Vishaal Krishnan

Postdoctoral Fellow School of Engineering and Applied Sciences, Harvard University Vision Group, Lund University [CV] [Google Scholar] E-mail: vkrishnan <at> seas <dot> harvard <dot> edu

Bio

I am a Postdoctoral Fellow jointly in Applied Mathematics at the School of Engineering and Applied Sciences, Harvard University and in the Vision Group at the Department of Biology, Lund University. Previously, I was a Postdoctoral Scholar in the Department of Mechanical Engineering at UC Riverside, working with Prof. Fabio Pasqualetti. I completed my Ph.D. in the Department of Mechanical and Aerospace Engineering at UC San Diego in 2019, where my advisor was Prof. Sonia Martínez. Before that, I received the B.Tech and M.Tech degrees in Mechanical Engineering from IIT Madras in 2014.

Research

I am interested in the design and analysis of complex and adaptive autonomous systems, with an eye towards applications in robotics. Typical concerns include: 1) Optimality and robustness of performance, 2) Guaranteed safe and secure operation, 3) Scalability of design. Consequently, my efforts are directed towards uncovering the principles of: 1) organization of internal complexity, 2) adaptation to complex environments, 3) the interplay between the above. This places my research at the intersection of optimization, control theory, machine learning and infinite-dimensional analysis.

Papers

2021

• A Multiscale Analysis of Multi-Agent Coverage Control Algorithms
  V. Krishnan and S. Martínez

• Learning Robust Feedback Policies from Demonstrations
  A. A. R. Al Makdah, V. Krishnan and F. Pasqualetti

• On Direct vs Indirect Data-driven Predictive Control
  V. Krishnan and F. Pasqualetti
  IEEE Conference on Decision and Control

2020

• Lipschitz Bounds and Provably Robust Training by Laplacian Smoothing
  V. Krishnan, A. A. R. Al Makdah and F. Pasqualetti
  NeurIPS

• Data-driven Attack Detection for Linear Systems
  V. Krishnan and F. Pasqualetti
  IEEE Control Systems Letters (presented at the IEEE Conference on Decision and Control)

• Distributed Online Optimization for Multi-Agent Optimal Transport
  V. Krishnan and S. Martínez

• A Probabilistic Framework for Moving Horizon Estimation: Stability and Privacy Considerations
  V. Krishnan and S. Martínez
  IEEE Transactions on Automatic Control

2019

• On Observability and Stability of Moving-Horizon Estimation in a Distributional Framework
  V. Krishnan and S. Martínez
  American Control Conference

2018

• Distributed Control for Spatial Self-Organization of Multi-Agent Swarms
  V. Krishnan and S. Martínez
  SIAM Journal on Control and Optimization

• Distributed optimal transport for the deployment of swarms
  V. Krishnan and S. Martínez
  IEEE Conference on Decision and Control

• Identification of critical nodes in large-scale spatial networks
  V. Krishnan and S. Martínez
  IEEE Transactions on Control of Network Systems

2017

• Identification of critical node clusters for consensus in large-scale spatial networks
  V. Krishnan and S. Martínez
  20th IFAC World Congress

• Formation control and trajectory tracking of nonholonomic mobile robots
  A. Saradgi, V. Muralidharan, V. Krishnan, S. Menta and A. D. Mahindrakar
  IEEE Transactions on Control Systems Technology

2016

• Self-Organization in Multi-Agent Swarms via Distributed Computation of Diffeomorphisms
  V. Krishnan and S. Martínez
  22nd International Symposium on Mathematical Theory of Networks and Systems

Thesis

2019

• Large-Scale Multi-Agent Transport: Theory, Algorithms and Analysis
  V. Krishnan
  Ph.D. Thesis, UC San Diego