Athina P. Petropulu is Distinguished Professor of the Electrical and Computer Engineering (ECE) Department at Rutgers, having served as chair of the department during 2010-2016. Before that she was faculty at Drexel University. She held Visiting Scholar appointments at SUPELEC, Universite' Paris Sud, Princeton University, and University of Southern California.
Her research interests span the area of statistical signal processing, wireless communications, signal processing in networking, physical layer security, and radar signal processing. Her research has been funded by various government industry sponsors including the National Science Foundation, the Office of Naval research, the US Army, the National Institute of Health, the Whitaker Foundation, Lockheed Martin.
A. Petropulu is Fellow of IEEE and recipient of the 1995 Presidential Faculty Fellow Award given by NSF and the White House. She has served as Editor-in-Chief of the IEEE Transactions on Signal Processing (2009-2011), IEEE Signal Processing Society Vice President-Conferences (2006-2008), and member-at-large of the IEEE Signal Processing Board of Governors. She was the General Chair of the 2005 International Conference on Acoustics Speech and Signal Processing (ICASSP), and the general co-chair of the 2018 IEEE workshop on Signal Processing advances in Wireless Communications (SPAWC). In 2005 she received the IEEE Signal Processing Magazine Best Paper Award, and in 2012 the IEEE Signal Processing Society Meritorious Service Award for "exemplary service in technical leadership capacities". She is IEEE Distinguished Lecturer for the Signal Processing Society for 2017-2018.
More info on her work can be found at www.ece.rutgers.edu/~cspl
Distributed, networked communication systems, such as relay beamforming networks are typically designed without considering how the positions of the respective nodes might affect the quality of the communication. That is, network nodes are either assumed to be stationary in space, or, if some of them are moving while communicating, their trajectories are assumed to be independent of the respective communication task. However, in most cases, the Channel State Information (CSI) observed by each network node, per channel use is both spatially and temporally correlated. One could then ask whether the performance of the communication system could be improved by predictively controlling the positions of the network nodes (e.g., the relays), based on causal CSI estimates and by exploiting the spatiotemporal dependencies of the communication medium. In this talk, we address the problem of enhancing Quality-of-Service (QoS) in power constrained, mobile relay beamforming networks, by optimally exploiting relay mobility. We consider a time slotted system, where the relays update their positions before the beginning of each time slot. Adopting a spatiotemporal stochastic field model of the wireless channel, we propose a novel 2-stage stochastic programming formulation for specifying the relay positions at each time slot, such that the QoS of the network is maximized on average, based on causal CSI and under a total relay transmit power budget. The motion control problem considered is shown to be approximately equivalent to a set of simple subproblems, which can be solved in a distributed fashion, one at each relay. Numerical simulations are presented, corroborating the efficacy of the proposed approach and confirming its properties.
Aarne Mämmelä received the degree of D.Sc. (Tech.) (with honors) from the University of Oulu in 1996. He was with the University of Oulu from 1982 to 1993. In 1993 he joined VTT Technical Research Centre of Finland in Oulu. Since 1996 he has been a Research Professor of digital signal processing in wireless communications. He has visited the University of Kaiserslautern in Germany in 1990-1991 and the University of Canterbury in New Zealand in 1996-1997. Since 2004 he has been a Docent (equivalent to Adjunct Professor) at the University of Oulu. He is a Technical Editor of the IEEE Wireless Communications and a member of the Research Council of Natural Sciences and Engineering in the Academy of Finland. His research interests are in intelligent use of resources in wireless communications.
It is now rather well known that exponential development of digital electronics, often called Moore’s law, will not continue after 2021. The fundamental limits of nature will become apparent: the manufacturing costs are a bottleneck since the 10 nm gate length will correspond only to some tens of atoms. The reliability of the switching operations would also reduce if the switching energy is close to the noise spectral density. Therefore we are entering a new stage where applications must be developed in a resource-limited, for example energy-limited environment. This calls for a systems approach to complement the conventional analytical approach. Future systems will be a combination of remotely controlled, automatic, and autonomous systems. The key instruments will be intelligent decision making, open loop and closed loop (feedback) optimization, hierarchy, and degree of centralization.
Levent Onural was born in Izmir, Turkey in 1957. He got his junior high-school education at Izmir Koleji ("Izmir College"; now called BAL), and his senior high-school education at Ankara Fen Lisesi ("Ankara Science High-School"). He received the B.S. and M.S. degrees in electrical engineering from Middle East Technical University , Ankara, Turkey, in 1979 and 1981, respectively, and the Ph.D. degree in electrical and computer engineering from State University of New York at Buffalo in 1985.
He was a Fulbright scholar between 1981 and 1985. After a Research Assistant Professor position at the Electrical and Computer Engineering Department of State University of New York at Buffalo, he joined the Electrical and Electronics Engineering Department of Bilkent University, Ankara, Turkey, where he is a Professor at present. He served Bilkent University as the Dean of Engineering, and as the Director of Graduate School of Engineering and Science between July 2010 and August 2016. Dr. Onural received a TUBITAK Incentive Award in 1995, an IEEE Third Millenium Medal in 2000, the IEEE Haraden Pratt Award in 2011 (IEEE news release, Levent Onural's Award Speech Video), the EURASIP Group Technical Achievement Award in 2011, and Bilkent University Distinguished Teacher Award in 2011.
His current research interests are in the areas of image and video processing with emphasis on various aspects of 3DTV. His research focus is on signal processing aspects of optical wave propagation, diffraction and holography with applications to holographic 3DTV. He has published about 250 papers and received about 4000 citations. (Publications). One of his early papers is among the top cited 40 papers ever published in Optical Engineering. In 2006 and 2007, two papers that Onural co-authored ranked among the top cited papers published in IEEE Transactions on CSVT; one of his papers published in Journal of Display Technology is among the top cited papers of that journal in April 2017. He was a member of the COST211ter Project Management Committee and the director of the Turkish COST211 team between 1991-1997. He and his team have contributed to COST211 Analysis Model. COST211ter project was a research collaboration activity of European Union; more information can be found here. Levent Onural has a video object segmentation patent ( US 6,337,917 ) and a holographic 3D video display patent ( US 9,501,036 ). He was the Coordinator of EC funded 3DTV Project (2004-2008), and the Co-leader of 3D Immersive Interactive Media Cluster (formerly 3D Media Cluster) (2008-2011). He contributed to EC funded Real3D and 3DPHONE projects (2008-2011). He was invited as a keynote speaker to many prestigious conferences. Dr. Onural served as the vice-chair of COST Trans-Domain Panel (2013-2014).
Dr. Onural is a fellow of IEEE (for his contributions to signal processing for optics, diffraction and holography). He was the organizer and the first chairman (1990-1991) of IEEE Turkey Section; and the chairman (1994-1996) of the IEEE Circuits and Systems Society Turkey Chapter. He served as the vice-chair of IEEE Region 8 (Europe, Africa and Middle East(1995-1998), and the vice-chair of the Regional Activities Board (RAB) (now called Member and Geographic Acitivies (MGA) Board) of IEEE (1998-1999) -in charge of student activities; he also served as the chair of the IEEE RAB Student Activities Committee (1998-1999). Dr. Onural was a general co-chair of IEEE 2000 International Conference on Acoustics Speech and Signal Processing ICASSP'2000; he also served as the general co-chair of the annual conference 3DTV-CON in 2007, 2009-2016. He was the Director of IEEE Region 8 (Europe, Africa and Middle East) (2001-2002) and a member of IEEE Board of Directors, which is the highest board of IEEE, between 2001-2003. He was a member of IEEE Assembly in 2001-2002. He served as the 2003 Secretary of IEEE, and he was a member of IEEE Executive Committee (now called IEEE Governance Committee) in 2003. Levent Onural was nominated by the IEEE Board of Directors to the position of 2005 IEEE President-elect (2006 IEEE President); he is the first person from outside of North America nominated for this position in 120 years of history of IEEE. Levent Onural served as an associate editor of IEEE Transactions on Circuits and Systems for Video Technology (2002-2013). He is also a member of the Editorial Board of SPIE Reviews (2009-2012). He served as a guest editor in Special Issue on 3DTV: Capture, Transmission and Display (EURASIP Journal on Advances in Signal Processing, 2009); Special Section on 3DTV, Special Issue on Multiview Video Coding and 3DTV (IEEE Transactions on Circuits and Systems for Video Technology, 2007); ``Lasers: The First Fifty Years'' (Applied Optics,2010); ``Issue on Emerging Techniques in 3-D'', (IEEE J. of Selected Topics in Signal Processing, 2012); Feature Issue on Digital Holography and 3D Imaging (Optics Express, 2014).
Üç-boyutlu olması, zamanla değişmesi, ve de dalgaboyu (renk) üzerinden de zengin olması nedeniyle etrafımızdaki görsel zenginliği bize (bir alıcıya) taşıyan optik dalgalar, anlaşılması ve işlenmesi hayli zor sinyallere iyi bir örnektir. Bu tür sinyallerin daha iyi anlaşılması ve modellenmesi, ardından da, kaydedilmesi, işlenmesi ve gerektiğinde üretilerek ortama verilmesi evrelerinin her biri kendine özgü ve genellikle zor sinyal işleme tekniklerini gerektirmektedir. Gerçek anlamda üç-boyutlu televizyon için gelinebilecek son nokta holografik televizyondur. Göze takılan bir aygıtla ve doğrudan gözlere verilen ışık sinyalleri ile sanal üç-boyutlu görsellik yaratılması veya gerçek görüntülerin üzerine üç-boyutlu sanal cisimlerin oturtulması gibi, son yıllarda ticarileşmeye başlayan konularda mükemmeliğe ulaşılması da holografik yöntemlerin kullanılması ile mümkündür. Holografinin temel amacı, etrafımızdaki üç-boyutlu görselliği bize taşıyan ışık sinyallerinin gereken tüm fiziksel özellikleri ile kaydedilebilmesi ve başka bir mekanda veya zamanda tıpkısının tekrar elde edilebilmesidir. Dalga yayılımı iki-boyutlu doğrusal ve zamanla değişmeyen bir sistem olarak modellenebilir; yayılan dalgalar için doğru bir model olan Rayleigh-Sommerfeld kırımı ile, bir yaklaştırma olan Fresnel kırınımı, iki-boyutlu doğrusal ve kaymayla değişmeyen sistemler olarak gösterilebilir. Bu modellerdeki iki-boyutlu sistemlerin sinyal işleme yönünden ilginç özellikleri vardır. Sayısal modeller kullanılarak, sayısal işleme yöntemleri ile elde edilen sonuçların pikselli ekranlar aracılığı ile görsel ortamlara döndürülmesi de kendine özgü sinyal işleme problemleri oluşturmaktadır. Bu konuşmada, yukarıda değinilen konularla ilgili genel bir değerlendirme yapılacak, ve yıllar içinde elde edilmiş değişik araştırma sonuçları kısaca sunulacaktır.
Murat Uysal was born in Istanbul, Turkey in 1973. He received the B.Sc. and the M.Sc. degree in electronics and communication engineering from Istanbul Technical University, Istanbul, Turkey, in 1995 and 1998, respectively, and the Ph.D. degree in electrical engineering from Texas A&M University, College Station, Texas, in 2001.
Dr. Uysal is currently a Full Professor and Chair of the Department of Electrical and Electronics Engineering at Ozyegin University, Istanbul, Turkey. He also serves as the Founding Director of Center of Excellence in Optical Wireless Communication Technologies (OKATEM). Prior to joining Ozyegin University, he was a tenured Associate Professor at the University of Waterloo, Canada, where he still holds an adjunct faculty position. Dr. Uysal’s research interests are in the broad areas of communication theory and signal processing with a particular emphasis on the physical layer aspects of wireless communication systems in radio, acoustic and optical frequency bands. He has authored some 290 journal and conference papers on these topics and received more than 7300 citations.
Dr. Uysal is a Senior IEEE member and an active contributor to his professional society. He currently serves as the Chair of IEEE Turkey Section. He leads the EU COST Action OPTICWISE which is a European scientific network for interdisciplinary research activities in the area of optical wireless communications. He serves on the editorial boards of IEEE Transactions on Communications and IEEE Transactions on Wireless Communications. In the past, he served as an Editor for IEEE Communications Letters, IEEE Transactions on Vehicular Technology, Wiley Wireless Communications and Mobile Computing (WCMC) Journal, Wiley Transactions on Emerging Telecommunications Technologies (ETT), and Guest Editor of IEEE JSAC Special Issues on Optical Wireless Communication (2009 and 2015). He was involved in the organization of several IEEE conferences at various levels. He served as the Chair of the Communication Theory Symposium of IEEE ICC 2007, Chair of the Communications and Networking Symposium of IEEE CCECE 2008, Chair of the Communication and Information Theory Symposium of IWCMC 2011, TPC Chair of IEEE WCNC 2014, General Chair of IEEE IWOW 2015 and TPC Chair of IEEE PIMRC 2018. Over the years, he has served on the technical program committee of more than 100 international conferences and workshops in the communications area.
Prof Uysal’s distinctions include the Marsland Faculty Fellowship in 2004, NSERC Discovery Accelerator Supplement Award in 2008, University of Waterloo Engineering Research Excellence Award in 2010, Turkish Academy of Sciences Distinguished Young Scientist Award in 2011 and Ozyegin University Best Researcher Award in 2014 among others.
Farid Melgani (M’04–SM’06–F’16) received the State Engineer degree in electronics from the University of Batna, Algeria, in 1994, the M.Sc. degree in electrical engineering from the University of Baghdad, Iraq, in 1999, and the Ph.D. degree in electronic and computer engineering from the University of Genoa, Italy, in 2003. From 1999 to 2002, he cooperated with the Signal Processing and Telecommunications Group, Department of Biophysical and Electronic Engineering, University of Genoa. Since 2002, he has been an Assistant Professor and then an Associate Professor of telecommunications at the University of Trento, Italy, where he has taught pattern recognition, machine learning, radar remote-sensing systems, and digital transmission. He is the Head of the Signal Processing and Recognition (SPR) Laboratory, Department of Information Engineering and Computer Science, University of Trento. His research interests are in the areas of remote sensing, signal/image processing, pattern recognition, machine learning and computer vision. He is coauthor of about 200 scientific publications and is a referee for numerous international journals. Dr. Melgani has served on the scientific committees of several international conferences and is an Associate Editor of the IEEE Geoscience and Remote Sensing Letters, International Journal of Remote Sensing, Remote Sensing, and Sensors.
Stuart Clayman received his PhD in Computer Science in 1994 and is a Senior Research Fellow at UCL EEE department. He co-authored over 40 conference and journal papers. His research interests are in the areas of software engineering and programming paradigms; distributed systems; virtualized compute and networks, network and systems management; sensor systems and smart city platforms. He does reviews for journals and has served on the TPC for many conferences, as well as being a Conference Organiser for NetSoft and the O4SDI workshops. He also has extensive experience in the commercial arena undertaking architecture and development for software engineering, distributed systems and networking systems. He has run his own technology start-up in the area of NoSQL databases, sensor data, and digital media.
Prof. dr. Theo Gevers is a Full Professor of Computer Vision at the University of Amsterdam. His research area is Artificial Intelligence with the focus on machine learning and computer vision and in particular image processing, 3D (object) understanding and human-behavior analysis with industrial and societal applications in fashion/retail, healthcare, real estate, smart cities, and automotive. He is the co-founder of Sightcorp, 3DUniversum and Scanm. Prof. Gevers has published over 150 papers and three books. He is an Organizer, General Chair, and Program Committee member for various conferences, and an Invited Speaker at major conferences.
Personal Web: https://staff.science.uva.nl/th.gevers/
Google Scholar: https://scholar.google.com/citations?user=yqsvxQgAAAAJ
Abstract: In this talk, I will present different face analysis methods using (unsupervised) deep learning to compute facial features (face intrinsics) such as shape, albedo, illumination, pose and even facial expressions. 3D face intrinsics are derived from 2D and 3D images. A demonstration will be given on how to create and detect deep fake videos of humans.
Bio: Anastasios Tefas received the B.Sc. in informatics in 1997 and the Ph.D. degree in informatics in 2002, both from the Aristotle University of Thessaloniki, Greece. Since 2017 he has been an Associate Professor at the Department of Informatics, Aristotle University of Thessaloniki. From 2008 to 2017, he was a Lecturer, Assistant Professor at the same University. From 2006 to 2008, he was an Assistant Professor at the Department of Information Management, Technological Institute of Kavala. From 2003 to 2004, he was a temporary lecturer in the Department of Informatics, University of Thessaloniki. From 1997 to 2002, he was a researcher and teaching assistant in the Department of Informatics, University of Thessaloniki. Dr. Tefas participated in 12 research projects financed by national and European funds. He has co-authored 80 journal papers, 188 papers in international conferences and contributed 8 chapters to edited books in his area of expertise. Over 4000 citations have been recorded to his publications and his H-index is 33 according to Google scholar. His current research interests include computational intelligence, deep learning, pattern recognition, statistical machine learning, digital signal and image analysis and retrieval and computer vision.
This keynote speech will focus on deep learning methods and their use in drones for increased perception, control and other innovative tasks. Deep learning emerged as one of the most promising research fields in artificial intelligence and Unmanned Aerial Vehicles (drones) are among the robotic units that have substantial needs for autonomous control and perception due to their increasing use in several applications like transportation, inspection, surveillance and cinematography among others. Deep Convolutional Neural Networks (CNNs) are among the state-of-the-art techniques for Visual Information Analysis that can provide increased perception capabilities. CNNs can be used to perform several drone perception tasks such as object detection and tracking, face detection and person identification, crowd detection for ensuring flight safety, emergency landing point detection, etc. However, deploying such deep learning models on drones is not a straightforward task, since there are significant memory and model complexity constraints. To overcome these limitations several methodologies have been proposed like training small lightweight CNNs, using knowledge transfer techniques, such as neural-network distillation, layer hints and similarity embeddings, to reduce the size of CNNs or using neural region proposals for fast object detection and classification (faster R-CNN, YOLO, SSD).
6th generation or 6G is the umbrella name of all technologies that will be used in the period 2030-2040. Artificial intelligence shows an exponentially increasing trend, but it is very difficult to predict where it will go. According to the predictions and statements of many scientists and experts, computers will be as intelligent as people in 2035. By 2045, estimates tell us that computers will have more intelligence than the sum of all the people in the world. For the last 100 years, we have been trying to increase our brain's power with our work. We continued to automate repetitive tasks. 200 years ago, about 90 percent of the people worked in agriculture. Now, only about 2 percent are working in farming. Nanotechnology is rapidly developing in medical technology. After 25 years, the current cell phone-sized computer will fit inside the blood cell, it will able to cure the diseased cells and the organs. It is easu to expect that all sectors will be integrated and many new applications will be developed. Autonomy and cyber security will be two main topics in the future. We are just starting , everything will change very rapidly. Are we getting better or worse?