Invited Talks
Topic: |
Delay-Doppler Communications and OTFS Modulation |
Speaker: |
Emanuele Viterbo, Professor, Department of Electrical and Computer Systems Engineering, Monash University, Australia |
Abstract:
Orthogonal time frequency space (OTFS) modulation has been recently proposed by Hadani et al. at WCNC’17, San Francisco. It was shown to offer significant advantages over OFDM in doubly dispersive channels for high mobility wireless communications. The OTFS waveform is based on the idea that the mobile wireless channels can be effectively modelled in the delay-Doppler domain. This domain provides a sparse representation closely resembling the physical geometry of the wireless channel. The key physical parameters such as relative velocity and distance of the reflectors with respect to the receiver can be considered roughly invariant in the duration of a frame up to a few milliseconds. This enables the information symbols encoded in the delay-Doppler domain to experience a flat fading channel even when they are affected by multiple Doppler shifts present in high-mobility environments.
This talk will introduce the general notion of delay-Doppler communications, starting from the fundamentals of high mobility wireless channels, followed by the transceiver architecture used for detection and channel estimation. Finally, we will present a general overview of future research directions and a range of applications of delay-Doppler domain signal processing.
Biography:
Emanuele Viterbo (F’2011) received his degree (Laurea) in Electrical Engineering in 1989 and his Ph.D. in 1995 in Electrical Engineering, both from the Politecnico di Torino, Torino, Italy. From 1990 to 1992 he was with the European Patent Office, The Hague, The Netherlands, as a patent examiner in the field of dynamic recording and error-control coding. Between 1995 and 1997 he held a post-doctoral position in the Dipartimento di Elettronica of the Politecnico di Torino. In 1997-98 he was a postdoctoral research fellow in the Information Sciences Research Center of AT\&T Research, Florham Park, NJ, USA. He became first Assistant Professor (1998) then Associate Professor (2005) in Dipartimento di Elettronica at Politecnico di Torino. In 2006 he became Full Professor in DEIS at University of Calabria, Italy. From September 2010 he is Professor in the ECSE Department and Associate Dean Graduate Research of the Faculty of Engineering at Monash University, Melbourne, Australia.
Emanuele Viterbo is a 2011 Fellow of the IEEE, an ISI Highly Cited Researcher and Member of the Board of Governors of the IEEE Information Theory Society (2011-2013 and 2014-2018).
He served as Associate Editor of IEEE Transactions on Information Theory, European Transactions on Telecommunications and Journal of Communications and Networks. His main research interests are in lattice codes for the Gaussian and fading channels, algebraic coding theory, algebraic space-time coding, digital terrestrial television broadcasting, and digital magnetic recording.
Topic: |
The Mathematics of Deception |
Speaker: |
Sidharth (Sid) Jaggi, Associate Professor, School of Mathematics at the University of Bristol |
Abstract:
In a variety of information-processing tasks (say Alice wishes to store data, or transmit it to Bob, or estimate some underlying signal from some sensors), one has to design schemes that are robust to noise (servers may crash, or there may be noise in the transmission or sensing mechanisms). Fundamental performance limits, and algorithms attaining these fundamental limits, are relatively well-understood when this noise is random. In this talk we focus on scenarios where the noise is chosen by an adversary whose goal is to disrupt the information-processing task. In such settings, the fundamental limits are often more pessimistic than in the random noise setting, since the adversary can attempt to “spoof” the information being stored/transmitted/estimated. We will attempt to shed light on what is known in some adversarial noise settings, and showcase a few open problems.
Biography:
Sidharth (Sid) Jaggi received his B. Tech. from I.I.T. Bombay 2000, his M.S. and Ph.D. degrees from the CalTech in 2001 and 2006 respectively, all in EE. He spent 2006 as a Postdoctoral Associate at LIDS MIT. He joined the Department of Information Engineering at the Chinese University of Hong Kong in 2007, and the School of Mathematics at the University of Bristol in 2020, where he is now an Associate Professor. His interests lie at the intersection of network information theory, coding theory, and algorithms. His research group thus (somewhat unwillingly) calls itself the CAN-DO-IT team (Codes, Algorithms, Networks: Design and Optimization for Information Theory). Examples of topics he has dabbled in include network coding, sparse recovery/group-testing, covert communication, and his current obsession is with adversarial channels.
Topic: |
Almost Optimal Variance-Constrained Best Arm Identification |
Speaker: |
Vincent Y. F. Tan, Associate Professor and Dean’s Chair, Department of Mathematics/Department of Electrical and Computer Engineering, National University of Singapore |
Abstract:
We design and analyze VA-LUCB, a parameter-free algorithm, for identifying the best arm under the fixed-confidence setup and under a stringent constraint that the variance of the chosen arm is strictly smaller than a given threshold. An upper bound on VA-LUCB’s sample complexity is shown to be characterized by a fundamental variance-aware hardness quantity $H_{VA}$. By proving a lower bound, we show that sample complexity of VA-LUCB is optimal up to a factor logarithmic in $H_{VA}$. Extensive experiments corroborate the dependence of the sample complexity on the various terms in HVA. By comparing VA-LUCB’s empirical performance to a close competitor RiskAverse-UCB-BAI by David et al. (2018), our experiments suggest that VA-LUCB has the lowest sample complexity for this class of risk-constrained best arm identification problems, especially for the riskiest instances.
This is joint work with Yunlong Hou (NUS) and Zixin Zhong (University of Alberta).
Biography:
Vincent Y. F. Tan (S’07-M’11-SM’15) was born in Singapore in 1981. He received the B.A. and M.Eng. degrees in electrical and information science from Cambridge University in 2005, and the Ph.D. degree in electrical engineering and computer science (EECS) from the Massachusetts Institute of Technology (MIT) in 2011. He is currently a Dean’s Chair Associate Professor with the Department of Mathematics and the Department of Electrical and Computer Engineering (ECE), National University of Singapore (NUS). His research interests include information theory, machine learning, and statistical signal processing.
Dr. Tan is an elected member of the IEEE Information Theory Society Board of Governors. He was an IEEE Information Theory Society Distinguished Lecturer from 2018 to 2019. He received the MIT EECS Jin-Au Kong Outstanding Doctoral Thesis Prize in 2011, the NUS Young Investigator Award in 2014, the Singapore National Research Foundation (NRF) Fellowship (Class of 2018), the Engineering Young Researcher Award in 2018, and the NUS Young Researcher Award in 2019. A dedicated educator, he was awarded the Engineering Educator Award in 2020 and 2021 and the (university level) Annual Teaching Excellence Award in 2022. He is currently serving as a Senior Area Editor for the IEEE Transactions on Signal Processing and as an Associate Editor in Machine Learning and Statistics for the IEEE Transactions on Information Theory.
Topic: |
Quantifying the Security Levels of Cryptographic Primitives |
Speaker: |
Kenji Yasunaga, Associate Professor, School of Computing, Tokyo Institute of Technology |
Abstract:
The security levels of cryptographic primitives are usually measured by the computational costs for breaking them.
This “definition” is widely accepted and used in the cryptographic community; however, we encounter difficulties when we define it mathematically, especially for decision-type primitives such as encryption schemes and pseudorandom generators.
In this talk, we review the recent studies on theoretical frameworks for measuring the security levels of primitives.
The talk is based on the joint work with Shun Watanabe.
Biography:
Kenji Yasunaga is an Associate Professor at the School of Computing, Tokyo Institute of Technology. He received his B.E., M.S., and Ph.D. degrees from Osaka University in 2003, 2005, and 2008, respectively. He was a co-recipient of the Outstanding Paper Award at GameSec 2018. His research interests include coding theory, cryptography, and computational complexity.
Topic: |
Efficient Repair of Reed-Solomon Codes and Locally Repairable Codes |
Speaker: |
Lalitha Vadlamani, Assistant Professor, IIIT Hyderabad |
Abstract:
Reed-Solomon codes are polynomial evaluation codes and they can be efficiently repaired if the code symbols of the code are considered as vectors over a subfield. We describe a trace-repair framework introduced by Guruswami-Wootters, which allows for efficient repair of Reed-Solomon codes. Also, we present an optimal construction of Reed-Solomon codes by Tamo et al., which achieve the cut-set bound. Tamo-Barg codes are a class of optimal locally repairable codes (LRCs) which are also polynomial evaluation codes. These codes have Reed-Solomon codes as their local codes. In the case of single node failures, the repair takes place only within the local groups. The repair bandwidth within the local group can be further reduced by using the technique of Reed-Solomon repair. We provide a construction of Tamo-Barg codes whose local Reed-Solomon codes can be optimally repaired. We also make the connection between this class of codes and the codes with local regeneration.
Biography:
Lalitha Vadlamani received her B.E. degree in Electronics and Communication Engineering from the Osmania University, Hyderabad, in 2003 and her M.E. and Ph.D. degrees from the Indian Institute of Science (IISc), Bangalore, in 2005 and 2015 respectively. From May 2015, she is working as Assistant professor in IIIT Hyderabad, where she is affiliated to Signal Processing and Communications Research Center. Her research interests include coding for distributed storage and computing, index coding, polar codes, learning-based codes and coded blockchains. She is a recipient of Prof. I.S.N. Murthy medal from IISc, 2005 and the TCS Research Scholarship for the year 2011.