Parth Paritosh

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Postdoctoral Fellow
Military Information Sciences
DEVCOM Army Research Laboratory

E-mail: pparitos <at> ucsd <dot> edu
Google Scholar, LinkedIn, GitHub

Brief Bio

I received my PhD degree in Engineering Sciences at University of California San Diego, working with advisors Sonia Martinez and Nikolay Atanasov. Prior to this, I received my Master's degree from Purdue University ( 1, 2 ) and Bachelor's degree from Indian Institute of Technology Guwahati. Some of my work with undergraduate students and interns at MURO lab is mentioned here.

Research

I have worked on several aspects of provably correct distributed estimation and optimization in networked systems, such as accuracy, approximations and privacy.

News

  • Apr 2024: Joined DEVCOM Army Research Laboratory as a postdoctoral fellow

  • Dec 2023: Defended my thesis titled “Scalable and Efficient Bayesian Algorithms for Distributed Estimation and Inference”

  • Sept 2023: Presented a poster on “Distributed Variational Inference for Online Supervised Learning” with a new Turtlebot4 team mapping implementation at SoCal Robotics Symposium 2023.

  • July 2023: Submitted our work on “Distributed Variational Inference for Online Supervised Learning” Read here.

  • Dec 2022: Presented our work on “Distributed Bayesian Estimation of Continuous Variables Over Time-Varying Directed Networks” at IEEE CDC 2022

  • Aug 2022: Our work titled “Distributed Bayesian Estimation of Continuous Variables Over Time-Varying Directed Networks” was accepted to IEEE Control Systems Letters

  • Mar 2022: Senate exam with a talk discussing “Scalable and Efficient Bayesian algorithms for Distributed Estimation and Inference”

Teaching

  • Teaching assistant for Cooperative Controls [MAE 247 syllabus], Spring 2023: Graded homework solutions and held office hours.

  • Additional teaching assistant MAE 242, Fall 2022: Discussion sessions and coding tutorials for motion planning.

  • Teaching assistant for Robot Motion Planning [MAE 242 syllabus], Spring 2022: Prepared homework solutions, created programming assignments, autograders and held office hours.

  • Teaching assistant for Introduction to Mathematical Analysis [MAE 289A syllabus], Fall 2021: Prepared homework solutions, and held office hours. <div id=“footer”> 2024 Parth Paritosh | Last updated: November 2024 </div>