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X-WR-CALNAME:Computer Science and Engineering
X-ORIGINAL-URL:https://homecse.iitd.ac.in
X-WR-CALDESC:Events for Computer Science and Engineering
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TZID:Asia/Kolkata
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TZOFFSETFROM:+0530
TZOFFSETTO:+0530
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DTSTART:20250101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250103T160000
DTEND;TZID=Asia/Kolkata:20250103T170000
DTSTAMP:20260924T065945
CREATED:20241203T110026Z
LAST-MODIFIED:20241212T122254Z
UID:420-1735920000-1735923600@homecse.iitd.ac.in
SUMMARY:Leveraging LLMs for Networking & Security in Cloud Environments
DESCRIPTION:Deepak Bansal\, Microsoft \nAbstract: Customer networks have grown\, mostly organically\, large and complex in cloud environments like Azure. Customers are often afraid to make changes and find it hard to diagnose when things go wrong. In this talk\, I am going to share how Microsoft is using LLMs to simplify network operations at scale in Azure and how it is enabling the same for its customers through Azure Copilot. On the security side\, I will share how LLMs are being used to enable security monitoring and threat hunting. \nBio: Deepak graduated from IIT D in CS in 1999 and did a Masters in CS at MIT. He is currently a Corp Vice President and Technical Fellow at Microsoft in Redmond\, WA USA and is driving cloud (Azure infrastructure) and security (Microsoft’s Secure Future Initiative).
URL:https://homecse.iitd.ac.in/event/leveraging-llms-for-networking-security-in-cloud-environments/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250120T143000
DTEND;TZID=Asia/Kolkata:20250120T163000
DTSTAMP:20260924T065945
CREATED:20241212T090010Z
LAST-MODIFIED:20241212T122237Z
UID:425-1737383400-1737390600@homecse.iitd.ac.in
SUMMARY:A Theory of Alternating Paths and Blossoms\, from the Perspective of Minimum Length
DESCRIPTION:Vijay V. Vazirani \, University of California\, Irvine. \nIt is well known that the proof of some prominent results in mathematics took a very long time — decades and even centuries. The first proof of the Micali-Vazirani (MV) algorithm\, for finding a maximum cardinality matching in general graphs\, was recently completed — over four decades after the publication of the algorithm (1980). MV is still the most efficient known algorithm for the problem. In contrast\, spectacular progress in the field of combinatorial optimization has led to improved running times for most other fundamental problems in the last three decades\, including bipartite matching and max-flow. \nThe new ideas contained in the MV algorithm\, and its proof remain largely unknown\, and hence unexplored. We hope to rectify this shortcoming and use ideas from the proof to give a simpler exposition of the algorithm. \nBased on this paper. \nBio: Vijay Vazirani is a distinguished professor at the University of California\, Irvine. A description of his research appears in the citation of his 2022 INFORMS John von Neumann Theory Prize. In 2001\, he published Approximation Algorithms\, which was followed by two co-edited books\, Algorithmic Game Theory in 2007 and Online and Matching-Based Market Design in 2023.
URL:https://homecse.iitd.ac.in/event/a-theory-of-alternating-paths-and-blossoms-from-the-perspective-of-minimum-length/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250121T120000
DTEND;TZID=Asia/Kolkata:20250121T130000
DTSTAMP:20260924T065945
CREATED:20241212T063048Z
LAST-MODIFIED:20241212T122213Z
UID:210-1737460800-1737464400@homecse.iitd.ac.in
SUMMARY:Cybersecurity: Why its hard\, solutions\, and careers
DESCRIPTION:Rajeev Barua\, University of Maryland. \nThe battle between cyber attackers and attack detection teams is an arms race that is not letting up. Attackers constantly devise new ways of exploiting system vulnerabilities\, and new methods to hide from detection. In response\, detection teams have responded with new technologies to detect attacks. \nThis talk will overview why cybersecurity is hard\, the solutions available\, and the latest industry trends\, and it will discuss careers in cybersecurity in India and worldwide. \nDr. Rajeev Barua is a Professor of Electrical and Computer Engineering at the University of Maryland. He is also the Founder and CEO of SecondWrite Inc\, which commercializes binary rewriting technology his research group developed at the university. He received his B.Tech in Computer Science from IIT Delhi\, and his Ph.D in Computer Science and Electrical Engineering from the Massachusetts Institute of Technology in 2000. Dr. Barua’s research interests are in the areas of program analysis\, cybersecurity\, and Applied AI. \nDr. Barua is a recipient of the NSF CAREER award in 2002\, the UMD George Corcoran Award for teaching excellence in 2003\, and the UMD Jimmy Lin Award for innovation in 2014. He has published over 70 academic papers and five issued patents. His company\, SecondWrite\, has raised over $2.4M in funding\, including $1.3M in US governments SBIR grants\, and the rest from professional private investors.
URL:https://homecse.iitd.ac.in/event/cybersecurity-why-its-hard-solutions-and-careers/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250124T120000
DTEND;TZID=Asia/Kolkata:20250124T130000
DTSTAMP:20260924T065945
CREATED:20250109T100500Z
LAST-MODIFIED:20250219T003504Z
UID:962-1737720000-1737723600@homecse.iitd.ac.in
SUMMARY:Online\, greedy\, and conceptually simple algorithms
DESCRIPTION:Allan Borodin\, University of Toronto \nWhat can and cannot be computed by “conceptually simple algorithms”? In this regard\, my primary interest is in approximation algorithms for combinatorial optimization problems and the relation of such problems to areas such as scheduling\, algorithmic game theory and computational social choice. \nWhy do we care about conceptual simplicity\, and can we formalize such a concept? For some problems\, simple algorithmic ideas provide the best-known solution or are reasonably competitive with the best-known algorithms\, especially in the context of real data. Moreover\, “in \npractice”\, it is often the case that users will opt for a quick understandable algorithm. While it is arguably impossible to precisely define a useful general definition of “simplicity”\, we can study well-used (albeit rarely precisely defined) combinatorial algorithmic paradigms such as various forms and extensions of online and greedy algorithms\, primal-dual algorithms\, local search\, and “simple” dynamic programming. Can we then provide definitions for such paradigms that are sufficiently expressive to capture many or most existing algorithms\, but still allow us to prove impossibility results that do not rely on computational complexity assumptions? To what extent is our theoretical analysis consistent with performance in practice? We will consider the specific problem of online interval selection in different online settings. In particular\, we will consider the problem in the random order arrival model when the online algorithm can permanently reject previously accepted intervals.
URL:https://homecse.iitd.ac.in/event/allan-borodin-speaks/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20250127T120000
DTEND;TZID=Asia/Kolkata:20250127T133000
DTSTAMP:20260924T065945
CREATED:20250121T160348Z
LAST-MODIFIED:20250219T003504Z
UID:1141-1737979200-1737984600@homecse.iitd.ac.in
SUMMARY:Distinct Elements in Streams and the Klee's Measure Problem
DESCRIPTION:Sourav Chakraborty  (Indian Statistical Institute)\n\nWe will present a very simple streaming algorithm on F0 estimation that also caught the eye of Donald E. Knuth.  In a recent article\, Donald E. Knuth started with the following two paragraphs:\n \n“Sourav Chakraborty\, N. V. Vinodchandran\, and Kuldeep S. Meel have recently proposed an interesting algorithm for the following problem: A stream of elements (a1\, a2\,…\,am) is input\, one at a time\, and we want to know how many of them are distinct. In other words\, if A = {a1\, a2\,…\,am} is the set of elements in the stream\, with multiplicities ignored\, we want to know |A|\, the size of that set. But we don’t have much memory; in fact\, |A| is probably a lot larger than the number of elements that we can hold in memory at any one time. What is a good strategy for computing an unbiased estimate of |A|?\n \nTheir algorithm is not only interesting\, it is extremely simple. Furthermore\, it’s wonderfully suited to teaching students who are learning the basics of computer science. (Indeed\, ever since I saw it\, a few days ago\, I’ve been unable to resist trying to explain the ideas to just about everybody I meet.) Therefore I’m pretty sure that something like this will eventually become a standard textbook topic. This note is an initial approximation to what I might write about it\, if I were preparing a textbook about data streams.”\n\nThis simple algorithm comes out of the first ever “efficient” streaming algorithm (from PODS 21) for the Klee’s Measure problem\, which was a big open problem in the world of streaming for many years.\n\nThis work is based on joint works with N. V. Vinodchandran\, and Kuldeep S. Meel across multiple articles\, notable the following: Estimating the Size of Union of Sets in Streaming Models. PODS 2021 [Paper 1]\nDistinct Elements in Streams: An Algorithm for the (Text) Book. ESA 2022 [Paper 2].
URL:https://homecse.iitd.ac.in/event/distinct-elements-in-streams-and-the-klees-measure-problem/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
CATEGORIES:Seminars
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