Swanson School of Engineering Making Research Work @ Pitt

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