Keynote Speakers
Jennifer Rexford
Princeton University, USAVisit Homepage
7th Jan 2021
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Title: Networks Capable of ChangeThe early designers of the Internet fostered tremendous innovation by leaving much of the network’s functionality to the programmable computers at its periphery. Unfortunately, the *inside* of the network has been much harder to change. Yet, changing the network is important to make the Internet more reliable, secure, performant, and cost-effective. The networking research community has struggled for many years to make networks more programmable. What has worked, and what hasn't, and what lessons have we learned along the way? This talk offers my perspective on these questions, through a 25-year retrospective of research on programmable networks, focusing on my own research experiences as well as reflections on major trends in the field. The talk advocates a sort of “ambitious pragmatism” that approaches an ambitious long-term goal (a programmable network infrastructure) through smaller, pragmatic steps while keeping an eye on the prize.
Jennifer joined the Computer Science Department at Princeton University in February 2005 after eight and a half years at AT&T Research. Her research focuses on Internet routing, network measurement, and network management, with the larger goal of making data networks easier to design, understand, and manage. Jennifer is co-author of the book Web Protocols and Practice: HTTP/1.1, Networking Protocols, Caching, and Traffic Measurement (Addison-Wesley, May 2001) and co-editor of She's an Engineer? Princeton Alumnae Reflect (Princeton University, 1993, see recent talk about the book). Jennifer served as the chair of ACM SIGCOMM from 2003 to 2007, and has served on the ACM Council, the board of the Computing Research Association, the advisory council of the Computer and Information Science and Engineering directorate at NSF, and the Computing Community Consortium. She received her BSE degree in electrical engineering from Princeton University in 1991, and her MSE and PhD degrees in computer science and electrical engineering from the University of Michigan in 1993 and 1996, respectively. She was the winner of ACM's Grace Murray Hopper Award for outstanding young computer professional of the year for 2004.
Sunita Sarawagi
IIT Bombay, IndiaVisit Homepage
8th Jan 2021
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Temporal sequences of discrete events or continuous values, placed regularly or irregularly along time, are commonplace in several applications. Forecasting, anomaly detection, and missing value imputation are critical analysis tools in these applications, and have been extensively researched across communities for multiple decades. Recently, deep recurrent models have been shown to surpass conventional models on these tasks. However, several problems still remain unresolved. One challenge is how to best combine global and local models where global models learn complex data transformations across multiple time series, whereas local models like ARIMA provide per-series localization. A second challenge is training models for long range forecasting. Existing recurrent models are easily parallelizable since they are trained for the next event prediction, but show degraded accuracy when deployed for multi-step forecasting. Another challenge is efficiently modeling the correlation of subsets of related time-series. In this talk I will highlight recent research efforts in addressing them, and present directions for future research.
Sunita Sarawagi researches in the fields of databases and machine learning. She is institute chair professor at IIT Bombay. She got her PhD in databases from the University of California at Berkeley and a bachelors degree from IIT Kharagpur. She has also worked at Google Research (2014-2016), CMU (2004), and IBM Almaden Research Center (1996-1999). She was awarded the Infosys Prize in 2019 for Engineering and Computer Science, and the distinguished Alumnus award from IIT Kharagpur. She has several publications including best paper awards at ACM SIGMOD, VLDB, ICDM, NIPS, and ICML conferences. She has served on the board of directors of the ACM SIGKDD and VLDB foundation. She was program chair for the ACM SIGKDD 2008 conference, research track co-chair for the VLDB 2011 conference and has served as program committee member for SIGMOD, VLDB, SIGKDD, ICDE, and ICML conferences, and on the editorial boards of the ACM TODS and ACM TKDD journals.
Michele Zorzi
University of Padua, ItalyVisit Homepage
6th Jan 2021
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Over the last ten years, the wireless research and industry communities have developed the fifth generation (5G) of mobile networks, currently being commercially deployed throughout the world. 5G networks are among the first to exploit the millimeter wave (mmWave) frequency bands for the access network, effectively introducing a 10x factor in the data rate achievable in cellular networks. At such high frequencies, indeed, there is a wide availability of spectrum that can be allocated to 5G services. However, mmWaves are affected by a higher path loss compared to their sub-6 GHz counterparts, and signals at such high frequencies cannot propagate through obstacles, thus decreasing reliability, which is a key element in public safety scenarios. In this talk, we discuss how first responders could benefit from the introduction of 5G mmWave communications in public safety networks, presenting the challenges and opportunities that have emerged from a three-year project funded by the U.S. National Institute for Standards and Technologies (NIST), in collaboration with New York University and the Austin Fire Department. We will describe how this technology can be introduced in highly mobile contexts (e.g., vehicular, aerial) that are of particular relevance for first responders operations, and which are the main engineering and design challenges we addressed to increase the reliability of such systems. Moreover, we will introduce the open source simulation tools developed as part of this project, to simulate mmWave cellular, aerial, vehicular scenarios, following the latest 3GPP specifications for 5G mmWave networks.
MICHELE ZORZI (F’07) received the Laurea and Ph.D.degrees in electrical engineering from the University of Padova in 1990 and 1994, respectively. From 1992 to 1993, he was on leave with the University of California at San Diego (UCSD). After being affiliated with the Dipartimento di Elettronica e Informazione, Politecnico di Milano, the Center for Wireless Communications, UCSD, and the University of Ferrara, in 2003 he joined the faculty of the Information Engineering Department, University of Padova, Italy, where he is currently a Professor. His current research interests include performance evaluation in mobile communications systems, random access in mobile radio networks, ad hoc and sensor networks, energy-constrained communications protocols, 5G millimeter-wave cellular systems, and underwater communications and networking. He was the Editor-in-Chief of IEEE Wireless Communications from 2003 to 2005, the Editor in-Chief of the IEEE Transactions on Communications from 2008 to 2011, and the Founding Editor-in-Chief of the IEEE Transactions on Cognitive Communications and Networks from 2014 to 2018. He was a Guest Editor for several special issues in the IEEE Personal Communications, the IEEE Wireless Communications, the IEEE Network, and the IEEE Journal on Selected Areas in Communications. He served the IEEE Communications Society as a Member at-Large in the Board of Governors from 2009 to 2011, as Director of Education and Training from 2014 to 2015 and as Director of Journals from 2020 to 2021. He received many awards from the IEEE Communications Society, including the Best Tutorial Paper Award in 2008 and 2019, the Education Award in 2016, and the S.O. Rice Best Paper Award in 2018.
