Curriculum Vitae

The detailed PDF version of my CV can be found here - Curriculum Vitae

Research Interests

I am interested in understanding machine learning problems through the lens of geometry, statistics, and optimization.

Current research interests - trustworthy machine learning, multi-agent learning, learning theory
Other interests - machine teaching, algorithmic high-dimensional robust statistics, causal inference, geometric deep learning

Theses

• A Study of Robust Learning under Label Noise with Neural Networks, Master’s Thesis
  Advisor: Prof. PS Sastry
  [Thesis] | [Slides] | [Codes]

Publications [Related to my Thesis]

• Solving Neural Min-Max Games: The Role of Architecture, Initialization, and Dynamics - NeurIPS 2025 (Spotlight) [paper] [video (5 mins.)] [poster] [slides (5 mins)] [slides (long)]

Other Publications/Preprints

Algorithmic Machine Teaching

• Optimal Dataset Design for Nurture-then-Nature Teaching (2025) - Under review [preprint]

Robust Learning under Label Noise

• Estimating Label Noise Rates with Class-specific Thresholds (2025) - To Be Uploaded
• Adaptive Sample Selection for Robust Learning under Label Noise - WACV 2023 [paper] [code] [video] [poster]
• Memorization in Deep Neural Networks: Does the Loss Function matter? - PAKDD 2021 [paper] [video] [code] [presentation]

Analysis of Speech Signals

• Comparison of Speech Tasks and Recording Devices for Voice Based Automatic Classification of Healthy Subjects and Patients with Amyotrophic Lateral Sclerosis - Interspeech, 2019 [paper] [poster]
• Comparison of Speech Tasks for Automatic Classification of Patients with Amyotrophic Lateral Sclerosis and Healthy Subjects - International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2018 [paper]

Presentations and Talks

• Adaptive Sample Selection for Robust Learning under Label Noise [poster]
  Online Asian Machine Learning School, ACML 2022, Hyderabad
  
• Adaptive Sample Selection for Robust Learning under Label Noise [video] [presentation]
  EECS Symposium 2021, Indian Institute of Science, Bangalore
  

Education

• Ph.D, 2023 - Present
  Department of Computer Sciences, University of Wisconsin-Madison, USA
  

• Ph.D, 2021 - 2023 (discontinued)
  Department of Electrical Engineering, Indian Institute of Science, Bengaluru
  Advisor: Prof. PS Sastry

• M.Tech (Research), 2018 - 2021
  Department of Electrical Engineering, Indian Institute of Science, Bangalore
  Advisor: Prof. PS Sastry

• B.Tech (Electrical Engineering), 2012 - 2016
  School of Technology,
  PDPU, Gujarat
  

Other Research Experiences

• September 2017 - July 2018: Project Assistant
  • Department of Electrical Engineering
  • Mentor: Dr. Prasanta Kumar Ghosh
    • Details in CV

Teaching experience

• Fall’25: Teaching Assistant
  • Course: Programming for Behavioural Data Science
  • Instructor: Dr. Adam Ross Nelson
• Spring’25: Teaching Assistant
  • Course: Design and Analysis of Psychological Experiments II
  • Instructor: Dr. Benjamin Douglas
• Fall’24: Teaching Assistant
  • Course: Programming for Behavioural Data Science
  • Instructor: Dr. Adam Ross Nelson
• Spring’24, Fall’23: Teaching Assistant
  • Course: Basic Statistics for Psychology
  • Instructor: Prof. Rebecca Addington
• Fall ‘22: Teaching Assistant
  • Course: Random Processes
  • Instructor: Prof. Aditya Gopalan
• Spring ‘20: Teaching Assistant
  • Course: Pattern Recognition and Neural Networks
  • Instructor: Prof. PS Sastry
• Fall ‘19, Fall ‘20, Fall ‘21: Teaching Assistant
  • Course: Stochastic Models & Applications
  • Instructor: Prof. PS Sastry

Projects

Adaptive Sample Selection for Robust Learning under Label Noise
Memorization in Neural Networks: Does the Loss Function matter?
Speech-based detection of ALS and Parkinson’s Disease - SPIRE Lab, Indian Institute of Science