David Tse received the BASc degree in systems design engineering from University of Waterloo in 1989, and the MS and PhD degrees in electrical engineering from Massachusetts Institute of Technology in 1991 and 1994 respectively. From 1994 to 1995, he was a postdoctoral member of technical staff at A.T. & T. Bell Laboratories. From 1995 to 2014, he was on the faculty of the University of California at Berkeley. He is currently the Thomas Kailath and Guanghan Xu Professor at Stanford University.
David Tse was elected member of the U.S. National Academy of Engineering in 2018. He was the recipient of the IEEE Claude E. Shannon Award in 2017 and the IEEE Richard W. Hamming Medal in 2019. Previously, he received a NSF CAREER award in 1998, the Erlang Prize from the INFORMS Applied Probability Society in 2000 and a Gilbreth Lectureship from the National Academy of Engineering in 2012. He received multiple best paper awards, including the Information Theory Society Paper Award in 2003, the IEEE Communications Society and Information Theory Society Joint Paper Awards in 2000, 2013 and 2015, the Signal Processing Society Best Paper Award in 2012 and the IEEE Communications Society Stephen O. Rice Prize in 2013. For his contributions to education, he received the Outstanding Teaching Award from the Department of Electrical Engineering and Computer Sciences at U.C. Berkeley in 2008 and the Frederick Emmons Terman Award from the American Society for Engineering Education in 2009. He is a coauthor, with Pramod Viswanath, of the text Fundamentals of Wireless Communication, which has been used in over 60 institutions around the world. He is the inventor of the proportional-fair scheduling algorithm used in all third and fourth-generation cellular systems, serving 2.7 billion subscribers around the world. He is a member of the Stanford Center for Blockchain Research.
Benjamin Van Roy is a Professor at Stanford University, where he has served on the faculty since 1998. His research focuses on the design, analysis, and application of reinforcement learning algorithms. Beyond academia, he leads a DeepMind Research team in Mountain View, and has also led research programs at Unica (acquired by IBM), Enuvis (acquired by SiRF), and Morgan Stanley.
He is a Fellow of INFORMS and IEEE and has served on the editorial boards of Machine Learning, Mathematics of Operations Research, for which he co-edited the Learning Theory Area, Operations Research, for which he edited the Financial Engineering Area, and the INFORMS Journal on Optimization.
He received the SB in Computer Science and Engineering and the SM and PhD in Electrical Engineering and Computer Science, all from MIT, where his doctoral research was advised by John N. Tstitsiklis. He has been a recipient of the MIT George C. Newton Undergraduate Laboratory Project Award, the MIT Morris J. Levin Memorial Master's Thesis Award, the MIT George M. Sprowls Doctoral Dissertation Award, the National Science Foundation CAREER Award, the Stanford Tau Beta Pi Award for Excellence in Undergraduate Teaching, and the Management Science and Engineering Department's Graduate Teaching Award. He has held visiting positions as the Wolfgang and Helga Gaul Visiting Professor at the University of Karlsruhe, the Chin Sophonpanich Foundation Professor and the InTouch Professor at Chulalongkorn University, a Visiting Professor at the National University of Singapore, and a Visiting Professor at the Chinese University of Hong Kong, Shenzhen.
Technische Universität Braunschweig
Eduard A. Jorswieck was born in 1975 in Berlin, Germany. He is managing director of the Institute of Communications Technology and the head of the Chair for Communications Systems and Full Professor at Technische Universitaet Braunschweig, Brunswick, Germany. From 2008 until 2019, he was the head of the Chair of Communications Theory and Full Professor at Dresden University of Technology (TUD), Germany. Eduard's main research interests are in the broad area of communications. He has published more than 130 journal papers, 15 book chapters, 3 monographs, and some 275 conference papers on these topics. Dr. Jorswieck is IEEE Fellow. He is member of the IEEE SAM Technical Committee since 2015. Since 2017, he serves as Editor-in-Chief of the EURASIP Journal on Wireless Communications and Networking. He serves currently on the editorial board for IEEE Transactions on Information Forensics and Security. In 2006, he received the IEEE Signal Processing Society Best Paper Award.
Erik G. Larsson is Professor and Head of the Division for Communication Systems in the Department of Electrical Engineering (ISY) at Linköping University (LiU) in Linköping, Sweden. He joined LiU in September 2007. He has previously held positions at the Royal Institute of Technology (KTH) in Stockholm, University of Florida, George Washington University (USA), and Ericsson Research (Stockholm). He received his Ph.D. from Uppsala University in 2002. In the spring of 2015 he was a Visiting Fellow at Princeton University, USA, for four months.
His main professional interests are within the areas of wireless communications and signal processing. He has published some 200 journal papers on these topics, he is co-author of the two Cambridge University Press textbooks Space-Time Block Coding for Wireless Communications (2003) and Fundamentals of Massive MIMO (2016) and he holds 19 issued and many pending patents on wireless technology.
He has served as Associate Editor for several major journals, including the IEEE Transactions on Communications (2010-2014) and IEEE Transactions on Signal Processing (2006-2010). During 2015-2016 he served as chair of the IEEE Signal Processing Society SPCOM technical committee, and in 2017 he was the past chair of this committee. He served as chair of the steering committee for the IEEE Wireless Communications Letters in 2014-2015. He was the General Chair of the Asilomar Conference on Signals, Systems and Computers in 2015, and the Technical Chair in 2012. He was a member of the IEEE Signal Processing Society Awards Board during 2017-2019, and is a member of the IEEE Signal Processing Magazine editorial board during 2018-2020. He serves on the steering committee of the IEEE Transactions on Wireless Communications, 2019-2022.
He received the IEEE Signal Processing Magazine Best Column Award twice, in 2012 and 2014, and the IEEE ComSoc Stephen O. Rice Prize in Communications Theory in 2015, the IEEE ComSoc Leonard G. Abraham prize in 2017, the IEEE ComSoc Best Tutorial Paper Award in 2018, and the IEEE ComSoc Fred W. Ellersick Prize in 2019. He is a Fellow of the IEEE.
David Gesbert (IEEE Fellow) is Professor and Head of the Communication Systems Department, EURECOM. He obtained the Ph.D degree from Ecole Nationale Superieure des Telecommunications, France, in 1997. From 1997 to 1999 he has been with the Information Systems Laboratory, Stanford University. He was then a founding engineer of Iospan Wireless Inc, a Stanford spin off pioneering MIMO-OFDM (now Intel). Before joining EURECOM in 2004, he has been with the Department of Informatics, University of Oslo as an adjunct professor. D. Gesbert has published about 300 papers and 25 patents, some of them winning 2019 ICC Best Paper Award, 2015 IEEE Best Tutorial Paper Award (Communications Society), 2012 SPS Signal Processing Magazine Best Paper Award, 2004 IEEE Best Tutorial Paper Award (Communications Society), 2005 Young Author Best Paper Award for Signal Proc. Society journals, and paper awards at conferences 2011 IEEE SPAWC, 2004 ACM MSWiM. He has been a Technical Program Co-chair for ICC2017. He was named a Thomson-Reuters Highly Cited Researchers in Computer Science. Since 2015, he holds the ERC Advanced grant "PERFUME" on the topic of smart device Communications in future wireless networks. He is a Board member for the OpenAirInterface (OAI) Software Alliance. Since early 2019, he heads the Huawei-funded Chair on Adwanced Wireless Systems Towards 6G Networks. He sits on the Advisory Board of HUAWEI European Research Institute. In 2020, he was awarded funding by the French Interdisciplinary Institute on Artificial Intelligence for a Chair in the area of AI for the future IoT.
D. Gesbert was a co-editor of several special issues on wireless networks and communications theory, for JSAC (2003, 2007, 2009), EURASIP Journal on Applied Signal Processing (2004, 2007), Wireless Communications Magazine (2006). He served on the IEEE Signal Processing for Communications Technical Committee, 2003-2008. He was an associate editor for IEEE Transactions on Wireless Communications and the EURASIP Journal on Wireless Communications and Networking. He serves on the Scientific Boards of EURECOM and the UCN (User Centric Networking) Laboratory of Excellence (LABEX) in France. He co-authored the book “Space time wireless communications: From parameter estimation to MIMO systems”, Cambridge Press, 2006. He held visiting professor positions in KTH (2014) and TU Munich (2016). Since 2017 he is also a visiting Academic Master within the Program 111 at the Beijing University of Posts and Telecommunications as well as as a member in the Joint BUPT-EURECOM Open5G Lab.
University of Luxembourg
Björn Ottersten received the M.S. degree in electrical engineering and applied physics from Linköping University, Linköping, Sweden, in 1986, and the Ph.D. degree in electrical engineering from Stanford University, Stanford, CA, USA, in 1990. He has held research positions with the Department of Electrical Engineering, Linköping University, the Information Systems Laboratory, Stanford University, the Katholieke Universiteit Leuven, Leuven, Belgium, and the University of Luxembourg, Luxembourg. From 1996 to 1997, he was the Director of Research with ArrayComm, Inc., a start-up in San Jose, CA, USA, based on his patented technology. In 1991, he was appointed Professor of signal processing with the Royal Institute of Technology (KTH), Stockholm, Sweden. Dr. Ottersten has been Head of the Department for Signals, Sensors, and Systems, KTH, and Dean of the School of Electrical Engineering, KTH. He is currently the Founding Director for the Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg. He is a recipient of the IEEE Signal Processing Society Technical Achievement Award and the European Research Council advanced research grant twice. He has co-authored journal papers that received the IEEE Signal Processing Society Best Paper Award in 1993, 2001, 2006, 2013, and 2019, and 8 IEEE conference papers best paper awards. He has been a board member of IEEE Signal Processing Society, the Swedish Research Council and currently serves of the boards of EURASIP and the Swedish Foundation for Strategic Research. He has served as an Associate Editor for the IEEE TRANSACTIONS ON SIGNAL PROCESSING and the Editorial Board of the IEEE Signal Processing Magazine. He is currently a member of the editorial boards of IEEE Open Journal of Signal Processing, EURASIP Signal Processing Journal, EURASIP Journal of Advances Signal Processing and Foundations and Trends of Signal Processing. He is a fellow of EURASIP.
Tsinghua-Berkeley Shenzhen Institute
Ercan Engin Kuruoğlu received MPhil and PhD degrees in information engineering from the University of Cambridge, Cambridge, United Kingdom, in 1995 and 1998, respectively. In 1998, he joined Xerox Research Center Europe, Cambridge. He was an ERCIM fellow in 2000 with INRIA-Sophia Antipolis, France. In January 2002, he joined Institute of Science and Technology of Information-CNR (Italian National Council of Research), Pisa, Italy where he became a Chief Scientist in 2020. He was a visiting professor with Georgia Tech-China in 2007, 2011 and 2016, Izmir Institute of Technology in 2009, Southern University of Science and Technology of China, Shenzhen in 2017, Fraunhofer Heinrich Hertz Institute of Telecommunications in 2018 and University of Southern Australia in 2019. He is currently a Visiting Professor at Tsinghua-Berkeley Shenzhen Institute. He served as an Associate Editor for the IEEE Transactions on Signal Processing and IEEE Transactions on Image Processing. He is currently the editor in chief of Digital Signal Processing: A Review Journal. He acted as a Technical co-Chair for EUSIPCO 2006 and a Tutorials co-Chair of ICASSP 2014. He is a member of the IEEE Technical Committees on Signal Processing Theory and Methods, on Image, Video and Multidimensional Signal Processing and on Machine Learning for Signal Processing. He is also a member of Special Area Teams of EURASIP on Biomedical Signal and Image Analytics and on Machine Learning for Signal and Data Analytics. He was a plenary speaker at DAC 2007, ISSPA 2010, IEEE SIU 2017, Entropy 2018, WODS-TBSI 2019 and WOLT-TBSI 2020 and tutorial speaker at IEEE ICSPCC 2012. He was an Alexander von Humboldt Experienced Research Fellow in the Max Planck Institute for Molecular Genetics in 2013-2015. His research interests are in the areas of statistical signal and image processing and Information and coding theory with applications in remote sensing, telecommunications and computational biology.
University of Washington
Fei Xia is a Professor at the Linguistics Department at the University of Washington (UW) and an adjunct faculty at the Department of Biomedical and Health Informatics at the UW Medical School. Her research area is computational linguistics, and her research covers a wide range of NLP tasks including morphological analysis, grammar extraction and grammar generation, corpus development, machine translation, information extraction, and NLP for low-resource languages. One of her current research interests is bioNLP in the clinical domain, which is the focus of this talk. Her work is supported by grants from NSF, NIH, IARPA, IBM, Microsoft, Tencent, and UW. Fei Xia received her Bachelor's degree from Peking University, and M.S. and Ph.D. from the University of Pennsylvania (UPenn). After graduation, she worked at the IBM T. J. Watson Research Center before joining UW.
Shanghai Jiao Tong University
Meixia Tao is a Professor with the Department of Electronic Engineering, Shanghai Jiao Tong University, China. She received the Ph.D. degree in electrical and electronic engineering from Hong Kong University of Science and Technology in 2003. Her current research interests include wireless caching, edge computing, physical layer multicasting, and resource allocation.
Dr. Tao served as a member of the Executive Editorial Committee of the IEEE Transactions on Wireless Communications. She was on the Editorial Board of the IEEE Transactions on Wireless Communications (2007-2011), and the IEEE Transactions on Communications (2012-2018), the IEEE Communications Letters (2009-2012), and the IEEE Wireless Communications Letters (2011-2015). She has also served as Symposium Oversight Chair of IEEE ICC 2019, Symposium Co-Chair of IEEE GLOBECOM 2018, the TPC chair of IEEE/CIC ICCC 2014 and Symposium Co-Chair of IEEE ICC 2015.
Dr. Tao is a Fellow of IEEE. She is the recipient of the IEEE Marconi Prize Paper Award in 2019, the IEEE Heinrich Hertz Award for Best Communications Letters in 2013, the IEEE/CIC International Conference on Communications in China (ICCC) Best Paper Award in 2015, and the International Conference on Wireless Communications and Signal Processing (WCSP) Best Paper Award in 2012.
University of Chinese Academy of Sciences
Luonan Chen received BS degree in the Electrical Engineering, from Huazhong University of Science and Technology, and the M.E. and Ph.D. degrees in the electrical engineering, from Tohoku University, Sendai, Japan, in 1988 and 1991, respectively. From 1997, he was an associate professor of the Osaka Sangyo University, Osaka, Japan, and then a full Professor. Since 2010, he has been a professor and executive director at Key Laboratory of Systems Biology, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences. He was elected as the founding president of Computational Systems Biology Society of OR China, and Chair of Technical Committee of Systems Biology at IEEE SMC Society.In recent years, he published over 350 journal papers and two monographs (books) in the area of bioinformatics, nonlinear dynamics and machine learning.
Xuegong Zhang earned his BS degree in Industrial Automation in 1989 and Ph.D. degree in Pattern Recognition and Intelligent Systems in 1994, both from Tsinghua University. He joined the faculty of Tsinghua University in 1994, where he is now a Professor of Pattern Recognition and Bioinformatics in the Department of Automation, and an Adjunct Professor of the School of Life Sciences and the School of Medicine. Dr. Zhang worked at Harvard T.H. Chan School of Public Health as a visiting scientist on computational biology in 2001-2002 and 2006, and had been a visiting scholar in the MCB program at University of Southern California in 2007. He is the Director of the Bioinformatics Division, Beijing National Research Institute for Information Science and Technology (BNRist). He is the Chair of the Committee for Bioinformatics and Artificial Life in the Chinese Association for Artificial Intelligence (CAAI), and is a member of the Board of Directors of the International Society for Computational Biology (ISCB). Dr. Zhang was elected as ISCB Fellow and CAAI Fellow in 2020. His research interests include machine learning, bioinformatics, human cell atlas and intelligent medicine.
University of Chinese Academy of Sciences
Chengqing Zong received his Ph.D. degree from the Institute of Computing Technology of the Chinese Academy of Sciences, in March, 1998. He is currently professor at the National Laboratory of Pattern Recognition in the Institute of Automation of the Chinese Academy of Sciences. His research interests include natural language processing, machine translation, and linguistic cognitive computing as well.
Dr. Zong authored a book titled Statistical Natural Language Processing and co-authored a book titled Text Data Mining. He is currently a Fellow of Chinese Association for Artificial Intelligence, senior member of IEEE, and the President of Asian Federation on Natural Language Processing (AFNLP). He serves on the journals ACM Transactions on Asian and Low-Resource Language Information Processing as Associate Editor, and IEEE Intelligent Systems as a member of editorial board. He served many top-tier international conferences, such as ACL-IJCNLP’2021 as conference chair, ACL-IJCNLP’2015 and COLING’2020 as PC Co-Chair, AAAI’2019 and AAAI’2020 as area chair and IJCAI’2017 and IJCAI-ECAI’2018 as senior area chair as well. He won the prize of the State Preeminent Science and Technology Award of China in 2015.
Zaiwen Wen, Peking University. His research interests include large-scale computational optimization and their applications in data sciences. Together with his coauthors, he has developed both deterministic and stochastic semi-smooth Newton algorithms for composite convex program and Newton type algorithms for Riemannian optimization, as well as academic software packages such as SSNSDP, ARNT, Arrabit, LMSVD and LMAFIT, etc. He was awarded the Science and Technology Award for Chinese Youth in 2016, and the Beijing Science and Technology Prize-Outstanding Youth Scholar Zhongguan Village Prize in 2020. He is an associate editor of Journal of the Operations Research Society of China, Journal of Computational Mathematics and a technical editor of Mathematical Programming Computation.
The Chinese University of Hong Kong, Shenzhen
Guang Cheng is currently Presidential Chair Professor in The Chinese University of Hong Kong, Shenzhen, while being on leave from Purdue University. His research interests include deep learning theory, statistical machine learning and high dimensional statistics. His academic achievements have been acknowledged by NSF-CAREER award, Fellow in Institute of Mathematical Statistics, Simons Fellow in Mathematics and Noether Young Scholar award.
Prof. Cheng obtained his bachelor in Economics from Tsinghua University, and then earned his PhD of Statistics from University of Wisconsin-Madison in 2006. He has published extensively on prestigious conferences and journals such as NeurIPS, Annals of Statistics and IEEE-Information Theory. He is also editor or associate editor in the renowned journals such as Statistical Analysis and Data Mining, Journal of American Statistical Association, Canadian Journal of Statistics and Journal of Blockchain Research.
The Chinese University of Hong Kong, Shenzhen
Tsung-Hui Chang (S’07–M’08–SM’17) received the B.S. degree in electrical engineering and the Ph.D. degree in communications engineering from National Tsing Hua University (NTHU), Hsinchu, Taiwan, in 2003 and 2008, respectively. From 2012 to 2015, he was an Assistant Professor with the Department of Electronic and Computer Engineering, National Taiwan University of Science and Technology (NTUST), Taipei, Taiwan. In August 2015, he joined the School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, China, as an Assistant Professor, where he has been an Associate Professor since August 2018. He was a Visiting Ph.D. Student with the University of Minnesota, Minneapolis, MN, USA, from 2006 to 2008, and a Post-Doctoral Researcher with NTHU from 2008 to 2011 and with the University of California at Davis, Davis, CA, USA, from 2011 to 2012. His research interests include signal processing and optimization problems in data communications, machine learning, and big data analysis. Dr. Chang was a recipient of the Young Scholar Research Award of NTUST in 2014, the IEEE ComSoc Asian–Pacific Outstanding Young Researcher Award in 2015, and the IEEE Signal Processing Society Best Paper Award in 2018. He served as an Associate Editor for IEEE TRANSACTIONS ON SIGNAL PROCESSING and IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS from 2015 to 2018.
Xi'an Jiaotong University
Zongben Xu is an academician of the Chinese Academy of Sciences, a mathematician and an expert of Signal and Information Processing. He received his PhD degree of Xi’an Jiaotong University, China. He then went to Strathclyde University of England for postdoctoral research. In 1990, he was fast-tracked as a professor, which was authorized by the State Education Commission. During 1990 and 2001, he worked as a researcher and visiting professor in CUHK, Essex University in England and Naplpli University in Italy one after another. Now, he serves as a chief scientist of “The Basic Theory and Key Technology of Intellisense for Unstructured Environment”, the National Basic Research Program of China (973 Project) and Beijing Center for Mathematics and Information Interdisciplinary Sciences. He has directed and completed 21 national scientific research projects funded by 973 Project, 863 Project, National Science Foundation and Hong Kong UGC Scientific Foundation.
Zongben Xu's research field includes applied mathematics, intelligent information processing, and data science and technology.
XU has been long engaging in Banach Spatial Geometry Theory and Intelligent Information Processing for mathematics teaching and research, including proposal of the L (1/2) Regularization Theory, the discovery and identification of Xu-Roach Theom in machine learning, and new modeling theories and methodologies based on visual cognition, formulates series of new algorithms for clustering analysis, discriminant analysis, and latent viable analysis. He is the owner of the National Natural Science Award of China, and the winner of CSIAM SUBuchin Applied Mathematics Prize. He delivered a 45-minute sectional talk at the International Congress of Mathematicians (ICM 2010) upon the invitation of the congress committee.