchamp Advisor: Jim Boerkoel

Students: Kyra Clark (PM-S), Miles Bernhard (PM-F), Nicole Garcia, Max Guo, Tyson Saena, Roxanne Oglesby

Single Cell Research Initiative at Memorial Sloan Kettering Cancer Center (MSKCC)

Querying and Visualizing Single-cell Data Liaisons: Dr. Roshan Sharma, Dr. Dana Pe’er Advisor: Yi-Chieh (Jessica) Wu Students: Erin Burke, Christina Catlett, Eve Kazarian, Natalia Orbach-Mandel (PM-F), Julia Qian (PM-S)

TechEquity Collaborative

Mapping the Disparate Effects of California’s Prop 13 Liaison: Matt Brooks Advisor: Xanda Schofield ’13 Students: Anna Singer (PM-F), Yury Namgung (PM-S), Arun Ramakrishna, Kripesh Ranabhat, Mariesa Teo

Tradeweb

Anomaly Detection in High-Performance Trading Systems

Liaisons: Stefan Kutko, Jeremy Jess ’20 Advisor: Elizabeth Sweedyk Students: Wenxuan Zhang (PM), Allen Wu, Nicholas Perez Vergel, Nick Tan, Nick Dazell

CS Research

A Robust and Responsive Interface to Analyze Spatial Genomic Data Student: Michelle Lee Advisor: Katherine Breeden

Computer Science Class Project, CS 186: Computer Science Research/ Independent Study Advisor: Xanda Schofield ’13

2021–2022 Departmental Awards & Recognition

Don Chamberlin Computer Science Research Award

Nicholas Espinosa Dice, Megan Larisa Kaye, Tatsuki Kuze, Santi Santichaivekin, Mia Taylor

Class of ’94 Award

Vibha Rohilla, Ingrid Tsang Clinic Team Award

Sofiane Dissem

Skyler Alexis Gering Eve Kazarian Swamik Lamichhane Joaquin I Fuenzalida Nunez Natalie Orbach-Mandel Julia Flora Qian Ashley Tung

Class of 2022 Departmental Honors

Emily Win Chin

Howard Cooper Deshong IV

Isabella Duan

Ryan Edmonds

Nicolas Espinosa Dice

Thomas Michael Fleming

Chenlian Fu

Skylar Alexis Gering

Kevin Ji

Megan Larisa Kaye

Tatsuki Kuze

William La

Thuy-Linh Thanh Le

Ki Pheng Lim Ignacio Lista Rosales

Clinic Individual Award

Nicholas Espinosa Dice

Julia Flora Qian

Thomas Michael Flemming

Computer Science Service Award

William La, Ki Pheng Lim, Julia Flora Qian

Wing and Ellen Tam Award

Josh Cordova, Sofia Kai Devin, Sofiane Dissem, Emily Lu (Scripps), Benjamin Joseph Bracker (2021)

Skylar Linda Heffernan Litz

An Khanh Nguyen

Julia Flora Qian

Vibha Rohilla

Santi Santichaivekin

Kariessa Corinna Schultz

Jeremy E. Tsai

Ingrid Tsang

Adam Lawrence Walker

Huaxiaoyue Wang JiyuanWu Wayne Ying Mengjun Zhao

CS Majors, Environmental Analysis Concentration

Skylar Alexis Gering, Shanni Lam, Noah Jerry Ming-Te Smith, Ingrid Tsang

First-Gen Pride

It wasn’t until her junior year of high school that Shanni Lam ’22 realized she was on her way to becoming a first-generation college student.

“I just assumed that most people were first-gen, because that’s how it was in my community,” she says. “I didn’t understand why colleges thought it was such a big thing, but now that I attend Mudd, I’m a lot more proud and a lot more vocal about it.”

Today, the math/computer science major is helping other first-generation students find their way. Lam leads Project Decode, a studentrun organization for first-generation and/or low-income students, and served as a mentor for Mudd’s Summer Institute program, which helps underrepresented incoming first years with the college transition process. “First-generation students have to overcome a lot more barriers than other students, so I have a newfound appreciation for my identity,” Lam says.

What are the barriers first-generation college students face?

An obvious barrier is that we don’t have parents who can help with applying to college. First-gen students are also often low-income and attend more average (or below average) public schools, where the curriculum is less likely to prepare them for a college curriculum, especially Mudd’s curriculum. Another big barrier is a feeling of alienation. Prior to Mudd, I went to schools where most students were people of color and on free/reduced lunch. I only knew a handful of students whose parents went to college. Now, it’s weird hearing people tell me their parents are research biologists or engineers. It’s also weird hearing people speaking to their parents in full English, seeking job advice and getting help on their engineering homework, while I do the opposite, helping my parents find jobs. It reminds me how deeply class inequality hits in America.

Tell us about Project Decode.

Project Decode is Mudd’s student-led affinity group that provides guidance and networking

for first-generation and low-income students. I serve as the group’s co-president and help plan many of the events, including workshops to help students understand things like financial aid and healthcare. The organization is also a space for people to hang out, meet new people and discuss the first-generation lived experience and issues at Mudd.

Through your experiences with Project Decode and Summer Institute, what have you learned about how Mudd can support its first-gen students?

A major way is through recruiting and admissions. We need to have a more socioeconomically diverse student body. It’s important for first-gen students to know that there are others just like them at Mudd. Firstly though, most first-gen students likely won’t even know what Mudd or the other Claremont Colleges are. I didn’t until I lived literally 15 minutes away from Claremont my junior year, and even then, I only ever felt pushed toward public colleges.

You study many languages. What do you enjoy about that?

I come from an interesting multilingual background. My parents and grandparents are ethnically Chinese, born and raised in Vietnam, so they speak Cantonese and Vietnamese. It wasn’t until recently that I learned that my dialect of Cantonese apparently has a Vietnamese accent and sounds somewhat old-fashioned and rural, as if I was from the ’60s. This motivated me to learn more about Cantonese, as it reinforced that every language has its own rich varieties. I am also learning Mandarin because it’s interesting to see the phonological and grammatical similarities and differences between Mandarin and Cantonese.

Because of Sinospheric influence, I can also find similar sounding words in Vietnamese and Korean, the latter of which I began learning because I was briefly interested in K-pop and K-dramas. Since eighth grade, I’ve studied Spanish because it was very commonly spoken in the places I lived and most often offered at

the high schools I attended. It’s very enriching to learn about different cultures and writing systems.

What do you like to do in your spare time?

I consider myself a film buff, so I like to watch a lot of movies. I also like to go to the desert; it’s my favorite ecosystem. That sounds kind of weird, but it’s a nice place with its own flora and fauna with minimal light and noise pollution to slow down and think peacefully. I also like to go to different ghost towns or abandoned places. When I’m driving and see abandoned structures, I wonder what happened to them and feel nostalgic. It’s cool to explore and think about the past.

What do you hope to do after graduation?

There are a few paths I’m considering. One is data analytics. More recently, I’ve been thinking about consulting. I feel like I’m good at quick math and being able to provide recommendations for other people. It would allow me to use more of my communication skills. I’ve also thought about being a community college professor because I’ve had some experience with tutoring and find it to be more accessible and widely impactful.

Reprinted from Mudd Magazine, fall/winter 2021

Spotlight on Kurt Dresner ’02

Kurt Dresner (CS/math) received the HMC Alumni Association’s Spotlight Recognition Award. He is an innovator in the field of autonomous intersection management. He and a co-author were awarded the International Federation on Autonomous Agents and Multi-Agent Systems’ Influential Paper Award for setting a new direction in the research of transportation systems for autonomous vehicles. In a world where drivers don’t get distracted, don’t fall asleep and can plan using more than just red, yellow and green, there’s no need to stop for an empty intersection. He got to work imagining such a future and the ways we could coordinate autonomous vehicle traffic for both increased throughput and safety.

GOLDen Moments

GOLD (Graduates of the Last Decade) Society acts as a bridge between the student experience and the greater Mudd alumni community. Through this program, all recent alumni are able to participate in exclusive professional development opportunities, social events, community service initiatives and more. Hosts choose the date/time, venue and activity for their event, and the Office of Alumni and Parent Relations helps with logistics and invitations. CS alums who served as hosts during 2021–2022 were Obosa Obazuaye ’14 (Happy Hour in Escondido), Arielle Isaacs ’21 and Teal Stannard ’18 (Happy Hour in Seattle), and Julia Read ’20 (Pizza & Board Games in Vancouver).

Find out more at alumni.hmc.edu/GOLD

Happy Hour in Escondido

Happy Hour in Seattle

Pizza and Board Games in Vancouver

1972

John Sell: “AMD corporate vice president for Strategic Silicon Solutions architecture. Customer products incorporating S3 designs include Microsoft Xbox Series X and S, Sony PlayStation 5, and Valve Steamdeck.”

1995

Gregg Snodgrass: “In my 26th year at IBM working on enterprise data warehouses. Spending time with my wife tending our backyard as our son will be entering year two at UIUC.”

1997

Joe Beda: “Started Google Compute Engine and Kubernetes while at Google. Left to found Heptio, an enterprise Kubernetes company that was sold to VMware. Left VMware very recently and looking forward to ‘retirement’ while I figure out what to do next and focus on my family, Rachel ’97, Anne and Nora.”

2001

Gillian Allen: “After a few years out of work to be a stay-at-home-mom, I recently rejoined Microsoft! This time, I’m on the Bing Maps and Geospatial team implementing routing algorithms at scale.”

2002

Drew Levin: “I received my CS PhD from the University of New Mexico in 2016 with a focus on complex systems modeling and analysis, and I have been working as a research scientist at Sandia National Labs ever since. During the early days of COVID, I led Sandia’s Data Science Covid Modeling team. I currently lead a diverse set of projects including applying deep learning medical data to improve health risk prediction and using deep reinforcement learning to help regulate the electric grid. I live in Albuquerque with my wife, Meg, my daughter, Norah (9), and my son, Drake (6) and spend my free time playing board games with my family and ultimate frisbee with my friends. Cheers!”

2002

Eric Heitzman: “I became an ethical hacker and penetration tester for a while (Foundstone, MANDIANT), then started working with security software vendors (Ounce Labs, IBM, Qualys, Security Compass). My career started as intensely manual, hands-on security testing and progressed toward automation and scalability. Today, I work with threat modeling software. I also invest in several startups, including one founded by Mudder Tim Morgan (www.DeepSurface.com)”.

2003

Ed Miller: “I am completing my 11th year teaching math and computer science and my fifth year at Athens Academy in Athens, Georgia. I started the computer science program at Athens Academy four years ago with a whopping two students in the first class, and it’s grown to over 30 students in a two-course sequence. I’ve benefited greatly from the CS 5 resources that HMC has posted online—thank you so much for making those available. Next year, I will take over as the Math Department chair, continue to develop the CS program and continue to search for ways to engage students in mathematical thinking.

2010

Joshua Swanson: “PhD in mathematics from University of Washington in Seattle in 2018; postdoc at UCSD 2018–2021, postdoc at USC in L.A. 2021 to present. Also, finishing a lovely trip to Iceland as I write this!”

2011

Audrey Lawrence: “Philip Winston ’95 and I chatted about time series databases on a Software Engineering Radio podcast episode last fall: se-radio.net/2021/11/episode-484audrey-lawrence-on-timeseries-databases/. ”

2014

Miranda Parker: “I’ve just wrapped up a postdoctorate at the University of California, Irvine and accepted an assistant professor position at San Diego State University, starting fall 2022. I’m excited to channel everything I learned from my CS profs at HMC as I start teaching CS undergrads!”