Jayant Haritsa

Jayant R. Haritsa is an Indian Computer Scientist and Professor. He is on the faculty of the CDS and CSA departments at Indian Institute of Science, Bangalore, India. He works on the design and analysis of Database Systems. In 2009 he won the Shanti Swarup Bhatnagar Prize sponsored by CSIR, India. He did his SSLC from Vijaya High School, Jayanagar, Bangalore and Pre-University in Science, from National College(Basavanagudi), Bangalore. He did his B.Tech (Electronics) from Dept. of Electrical Engineering, Indian Institute of Technology, Madras and MS and PhD (Computer Science), Computer Sciences Department, University of Wisconsin, Madison.

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Gabriele Kotsis

Gabriele Kotsis is an Austrian Computer Scientist. She is full professor in computer science at Johannes Kepler University, Linz, Austria, while leading the Department of Telecommunication and the division of Cooperative Information Systems. Gabriele Kotsis received her master's degree in business informatics at the University of Vienna and finished her doctoral studies in social- and economic sciences at the University of Vienna, graduating two times with distinction. In 2000, she habilitated in Informatics at the University of Vienna. She received scientific recognition early on: her master's thesis Interconnection Topologies and Routing for Parallel Processing Systems at the University of Vienna was honored with a student sponsorship award of the Austrian Computer Society. Furthermore, her PhD dissertation Workload Modeling for Parallel Processing was honored with the prestigious Heinz Zemanek Award in 1996.

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Manik Varma

Manik Varma is a Partner Researcher at Microsoft Research India where he manages a team carrying out research in machine learning, systems, information retrieval, natural language processing, AI for social good, causality and related areas. He also leads a developer team that has won multiple awards for its engineering excellence and impact benefitting hundreds of millions of people worldwide. Manik is best known for having started the research area of extreme classification which is thriving in both academia and industry with extreme classifiers being deployed in various products where they are making billions of predictions a day and generating revenue for many businesses around the world. Manik is a recipient of the Shanti Swarup Bhatnagar Prize, a Fellow of the Indian Academy of Sciences, a Fellow of the Indian National Academy of Engineering, has been a Visiting Miller Professor at UC Berkeley and a Rhodes Scholar at Oxford. He is an Associate Editor-in-Chief of the IEEE TPAMI journal, has been awarded the Microsoft Gold Star and Achievement Awards, the WSDM 2019 Best Paper Award and has won the PASCAL VOC Object Detection Challenge at ICCV 2009 as well as Pepsi drinking competitions and Chicken Chess tournaments.

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Srikanth Srinivasan

Srikanth Srinivasan got his PhD from the Institute of Mathematical Sciences in Chennai, India, in 2011 under the guidance of V Arvind. He spent two years as a postdoc in the US, at the Institute of Advanced Study and DIMACS, Rutgers University. From 2012 to 2020, he was an Assistant Professor at the Department of Mathematics at IIT Bombay. Since 2020, he has been Associate Professor at the Department of Computer Science at Aarhus University, Denmark. He was the recipient of FOCS 2021 Conference Best Paper Award.

Margaret Martonosi

Margaret Martonosi is the H. T. Adams Professor of Computer Science at Princeton University, where she has been on the faculty since 1994. Martonosi's research interests are in computer architecture and mobile computing. Her work has included the widely-used Wattch power modeling tool and the Princeton ZebraNet mobile sensor network project for the design and real-world deployment of zebra tracking collars in Kenya. Her current research focuses on computer architecture and hardware-software interface issues in both classical and quantum computing systems. Martonosi is a member of the United States National Academy of Engineering, and a Fellow of IEEE and ACM. She was the 2021 recipient of the ACM / IEEE Eckert-Mauchly Award for her contributions to power-efficient computer architecture.

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Alfred Aho

Alfred Aho is a Canadian Computer Scientist best known for his work on programming languages, compilers, and related algorithms, and his textbooks on the art and science of computer programming. Aho was elected into the National Academy of Engineering in 1999 for his contributions to the fields of algorithms and programming tools. Aho is also widely known for his co-authorship of the AWK programming language with Peter J. Weinberger and Brian Kernighan (the "A" stands for "Aho").[20] As of 2010 Aho's research interests include programming languages, compilers, algorithms, and quantum computing. He is part of the Language and Compilers research-group at Columbia University. He is the recipient of 2020 ACM Turing Award.

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Sriram Rajamani

Sriram Rajamani is Distinguished Scientist and Managing Director of Microsoft Research India.His research interests are in designing, building and analyzing computer systems in a principled manner. Over the years he has worked on various topics including Hardware and Software Verification, Type Systems, Language Design, Distributed Systems, Security and Privacy. His current research interest is in combining Program Synthesis and Machine Learning.
Sriram has a PhD from UC Berkeley, MS from University of Virginia and BEng from College of Engineering, Guindy, all with specialization in Computer Science. In 2020, he was named as a Distinguished Alumnus by College of Engineering, Guindy.
Sriram was general chair for POPL 2015 in India,and was program Co-Chair for CAV 2005. He co-founded the Mysore Park Series, and the ISEC conference series in India. He serves on the CACM editorial board as co-chair for special regional sections, to bring computing innovations from around the world to CACM.Sriram was elected ACM Fellow in 2015 for contributions to software analysis and defect detection, and Fellow of Indian National Academy of Engineering in 2016.

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A Fireside Chat with Ed Catmull

Abstract: Ed Catmull proposed three ideas that transformed computer graphics fundamentally during his graduate student life at University of Utah: texture mapping, depth buffering, and subdivision surfaces. He also made real time, realistic animation as his mission through his time in NYIT, Lucasfilms, ILM, Pixar, and Walt Disney Animation Studios. It is not an exaggeration to state that his work touches every rendered pixel that we see on screen. In a freewheeling chat, Dr Catmull discusses his experiences at graduate school, in NYIT, and how the practice of computer-generated animation has changed over the years.

Interdisciplinarity and Engineering: The Road Ahead

Abstract: The talk will begin with an appreciation of what engineering means for a society and how to measure it. We then present some data on how engineering fares in Indian society and problem areas. I argue that (i) better but applicable research (ii) and creating entry points for entrepreneurs, will improve social outcomes. But this needs a different interdisciplinary outlook and training in field work, documentation and analysis. Given our systems-approach, the CS-IT graduate is specially well-equipped to undertake such work. I will look at public transport as a sector and illustrate this approach. We will first see the broad significance of the sector. Next, we will look at the taluka bus depot as an enterprise and the data sets by which they operate. We will then show how the notion of a Digital Geography can improve the analysis of their operations. In the second part, we will look at the transport system from outside, i.e., the question of how well is the taluka Bus Depot serving society. We will take the example of school-going children and their transport needs and analyse how well they are being provided. This will need supplementing the Digital Geography with additional (and easily available) socio-economic datasets. Finally, we argue that such analysis and the use of local data is essential for the training of the new engineer. Such skills will prepare the engineer as a social change-agent and an entrepreneur, and not merely an employee.

Almost Envy-Free Division of Indivisible Goods

Abstract: Fair division of indivisible goods is a basic problem in economics, law, computer science, and the social sciences. The goal is to distribute m goods to n agents in a fair manner. The goods are assumed to be indivisible. Every agent has a value (= a nonnegative number) for each subset of goods. In this setting, envy is unavoidable. Think of two agents and one good which both value. The agent that does not get the good will envy the agent that gets the good. The literature on fair division dates back more than 100 years. Fair division of divisible goods is also known as the cake-cutting problem. For this talk, fairness is envy-freeness up to any good (EFX). No agent should envy any other after the removal of any single good from the other agent’s bundle. It is not known whether or not such an allocation always exists. We survey results on fair division and sketch two results towards existence of EFX-allocations. 1. For additive valuations and three agents EFX-allocations exist (Bhaskar Ray Chaudhury, Jugal Garg, and Kurt Mehlhorn: EFX Exists for Three Agents. In EC ’20, pages 1–19). 2. There is always (Bhaskar Ray Chaudhury, Tellikepalli Kavitha, Kurt Mehlhorn, and Alkmini Sgouritsa: A Little Charity Guarantees Almost Envy-Freeness. In SODA ’20, pages 2658–2672) a partition of the good set X into n + 1 subsets (X1, . . . , Xn, P) such that
• the allocation (X1, . . . , Xn) is EFX,
• no agent values P (= the goods donated to charity) higher than her own bundle, and
• fewer than n goods go to charity, i.e., |P| < n (typically m » n).
Our proofs are constructive.

The role of massively parallel computing in personalized blood flow modeling

Abstract: The recognition of the role hemodynamic forces have in the localization and development of disease has motivated large-scale efforts to enable patient-specific simulations. When combined with computational approaches that can extend the models to include physiologically accurate hematocrit levels in large regions of the circulatory system, these image-based models yield insight into the underlying mechanisms driving disease progression and inform surgical planning or the design of next generation drug delivery systems. Building a detailed, realistic model of human blood flow, however, is a formidable mathematical and computational challenge. The models must incorporate the motion of fluid, intricate geometry of the blood vessels, continual pulse-driven changes in flow and pressure, and the behavior of suspended bodies such as red blood cells. In this talk, I will discuss the development of HARVEY, a parallel fluid dynamics application designed to model hemodynamics in patient-specific geometries. I will cover the methods introduced to reduce the overall time-to-solution and effectively leverage leadership class systems. Finally, I will discuss the role of personalized blood flow models for applications ranging from treatment planning for cardiovascular disease to studying cancer cell adhesion and metastatic progression.

Title : A Turing Test for Recommendation

Abstract: I will propose a Turing Test for Recommendation that can serve as a grand challenge for our community and will identify some of the novel research problems that arise from the Test. I will discuss some of the preliminary solutions being explored in my group to tackle these problems placing particular emphasis on extreme classification which focuses on tackling classification problems involving millions of categories and which has opened a new paradigm for search and recommendation. I will illustrate through case studies how such an extreme classification based reformulation can significantly improve the quality of personalized recommendations thereby benefitting billions of people worldwide and taking us a step closer to a potential solution to the proposed Turing Test.

Title : Algebra and Computational Complexity

Abstract: The terms "Algebra" and "Algorithm" both go back a thousand years to the Persian mathematician Al-Khwarizmi, which gives us some idea of the close connections between these two lines of inquiry. In modern times, algebra interacts with theoretical computer science in myriad ways, both as a source of algorithmic problems, and as a tool for algorithmic analysis. In this talk, we will give a survey of some interesting results of this form, with a focus on computational complexity, the topic of the speaker's research.

Seismic Shifts: Challenges and Opportunities in the “Post-ISA” Era of Computer Systems Design

Abstract: For decades, Moore’s Law and its partner Dennard Scaling have together enabled exponential computer systems performance improvements at manageable power dissipation. With the slowing of Moore/Dennard improvements, designers have turned to a range of approaches for extending scaling of computer systems performance and power efficiency. Unfortunately, the scaling gains afforded by these techniques come with significant costs: increased hardware and software complexity, degraded programmability and portability, and increased likelihood of design errors and security vulnerabilities. The long-held hardware-software abstraction offered by the Instruction Set Architecture (ISA) interface is fading quickly in this post-ISA era. The talk will cover a range of design opportunities and challenges, with a particular emphasis on the surprising alignments between full-stack issues in both classical and quantum computing systems.