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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:20260101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20260306T120000
DTEND;TZID=Asia/Kolkata:20260306T130000
DTSTAMP:20261010T130701
CREATED:20260303T103646Z
LAST-MODIFIED:20260303T103646Z
UID:2432-1772798400-1772802000@homecse.iitd.ac.in
SUMMARY:Neural Circuit Discovery via Representation and Dynamics by Savik Kinger
DESCRIPTION:Abstract: Neuroscience and AI share a bottleneck: while one can build (artificial) or record (biological) complex networks\, we struggle to explain their functional circuitry; i.e.\, how they compute. In this talk I use whole-brain recordings from C. elegans\, a canonical neurobiological system\, as a concrete testbed for “circuit interpretability.” I then introduce two complementary inference approaches for turning high-dimensional activity data into mechanistic structure. Approach 1 treats circuit discovery as a representation problem: learn time-varying functional structure and uncover recurring\, stimulus-dependent modules rather than a single static connectivity map. Approach 2 treats circuit discovery as a dynamics problem: go beyond correlation to estimate directed\, time-lagged influence—i.e.\, which units appear to drive others and over what delays—using modern score-based generative modeling ideas. I will show how these ML methods produce testable hypotheses for biologists and\, potentially\, offer new avenues for understanding complex networks in AI. \nBio: Savik Kinger is a PhD candidate in Computer Science at Yale University\, advised by Steven Zucker. His research focuses on developing methods to analyze biological and artificial neural networks\, integrating ideas from machine learning\, dynamical systems\, and causal inference. He received Bachelor’s degrees in Math and Computer Science from Columbia University. He is supported by a Nathan Hale fellowship.
URL:https://homecse.iitd.ac.in/event/neural-circuit-discovery-via-representation-and-dynamics-by-savik-kinger/
LOCATION:SIT 113\, Amar Nath and Shashi Khosla School of Information Technology\, Indian Institute of Technology\, Delhi\, Hauz Khas\, New Delhi\, Delhi\, 110016\, India
CATEGORIES:Seminars
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DTSTART;TZID=Asia/Kolkata:20260310T090000
DTEND;TZID=Asia/Kolkata:20260310T100000
DTSTAMP:20261010T130701
CREATED:20260302T102353Z
LAST-MODIFIED:20260302T102353Z
UID:2429-1773133200-1773136800@homecse.iitd.ac.in
SUMMARY:Integration of Structured Reasoning and Data-driven Learning for Acting and Planning by Dr. Sunandita Patra
DESCRIPTION:Teams Link: MS Teams\nAbstract: The talk will focus on enabling autonomous actors\, such as digital agents or robots\, to take deliberative actions towards achieving their long horizon goals\, in the face of uncertainty and dynamic events. Today\, dynamic events or failures often require human intervention\, system restarts\, retraining\, or redesign\, for example\, when robots get stuck in dead ends or digital agents collapse under unanticipated events. Existing methods either rely on rule-based reasoning\, where it is extremely difficult for human experts to compile and maintain a complete set of rules\, or black-box machine learning models that need to be trained extensively for individual tasks. Neither approach is well suited when actors are operating in a dynamically changing environment. This work aims to overcome these limitations by creating integrated planning and learning algorithms that are practical to be executed in real-world environments (spanning finance\, robotics and cybersecurity) by incorporating within a single framework: (a) deliberative acting\, (b) online planning\, and (c) data-driven learning from the actor’s experiences.\n\n\nBy integrating structured reasoning with data-driven learning\, the goal of this research is to push towards the next generation of autonomous systems\, general-purpose agentic AI that can plan and act deliberately across a set of diverse tasks and domains.\n\n \nBio: Sunandita Patra is a Research Lead at J. P. Morgan AI Research\, Chicago\, USA. Her research interests include the integration of acting\, planning\, and machine learning\, focusing on finance\, cybersecurity\, and robotics domains. She completed her PhD and PostDoc in Computer Science at the University of Maryland\, College Park\, and holds BTech and MTech degrees in Computer Science and Engineering from IIT Kharagpur.  Her work received the Best Student Paper Honorable Mention Award at ICAPS 2020\, and the Best Student Paper Finalist Award (Top 3) at ECMR 2025. For more details\, please visit https://sunanditapatra.wixsite.com/camp
URL:https://homecse.iitd.ac.in/event/integration-of-structured-reasoning-and-data-driven-learning-for-acting-and-planning-by-dr-sunandita-patra/
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DTSTART;TZID=Asia/Kolkata:20260313T120000
DTEND;TZID=Asia/Kolkata:20260313T130000
DTSTAMP:20261010T130701
CREATED:20260309T161051Z
LAST-MODIFIED:20260309T161051Z
UID:2434-1773403200-1773406800@homecse.iitd.ac.in
SUMMARY:Genteel-Negotiator: LLM-enhanced mixture-of-expert-based reinforcement learning approach for polite negotiation dialogue by Dr. Mauajama Firdaus
DESCRIPTION:Venue: SIT001 \nAbstract : Developing intelligent negotiation dialogue systems that promote fair and sustainable outcomes is crucial for advancing automated negotiation for social good. Since effective negotiation requires balancing cooperation and competition while maintaining respect\, we propose GENTEEL-NEGOTIATOR\, a polite negotiation dialogue system for tourism and e-commerce domains. We introduce NEGOCHAT\, a tourism negotiation dataset\, and enrich it along with the Integrative Negotiation Dataset (IND) using diverse negotiation strategies. Built on an LLM-enhanced Mixture-of-Experts reinforcement learning framework\, the model incorporates dedicated experts for negotiation\, politeness\, and coherence\, guided by a reward function capturing strategy alignment\, politeness\, coherence\, and engagingness. Extensive automatic and human evaluations demonstrate its effectiveness in generating polite\, coherent\, and goal-oriented negotiation responses. \n\nBio: Dr. Mauajama Firdaus is an Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology (ISM) Dhanbad. She completed her Ph.D. in Computer Science & Engineering from IIT Patna and pursued postdoctoral research at the University of Alberta\, Canada. Her research expertise lies in Natural Language Processing\, Multimodal and Multilingual AI\, Dialogue Systems\, Explainable AI\, and Affective Computing. Her work focuses on building empathetic\, polite\, and emotion-aware conversational AI systems\, with applications in social good\, mental health\, customer care\, and multilingual settings. She has published extensively in top-tier journals and conferences including IEEE\, ACM\, AAAI\, ACL\, EMNLP\, and Information Fusion\, and holds a US patent in spoken language understanding. She also serves as Associate Editor for reputed international journals published by Elsevier.
URL:https://homecse.iitd.ac.in/event/genteel-negotiator-llm-enhanced-mixture-of-expert-based-reinforcement-learning-approach-for-polite-negotiation-dialogue-by-dr-mauajama-firdaus/
LOCATION:SIT 001\, Amar Nath and Shashi Khosla School of Information Technology\, IIT Delhi\, Hauz Khas\, New Delhi 110016\, India\, Delhi\, Delhi\, 110016\, India
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DTSTART;TZID=Asia/Kolkata:20260316T120000
DTEND;TZID=Asia/Kolkata:20260316T130000
DTSTAMP:20261010T130701
CREATED:20260312T134932Z
LAST-MODIFIED:20260312T134932Z
UID:2437-1773662400-1773666000@homecse.iitd.ac.in
SUMMARY:Logical explorations for security theory by Prof. Vaishnavi Sundararajan
DESCRIPTION:Venue: Bharti 501 \nAbstract: Logics and proof theories play a large role in the formal study and analysis of systems\, especially for formal verification. The exact shape of the syntax and proof rules involved depend heavily on the systems being modelled and verified. In this talk\, we will introduce a logical syntax for communicated messages and an associated proof system originally used in the verification of cryptographic protocols\, dating back to a very robust model from 1983\, which captures even the operational aspects of today’s internet. We will show how to extend thissystem to be able to better handle protocols that involve the communication of certificates\, and investigate some of the various logical and algorithmic questions that manifest during this endeavour.
URL:https://homecse.iitd.ac.in/event/logical-explorations-for-security-theory-by-prof-vaishnavi-sundararajan/
LOCATION:Bharti 501\, IIT Campus\, Hauz Khas\, New Delhi
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