UNIVERSITY OF PITTSBURGH
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S WA N S O N S C H O O L O F E N G I N E E R I N G
RESEARCH APPLICATIONS FOR BUSINESS AND INDUSTRY
Internet of Things
Making Research Work @ PITT
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RESEARCH APPLICATIONS FOR BUSINESS AND INDUSTRY
Internet of Things
Table of Contents Neuromorphic Computing – Yiran Chen, PhD and Helen Li, PhD.................................................................. 1 Additive Manufacturing of Functional Materials for Power Generation, Sensing and Cooling – Markus Chmielus, PhD........................................................... 2 Morphogenesis and Developmental Biomechanics – Lance Davidson, PhD.......................................... 3 Nanoionic and Electronic Devices – Susan Fullerton, PhD........................................................................ 4 Rationally Tailoring Surface Topography to Design in Surface Functionality – Tevis Jacobs, PhD.................................................................................................... 5 Advanced IoT Architectures and Prototyping – Alex Jones, PhD............................................................. 6 Integrated Power Generation, Energy Storage and Traffic Management in Wireless Communication Networks – Alexis Kwasinski, PhD..................................................................................... 7 Real-Time, Scalable, and Elastic Processing of Streaming Data – Alex Labrinidis, PhD........................................................................................................... 8 Cryptographically Enforced Access Controls for Outsourced Data Stream Processing – Alex Labrinidis, PhD...................................................................... 9 Energy-Efficient Sensing and Computing for Microgrid Performance – Gregory Reed, PhD............................................................................................. 10 Enhancing Human Health via Machine Learning and Cyber-physical Systems – Ervin Sejdi’c, PhD............................................................................................... 11 Multiscale Modeling of Our Immune Response – Jason Shoemaker, PhD............................................ 12 Lightweight Structure Design Optimization for Additive Manufacturing – Albert C. To, PhD................................................................................................ 13 Economics and Policy Aspects of Radio Spectrum Sharing – Martin Weiss, PhD.............................. 14
Research excellence has been a pillar of the University of Pittsburgh’s ascension into the top tier of public universities across the United States, and around the world. Our diverse portfolio of research extends throughout our engineering, medicine and science programs which are recognized for their interdisciplinary approach to problem-solving. Because of the growing relationships between these fields, the University is fast-tracking exploration of new opportunities in the massive research and development field known as the Internet of Things or “IoT.” The IoT is a paradigm that reveals the fast-growing world of connected objects and systems which are creating new ways to improve operations, product development, manufacturing equipment and processes, supply chain dynamics and more of the challenges businesses face in a global marketplace. The opportunities IoT presents are great, but there is still uncertainty for companies, as with any emerging trend. Questions remain about how to accurately assess the business opportunities in the Internet of Things, how to build a technology stack (the layers of hardware, software applications, operating platforms, and networks that make up IT architecture) to support current and future Internet of Things applications and devices, and whether companies should invest in open or proprietary technologies. The University of Pittsburgh is seeking interested partners for projects and/or services in the Internet of Things space. This booklet provides a glimpse of where Pitt’s strengths lie today, and where we’re seeking these opportunities to work more closely with industry. If you are interested in exploring how you and your company can collaborate with one of the nation’s best public research universities, please contact Dr. Ervin Sejdi’c, Director of the RFID Center for Excellence at esejdic@pitt.edu, or via phone at 412-624-0508.
David A. Vorp PhD Associate Vice Dean for Research and William Kepler Whiteford Professor of Bioengineering Ervin Sejdi’c, PhD Assistant Professor of Electrical and Computer Engineering Director of the University of Pittsburgh RFID Center for Excellence
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Neuromorphic Computing • Neuromorphic computing systems refer to the computing architecture inspired by the working mechanism of human brains • New material/devices for massively parallel operations with closely coupled memory and computing • Ultra computing performance at extremely low power, leading to 100X to 1000X less energy consumption • Superior to conventional systems for cognitive applications, such as image recognition and natural language • Essential for mobile cyber-physical systems
For more information, please contact Yiran Chen, PhD
Helen Li, PhD
yic52@pitt.edu
hal66@pitt.edu
Professor, Electrical and Computer Engineering
Professor, Electrical and Computer Engineering
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Additive Manufacturing of Functional Materials for
Power Generation, Sensing and Cooling • Additive manufacturing of Heusler alloys that have a variety of functional properties: • Shape change due to applied magnetic field (actuation) • Change of magnetization due to actuation (power generation and sensing) • Magnetocaloric effect used for solid state cooling (up to 30% more efficient) • High temperature shape memory effect • Additive manufacturing results in complex shapes that can be adapted to application • Functionality can be designed to meet desired properties • Use of a variety of additive manufacturing techniques can optimize metal powder use and properties • Characterization of all properties of additive manufactured metals and functional materials including mechanical properties, phase and microstructure characterization
For more information, please contact Markus Chmielus, PhD
Assistant Professor of Mechanical Engineering and Materials Science
chmielus@pitt.edu
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Morphogenesis and Developmental Biomechanics • Design principles of tissue self-assembly • Micromechanical test systems for extremely small and ultrasoft materials • Integration of high resolution dynamic imaging with mechanical tests
• Computational simulation of complex Multiphysics problems from tissue biology • Microfluidic technologies to investigate biological tissue control circuits • Engineering technologies applied in the fields of regenerative and cancer biology
For more information, please contact Lance Davidson, PhD
Associate Professor of BioEngineering, Developmental Biology, and Computational and Systems Biology
lance.a.davidson@pitt.edu
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Nanoionic and Electronic Devices Ion-gated, 2D Crystals for Low-power, Beyond CMOS Transistors
2D Nanoionic Memory
Logic 0, OFF state high resistance
FUNDING SRC/DARPA (Low-Energy Systems Technology Center)
FUNDING NSF-ECCS/GOALI
Logic 1, ON state low resistance
Vanishing Programmable Devices for Security Programmed
SEEKING FUNDING
De-Programmed
For more information, please contact Susan Fullerton, PhD
Assistant Professor of Chemical and Petroleum Engineering
fullerton@pitt.edu
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Rationally Tailoring Surface Topography to
Design in Surface Functionality • Surface adhesion, wetting, friction and wear, and electrical and thermal transport • These depend not only on surface chemistry, but also critically on surface topography • Analytical models show a strong dependence on sub-nanometer-scale roughness – which cannot be controlled using conventional fabrication strategies • We use leading-edge manufacturing approaches and novel surface characterization to establish the science and technology of roughness-tailored surface properties
For more information, please contact Tevis Jacobs, PhD
Professor of Mechanical Engineering and Materials Science
tjacobs@pitt.edu
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Advanced IoT
Architectures and Prototyping Prototypes and experimental test-bed for wireless sensor networks (WSNs)
Advanced Emerging Memory Integration for High Density and Low Power
• Lynx: Self-organizing WSN layer
• STT-MRAM and domain-wall memory
• Ocelot: Grid computing for WSNs
• Tradeoffs and optimizations of access speed, density, and energy
Memory/Communication Co-design for Cross-layer WSN optimization
Application of WSN test-bed in different domains
• Data reorganization for enhanced lightweight in-memory compression
• Indoor environmental quality (IEQ) for green building design
• Integrated packet compression
• Bio-instrumentation applications
PALMTOP DEVICE Distributed Computing in WSN Ocelot: a distributed computing engine Lynx: a self-organizing WSN
APPLICATION LAYER OS LAYER: iOS, ANDROID
Memory Network Co-design Packetization of hardware-compressed memory pages for fast WSN transfer
NETWORK LAYER MEMORY LAYER
PROCESSOR
Check 0
…
COMPRESSION & DECOMPRESSION UNIT
Compressible?
… ...
NETWORK INTERFACE Compressed Packet
MEMORY PAGE Uncompressed REP-4 B8D2 .. . ZERO
REDUCED PAYLOADS
PACKETIZATION UNIT
Concatinater
MAIN MEMORY
MEMORY BANK memory page memory page memory . . page .. memory page
Compression Vector
MEMORY
Payload 1 Payload 2 Payload 3
PACKET
Ad-hoc node
HEADER PAYLOAD Compression Concatinated Code Data
For more information, please contact Alex Jones, PhD Professor of Electrical and Computer Engineering
akjones@pitt.edu
Lynx
Dedicated WSN node
Ocelot
Dashboard or kiosk
Sensor
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Integrated Power Generation, Energy Storage and Traffic Management in
Wireless Communication Networks • Coordinated energy management in microgrids for wireless communication networks cell sites for • Increased use of renewable energy sources • Increased resiliency, availability and sustainability • Reduced vulnerability and dependence on lifelines • Energy storage (e.g., batteries) cost reduction of up to 25 percent and 10 percent improvement in battery life.
• 40 percent footprint reduction of PV arrays. • Up to 40 percent resiliency improvement depending on the configuration. • This solution can be directly extended into other applications, such as residential energy management systems.
For more information, please contact Alexis Kwasinski, PhD
Associate Professor of Electrical and Computer Engineering
akwasins@pitt.edu
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Real-Time, Scalable, and Elastic Processing of
Streaming Data
• Velocity Dimension of Big Data: data at speed • Data stream management systems (DSMS) • Input: ``can-only-see-once,’’ never-ending data streams
• Perform smart scheduling of different operators (esp., in the presence of different importance classes of continuous queries) • Develop efficient ways to support data aggregation (over sliding time windows)
• Execute: stored continuous queries (looking for patterns/events of interest)
• Up to four orders of magnitude better execution plans!
• Output: never-ending results stream • Provide real-time guarantees (e.g., maximum delay tolerance)
For more information, please contact Alex Labrinidis, PhD
Associate Professor of Computer Science Co-Director, Advanced Data Management Technologies Laboratory
labrinid@cs.pitt.edu http://labrinidis.cs.pitt.edu Joint work with Panos Chrysanthis
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Cryptographically Enforced Access Controls for
Outsourced Data Stream Processing • Our proposal: PolyStream
• Distributed Data stream management systems (DDSMS) • Data providers lose access control over their data as soon as it leaves • E.g., fitbit data that is processed at the cloud and potentially shared with select others, as specified by user (=data provider)
• cryptographically enforces specified access control policies (in real-time)
• scheme for distributing and managing keys based on user attributes
• allows computation over encrypted data at intermediary nodes (as permitted)
• handles any type of query • handles policy changes in real-time (using punctuations)
plain-text DSMS
Po up to 550x
am
re
St
ly
Efficiency
best
am
re
St ce
r Fo
worst
worst
full-encryption DSMS
Confidentiality
best
For more information, please contact Alex Labrinidis, PhD
Associate Professor of Computer Science Co-Director, Advanced Data Management Technologies Laboratory
labrinid@cs.pitt.edu http://labrinidis.cs.pitt.edu Joint work with Panos Chrysanthis
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Energy-Efficient Sensing and Computing for
Microgrid Performance
• Laboratory Power Ratings: AC: 5MVA, 15kV / 4160V / 480V / 208-V; DC: 1MVA, 1.5kV • Base Hardware: Reconfigurable microgrid layout/ network at all bus voltages to evaluate system operations and automation techniques under increased DER penetration, etc. • System Sensing: Utility/Industrial grade SCADA and EMS system for measuring and monitoring system events in a controlled, high power environment + u-PMU, relays, automation • Industry-specific Technology: Social laboratory environment to meet the needs of the future electric utility with the aid of power equipment manufacturers. • Utility/Industrial Grade Computational Power: Real-Time Digital Simulation (RTDS) capability to evaluate computer based, hardware controllers in grid equipment.
Electric Power Technologies Lab @ the Energy Innovation Center, Pittsburgh
For more information, please contact Gregory Reed, PhD
Director, Center for Energy Director, Electric Power Systems Laboratory
gfr3@pitt.edu
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Enhancing Human Health via
Machine Learning and Cyber-physical Systems • Developing novel machine learning algorithms to: (a) detect walking instabilities in older adults, (b) swallowing difficulties in patients with neurological disorders, (c) predict smoking urges in heavy smokers wanting to quit smoking; (d) infer about changes in brain networks to understand their effects on functional outcomes. • Developing small medical implantable and non-implantable gadgets that can be used to infer about a patient’s health beyond the current gold standards.
For more information, please contact Ervin Sejdic, ’ PhD
Professor of Electrical and Computer Engineering
esejdic@pitt.edu
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Multiscale Modeling of Our Immune Response • Prioritize drug targets
• Guide patient-specific treatment design
• Identify “optimal” immune responses
• Predict long-term effects of toxin exposure
For more information, please contact Jason Shoemaker, PhD
Professor of Chemical and Petroleum Engineering
jason.shoemaker@pitt.edu
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Lightweight Structure Design Optimization for
Additive Manufacturing
Advantages of Incorporating Cellular Structure into AM Parts/Components • Reduce manufacturing costs
• Reduce weight and energy consumption
• Reduce material use
• Relieve residual stress
Final Design
For more information, please contact Albert C. To, PhD
Associate Professor of Mechanical Engineering and Materials Science, CNG Faculty Fellow
albertto@pitt.edu
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Economics and Policy Aspects of
Radio Spectrum Sharing • Enforcement of spectrum sharing agreements
• Automated detection, forensics and adjudication in shared spectrum system • Modelling of secondary markets for radio spectrum • Public policy for database-based spectrum sharing systems • Governance of shared spectrum systems
For more information, please contact Martin Weiss, PhD
Professor of Telecom & Networking
mbw@pitt.edu
The information printed in this document was accurate to the best of our knowledge at the time of printing and is subject to change at any time at the University’s sole discretion. The University of Pittsburgh is an affirmative action, equal opportunity institution. 
08/2016