Distinguished Lecturers

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Distinguished Lecturers

The following is a list of Signal Processing Society's distinguished lecturers.

Distinguished Lecturers Page Image

2020 Distinguished Lecturers

Andrea Cavallaro

Andrea Cavallaro (M) is Professor of Multimedia Signal Processing and the founding Director of the Centre for Intelligent Sensing at Queen Mary University of London, UK. He is Fellow of the International Association for Pattern Recognition (IAPR) and Turing Fellow at the Alan Turing Institute, the UK National Institute for Data Science and Artificial Intelligence. He received his Ph.D. in Electrical Engineering from the Swiss Federal Institute of Technology (EPFL), Lausanne, (2002) and was a Research Fellow with British Telecommunications (BT) (2004/2005).

Prof. Cavallaro is Chair, IEEE Signal Processing Society, Image, Video, and Multidimensional Signal Processing Technical Committee (2020-2021); Member, IEEE Circuits and Systems Society Visual Signal Processing and Communication Technical Committee (since 2015). He is Senior Area Editor, IEEE Transactions on Image Processing (2016-2021); Associate Editor, IEEE Transactions on Circuits and Systems for Video Technology (2016-2019) and IEEE Transactions on Multimedia (2016-2018); Area Editor, IEEE Signal Processing Magazine (2012-2014); and past Associate Editor, for the IEEE Transactions on Image Processing (2011-2015), IEEE Transactions on Signal Processing (2009-2011), IEEE Transactions on Multimedia (2009-2010) and IEEE Signal Processing Magazine (2008-2011). Prof. Cavallaro is a past elected member, IEEE Multimedia Signal Processing Technical Committee (2006-2009); IEEE Image, Video, and Multidimensional Signal Processing Technical Committee (2011-2016), and chair of its Awards committee (2013-2016).

Prof. Cavallaro was awarded the Royal Academy of Engineering teaching Prize in 2007; three student paper awards on target tracking and perceptually sensitive coding at IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) in 2005, 2007 and 2009; and the best paper award at IEEE International Conference on Advanced Video and Signal-based Surveillance (AVSS) in 2009. Prof. Cavallaro has published over 270 journal and conference papers, one monograph on Video tracking (2011, Wiley) and three edited books: Multi-camera networks (2009, Elsevier); Analysis, retrieval and delivery of multimedia content (2012, Springer); and Intelligent multimedia surveillance (2013, Springer).

Lecture Topics

  • Audio-visual robotic perception
  • Body cameras and first-person vision
  • Machine learning for robust and privacy preserving analytics
  • Underwater image processing and restoration

Gaurav Sharma

Gaurav Sharma (F) is with the University of Rochester (UR), Rochester, NY, where he is a Professor in the Departments of Electrical and Computer Engineering, Computer Science, and Biostatistics and Computational Biology, and a Distinguished Researcher in Center of Excellence in Data Science (CoE) at the Goergen Institute for Data Science. He served as the Director for the Center for Emerging and Innovative Sciences (CEIS) (2008-2010). From 1996 through 2003, he was with Xerox Research and Technology in Webster, NY first as a member of research and technology staff and then as a Principal Scientist and Project Leader. He received the Ph.D. in Electrical and Computer Engineering in 1996 from North Carolina State University (NCSU), Raleigh, NC, and Masters degrees in Applied Mathematics from NCSU (1995) and in Electrical Communication Engineering (1992) from the Indian Institute of Science (IISc), Bangalore, India. He received his bachelor of engineering degree in Electronics and Communication Engineering in 1990 from Indian Institute of Technology, Roorkee (formerly, Univ. of Roorkee).

Dr. Sharma is a Fellow of the IEEE (2013), a Fellow of SPIE -- the international society for optics and photonics (2013), and a Fellow of the Society for Imaging Science and Technology (IS&T) (2013). He is also an elected member of Sigma Xi - the scientific research society (1997) and the Phi Kappa Phi (1994) and Pi Mu Epsilon (1995) honor societies. He received an IEEE Region I Technical Innovation Award in 2008 for “Contributions to the Theory and Practice of Color Imaging and Imaging Systems.” Dr. Sharma has been inducted into the NCSU Electrical and Computer Engineering Department Alumni Hall of Fame (2018) and awarded the M.N.S. Swamy and S.V.C. Aiya medals at IISc in 1992.

Dr. Sharma is Editor-in-Chief, IEEE Transactions on Image Processing (2018-present), Editor-in-Chief, IEEE Journal of Electronic Imaging (2011 through 2015), Associate Editor, IEEE Transactions on Information Forensics and Security (2004-2009), and for the IEEE Transactions on Image Processing (2003-2008). Dr. Sharma served as Chair, Image, Video, and Multi-dimensional Signal Processing (IVMSP) Technical Committee (2010-2011), Member, Image, Video, and Multi-dimensional Signal Processing Technical Committee (2006-2012), Information Forensics and Security Technical Committee (2010-2012), Multimedia Signal Processing Technical Committee (2015-2017), and the IEEE Signal Processing Society ‘s Industry DSP Technology Standing Committee (2005-2008). In 2015 and 2016, he served on the IEEE Signal Processing Society's Conference Board and its Executive subcommittee. Dr. Sharma was Technical Program Co-Chair for the IEEE International Conference on Image Processing (ICIP) (2012 and 2016) and Chair for the Rochester, NY SPS Chapter (2003).

Lecture Topics

  • Large scale visual data analytics for geospatial applications
  • Turbo-decoding and belief propagation in bioinformatics
  • Imaging arithmetic: physics u math > physics + math
  • Set theoretic feasibility and optimality frameworks for data hiding and privacy
  • High capacity data hiding for printed images
  • Color barcodes for mobile and other applications

Ami Wiesel

Ami Wiesel (SM) received the B.Sc. and M.Sc. degrees in electrical engineering from Tel-Aviv University, Tel-Aviv, Israel, in 2000 and 2002, respectively, and the Ph.D. degree in Electrical Engineering from the Technion-Israel Institute of Technology, Haifa, Israel, in 2007. He was a Postdoctoral Fellow in the Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA, during 2007–2009. He is currently an Associate Professor in the Rachel and Selim Benin School of Computer Science and Engineering, Hebrew University, Jerusalem, Israel. Since 2018, he is also a Visiting Researcher in Google.

Prof. Wiesel has served as Associate Editor, IEEE Transactions on Signal Processing in (2013-2017), on the Sensor Array and Multichannel Technical Committee (2013-2017), and on the Signal Processing Theory and Methods Technical Committee (2013-2015). He received the IEEE Signal Processing Society Young Author Paper Award in 2008, and co-authored award winning papers in the IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) (2005 and 2017).

Lecture Topics

  • Binary optimizations in signal processing
  • Multitask regressions and flood forecasting
  • Structured and robust covariance estimation

Xiao-Ping (Steven) Zhang

Xiao-Ping (Steven) Zhang (SM) received B.S. and Ph.D. degrees from Tsinghua University, in 1992 and 1996, respectively, both in Electronic Engineering. He holds an MBA in Finance, Economics and Entrepreneurship with Honors from the University of Chicago Booth School of Business, Chicago, IL. Since Fall 2000, he has been with the Department of Electrical and Computer Engineering, Ryerson University, where he is now Professor, Director of Communication and Signal Processing Applications Laboratory (CASPAL). He has served as Program Director of Graduate Studies. He is cross appointed to the Finance Department at the Ted Rogers School of Management at Ryerson University. He was Visiting Scientist at Research Laboratory of Electronics (RLE), Massachusetts Institute of Technology, in 2015 and 2017.

Dr. Zhang is a registered Professional Engineer in Ontario, Canada, and a member of Beta Gamma Sigma Honor Society. He is the General Co-Chair, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) (2021); General Co-Chair, IEEE Global Conference on Signal and Information Processing (GlobalSIP) Symposium on Signal, Information Processing and AI for Finance and Business (2019); and the General Co-Chair, GlobalSIP Symposium on Signal and Information Processing for Finance and Business (2017). He is an elected Member, IEEE International Conference on Multimedia and Expo (ICME) steering committee (2017-present); General Chair, IEEE International Workshop on Multimedia Signal Processing (MMSP) (2015); Publicity Chair, IEEE International Conference on Multimedia and Expo (ICME) (2006); and Program Chair, International Conference on Intelligent Computing (ICIC) (2005 and 2010). He served as Guest Editor, Multimedia Tools and Applications and International Journal of Semantic Computing. He is a tutorial speaker in ACM Multimedia (ACMM) (2011); IEEE International Symposium on Circuits and Systems (ISCAS) (2013); IEEE International Conference on Image Processing (ICIP) (2013); IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2014); International Joint Conference on Neural Networks (IJCNN) (2017); and IEEE International Symposium on Circuits and Systems (ISCAS) (2019).

Dr. Zhang is Senior Area Editor, IEEE Transactions on Signal Processing (2017-present) and IEEE Transactions on Image Processing (2019-present). He was Associate Editor, IEEE Transactions on Signal Processing (2012-2016), IEEE Transactions on Image Processing (2015-2019), IEEE Transactions on Multimedia (2012-2016), IEEE Transactions on Circuits and Systems for Video Technology (2015-2019), and IEEE Signal Processing Letters (2011-2015). He is an elected Member of Image, Video, and Multidimensional Signal Processing Technical Committee (2014-present), Multimedia Signal Processing Technical Committee (2014-2019), Signal Processing Theory and Methods Technical Committee (2018-present), Sensor Array and Multichannel Technical Committee (2019-present), and Industry DSP Technology Standing Committee (2011-2016) of IEEE Signal Processing Society.

Dr. Zhang’s research interests include image and multimedia content analysis, statistical signal processing, machine learning, and applications in big data, finance, and marketing.

Lecture Topics

  • signal processing, ai and big data for finance, economics, and business
  • passive localization and tracking for internet of things
  • graphical probabilistic modeling, machine learning and signal processing on graph with applications in multimedia

Qing Zhao

Qing Zhao (F) is a Joseph C. Ford Professor of Engineering at Cornell University. Prior to that, she was a Professor in the Electrical and Computer Engineering Department at University of California, Davis (2004-2015). She received a Ph.D. degree in Electrical and Computer Engineering from Cornell in 2001.

Dr. Zhao is a Fellow of IEEE (2013), a Marie Skłodowska-Curie Fellow of the European Union Research and Innovation Program (2018), and a Jubilee Chair Professor of Chalmers University during her 2018-2019 sabbatical leave. She received the IEEE Signal Processing Magazine Best Paper Award (2010) and the IEEE Signal Processing Society Young Author Best Paper Award (2000). She is a coauthor of Student Paper Award at the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) (2006) and the first place winner of Student Paper Contest at IEEE Asilomar Conference on Signals, Systems, and Computers (2006).

Dr. Zhao is a member of the IEEE Signal Processing Magazine Senior Editorial Board since 2018. She was an elected member of the Signal Processing Theory and Method Technical Committee (2012-2015) and the Signal Processing for Communications and Networking Technical Committee (2006-2011); Organizing Committee Member, IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) (2018, 2005); Symposium Co-Chair, IEEE Global Conference on Signal and Information Processing (GlobalSIP) (2013); Co-Chair, IEEE Global Communications Conference (GLOBECOM) (2011). She served as Associate Editor, IEEE Transactions on Signal Processing (2006-2009) and edited several special issues for IEEE Journal of Selected Topics in Signal Processing (2013, 2008), IEEE Journal on Selected Areas in Communications (2012), and IEEE Signal Processing Magazine (2007).

Dr Zhao’s research interests include statistical inference, sequential decision theory, stochastic optimization, machine learning, and algorithmic theory with applications in infrastructure, communications, and social-economic networks.

Lecture Topics

  • Active hypothesis testing for anomaly detection in large-scale complex networks
  • Multi-armed bandits for online learning
  • Adversarial machine learning: label efficiency, prediction accuracy, and robustness
  • Stochastic convex optimization and approximation: classical results and recent advances
  • Distributed no-regret learning in multi-agent systems

 

2019 Distinguished Lecturers

Petros T. Boufounos

Petros T. Boufounos (SM) is Senior Principal Research Scientist and the Computational Sensing Team Leader at Mitsubishi Electric Research Laboratories (MERL), and a visiting scholar at the Rice University Electrical and Computer Engineering Department. Dr. Boufounos completed his undergraduate and graduate studies at MIT. He received the S.B. degree in Economics in 2000, the S.B. and M.Eng. degrees in Electrical Engineering and Computer Science (EECS) in 2002, and the Sc.D. degree in EECS in 2006. Between September 2006 and December 2008, he was a postdoctoral associate with the Digital Signal Processing Group at Rice University. Dr. Boufounos joined MERL in January 2009, where he has been heading the Computational Sensing Team since 2016.

Dr. Boufounos has served as Area Editor, IEEE Signal Processing Letters (2012-2014); Senior Area Editor, IEEE Signal Processing Letters (2014-2018); Member, SigPort Editorial Board (2015-2017); and is currently Member, IEEE Signal Processing Theory and Methods Technical Committee (2016-present). He received the SPS Best Paper Award (2015) and the Geoscience and Remote Sensing Society (GRSS) Symposium Paper Award (2014).

Dr. Boufounos' immediate research focus includes signal acquisition and processing, inverse problems, frame theory, quantization and data representations, with applications in compression, sensing, array processing, and LIDAR, among others. He is also interested into how signal acquisition interacts with other fields that use sensing extensively, such as machine learning, robotics and dynamical system theory.

Petros T. Boufounos
Mitsubishi Electric Research Laboratories
E: petrosb@merl.com; petros@boufounos.com

Lecture Topics

  • Embeddings and Information Representation
  • Inverse Problems in Array and Multichannel Signal Processing
  • Depth Sensing
  • Inverse Problems in Multi-Sensor Fusion

Israel Cohen

Israel Cohen (F) is a Professor of electrical engineering at the Technion - Israel Institute of Technology, Haifa, Israel. He received the B.Sc. (Summa Cum Laude), M.Sc. and Ph.D. degrees in electrical engineering from the Technion - Israel Institute of Technology, in 1990, 1993 and 1998, respectively.

Dr. Cohen served as Associate Editor, IEEE Transactions on Audio, Speech, and Language Processing (2004-2007); Associate Editor, IEEE Signal Processing Letters (2004-2008); Member, Audio and Acoustic Signal Processing Technical Committee (2012-2017); and Member, Speech and Language Processing Technical Committee (2013-2015).

Dr. Cohen is a Fellow of the IEEE “for contributions to the theory and application of speech enhancement”. He was awarded the Norman Seiden Prize for Academic Excellence (2017), the SPS Signal Processing Letters Best Paper Award (2014), the Alexander Goldberg Prize for Excellence in Research (2010), and the Muriel and David Jacknow Award for Excellence in Teaching (2009). He is a coauthor of Fundamentals of Signal Enhancement and Array Signal Processing (Wiley-IEEE Press, 2018).

Dr. Cohen’s research interests are in the broad area of signal processing, with a specific focus on array processing, statistical signal processing, analysis and modeling of acoustic signals, speech enhancement, noise estimation, microphone arrays, source localization, blind source separation, system identification and adaptive filtering.

Israel Cohen
Technion - Israel Institute of Technology

E: icohen@ee.technion.ac.il
https://israelcohen.com

Lecture Topics

  • Multichannel Signal Enhancement
  • Optimal Array Processing
  • Differential Beamforming
  • Robust Design of Beampatterns
  • Canonical Correlation Analysis in Speech Enhancement
  • Kronecker Product Beamforming
  • Array Processing in the Time Domain

Janusz Konrad

Janusz Konrad (F) received the Master’s degree from Technical University of Szczecin, Poland (1980) and the PhD degree from McGill University, Montréal, Canada (1989), both in electrical engineering. He joined INRS-Télécommunications, Montréal as a postdoctoral fellow (1989-1991) and then as a faculty member (1991-2000). Subsequently, he moved to Boston University where he is currently a Professor in the Department of Electrical and Computer Engineering.

Dr. Konrad is an IEEE Fellow. He was awarded the IEEE Signal Processing Magazine Best Paper Award (2001) and the EURASIP Image Communication Best Paper Award (2004-2005). He was also co-recipient of the Best Paper Award at the IEEE International Conference on Advanced Video and Signal Based Surveillance (2010) and a member of the winning team in Aerial View Activity Classification Challenge at the International Conference on Pattern Recognition (2010).

Dr. Konrad served as Member-at-Large on the Conference Board of the IEEE Signal Processing Society (2015-2016); Member, IEEE Image, Video, and Multidimensional Signal Processing Technical Committee (2000-2006); and currently Steering Committee Member, IEEE International Conference on Advanced Video and Signal Based Surveillance (2014-present). His service on Editorial Boards includes IEEE Transactions on Image Processing (1996-2000, 2013-2016 as Associate Editor, and since 2017 as a Senior Associate Editor), EURASIP Signal Processing: Image Communication (2011-present), IEEE Communications Magazine (1998-2012), EURASIP Journal on Image and Video Processing (2006-2010) and IEEE Signal Processing Letters (2002-2004). He was the General Chair of IEEE International Conference on Advanced Video and Signal Based Surveillance (2015) and served on organizing committees of many IEEE conferences.

Dr. Konrad’s interests include video processing and computer vision, stereoscopic and 3-D imaging and displays, visual sensor networks, human-computer interfaces, and cybersecurity.

Janusz Konrad
Boston University
E: jkonrad@bu.edu
http://sites.bu.edu/jkonrad

Lecture Topics

  • Privacy-Preserving Localization and Recognition of Human Activities
  • User Authentication for Natural User Interfaces
  • Towards Autonomous Video Surveillance

Anna Scaglione

Anna Scaglione (F) (M.Sc.'95, Ph.D. '99) is currently a professor in electrical and computer engineering at Arizona State University. She was Professor of Electrical Engineering previously at the University of California at Davis (2008-2014), and at Cornell University, (2001-2008). Prior to joining the engineering faculty at Cornell, Dr. Scaglione was an assistant professor at the University of New Mexico (2000-2001).

Dr. Scaglione was elected IEEE Fellow (2011). She was Editor-in-Chief, IEEE Signal Processing Letters (2012-2013); Associate Editor, IEEE Transactions on Wireless Communications (2002 to 2005); Editorial Board Member, IEEE Transactions on Signal Processing (2008 to 2010); Area Editor, IEEE Transactions on Signal Processing (2010-2011); Senior Editor, IEEE Transactions on Control of Networked Systems; General Chair, SPAWC (2005); Member, Signal Processing for Communications and Networking Technical Committee (2004 to 2009); Steering Committee Member, IEEE SmartGridComm Conference (2010 to 2015); Member-at-Large, IEEE Signal Processing Society Board of Governors (2012-2014).

Dr. Scaglione received the IEEE Signal Processing Best Paper Award (2000); and the IEEE Donald G. Fink Prize Paper Award (2013). Her research with her students was also honored with the IEEE Signal Processing Society Young Author Best Paper Award (Lin Li) (2013), and three conference best paper awards: the Ellersick Best Paper Award at MILCOM (2005), the Student Best Paper Award at Smartgridcomm (2014), and the Student Best Paper Award at ICASSP (2017). She was also a recipient of the NSF CAREER Grant (2002).

Dr. Scaglione’s expertise is in the broad area of statistical signal processing for communication, electric power systems and information and social networks. Her current research focuses on studying and enabling decentralized learning and signal processing in networked systems.

Anna Scaglione
Ira A. Fulton Schools of Engineering
E: Anna.Scaglione@asu.edu
http://lab.engineering.asu.edu/scaglione/

Lecture Topics

  • Distributed Signal Processing
  • Opinion Dynamics in Social Networks
  • Networked System Identification
  • Cooperative Transmission in Networked System
  • Distributed Synchronization and Scheduling via Pulse-Coupled Oscillators Model
  • Signal Processing in Energy Systems

Rui Zhang

Rui Zhang (F) received the B.Eng. and M.Eng. degrees from National University of Singapore in 1999 and 2001, respectively, and the Ph.D. degree from Stanford University, Stanford, CA USA, in 2007, all in electrical engineering. From 2007 to 2009, he worked as a Research Scientist at the Institute for Infocomm Research, ASTAR, Singapore. Since 2010, he has joined the Department of Electrical and Computer Engineering of National University of Singapore, where he is now a Dean’s Chair Associate Professor with the Faculty of Engineering.

Dr. Zhang was the recipient of the IEEE Communications Society Asia-Pacific Region Best Young Researcher Award (2011), and the Young Researcher Award of National University of Singapore (2015). He was co-recipient of the IEEE Marconi Prize Paper Award in Wireless Communications (2015), the IEEE Communications Society Asia-Pacific Region Best Paper Award (2016), the IEEE Signal Processing Society Best Paper Award (2016), the IEEE Communications Society Heinrich Hertz Prize Paper Award (2017), the IEEE Signal Processing Society Donald G. Fink Overview Paper Award (2017), and the IEEE Technical Committee on Green Communications & Computing (TCGCC) Best Journal Paper Award (2017). His co-authored paper received the IEEE Signal Processing Society Young Author Best Paper Award (2017).

Dr. Zhang served as the Guest Editor for three special issues in IEEE Journal of Selected Topics in Signal Processing and IEEE Journal on Selected Areas in Communications. He served as Member, IEEE Signal Processing for Communications and Networking Technical Committee (2012-2017); IEEE Sensor Array and Multichannel Technical Committee (2013-2015); and Vice Chair, IEEE Communications Society Asia-Pacific Board Technical Affairs Committee (2014-2015). He served as Editor, IEEE Transactions on Wireless Communications (2012-2016); the IEEE Journal on Selected Areas in Communications - Green Communications and Networking Series (2015-2016); and the IEEE Transactions on Signal Processing (2013-2017). He is now Editor for the IEEE Transactions on Communications and the IEEE Transactions on Green Communications and Networking. He serves as a member of the Steering Committee, IEEE Wireless Communications Letters.

Dr. Zhang’s current research interests include wireless information and power transfer, drone communication, wireless eavesdropping and spoofing, energy-efficient and energy-harvesting-enabled wireless communication, multiuser MIMO, cognitive radio, and optimization methods.

Rui Zhang
National University of Singapore
E: elezhang@nus.edu.sg
Website

Lecture Topics

  • Signal Processing and Optimization in UAV Communication and Trajectory Design
  • MIMO Communication and Signal Processing with Passive Intelligent Surface
  • Signal and System Design for Wireless Information and Power Transfer

 

2018 Distinguished Lecturers

 

Rick Blum

Rick S. Blum (F) received a B.S. in Electrical Engineering from the Pennsylvania State University (1984) and his M.S. and Ph.D in Electrical Engineering from the University of Pennsylvania (1987 and 1991).

Dr. Blum was a member of technical staff at General Electric Aerospace in Valley Forge, Pennsylvania (1984 to 1991) and he graduated from GE`s Advanced Course in Engineering. Since 1991, he has been with the Electrical and Computer Engineering Department at Lehigh University in Bethlehem, Pennsylvania where he is currently a Professor and holds the Robert W. Wieseman Endowed Research Professorship in Electrical Engineering.

Dr. Blum was on the editorial board for the Journal of Advances in Information Fusion of the International Society of Information Fusion. He was Associate Editor, IEEE Transactions on Signal Processing (2000-2002) and IEEE Communications Letters. He has edited special issues for IEEE Transactions on Signal Processing, IEEE Journal of Selected Topics in Signal Processing and IEEE Journal on Selected Areas in Communications. He was Member, Sensor Array and Multichannel Signal Processing Technical Committee (2009-2014); Member, Signal Processing for Communications and Networking Technical Committee (1999-2001); Member, Communications Theory Technical Committee of the IEEE Communications Society; and Member, Awards Committee of the IEEE Communications Society.

Dr. Blum is a Fellow of the IEEE “for scientific contributions to detection, data fusion and signal processing with multiple sensors”, which acknowledges contributions to the field of sensor networking. He is a former IEEE Signal Processing Society Distinguished Lecturer, an IEEE Third Millennium Medal winner, a Member of Eta Kappa Nu and Sigma Xi, and holds several patents. Dr. Blum was awarded an ONR Young Investigator Award and an NSF Research Initiation Award.

Dr. Blum’s research interests include signal processing for smart grid, communications, sensor networking, radar and sensor processing.

Rick S. Blum
Lehigh University
E: rblum@eecs.lehigh.edu

Lecture Topics

  • Cyber Attacks on Internet of Things Systems
  • Cyber Attacks on Sensor Systems for Estimation and Detection
  • Cyber Attacks on Smart Grid Systems
  • Improved IEEE 1588 Synchronization using Estimation Theory and Low Complexity
  • Realistic Performance Bounds on Passive Radar Systems
  • Ordering for Distributed Estimation and Detection

Kevin Bowyer

Kevin W. Bowyer (F) is the Schubmehl-Prein Professor of Computer Science and Engineering at the University of Notre Dame. Professor Bowyer earned his undergraduate degree at George Mason University, and his PhD in Computer Science at Duke University. He previously served on the faculty at the University of South Florida, the Swiss Federal Technical Institute and Duke University.

Professor Bowyer received an IEEE Technical Achievement Award from the IEEE Computer Society, “for pioneering contributions to the science and engineering of biometrics” (2014). Professor Bowyer is a Fellow of the IEEE, “for contributions to algorithms for recognizing objects in images”, and a Fellow of the IAPR, “for contributions to computer vision, pattern recognition and biometrics”. He has served as Editor-in-Chief, IEEE Transactions on Pattern Analysis and Machine Intelligence; Editor-In-Chief, IEEE Biometrics Compendium; and is currently serving on the editorial board of IEEE Access (for which was “Reviewer of the Month” in March 2016). He is serving as General Chair of the 2019 IEEE Winter Conference on Applications of Computer Vision.

Professor Bowyer’s most recent book is the Handbook of Iris Recognition, edited with Dr. Mark Burge.

Kevin Bowyer
University of Notre Dame
E: kwb@nd.edu
http://www.cse.nd.edu/~kwb

Lecture Topics

  • Iris Matching and De-Duplication of Voter Registration Lists
  • Detection of Contact-Lens-Based “Spoofing” In Iris Recognition
  • Lessons from Analyzing a Large, Operational Iris-Recognition Dataset
  • Biometric Recognition of Identical Twins
  • Synthesis of Realistic-Looking Face Images

Geert Leus

Geert Leus (F) received the M.Sc. and Ph.D. degree in Electrical Engineering from the KU Leuven, Belgium, in June 1996 and May 2000, respectively. He is now an "Antoni van Leeuwenhoek" Full Professor at the Faculty of Electrical Engineering, Mathematics and Computer Science of the Delft University of Technology, The Netherlands.

Dr. Leus is a Fellow of the IEEE and a Fellow of EURASIP. He received the IEEE Signal Processing Society Young Author Best Paper Award (2002); the IEEE Signal Processing Society Best Paper Award (2005); was Member-at-Large, Board of Governors of the IEEE Signal Processing Society (2015-2016); Chair, IEEE Signal Processing for Communications and Networking Technical Committee (2009-2010); Editor in Chief, EURASIP Journal on Advances in Signal Processing; Editorial Board Member, IEEE Transactions on Signal Processing (2007-2010); Editorial Board Member, IEEE Transactions on Wireless Communications; Editorial Board Member, IEEE Signal Processing Letters (2002-2005); and Editorial Board Member, the EURASIP Journal on Advances in Signal Processing. Currently, Dr. Leus is a Member of the IEEE Sensor Array and Multichannel Technical Committee (2012-Present); Associate Editor of Foundations and Trends in Signal Processing; and Editor-in-Chief, EURASIP Signal Processing.

Dr. Leus’ research interests are in the broad area of signal processing, with a specific focus on wireless communications, array processing, sensor networks, and graph signal processing.

Geert Leus
Delft, The Netherlands
E: g.j.t.leus@tudelft.nl
http://cas.et.tudelft.nl/~leus

Lecture Topics

  • Compressive Sensing for Power Spectral Estimation
  • Sparse Sensing for Statistical Inference
  • Graph Signal Processing: Filtering and Sampling
  • Stationary Graph Processes and Spectral Estimation
  • Subsampling for Graph Power Spectral Estimation
  • Prediction-Correction Methods for Time-Varying Optimization
  • Compressive Ultrasound Imaging

Marco Lops

Marco Lops (SM) was born and educated in Naples (Italy), where he received his Laurea and Ph. D. degrees from “Federico II” University. He was Assistant Professor and Associate Professor with the Department of Electronic Engineering at Federico II. Since 2000, he has been with the Department of Electrical and Information Engineering at University of Cassino and Southern Latium as a Professor. He was a visiting Research Fellow with the University of Connecticut and Rice University, and visiting Professor with University of Minnesota (2008) and Columbia University (2009). In 2009-2012, he was with Enseeiht, University of Toulouse (France) as a Full Professor (on leave of absence from University of Cassino and Southern Latium) and as a visiting Professor.

Dr. Lops served two terms as Member, Sensor Array and Multichannel Signal Processing Technical Committee (2009-2015); Associate Editor, Journal of Communications and Networks, IEEE Transactions on Information Theory, IEEE Signal Processing Letters, and he has been serving his second term as Associate Editor, IEEE Transactions on Signal Processing (2015-Present). In 2015, he was co-recipient of the 2014 Best Paper Award from the Journal of Communication and Networks. During 2018-2020, he will be serving as Distinguished Lecturer for the IEEE Signal Processing Society.

Dr. Lops’ research interests are in the field of detection and estimation, with emphasis on radar signal processing and signal processing for communications.

Marco Lops
University of Cassino and Southern Latium
E: lops@unicas.it

Lecture Topics

  • Track-Before-Detect for Early Detection and Track Initiation
  • Trade-Offs in MIMO Radar
  • Co-Existence Between Radar and Communication Systems
  • Wireless Communications in a Dynamic Scenario: A Random-Set-Theoretic Approach

Wing-Kin (Ken) Ma

Wing-Kin Ma (F) received the B.Eng. degree in electrical and electronic engineering from the University of Portsmouth, Portsmouth, U.K., in 1995, and the M.Phil. and Ph.D. degrees, both in electronic engineering, from The Chinese University of Hong Kong (CUHK), Hong Kong, in 1997 and 2001, respectively. He is currently an Associate Professor with the Department of Electronic Engineering, CUHK. From 2005 to 2007, he was also an Assistant Professor with the Institute of Communications Engineering, National Tsing Hua University, Taiwan, R.O.C. Prior to becoming a faculty member, he held various research positions with McMaster University, Canada; CUHK; and the University of Melbourne, Australia.

Dr. Ma is an IEEE Fellow. He is currently Senior Area Editor, IEEE Transactions on Signal Processing; Associate Editor, IEEE Transactions on Signal Processing (2008-2011); Associate Editor and Guest Editor of several journals, which include IEEE Signal Processing Letters (2012), IEEE Journal of Selected Areas in Communications, and IEEE Signal Processing Magazine. He was a tutorial speaker in EUSIPCO (2011) and ICASSP (2014). He is a Member, Signal Processing Theory and Methods Technical Committee (2012-Present); and Member, Signal Processing for Communications and Networking Technical Committee (2015-Present). Dr. Ma received the Research Excellence Award by CUHK (2013–2014), the IEEE Signal Processing Magazine Best Paper Award (2015), and the IEEE Signal Processing Letters Best Paper Award (2016).

Dr. Ma’s research interests are in signal processing, optimization and communications, with recent activities focused on MIMO transceiver designs and interference management, and structured matrix factorization with application to blind signal separation and hyperspectral remote sensing.

Wing-Kin Ma
The Chinese University of Hong Kong
E: wkma@ee.cuhk.edu.hk

Lecture Topics

  • Semidefinite Relaxation: From Classical Concepts to Recent Advances
  • Hyperspectral Unmixing in Remote Sensing: Learn the Wisdom There and Go Beyond (Machine Learning Included)
  • MIMO Transceiver Designs and Optimization: Beyond Beamforming and Perfect Channel Information

Patrick Wolfe (Data Science Lecturer)

Patrick J. Wolfe (SM) received B.S.E.E. and B.Mus. degrees from the University of Illinois at Urbana-Champaign (1998) and his Ph.D. from the University of Cambridge (2003) as U.S. National Science Foundation Graduate Research Fellow. After teaching at Cambridge from 2001–2003, he joined the faculty of Harvard University (2004) and received the Presidential Early Career Award for Scientists and Engineers from the White House (2008). In 2012, he returned to the UK to take up an Established Career Fellowship in the Mathematical Sciences at University College London (UCL), where he also served as a Royal Society Research Fellow and as founding Executive Director of UCL’s Big Data Institute. In 2017, he was appointed the Frederick L. Hovde Dean of Science at Purdue University.

Dr. Wolfe is also a trustee and non-executive director of the Alan Turing Institute, the U.K.’s National Institute for Data Science, and serves on the board of its commercial subsidiary. Previously the Institute’s Deputy Director and recently named its first honorary fellow, he played a leading role in establishing the institute and shaping its priorities through an extensive program of engagement with a diverse range of experts and stakeholders. He has provided expert advice on applications of data science to policy, societal, and commercial challenges, including to the U.S. and U.K. governments and to a range of public and private bodies—including most recently the U.K. Food Standards Agency as an inaugural member of its Science Council. Dr. Wolfe is currently Chair, IEEE SPS Big Data Special Interest Group and serves on the steering committee of the IEEE SPS Data Science Initiative, as well as Co-Chair, Data Science Section of the Institute for Mathematical Statistics.

Dr. Wolfe has received awards for his research from a number of international bodies, including the Royal Society, the Acoustical Society of America, and the IEEE. He is active in the global mathematics, statistics, and physical sciences communities, and most recently was an organizer and Simons Foundation Fellow at the Isaac Newton Institute for Mathematical Sciences 2016 semester research program on Theoretical Foundations for Statistical Network Analysis.

Patrick J. Wolfe, Frederick L. Hovde Dean
College of Science, Purdue University
E: patrick@purdue.edu
Assistant: Angie Teel
E: teel@purdue.edu

Lecture Topics

  • Core Technical Challenges in Data Science
  • Data Science for Policy and Public Good
  • Data Science Education and Academic Programs
  • Data Governance, Data Sharing, Legal Frameworks, and Ethics
  • Algorithms, Artificial Intelligence, and The Law
  • Setting Up Successful Data Science Initiatives: Lessons Learned
  • Big Network Data: Challenges and Opportunities
  • Understanding the Behavior of Large Networks
  • Nonparametric Statistics for Network Analysis and Comparison

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