Since 1982, CATT has been improving existing technologies and anticipating future challenges, often developing innovative solutions before commercial implications are understood or recognized. The faculty at CATT are leading researchers in the fields of Wireless Networks, Cyber-Security, and Media/Network Applications.
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Professor Anna Choromanska did her Post-Doctoral studies in the Computer Science Department at Courant Institute of Mathematical Sciences in NYU and joined the Department of Electrical and Computer Engineering at NYU Tandon School of Engineering in Spring 2017 as an Assistant Professor. She is affiliated with the NYU Center for Data Science.
Prof. Choromanska’s research interests focus on machine learning both theoretical and applicable to the variety of real-life phenomena. Currently, her main research projects focus on optimization (deep learning landscape, deep learning optimization, and general machine learning optimization), large data analysis (extreme multi-class and multi-label classification and density estimation), and machine learning for robotics and autonomy (autonomous driving systems, self-driving cars, AI-based robotics). Prof. Choromanska collaborates with NVIDIA (New Jersey lab) on the autonomous car driving project.
Prof. Choromanska was a recipient of The Fu Foundation School of Engineering and Applied Science Presidential Fellowship at Columbia University in the City of New York. She co-authored several international conference papers and refereed journal publications, as well as book chapters. The results her works are used in production by Facebook (training production vision systems and entry to COCO competition) and Baidu, and in product development by NVIDIA. She is also a contributor to the open source fast out-of-core learning system Vowpal Wabbit (aka VW). Prof. Choromanska gave over 50 invited and conference talks and serves as a book editor (MIT Press volume), organizer of top machine learning events (workshops at conferences such as the International Conference on Neural Information Processing Systems), and a reviewer and area chair for several top machine learning conferences and journals.
Area of Expertise: Algorithms
Cláudio Silva is a professor of computer science and engineering and data science at New York University. His primary research interests are in visualization, geometric computing, data science, sports analytics, and urban computing. He received a BS in mathematics from the Federal University of Ceará (Brazil) in 1990, and a PhD in computer science from State University of New York at Stony Brook in 1996. He was also a postdoc in applied mathematics at Stony Brook in 1996-7.
He has held positions in academia and industry, including at AT&T, IBM, Lawrence Livermore, Sandia, and the University of Utah. Cláudio has made contributions to visualization and graphics, notably in the areas of point-based modeling, surface reconstruction, isosurface generation, out-of-core and streaming techniques, visibility computations, volume rendering, and urban data visualization. Having participated in interdisciplinary projects, his work has had impact in multiple scientific domains. Cláudio has advised 15 PhD and 8 MS students, and mentored 6 post-doctoral associates; he currently advises over 8 PhD and MS students. He has published over 200 journal and conference papers, is an inventor of 12 US patents, and co-authored 12 papers that have received “Best Paper Awards” (including honorable mention) in visualization and geometric computing conferences. He has over 9,900 citations according to Google Scholar. He is an IEEE Fellow and was the recipient of the 2014 Visualization Technical Achievement Award “in recognition of seminal advances in geometric computing for visualization and for contributions to the development of the VisTrails data exploration system.”
NYU School of Engineering Presidential Fellow and Professor Emeritus
David Goodman is a Presidential Fellow of Polytechnic Institute of New York University (NYU-Poly) and has been a Professor Emeritus in its Department of Electrical and Computer Engineering since 2008. He was previously a Professor, Head of the department from 1999 to 2001, and Director of the Wireless Internet Center for Advanced Technology (WICAT), an industry-academic research center at Poly.
His research has made fundamental contributions to digital signal processing, speech coding and wireless information networks.
In 2006 and 2007, he was a Program Director in the Computer and Network Systems Division of the National Science Foundation.
Prior to joining Polytechnic University in 1999, he founded and directed the Wireless Information Network Laboratory (WINLAB) at Rutgers University. He was previously a Research Associate at the Program on Information Resources Policy at Harvard University. In 1997, he chaired the National Research Council Committee studying “The Evolution of Untethered Communications.” From 1967 to 1988 he was at Bell Laboratories, where his final position was Head of the Radio Research Department.
Professor Davood Shahrjerdi received his Ph.D. in solid-state electronics from The University of Texas at Austin in 2008. Before joining NYU in 2014, he was a Research Staff Member at IBM T. J. Watson Research Center. He is currently an assistant professor of Electrical and Computer Engineering. He is also a faculty scientist at the NYU Wireless Research Center.
Professor Shahrjerdi’s research focuses on the study of new electronic materials and devices for making nano-engineered hybrid integrated systems. His work has been featured in various journals and conferences including Applied Physics Letters, Advanced Energy Materials, and IEEE Electron Device Meeting (IEDM). He is the author and co-author of over 100 journal and conference papers. Additionally, he holds over 100 pending and issued patents. He is a Senior Member of IEEE and the recipient of several prestigious recognitions and awards including IBM Master Inventor (2013), Journal of Electronic Materials best paper award (2013), IBM Research Division award (2012), and IBM Outstanding Technical Achievement award (2012).
Edward K. Wong received his B. E. degree from the State University of New York at Stony Brook, his Sc. M. degree from Brown University, and his Ph. D. degree from Purdue University, all in Electrical Engineering. He is currently Associate Professor in the Department of Computer Science and Engineering at the Polytechnic Institute of NYU. His research interests are in the areas of image processing, computer vision, and pattern recognition. He has published extensively and his research had been funded by federal and state government agencies, as well as private industry. He was a technical consultant to several companies in the New York area. He is currently an associate editor for the journal Springer LNCS Transactions on Data Hiding and Multimedia Security. Dr. Wong had also served on the organizing and technical program committees of several major conferences.
Elza Erkip an Institute Professor in the Electrical and Computer Engineering Department at New York University Tandon School of Engineering. She received the B.S. degree in Electrical and Electronics Engineering from Middle East Technical University, Ankara, Turkey, and the M.S. and Ph.D. degrees in Electrical Engineering from Stanford University, Stanford, CA, USA. Her research interests are in information theory, communication theory, and wireless communications.
Dr. Erkip is a member of the Science Academy Society of Turkey and is among the 2014 and 2015 Thomson Reuters Highly Cited Researchers. She received the NSF CAREER award in 2001, the IEEE Communications Society WICE Outstanding Achievement Award in 2016 and the IEEE Communications Society Communication Theory Technical Committee (CTTC) Technical Achievement Award in 2018. Her paper awards include the IEEE Communications Society Stephen O. Rice Paper Prize in 2004, and the IEEE Communications Society Award for Advances in Communication in 2013. She has been a member of the Board of Governors of the IEEE Information Theory Society since 2012 where she is currently the Society President. She was a Distinguished Lecturer of the IEEE Information Theory Society from 2013 to 2014.
I received the B.Sc. degree and the M.Sc. degree (summa cum laude) in electrical engineering from the National Polytechnic Institute (IPN), Mexico, in 1983 and 1986, respectively. In 1992 I have obtained the Ph.D. degree also in electrical engineering from the University of Toronto, Canada. From 1992 to 1997 I was with the Graduate Division of the School of Electrical and Mechanical Engineering of the IPN, Mexico. From September 1997 to August 1998 I was on a sabbatical leave at McGill University in Montreal, and from September 1998 to April 1999 I was a post-doctoral researcher at the University of Toronto.
From 1999 to 2007 I held several academic positions in Mexico and worked for the Canadian electric industry in the research and development of standard and special motors and transformers. From 2004 to 2007 I was the Director of R&D at CYME International T&D in St. Bruno (Quebec) developing professional grade software for the analysis of power and distribution systems and cable ampacity. In September 2007 I have joined the Department of Electrical and Computer Engineering of Polytechnic University (the old Brooklyn Poly and now the NYU School of Engineering) as Associate Professor and obtained tenure in 2013.
Professor in the Dept. of Computer Science;
Internet real-time and multimedia services and protocols; Internet economics and policy; ubiquitous computing; mobile systems; quality of service; modeling and analysis of computer-communication networks; operating systems; network security.
Department Chair and Professor of Electrical & Computer Engineering; Professor of Biomedical Engineering, and Radiology
Ivan Selesnick is a Professor of Electrical and Computer Engineering at NYU Tandon School of Engineering. He received the BS, MEE, and PhD degrees in Electrical Engineering from Rice University in Houston, Texas. He joined Polytechnic University in 1997 (now NYU Tandon School of Engineering).
He received an Alexander von Humboldt Fellowship in 1997 and a National Science Foundation Career award in 1999. In 2003, he received the Jacobs Excellence in Education Award from Polytechnic University. He became an IEEE Fellow in 2016.
His research interests are in signal and image processing, wavelet-based signal processing, sparsity techniques, and biomedical signal processing. He has been an associate editor for the IEEE Transactions on Image Processing, IEEE Signal Processing Letters, IEEE Transactions on Signal Processing, and IEEE Transactions on Computational Imaging.
Research Interests: Signal Processing, Sparse Signal Models and Optimization, Biomedical Signal Processing, Wavelet Analysis
Jason Nieh is a Professor of Computer Science and Co-Director of the Software Systems Laboratory at Columbia University. He has served as a consultant to both government and industry, including as the technical advisor to nine States on the Microsoft Antitrust Settlement, and as an expert witness before the US International Trade Commission. He was previously Chief Scientist of Cellrox and Desktone, acquired by VMware. Nieh has made research contributions across a broad range of areas, including operating systems, virtualization, computer architecture, thin-client computing, cloud computing, mobile computing, multimedia, web technologies, and performance evaluation. Technologies he developed are now widely used in major operating system platforms, including Android and Linux, and are built into ARM processors, billions of which ship each year. Nieh is an IEEE Fellow. Honors for his research work include the Sigma Xi Young Investigator Award, awarded once every two years in the physical sciences and engineering, a National Science Foundation CAREER Award, a Department of Energy Early Career Award, five IBM Faculty Awards and two IBM Shared University Research Awards, six Google Research Awards, and various best paper awards, including those from MobiCom, SIGCSE, SIGMETRICS, and SOSP. A dedicated teacher, he received the Distinguished Faculty Teaching Award for his innovations in teaching operating systems and for introducing virtualization as a pedagogical tool, which has become common practice at universities around the world. Nieh earned his B.S. from MIT and his M.S. and Ph.D. from Stanford University, all in Electrical Engineering. He is married to Belinda Nieh and they have four children, Joanna, Caleb, Emma, and Zachary. They live in New York City.
H. Jonathan Chao, a recognized expert in networking, datacenters, and switches/routers, is professor in the Department of Electrical and Computer Engineering (ECE). He joined the NYU-Poly faculty in January 1992. He was Head of ECE Department from 2004 to 2014.
He is currently Director of High-Speed Networking Lab, leading a team of a Research Associate Professor, 6 PhD students, and 10 Master Students. He has been doing research in the areas of software defined networking, network function virtualization, datacenter networks, high-speed packet processing, switching, routing, network security, quality of service control, and network on chip. He holds 58 patents and has published over 200 journal and conference papers.
Chao is the co-founder and former CTO of Coree Networks, where he led a team in implementing a multi-terabit Multi-Protocol Label Switching (MPLS) switch router with carrier-class reliability. He helped raise $30 million for the first round of implementation. From 1985 to 1992, he was a member of technical staff at Telcordia, where he was involved in transport and switching system architecture designs and Application-specific Integrated Circuits (ASIC) implementations. He was a senior engineer at Telecommunication Labs of Taiwan performing circuit designs for a digital telephone switching system from 1977 to 1981.
He is a Fellow of National Academy of Inventors (NAI) for “having demonstrated a highly prolific spirit of innovation in creating or facilitating outstanding inventions that have made a tangible impact on quality of life, economic development, and the welfare of society.” He is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) for his contributions to the architecture and application of VLSI circuits in high-speed packet networks and was elected Speaker of the Year by IEEE New Jersey Coast Section in 2003. Chao was the 1987 recipient of the Telcordia Excellence Award and a co-recipient of the 2001 Best Paper Award from the IEEE Transaction on Circuits and Systems for Video Technology. He coauthored three networking books, Broadband Packet Switching Technologies—A Practical Guide to ATM Switches and IP Routers (New York: Wiley, 2001), Quality of Service Control in High-speed Networks (New York: Wiley, 2001), and High-performance Switches and Routers (New York: Wiley, 2007).
He has served as a guest editor for the IEEE’s Journal on Selected Areas in Communications (JSAC) on the special topics of “Advances in ATM Switching Systems for B-ISDN” (June 1997), “Next Generation IP Switches and Routers” (June 1999), two issues on “High-performance Optical/Electronic Switches/Routers for High-speed Internet” (May and September 2003), and “High-speed Network Security” (October 2006). He also served as an editor for IEEE/ACM Transactions on Networking from 1997–2000.
Juliana Freire is a Professor at the Department of Computer Science and Engineering at New York University. She also holds an appointment in the Courant Institute for Mathematical Science and is a faculty member at the NYU Center of Data Science. Her research interests are in large-scale data analysis, visualization, and provenance management. An important theme is Professor Freire’s work is the development of data management techniques and infrastructure to address problems introduced by emerging applications. Recently, her work has focused on the analysis and visualization urban, scientific and Web data. Within scientific data management, she is best known for her work in provenance and computational reproducibility, and for being a co-creator of the open-source VisTrails system (http://www.vistrails.org). Professor Freire is an active member of the database and Web research communities, having co-authored over 130 technical papers and holding 9 U.S. patents. She has chaired or co-chaired several workshops and conferences, and has participated as a program committee member in over 60 events. She has received several awards, including an NSF CAREER, an IBM Faculty award, and a Google Faculty Research award. Her research has been funded by grants from the National Science Foundation, Department of Energy, National Institutes of Health, University of Utah, NYU, Sloan Foundation, Betty Moore Foundation, Google, Amazon, Microsoft Research, Yahoo! and IBM.
Research Interests: Big Data
Data analysis and visualization
Large-scale information integration
Justin Cappos is a professor in the Computer Science and Engineering department at New York University. Justin’s research philosophy focuses on improving real world systems, often by addressing issues that arise in practical deployments.
His dissertation work was on Stork, the first package manager designed for environments that use operating system virtualization, such as cloud computing. Improvements in Stork, particularly relating to security, have been widely adopted and are used on the majority of Linux systems via integrations into Apt, YUM, YaST, and Pacman. His later research advances have been adopted into production use including by Microsoft, IBM, VMware, Cloudflare, Docker, RedHat, ControlPlane, Datadog, and git, as well as a substantial percentage of automobiles. More information is available at https://ssl.engineering.nyu.edu/personalpages/jcappos/
Research Interests: Practical security, virtualization, cloud computing, software update systems, testbeds
Lakshminarayanan Subramanian is a Professor in the Courant Institute of Mathematical Sciences at NYU. His research interests are in the areas of networked systems and data science with applications in computing for development (also referred by the acronymn ICTD). He leads the Open Networks and Big Data Lab and is a member of the NYU Systems group. He is associated with the Center for Technology and Economic Development, Center for Data Science and NYU WIRELESS.
He is a Co-founder and Chief Scientist at Entrupy Inc, a startup that uses machine vision algorithms and microscopy to authenticate physical goods and enable trustworthy commerce.
Research Interests: Computational learning theory Machine learning Algorithms Complexity theory Discrete mathematics
Research Interests: Computational learning theory Machine learning Algorithms Complexity theory Discrete mathematics
Area of Expertise: Antennas, Circuits, RF and Microwave, Wireless Communications
Nasir Memon is a professor in the Department of Computer Science and Engineering at NYU Tandon. He is an affiliate faculty at the computer science department in the Courant Institute of Mathematical Sciences at NYU.
Research Interests: Data Compression
Security and Human Behavior
Computer and Network Security
Multimedia Security and Forensics
Associate Dean of Engineering; Professor of Electrical and Computer Engineering
Ozgur Sinanoglu is a professor of electrical and computer engineering at New York University Abu Dhabi. He earned his BS degrees, one in Electrical and Electronics Engineering and one in Computer Engineering, both from Bogazici University, Turkey in 1999. He obtained his MS and PhD in Computer Science and Engineering from University of California San Diego in 2001 and 2004, respectively. During his PhD, he won the IBM PhD fellowship award twice. He has industry experience at Texas Instruments, IBM, and Qualcomm, and has been with NYU Abu Dhabi as an assistant professor during 2010-2014, associate professor with tenure during 2014-2018, and full professor with tenure since 2018.
Professor Sinanoglu’s research interests include design-for-test, design-for-security, and design-for-trust for VLSI circuits, where he has more than 170 conference and journal papers, and 20 issued and pending US Patents. He is the recipient of the best paper awards at IEEE VLSI Test Symposium 2011 and ACM Conference on Computer and Communication Security 2013. Sinanoglu has given around two dozen tutorials on hardware security and trust in leading CAD and test conferences, such as DAC, DATE, ITC, VTS, ETS, ICCD, ISQED, etc. He is serving or has served as general/program/track/topic chair or technical program committee member in about 20 conferences, and as (guest) associate editor for IEEE TIFS, IEEE TETC, IEEE TCAD, ACM JETC, Elsevier MEJ, JETTA, and IET CDT journals. He chaired and hosted the top cybersecurity conference in Asia, ACM ASIACCS 2017, in Abu Dhabi.
Professor Sinanoglu is the director of the Design-for-Excellence Lab at NYU Abu Dhabi. His recent research in hardware security and trust has been funded by US National Science Foundation, US Department of Defense (Army Research Office and DARPA), Intel Corporation, Semiconductor Research Corporation, and Mubadala Technology.
Research Assistant Professor, Polytechnic Institute of New York University
Research Interests: Communications and Signal Processing
Research Interests: Game Theory and Applications
Resilient and Secure Socio-Cyber-Physical Systems
Adversarial Machine Learning and Signal Processing
Internet of Things
Game and Decision Theory for Cyber Security
Economics and Optimization of Infrastructure Systems
Resource Allocations in Communication Networks
Professor; Co-founder and co-chair NYU Center for Cyber Security; Founder and Organizer: Annual CSAW Embedded Security Challenge
Ramesh Karri is a Professor of Electrical and Computer Engineering at Tandon School of Engineering, New York University. He has a Ph.D. in Computer Science and Engineering, from the University of California at San Diego. His research and education activities span hardware cybersecurity including trustworthy ICs, processors and cyberphysical systems; security-aware computer aided design, test, verification, validation and reliability; nano meets security; metrics; benchmarks; hardware cybersecurity competitions; additive manufacturing security.
He has over 200 journal and conference publications including tutorials on Trustworthy Hardware in IEEE Computer (2) and Proceedings of the IEEE (5). His groups work on hardware cybersecurity was nominated for best paper awards (ICCD 2015 and DFTS 2015) and received awards at conferences (ITC 2014, CCS 2013, DFTS 2013 and VLSI Design 2012) and at competitions (ACM Student Research Competition at DAC 2012, ICCAD 2013, DAC 2014, ACM Grand Finals 2013, Kaspersky Challenge and Embedded Security Challenge).
Dr. Rumi Chunara researches and develops ways to use unstructured data in real-world applications and understand population health. As a computer engineers and scientist, she has revolutionized how medical and public health researchers collect health information through the Internet and mobile technology.
Driven to understand how and why diseases spread in populations, she has developed cutting-edge research models at HealthMap and the Children’s Hospital Informatics Program at Harvard Medical School. Through the GoViral study, Dr. Chunara works closely with students on campus to collect crowd sourced data of influenza in real-time. GoViral uses the collected data and modeling methods to better understand viral spread, uncover geographical variation in spread and epidemiology, and predict and recommend behaviors that limit disease spread. At NYU, Dr. Chunara also leads the Chunara Lab, which develops computational and statistical methods across data mining, natural language processing, spatio-temporal analyses and machine learning, to study population health.
S. Farokh Atashzar
S. Farokh Atashzar is an Assistant Professor of Electrical and Computer Engineering, as well as Mechanical and Aerospace Engineering at New York University (NYU). Prior to joining NYU, Atashzar was a senior postdoctoral scientist in the Department of Bioengineering, Imperial College London, UK, sponsored by Natural Sciences and Engineering Research Council (NSERC) of Canada. From February 2017 to August 2018, he served as a postdoctoral research associate at Canadian Surgical Technologies and Advanced Robotics (CSTAR) center. From 2015 to 2018, he conducted research for the Network of Centres of Excellence (NCE) of Canada program “Aging Gracefully across Environments using Technology to Support Wellness, Engagement and Long Life (AGE-WELL)”.
Shivendra S. Panwar is a Professor in the Electrical and Computer Engineering Department at NYU Tandon School of Engineering. He received the B.Tech. degree in electrical engineering from the Indian Institute of Technology Kanpur, in 1981, and the M.S. and Ph.D. degrees in electrical and computer engineering from the University of Massachusetts, Amherst, in 1983 and 1986, respectively.
He joined the Department of Electrical Engineering at the Polytechnic Institute of New York, Brooklyn (now Polytechnic Institute of New York University). He is currently the Director of the New York State Center for Advanced Technology in Telecommunications (CATT), and member of NYU WIRELESS. He spent the summer of 1987 as a Visiting Scientist at the IBM T.J. Watson Research Center, Yorktown Heights, NY, and has been a Consultant to AT&T Bell Laboratories, Holmdel, NJ. His research interests include the performance analysis and design of networks. Current work includes cooperative wireless networks, switch performance and multimedia transport over networks.
Area of Expertise: Algorithms, Circuits, Computer Architectures, Nano-scale Architectures, VLSI Systems
Professor, Associate Director NYU WIRELESS
Dr. Rangan received the B.A.Sc. at the University of Waterloo, Canada and the M.Sc. and Ph.D. at the University of California, Berkeley, all in Electrical Engineering. He has held postdoctoral appointments at the University of Michigan, Ann Arbor and Bell Labs. In 2000, he co-founded (with four others) Flarion Technologies, a spin-off of Bell Labs, that developed Flash OFDM, the first cellular OFDM data system and pre-cursor to 4G cellular systems including LTE and WiMAX. In 2006, Flarion was acquired by Qualcomm Technologies. Dr. Rangan was a Director of Engineering at Qualcomm involved in OFDM infrastructure products. He joined the ECE department at NYU Tandon (formerly NYU Polytechnic) in 2010. He is a Fellow of the IEEE and the Associate Director of NYU WIRELESS, an industry-academic research center on next-generation wireless systems.
Research Assistant Professor
Thanasis Korakis was born on December 4, 1972 in Ioannina, Greece. He obtained the Bachelor and the M.S. degree in Informatics and Telecommunications from the University of Athens, Greece, in 1994 and 1997 respectively. He obtained the Ph.D. degree in Computer and Communication Engineering from the University of Thessaly, Greece in 2005, under the supervision of Professor Leandros Tassiulas. In the summer of 2004 he was a visiting researcher at the Computer Science & Engineering Department at the University of California, Riverside. From 2005 to 2006 he was a Research Scientist associated with the New York State Center for Advanced Technologies in Telecommunications (CATT).
Dr. Korakis is currently a Research Assistant Professor in the Electrical and Computer Engineering Department of Polytechnic Institute of NYU. He is also affiliated with CATT at NYU Polytechnic School of Engineering. His research interests are in the field of wireless networks with emphasis on access layer protocols, cooperative networks, directional antennas, quality of service provisioning and network management. He leads the Wireless Implementation Testbed Laboratory (Witest Lab) of the Department of Electrical and Computer Engineering at Polytechnic Institute of NYU.
Distinguished Industry Professor
Thomas Marzetta is Distinguished Industry Professor at NYU Tandon School of Engineering’s Electrical and Computer Engineering Department and an Associate Director of NYU Wireless. Born in Washington, D.C., he received the Ph.D. and SB in Electrical Engineering from Massachusetts Institute of Technology in 1978 and 1972, and the MS in Systems Engineering from University of Pennsylvania in 1973. Prior to joining NYU in 2017, he had three industrial research careers: petroleum exploration (Schlumberger-Doll Research, 1978 – 1987), defense (Nichols Research Corporation, 1987 – 1995), and telecommunications (Bell Labs, 1995 – 2017). At Bell Labs, he directed the Communications and Statistical Sciences Department within the former Mathematical Sciences Research Center, and he was elected a Bell Labs Fellow. He originated Massive MIMO, one of the cornerstones of fifth-generation wireless technology. He is lead author of the book Fundamentals of Massive MIMO.
Torsten Suel is a Professor in the Department of Computer Science and Engineering at the NYU Polytechnic School of Engineering, where he directs a research group working on search engines and web mining technology. He holds a Diplom degree from the Technical University of Braunschweig (Germany), and a Ph.D. from the University of Texas at Austin. He joined the department in 1998 after postdoctoral and visiting positions at the NEC Research Institute, UC Berkeley, and Bell Labs. During 2008, he was a Principal Research Scientist at Yahoo! Research in Santa Clara, CA, while on leave from NYU Poly.
Research Interests: Web search engines
Scalable information retrieval
Vishal Misra is an Indian-American scientist at Columbia University, New York, NY and known for his numerous contributions to Computer Networking. He was named Fellow of the Institute of Electrical and Electronics Engineers (IEEE) in 2016 for contributions to network traffic modeling, congestion control and Internet economics. He was elected as an ACM Fellow in 2018.
He is a Professor in the Computer Science and Electrical Engineering Departments at Columbia University. He is also an entrepreneur, having co-founded the world’s most popular single sport portal ESPNCricinfo, where he designed and implemented the world’s  in 1996. In 2011 he founded the data center storage company Infinio.
As a researcher, he developed the first stochastic differential equation (fluid) model of TCP that led to formal control theoretic analysis of congestion control mechanisms on the Internet. Based on his work a team at Cisco developed the PIE (PI enhanced) controller that is being used to solve the problem of bufferbloat (excessive delays on the Internet because of larger than needed buffers). The PIE controller has become a part of the DOCSIS 3.1.
He has also worked on the topic of Network neutrality, and worked actively with both the citizen’s movement and the regulators in India. The pro-net neutrality citizen’s movement adopted his definition of Net Neutrality, and eventually the regulators in India passed regulations that are consistent with his definition, recognized as the strongest Net Neutrality protections anywhere in the world.
Area of Expertise: Image and Video Processing, Medical Imaging, Video Compression and Transport
Research Interests: Computer Graphics and Visualization: big data analysis and visualization, out-of-core graphics and scientific visualization, isosurface extraction, surface simplification and view-dependent rendering, volume simplification, graphics compression, volume rendering, computational topology and topology-driven visualization, robot motion planning.
Computer Algorithms: out-of-core algorithms, computational geometry, algorithmic motion planning, graph algorithms, approximation algorithms, data structures, computational topology.
Yong Liu is an associate professor at the Electrical and Computer Engineering department of the Polytechnic Engineering School of New York University. He received his Ph.D. degree from Electrical and Computer Engineering department at the University of Massachusetts, Amherst, in May 2002. His current research directions include Peer-to-Peer systems, overlay networks, network measurement, online social networks, and recommender systems. He is a member of IEEE and ACM and is currently serving as an associate editor for IEEE/ACM Transactions on Networking, and Elsevier Computer Networks Journal. He is the winner of the Best Paper Award of ACM/USENIX Internet Measurement Conference (IMC) 2012, the National Science Foundation Career Award in 2010, the Best Paper Award of IEEE Conference on Computer Communications (INFOCOM) in 2009, and the IEEE Communication Society Multimedia Communications Best Paper Award in 2008. More information about him is available at: http://eeweb.poly.edu/faculty/yongliu/
Research Interests: Design, Analysis and Simulation of Communication Networks
Modeling, Control and Optimization of Complex Systems
Prof. Jiang is known for his contributions to stability and control of interconnected nonlinear systems, and is a key contributor to the nonlinear small-gain theory. His recent research focuses on robust adaptive dynamic programming, distributed nonlinear control, and their applications to computational and systems neuroscience, connected and autonomous vehicles, and cyber-physical systems.
Prof. Jiang is a Senior Editor for the IEEE Control Systems Letters (L-CSS), an Editor for the International Journal of Robust and Nonlinear Control and has served as an Associate Editor and/or a Guest Editor for several journals including Mathematics of Control, Signals and Systems, Systems & Control Letters, IEEE Transactions on Automatic Control, European Journal of Control, and Science China: Information Sciences. He is also a Deputy co-Editor-in-Chief of the IEEE/CAA Journal of Automatica Sinica and the Journal of Control and Decision.
Research Interests: Basic stability problems for interconnected systems
Nonlinear control theory and applications
Robust adaptive dynamic programming
Control of underactuated mechanical systems – for example, mobile robots, ships,underwater systems
Energy and power systems
Tools for cyber-physical systems
Brandon Reagen is an Assistant Professor in the Department of Electrical and Computer Engineering with affiliation appointments in the Computer Science. He earned a PhD in computer science from Harvard in 2018 and received his undergraduate degrees in computer systems engineering and applied mathematics from the University of Massachusetts, Amherst, in 2012.
A computer architect by training, Brandon has a research focus on designing specialized hardware accelerators for applications including deep learning and privacy preserving computation. He has made several contributions to ease the use accelerators as general architectural constructs including benchmarking, simulation infrastructure, and System on a Chip (SoC) design. He has led the way in highly efficient and accurate deep learning accelerator design with his studies of principled unsafe optimizations, and his work has been published in conferences ranging from computer architecture, machine learning, computer aided design, and circuits.
Prior to joining NYU, he was a research scientist with Facebook’s AI Infrastructure Research working on privacy preserving machine learning and systems for neural recommendation. During his PhD he was a Siebel Scholar (2018) and was selected as a 2018 Rising Star in Computer Architecture by Georgia Tech.
Danny Y. Huang is broadly interested in the security and privacy of consumer-facing technologies, such as Internet-of-Things.
Before joining NYU, he was a postdoctoral fellow at Princeton University. He obtained a Ph.D. in Computer Science from University of California, San Diego, where he wrote a dissertation on using cryptocurrencies to study cyber-criminal activities. He graduated from Williams College (Massachusetts) with a BA in Computer Science.
Institute Associate Professor
Julia Stoyanovich is an Associate Professor in the Department of Computer Science and Engineering at the Tandon School of Engineering, and the Center for Data Science. She is a recipient of an NSF CAREER award and of an NSF/CRA CI Fellowship. Julia’s research focuses on responsible data management and analysis practices: on operationalizing fairness, diversity, transparency, and data protection in all stages of the data acquisition and processing lifecycle. She established the Data, Responsibly consortium, and serves on the New York City Automated Decision Systems Task Force (by appointment by Mayor de Blasio). In addition to data ethics, Julia works on management and analysis of preference data, and on querying large evolving graphs. She holds M.S. and Ph.D. degrees in Computer Science from Columbia University, and a B.S. in Computer Science and in Mathematics and Statistics from the University of Massachusetts at Amherst.
Damon McCoy received his Ph.D. in Computer Science from the University of Colorado, Boulder. He is a member of the Center for Automotive Embedded Systems Security (CAESS) that conducted one of the first security analysis of a modern automobile. His research focuses on empirically measuring the security and privacy of technology systems and their intersections with society. Currently, his primary focus is on online payment systems, economics of cybercrime, automotive systems, privacy-enhancing technologies and censorship resistance.
Research Interests: Machine Learning, Algorithms, Big Data, Signal and Image Processing.
Associate Professor and Interim Director of the Ph.D. Program
Rachel Greenstadt holds a bachelor’s degree in Computer Science (2001) and master’s degrees in Electrical Engineering and Computer Science (2002) from MIT, as well as a Ph.D. (2007) in Computer Science from Harvard. Her honors have included membership in the DARPA Computer Science Study Group, a U.S. Department of Homeland Security Fellowship, a PET Award for Outstanding Research in Privacy Enhancing Technologies, and a National Science Foundation CAREER Award.
Greenstadt’s research has focused on designing more trustworthy intelligent systems — systems that act not only autonomously, but also with integrity, so that they can be trusted with important data and decisions. She takes a highly interdisciplinary approach to this research, incorporating ideas from artificial intelligence, psychology, economics, data privacy, and system security.
Prior to joining NYU, Greenstadt was an Associate Professor of Computer Science at Drexel University, where she ran the highly regarded Privacy, Security, and Automation Laboratory (PSAL) and served as an advisor to the Drexel Women in Computing Society. Before that, she was a Postdoctoral Fellow at Harvard’s School of Engineering and Applied Sciences, a Visiting Scholar with the University of Southern California TEAMCORE group, and a Research Intern at Lawrence Livermore National Laboratory. Throughout her career, she has edited multiple volumes of the journal Proceedings on Privacy Enhancing Technologies (PoPETs) and has been in demand as a peer reviewer. Greenstadt has chaired the ACM Workshop on Artificial Intelligence and Security multiple times and has regularly participated in, spoken at, and served on program committees for several other workshops building ties between the security, AI, and usability communities. She has long been an active speaker and participant in the international hacking community, and her work has been presented at Hacking at Random, Vierhouten, NL, ShmooCon, DefCon, and the Chaos Communication Congress.
Guido Gerig is Department Chair and Institute Professor in the Department of Computer Science and Engineering and he is a professor of Biomedical Engineering. He also holds associated/affiliated appointments at NYU Courant CS, NYU Langone Child and Adolescent Psychiatry, Psychiatry and Radiology.
Guido Gerig has been named IEEE Fellow (class of 2019) and has also been appointed as a Fellow of the American Institute for Medical and Biological Engineering (AIMBE) in 2010.
Starting image analysis with applications to satellite imaging, he became increasingly interested in driving problems from medicine, tackled in close multidisciplinary collaboration between medicine, engineering, and statistics. His research supports a number of clinical imaging research studies with novel, innovative image analysis methodologies related to segmentation, registration, atlas building, shape analysis, and image statistics. Driving clinical problems include research in autism, Down’s syncdrome, eye diseases (Glaucoma, AMD), multiple sclerosis, Huntington’s disease, studies of infants at risk for mental illness, and in general analysis of anatomical changes from normal due to disease, therapy and recovery. Gerig’s research resulted in various new image analysis methodologies for nonlinear processing, multi-scale segmentation and shape analysis, some of them first and seminal to the field. Applications resulted in new clinical research discoveries such as vulnerability for schizophrenia, early diagnosis of autism based on differences in brain development trajectories, and correlation of shape atrophy with risk status in Huntington’s. New tools and methods are developed as open source software and made available to the public, including teaching materials and hands-on training workshops.
Guido Gerig was previously USTAR Professor of Computer Science at the University of Utah (2007-2015) establishing the Utah Center for Neuroimage Analysis (UCNIA), Taylor Grandy Professor of Computer Science and Psychiatry at the University of North Carolina at Chapel Hill (1998-2007) launching the UNC Neuro Image Research and Analysis Laboratories (NIRAL), and Assistant Professor at ETH Zurich (1993-1998). Gerig holds several awards from Utah and UNC for Excellence in Teaching.
Brendan Dolan-Gavitt is an Associate Professor in the Computer Science and Engineering Department at NYU Tandon. He holds a Ph.D. in computer science from Georgia Tech (2014) and a BA in Math and Computer Science from Wesleyan University (2006).
Dolan-Gavitt’s research interests span many areas of cybersecurity, including program analysis, virtualization security, memory forensics, and embedded and cyber-physical systems. His research focuses on developing techniques to ease or automate the understanding of large, real-world software systems in order to develop novel defenses against attacks, typically by subjecting them to static and dynamic analyses that reveal hidden and undocumented assumptions about their design and behavior.
His work has been presented at top security conferences such as USENIX Security, the ACM Conference on Computer and Communications Security (CCS) and the IEEE Symposium on Security and Privacy. He also led the development of PANDA, an open-source platform for architecture-neutral dynamic analysis, which has users around the world and has been featured in technical press such as The Register. Prior to joining NYU, he was a postdoctoral researcher at Columbia University.
Juan Pablo Bello is a Professor of Music Technology and Computer Science & Engineering at New York University. In 1998 he received a BEng in Electronics from the Universidad Simón Bolívar in Caracas, Venezuela, and in 2003 he earned a doctorate in Electronic Engineering at Queen Mary, University of London. Juan’s expertise is in digital signal processing, machine listening and music information retrieval, topics that he teaches and in which he has published more than 100 papers and articles in books, journals and conference proceedings. He is the director of the Music and Audio Research Lab (MARL), where he leads research on sound and music informatics. His work has been supported by public and private institutions in Venezuela, the UK, and the US, including Frontier and CAREER awards from the National Science Foundation and a Fulbright scholar grant for multidisciplinary studies in France.
Research Interests: Computer vision, Machine Learning, Deep learning, AI for science, Robotics.
Research Interests: Nonlinear Control and Large Scale Systems Robotics and Automation Unmanned Autonomous Vehicles Cyber Security Machine Learning with applications to Robotics and Cyber Security Multi-Agent Systems Cyber-Physical Systems security
Dr. Yuzhang Lin will join the Department of Electrical and Computer Engineering at NYU Tandon School of Engineering as an Assistant Professor in September 2023. He has been an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Massachusetts, Lowell since 2018.
Dr. Lin obtained his Ph.D. degree from Northeastern University, Boston, MA, and his B.Eng. and M.S. degrees from Tsinghua University, Beijing, China. His research interests focus on smart grid and renewable energy, especially in the aspects of modeling, situational awareness, cyber-physical resilience, and machine learning applications. He publishes widely in the top journals of the domain, and also serves as an editor/reviewer for many of these journals. He serves as the co-chair of the IEEE PES Task Force for Standard Test Cases for Power Systems State Estimation, and the Secretary of IEEE PES Distribution System Operation and Planning Subcommittee. He is a recipient of the prestigious Graduate Student Outstanding Research Award at Northeastern University, Boston, MA. His research is funded by NSF, DOE, and ONR. He is a recipient of NSF CAREER Award.
Prof. Giuseppe Loianno is an assistant professor at the New York University and director of the Agile Robotics and Perception Lab (https://wp.nyu.edu/arpl/) working on autonomous Micro Aerial Vehicles. Prior to NYU he was a lecturer, research scientist, and team leader at the General Robotics, Automation, Sensing and Perception (GRASP) Laboratory at the University of Pennsylvania. He received his BSc and MSc degrees in automation engineering, both with honors, from the University of Naples “Federico II” in December 2007 and February 2010, respectively. He received his PhD in computer and control engineering focusing in robotics in May 2014. Dr. Loianno has published more than 70 conference papers, journal papers, and book chapters. His research interests include perception, learning, and control for autonomous robots. He received the NSF CAREER Award in 2022 and DARPA Young Faculty Award in 2022. He is recipient of the IROS Toshio Fukuda Young Professional Award in 2022, Conference Editorial Board Best Associate Editor Award at ICRA 2022 and Best Reviewer Award at ICRA 2016. He is also currently the co-chair of the IEEE RAS Technical Committee on Aerial Robotics and Unmanned Aerial Vehicles and juror in several worldwide robotics competitions. He was the program chair of the 2019 and 2020 IEEE International Symposium on Safety, Security and Rescue Robotics and the general chair in 2021. He is in the organizing committee of IROS 2024. He organized a series of seven consecutive successful workshops at the IEEE/RSJ International Conference on Intelligent Robots and Systems (2015-2022). He has created the new International Symposium on Aerial Robotics (ISAR). His work has been featured in a large number of renowned international news and magazines.
Dr. Rahmani has been with IBM T. J. Research Center in Yorktown Heights, NY since 2022 and is currently a Research Staff Member working on research projects investigating Mixed-Signal CMOS circuits for high-speed electrical and optical data communication. Dr. Rahmani was also an Adjunct Professor at Columbia University in New York, NY, and a visiting lecturer at Princeton University where he offered graduate-level courses in analog and RF circuit design. From 2020 to 2022, He was a senior RFIC design engineer at Qualcomm Inc., Boxborough, MA where he focused on advanced 5G transmitters for cellular applications and RF front-end designs.
He is also the recipient of several prestigious awards and fellowships including the IEEE MTT-S Graduate Fellowship for medical applications and the Texas Instruments Distinguished fellowship. He serves on the technical committee for the International Microwave Symposium (IMS) 2022. Also, he is a member of “MTT-26: RFID, wireless sensors and IoT” and an affiliate member of ” MTT-25: wireless power transfer and energy conversion” technical committees of the IEEE Microwave Theory and Techniques Society.
Assistant Professor (Incoming Fall 2023)
Austin Rovinski is an incoming Assistant Professor (Fall ’23) in the Department of Electrical and Computer Engineering at New York University. He earned his Ph.D., master’s, and bachelor’s degrees all from the University of Michigan – Ann Arbor. Prior to joining NYU, Austin spent a year as a postdoc at Cornell University.
Austin is passionate about chip design, and his research interests span the areas of computer architecture, very large-scale integration (VLSI), and electronic design automation (EDA). In particular, Austin is interested in creating fast, high-quality EDA frameworks and prototyping next-generation chiplet-based systems. Austin has led the development of several novel chip prototypes and made substantial contributions to agile hardware design methodologies. Austin is a founding member of the OpenROAD project where he served as a design advisor and led the development of the OpenROAD RTL-to-GDS flow.
At Cornell, Austin focused on developing an optoelectronic interconnect system utilizing 2.5D packaging and design of domain-specific accelerators for EDA.
Austin has received a IEEE Micro Top Picks honor (2015), Michigan EECS Outstanding Research Award (2016), and NSF Graduate Research Fellowship honorable mention (2017, 2018).
Assistant Professor (Incoming Fall 2024)
Phone: +1 (617) 803-8806
Sai Qian Zhang will join the Electrical and Computer Engineering department at NYU Tandon School of Engineering and the Computer Science department at Courant Institute of Mathematical Sciences as an assistant professor in Fall 2024. Dr. Zhang received his Ph.D. degree from Harvard University in 2021 and obtained both his M.A.Sc and B.A.Sc degrees from the University of Toronto. Dr. Zhang has been with Meta Reality Labs in Burlingame, CA, and is currently a research scientist working on algorithm and hardware co-design for AR/VR applications.
Dr. Zhang’s research interests lie in algorithm and hardware co-design for efficient deep neural network implementation. He is also interested in reinforcement learning and its applications in hardware system design.
His work has been published in multiple top-tier conferences such as ASPLOS, NeurIPS, HPCA, and AAAI. He has won the Best Paper Award at the IEEE International Conference on Communication. He is also the recipient of the NSERC Postgraduate Scholarships.
Research Interests: Stroke, Traumatic Brain Injury, Acquired Brain Injury, Eye-Hand Coordination, Eye Movements, Ocular Motor Control, Manual Motor Control, Concussion, Biomechanics, Gait, Assistive Technology, Wearable Technology, Blindness and Visual Impairment (BVI), Sensory Augmentation, Electronic Travel Aids (ETAs) for BVI, Mobility in Low Vision
Nikhil Gupta joined the NYU-Tandon School of Engineering faculty in 2004 and currently serves as Professor in the Department of Mechanical and Aerospace Engineering. He is also affiliated with the Department of Civil and Urban Engineering and Center for Cybersecurity.
Gupta is an elected Fellow of ASM International and American Society for Composites and a Senior Member of IEEE. His other awards include the 2020 Brimacombe Medalist Award from TMS; 2013-ASM-International Silver Medal, 2013-TMS Young Leader Professional Development Award, 2007 and 2009 Visiting Lectureship Award from the American Society for Metals-Indian Institute of Metals, the Air Force Summer Faculty Fellowship administered by the American Society of Engineering Education, and the Junior Faculty Fellow, Othmer Institute for Interdisciplinary Studies, NYU-Tandon School of Engineering.
He served as the Chair of the Composites Materials Committee of TMS (2016-2018) and Membership Secretary of American Society for Composites. He is serving on the editorial board of Materials Science and Engineering A, Advanced Composites and Hybrid Materials and ASTM journal Materials Processing and Characterization and previously served on the editorial board of Composites Part B.
Director, Sustainable Engineering Initiative and Donald F. Othmer Associate Professor of Chemical Engineering
Our research lies at the interface of multifunctional material development and electrochemical engineering. Electrochemical devices are ubiquitous to a broad range of energy conversion technologies and chemical processes. Their core components rely on complex materials that provide the required electrocatalytic activity and mass transport functionality. Our group has expertise in composite materials development, processing and characterization; and this expertise is used to improve and redefine electrochemical reactors with direct industrial applications. Our applied research approach also relies on fundamental understanding of the materials’ self-assembly and how their morphology and surface properties affects the mass transport and performance of electrochemical devices.