mallika parulekar

I'm an Masters Student in Computer Science at Stanford University specializing in Artificial Intelligence. I'm broadly interested in applying machine learning to high-impact problems in learning, robotics and recommendation systems.

I completed my undergraduate degree from UC Berkeley in Computer Science. There, I was a research assistant at BAIR in Professor Goldberg's AUTOLab where I worked on problems in robot grasping and cable manipulation using analytic theory and deep learning. Previously, I worked on recommendation systems at Meta, backend and fullstack development at Caro, and anomaly detection at Abacus.AI. As an avid enjoyer of discrete math and probability who loves teaching, I was also a TA for CS 70.

In my free time, I enjoy playing ultimate frisbee with Stanford Women's Ultimate

Research

HANDLOOM: Learned Tracing of One-Dimensional Objects for Inspection and Manipulation

Vainavi Viswanath*, Kaushik Shivakumar*, Mallika Parulekar+, Jainil Ajmera+, Justin Kerr, Jeffrey Ichnowski, Richard Cheng, Thomas Kollar, Ken Goldberg

Conference on Robot Learning (CoRL), 2023. Oral Presentation.

[Paper] [Website] [Code]

Learning to Efficiently Plan Robust Frictional Multi-Object Grasps

Wisdom C. Agboh*, Satvik Sharma*, Kishore Srinivas, Mallika Parulekar, Gaurav Datta, Tianshuang Qiu, Jeffrey Ichnowski, Eugen Solowjow, Mehmet Dogar, Ken Goldberg

International Conference on Intelligent Robots and Systems (IROS), 2023.

[Paper]

MINDFUL: A Method to Identify Novel and Diverse Signals with Fast, Unsupervised Learning

Mallika Parulekar, Leelavati Narlikar

Great Lakes Bioinformatics Conference (GLBIO), 2019.

[Paper]