PEOPLE 2017-11-24T09:49:50+00:00

Waheed U. BajwaProf. Waheed U. Bajwa

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

Research Interests

High-dimensional inference and inverse problems, geometrical methods for “big data” analytics, sampling theory, statistical signal processing, machine learning, wireless communications, and applications in biological sciences, complex networked systems, and radar & image processing.

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 is currently an Associate Professor in the Department of Electrical and Computer Engineering at Rutgers University. His research interests include statistical signal processing, high-dimensional statistics, machine learning, networked systems, and inverse problems.

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 Engineering Governing Council ECE Professor of the Year Award (2016, 2017), and Rutgers University’s Presidential Fellowship for Teaching Excellence (2017). He is a co-investigator on the work that received the Cancer Institute of New Jersey’s Gallo Award for Scientific Excellence in 2017, a co-author on the paper that received the Best Student Paper Award at the IEEE IVMSP 2016 Workshop, and a Member of the Class of 2015 National Academy of Engineering Frontiers of Engineering Education Symposium. He co-guest edited a special issue of Elsevier Physical Communication Journal on “Compressive Sensing in Communications” (2012), co-chaired CPSWeek 2013 Workshop on Signal Processing Advances in Sensor Networks and IEEE GlobalSIP 2013 Symposium on New Sensing and Statistical Inference Methods, and served as the Publicity and Publications Chair of IEEE CAMSAP 2015 and General Chair of the 2017 DIMACS Workshop on Distributed Optimization, Information Processing, and Learning. He is currently Technical Co-Chair of the IEEE SPAWC 2018 Workshop, an Associate Editor of the IEEE Signal Processing Letters, a Senior Member of the IEEE, and serves on the MLSP, SAM, and SPCOM Technical Committees of the IEEE Signal Processing Society.

Haroon Raja

Intended degree: PhD
Joining date: Spring 2013
Previous affiliations: National University of Sciences and Technology (BS/MS)
Research interests: Distributed information processing; distributed optimization
Other information: Summer Intern, Bell Labs

Talal Ahmed

Intended degree: MS/PhD
Joining date: Spring 2013
Previous affiliations: Lahore University of Management and Sciences (BS)
Research interests: High-dimensional statistics; machine learning
Other information: ECE Research Excellence Award, 2013; IEEE SPS Student Travel Award, ICASSP 2013; Summer Intern, AT&T Research Lab

Zahra Shakeri

Intended degree: MS/PhD
Joining date: Fall 2013
Previous affiliations: Sharif University of Technology (BS)
Research interests: Information processing for tensor data; dictionary learning
Other information: IEEE Student Travel Award, ISIT 2016; ECE Research Excellence Award, 2015; ECE Best TA Award, 2015; Summer Intern, Technicolor Labs

Muhammad Asad Lodhi

Intended degree: PhD
Joining date: Fall 2014
Previous affiliations: Lahore University of Management and Sciences (BS/MS)
Research interests: Subspace-based information processing; computational imaging
Other information: ECE Research Excellence Award, 2017; ECE Best TA Award, 2015

Zhixiong Yang

Intended degree: PhD
Joining date: Spring 2015
Previous affiliations: Northeastern University (MS); Beijing Jiaotong University (BS)
Research interests: Robust information processing; distributed optimization
Other information: ECE Student Development Award, 2016

Arpita GangArpita Gang

Intended degree: PhD
Joining date: Fall 2017
Previous affiliations: Indraprastha Institute of Information Technology, Delhi (M. Tech); National Institute of Technology, Silchar (B. Tech)
Research interests: Distributed information processing; distributed optimization
Other information: N/A

Tong WuTong Wu (2012 – 2017)

Degree: PhD, Electrical Engineering, Rutgers University
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, IVMSP 2016; ECE Research Excellence Award, 2015; ECE Student Development Award, 2013; Visiting Student Researcher, Army Research Lab; Summer Intern, AT&T Research Lab

Andrew HarmsAndrew Harms (2011 – 2013)

Degree: PhD, Electrical Engineering, Princeton University (co-advised with R. Calderbank)
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

Neha TadimetiNeha Tadimeti (2015 – 2016)

Degree: MS, Electrical Engineering, Rutgers University
Thesis title: Multilinear algebra based techniques for foreground and background separation
Last known affiliation: Deep Learning R&D Engineer, NVIDIA Corporation
Other information: N/A

INSPIRE Lab AlumXinnan Cao (2014 – 2015)

Degree: MS, Electrical Engineering, Rutgers University (co-advised with M. Javanmard)
Thesis title: Detrending and denoising of impedance cytometry data
Last known affiliation: Engineer, LT Security Inc.
Other information: N/A

Andrea BurnsAndrea Burns (Summer 2017)

Degree: BS, Mathematics and Computer Science, Tulane University
Research topic: Machine learning from multimodal data
Last known affiliation: Senior at Tulane University
Other information: Rutgers DIMACS REU Student, Summer 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: Senior at Rutgers University
Other information: Aresty Research Assistant, 2016 – 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: Senior at Rutgers University
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
Other information: N/A