1) “Minimum variance constrained estimator” by Dr. Prabhat K Mishra (IIT Kharagpur)
Time & Venue: December 20, 2025 15:30 – 16:00 hrs IST; G21 (TCS Smart X Hub)
Abstract: This talk is concerned with the problem of state estimation for discrete-time linear systems in the presence of additional (equality or inequality) constraints on the state (or estimate). By use of the minimum variance duality, the estimation problem is converted into an optimal control problem. Two algorithmic solutions are described: the full information estimator (FIE) and the moving horizon estimator (MHE). The main result is to show that the proposed estimator is stable in the sense of an observer.
Brief Bio: Prabhat K. Mishra is an Assistant Professor at the Indian Institute of Technology Kharagpur (IIT Kgp) where he does research at the intersection of control theory and artificial intelligence for safety-critical applications and cyber-physical systems. He received a Ph.D. from the Indian Institute of Technology Bombay (IITB) and a Swiss Government Excellence Scholarship to study at Ecole polytechnique federale de Lausanne (EPFL) for a year. He was a Postdoctoral Associate at the Massachusetts Institute of Technology (MIT) and a Postdoctoral Research Associate at the University of Illinois at Urbana-Champaign (UIUC) before moving to IIT Kgp.
2) “Clearing the Path: Infeasibility in Motion Planning” by Dr. Antony Thomas (IIIT Hyderabad)
Time & Venue: December 20, 2025 15:30 – 16:00 hrs IST; G12 (TCS Smart X Hub)
Abstract: Motion planning, the task of finding a collision-free path in the presence of obstacles, lies at the heart of robotics. Equally important, yet often less explored, is the question of infeasibility, which concerns determining path non-existence. In task and motion planning, the ability to assess motion (in)feasibility is essential for robust decision-making and reliable execution of high-level tasks. When infeasibility is detected, alternative strategies or task plans must be formulated. Feasibility assessment also plays a critical role in manipulation amidst clutter and in rearrangement planning. In the Navigation Among Movable Obstacles (NAMO) paradigm, when no feasible path exists, obstacles are repositioned to create navigable paths.
This talk will explore why infeasibility detection is inherently challenging, present approaches for identifying and certifying infeasibility, and discuss methods for reasoning about its underlying causes within motion planning frameworks.
Brief Bio: Antony Thomas is an Assistant Professor with the Robotics Research Center (RRC) at the International Institute of Information Technology (IIIT) Hyderabad, India. He obtained his Ph.D. in Robotics and Autonomous Systems from the University of Genova, Italy, in 2021. His research interest include robot motion planning, motion planning infeasibility, collision avoidance planning, planning under uncertainty, integrated task and motion planning.
3) “A Two-Stage Mechanism for Demand Response Markets” by Dr. Bharadwaj Satchidanandan (IIT Madras)
Time & Venue: December 20, 2025 15:30 – 16:00 hrs IST; G11 (TCS Smart X Hub)
Abstract: Demand response involves system operators using incentives to modulate electricity consumption during peak hours or when faced with an incidental supply shortage. However, system operators typically have imperfect information about their customers’ baselines, that is, their consumption had the incentive been absent. The standard approach to estimate the reduction in a customer’s electricity consumption then is to estimate their counterfactual baseline. However, this approach is not robust to estimation errors or strategic exploitation by the customers and can potentially lead to overpayments to customers who do not reduce their consumption and underpayments to those who do. Moreover, optimal power consumption reductions of the customers depend on the costs that they incur for curtailing consumption, which in general are private knowledge of the customers, and which they could strategically misreport in an effort to improve their own respective utilities even if it deteriorates the overall system cost. The two-stage mechanism proposed in this paper circumvents the aforementioned issues. In the day-ahead market, the participating loads are required to submit only a probabilistic description of their next-day consumption and costs to the system operator for day-ahead planning. It is only in real-time, if and when called upon for demand response, that the loads are required to report their baselines and costs. They receive credits for reductions below their reported baselines. The mechanism for calculating the credits guarantees incentive compatibility of truthful reporting of the probability distribution in the day-ahead market and truthful reporting of the baseline and cost in real-time.
Brief Bio: Bharadwaj Satchidanandan is an Assistant Professor of Electrical Engineering at the Indian Institute of Technology Madras. Before this, he was a postdoctoral researcher at the Laboratory for Information and Decision Systems at Massachusetts Institute of Technology (MIT), where he was hosted by Prof. Munther A. Dahleh. He obtained his Ph.D. from Texas A&M University where he was advised by Prof. P. R. Kumar. His research interests include cyber-physical systems, security, renewable energy, game theory, mechanism design, communications, control, networks, etc.
4) “False data injection attack on consensus networks” by Dr. Vishal Sawant (IIT Hyderabad)
Time & Venue: December 20, 2025 15:30 – 16:00 hrs IST; 624 (TCS Smart X Hub)
Abstract: In networked control systems, consensus based algorithms are widely used for distributed optimization, sensor fusion, formation control etc. In this talk, we consider a finite-duration, magnitude bounded false data injection (FDI) attack on consensus network. The goal of the attacker is to induce maximum disagreement between nodes and consequently, influence the convergence of the consensus algorithm. We obtain closed-form expressions for the optimal attack input which results in the maximum disagreement and the corresponding value of disagreement. Further, the effect of varying attack duration on the induced disagreement is analyzed. Finally, it is shown that the criticality of nodes, measured as the disagreement induced by attack on them, has strong negative correlation with their degrees.
Brief Bio: Dr. Vishal Sawant is an assistant professor at the Department of Electrical Engineering of IIT Hyderabad. Prior to joining IIT Hyderabad, Vishal was a Postdoctoral Researcher at Aalborg University, Denmark and TU Delft, Netherlands. Vishal obtained his MTech. and Ph.D. degrees from IIT Bombay. His broad research area is Control Systems and his research interests include Multi-agent Systems, Optimal Control, and Cyber-Physical Security.