Waheed U. BajwaProf. Waheed U. Bajwa

Associate Professor
Department of Electrical and Computer Engineering
Department of Statistics
Rutgers, The State University of New Jersey

Research Interests

Statistical signal processing, high-dimensional statistics, machine learning, harmonic analysis, inverse problems, networked systems, and applications in biological sciences, radar and image processing, and wireless communications.

Biography

Waheed U. Bajwa received BE (with Honors) degree in electrical engineering from the National University of Sciences and Technology, Pakistan in 2001, and MS and PhD degrees in electrical engineering from the University of Wisconsin-Madison in 2005 and 2009, respectively. He was a postdoctoral research associate in the Program in Applied and Computational Mathematics at Princeton University from 2009 to 2010, and a research scientist in the Department of Electrical and Computer Engineering at Duke University from 2010 to 2011. He has been with Rutgers University since 2011, where he is currently an associate professor in the Department of Electrical and Computer Engineering and an associate member of the graduate faculty of the Department of Statistics. His research interests include statistical signal processing, high-dimensional statistics, machine learning, harmonic analysis, inverse problems, and networked systems.

Dr. Bajwa has received a number of awards in his career including the Best in Academics Gold Medal and President’s Gold Medal in Electrical Engineering from the National University of Sciences and Technology (2001), the Morgridge Distinguished Graduate Fellowship from the University of Wisconsin-Madison (2003), the Army Research Office Young Investigator Award (2014), the National Science Foundation CAREER Award (2015), Rutgers University’s Presidential Merit Award (2016), Rutgers University’s Presidential Fellowship for Teaching Excellence (2017), and Rutgers Engineering Governing Council ECE Professor of the Year Award (2016, 2017, 2019). He is a co-investigator on a work that received the Cancer Institute of New Jersey’s Gallo Award for Scientific Excellence in 2017, a co-author on papers that received Best Student Paper Awards at IEEE IVMSP 2016 and IEEE CAMSAP 2017 workshops, and a Member of the Class of 2015 National Academy of Engineering Frontiers of Engineering Education Symposium.

Dr. Bajwa, who is a Senior Member of the IEEE, has also been involved in a number of professional activities. He served as the US Liaison Chair of IEEE SPAWC 2019 Workshop, a Publicity & Publications Co-Chair of IEEE DSW 2019 Workshop, a member of the Data Science Initiative and an elected member of the Big Data Special Interest Group of the IEEE Signal Processing Society (2019), a Technical Co-Chair of IEEE SPAWC 2018 Workshop, a Technical Area Chair of 2018 Asilomar Conference on Signals, Systems, and Computers, the General Chair of 2017 DIMACS Workshop on Distributed Optimization, Information Processing, and Learning, an elected member of the Machine Learning for Signal Processing (MLSP) Technical Committee of the IEEE Signal Processing Society (2016 – 2018), the Publicity and Publications Chair of IEEE CAMSAP 2015 Workshop, and an Associate Editor of IEEE Signal Processing Letters (2014 – 2017). He also co-chaired IEEE GlobalSIP 2013 Symposium on New Sensing and Statistical Inference Methods and CPSWeek 2013 Workshop on Signal Processing Advances in Sensor Networks, co-guest edited a special issue of Elsevier Physical Communication Journal on “Compressive Sensing in Communications” (2012), and served as the Lead Guest Editor for a special issue of IEEE Signal Processing Magazine on “Distributed, Streaming Machine Learning” (2020). He is currently serving as a Senior Area Editor for IEEE Signal Processing Letters, an Associate Editor for IEEE Transactions on Signal and Information Processing over Networks, a guest editor for a special issue of Proceedings of the IEEE on “Optimization for Data-driven Learning and Control,” and an elected member of the Sensor Array and Multichannel (SAM) and Signal Processing for Communications and Networking (SPCOM) Technical Committees of IEEE Signal Processing Society.

Arpita GangArpita Gang

Joining date: Fall 2017
Intended degree: PhD
Research interests: Distributed information processing; distributed optimization

Previous affiliations: Indraprastha Institute of Information Technology, Delhi (M. Tech); National Institute of Technology, Silchar (B. Tech)

Other information: Research Assistant, Indraprastha Institute of Information Technology, Delhi (2016 – 2017)

Alireza NooraiepourAlireza Nooraiepour

Joining date: Fall 2017
Intended degree: PhD (co-advised with N. Mandayam)
Research interests: Wireless communications; statistical learning

Previous affiliations: Bilkent University, Ankara (MSc); Tehran Polytechnic (BSc)

Other information: N/A

Rishabh DixitRishabh Dixit

Joining date: Fall 2018
Intended degrees: MS and PhD
Research interests: Distributed signal processing; convex and nonconvex optimization

Previous affiliations: Indian Institute of Technology, Kanpur (B. Tech)

Other information: Consultant, Product Development Team, EXL Analytics (2015 – 2017); Senior Project Associate, Electrical Engineering, Indian Institute of Technology, Kanpur (2017 – 2018)

Batoul TakiBatoul Taki

Joining date: Fall 2018
Intended degrees: MS and PhD
Research interests: Tensor-based signal processing

Previous affiliations: American University of Science and Technology, Beirut (BS)

Other information: ECE Best TA Award, Fall 2018 and Spring 2019

Joseph ShenoudaJoseph Shenouda

Joining date: Fall 2019
Intended degree: BS
Research interests: Graph signal processing

Previous affiliations: N/A

Other information: N/A

Cheng FangCheng Fang

Joining date: Spring 2020
Intended degree: PhD
Research interests: Distributed machine learning

Previous affiliations: University of California, Los Angles (MS); Rutgers University (BS)

Other information: Rutgers ECE Ambassador and Fish Bowl Tutor (2016 – 2017)

Venkat RoyVenkat Roy

Joining date: Spring 2020
Position: Postdoctoral Research Associate
Research interests: Inverse problems; compressed sensing; graph signal processing; convex optimization

Previous affiliations: Postdoctoral Researcher, Delft University of Technology (2019 – 2020); Signal Processing Engineer, NXP Semiconductors, Eindhoven, The Netherlands (2017 – 2018)

Other information: PhD, Delft University of Technology, 2017

Muhammad Asad Lodhi (2014 – 2020)

Degree: PhD, Electrical Engineering, Rutgers University
PhD thesis title: Structure in modern data and how to exploit it: Some signal processing applications

Last known affiliation: Staff Researcher, InterDigital

Other information: ECE Graduate Academic Achievement Award, 2020; ECE Research Excellence Award, 2017; ECE Best TA Award, 2015; Intern, Mitsubishi Electric Research Labs

Zhixiong Yang (2015 – 2020)

Degree: PhD, Electrical Engineering, Rutgers University
PhD thesis title: Byzantine-resilient decentralized learning

Last known affiliation: Machine Learning Systems Engineer, Blue Danube Systems

Other information: ECE Student Development Award, 2016; Intern, Bell Labs

Bingqing XiangBingqing Xiang (2018 – 2020)

Degree: MS, Electrical Engineering, Rutgers University
MS thesis title: Edge-friendly distributed PCA

INSPIRE Lab AlumAndrii Hlyvko (2016 – 2020)

Degree: MS, Electrical Engineering, Rutgers University (co-advised with F. J. Diez)
MS thesis title: Performance comparison of stereo and RGB sensors for UAV collision avoidance

Talal Ahmed (2013 – 2019)

Degrees: MS and PhD, Electrical Engineering, Rutgers University
PhD thesis title: Some methods for statistical inference using high-dimensional linear models
MS thesis title: Geometric manifold approximation using locally linear approximations

Last known affiliation: Research Scientist, Tempus Labs

Other information: Best Student Paper Award (2nd place), IEEE CAMSAP 2017; ECE Research Excellence Award, 2013; IEEE SPS Travel Award, IEEE ICASSP 2013; Summer Intern, Philips Research; Summer Intern, AT&T Research Lab

Haroon Raja (2013 – 2019)

Degree: PhD, Electrical Engineering, Rutgers University
PhD thesis title: Nonconvex representation learning from distributed datasets

Last known affiliation: Research Fellow, University of Michigan

Other information: Intern, Bell Labs

Zahra Shakeri (2013 – 2019)

Degrees: MS and PhD, Electrical Engineering, Rutgers University
PhD thesis title: Dictionary learning and multidimensional processing for tensor data
MS thesis title: Identification of overcomplete dictionaries and their application in distributed classification problems

Last known affiliation: AI Scientist III, Electronic Arts (EA)

Other information: ECE Graduate Academic Achievement Award, 2020; IEEE Student Travel Award, ISIT 2016; ECE Research Excellence Award, 2015; ECE Best TA Award, 2015; Intern, Adobe Research; Intern, Technicolor Labs

Tong WuTong Wu (2012 – 2017)

Degree: PhD, Electrical Engineering, Rutgers University
PhD Thesis title: Learning the nonlinear geometric structure of high-dimensional data: Models, algorithms, and applications

Last known affiliation: Machine Learning Engineer, FactSet

Other information: Best Student Paper Award, IEEE IVMSP 2016; ECE Research Excellence Award, 2015; ECE Student Development Award, 2013; Visiting Student Researcher, Army Research Lab; Intern, AT&T Research Lab

Neha TadimetiNeha Tadimeti (2015 – 2017)

Degree: MS, Electrical Engineering, Rutgers University
MS thesis title: Multilinear algebra based techniques for foreground and background separation

Last known affiliation: System Software Engineer, NVIDIA Corporation

INSPIRE Lab AlumXinnan Cao (2014 – 2015)

Degree: MS, Electrical Engineering, Rutgers University (co-advised with M. Javanmard)
MS thesis title: Detrending and denoising of impedance cytometry data

Last known affiliation: Director, Customer Support, LT Security Inc.

Andrew HarmsAndrew Harms (2011 – 2013)

Degree: PhD, Electrical Engineering, Princeton University (co-advised with R. Calderbank)
PhD thesis title: Considerations on the optimal and efficient processing of information-bearing signals

Last known affiliation: Assistant Professor, Department of Electrical and Computer Engineering, University of Nebraska-Lincoln

Other information: Postdoctoral researcher at Duke University, 2013 – 2016

Kenza HamidoucheKenza Hamidouche (2018 – 2019)

Position: Postdoctoral Research Associate, Rutgers University
Research focus: Game theory and reinforcement learning

Last known affiliation: Postdoctoral Research Associate, Princeton University

Other information: PhD, CentraleSupelec, France, 2016; Visiting Scholar, Virginia Tech, 2015

Gianna GertonGianna Gerton (2018 – 2019)

Degree: BS, Computer Science, Rutgers University
Research topic: Decentralized machine learning

Last known affiliation: Full Stack Developer at ThankView.com

Other information: Aresty Research Assistant, 2018 – 2019

Andrea BurnsAndrea Burns (Summer 2017)

Degree: BS, Mathematics and Computer Science, Tulane University
Research topic: Machine learning from multimodal data

Last known affiliation: PhD Student, Boston University

Other information: Rutgers DIMACS REU Student, Summer 2017

Muhammad Talha ParachaMuhammad Talha Paracha (Summer 2017)

Degree: BS, Software Engineering, National University of Sciences and Technology, Pakistan
Research topic: Distributed averaging consensus for the internet-of-things

Last known affiliation: PhD Student, Northeastern University

Other information: NUST—Rutgers REU Program Student, Summer 2017

Zachary BlancoZachary Blanco (2016 – 2017)

Degree: BS, Electrical Engineering, Rutgers University
Research topic: Distributed averaging consensus for the internet-of-things

Last known affiliation: Software Engineer, Alluxio, Inc.

Other information: Aresty Research Assistant, 2016 – 2017

Marielle Jurist (2016 – 2017)

Degree: BS, Mathematics and Computer Science, Rutgers University
Research topic: Distributed averaging consensus for the internet-of-things

Last known affiliation: Data Scientist, Munich American Reassurance Company

Other information: Aresty Research Assistant, 2016 – 2017

Kien NguyenKien Nguyen (2016 – 2017)

Degree: BS, Electrical Engineering, Rutgers University
Research topic: GPU implementation of compressive sensing reconstruction algorithms

Last known affiliation: Engineer, Interactions Corporation