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Aditya Das Sarma

PhD CS @ UW-Madison

Education

PhD @ Computer Sciences

University of Wisconsin-Madison
2023 - Present

MS @ Computer Sciences

University of Wisconsin-Madison
2023 - Present

BE @ Electronics & Telecommunications Engineering

Jadavpur University
2019 - 2023

Languages

  • English (Professional)
  • Bengali (Native)
  • Hindi (Fluent)

Career Profile

I am a second-year Ph.D. student at the Department of Computer Sciences at the University of Wisconsin-Madison, advised by Prof. Tsung-Wei (TW) Huang. My research focuses on machine learning for systems and AI for chip design. My skillset includes C/C++ and JAX/XLA.

Experience

Research and Development Engineering Intern

Summer 2025
Synopsys Inc.
  • Worked on fixing bugs in the front-end of the Fusion Compiler (flagship product).
  • Introduced memory optimizations save upto 33% in peak memory utilization.

Research Assistant

Summer 2024
University of Wisconsin Madison
  • Worked on ICCAD 2024 contest Problem B (Power and Timing Optimization using Multi-Bit Flipflops) under the supervision of Prof Tsung-Wei (TW) Huang.
  • Placed 6th out of 90 teams (with Honorable Mention).

Teaching Assistant

2023 - Present
University of Wisconsin Madison
  • TA for Operating Systems
  • Organized discussion lectures and programming projects for this course

Achievements

Placed 6th out of 90 teams (with Honorable Mention) in ICCAD 2024 Contest
HZDR Summer Research Fellowship (selected as 1 among 30 accepted applicants out of 350 total applicants)
Ranked 208 (top 0.01%) out of nearly 100k students appearing at the state level university entrance examination

Publications

Conference Papers and Journals

  • A New Differentiable Approach to Task Graph Partitioning: A Case Study in RTL Simulation
    • Aditya Das Sarma, Wan-Luan Lee, Shui Jiang, Boyang Zhang, Tsung-Wei Huang
    Submitted to 2026 Design Automation Conference (DAC)
  • TIMBER: A Fast Algorithm for Timing and Power Optimization using Multi-bit Flip-flops
    • Aditya Das Sarma, Shui Jiang, Wan Luan Lee, Tsung-Yi Ho, Tsung-Wei Huang
    2026 IEEE/ACM Asia and South Pacific Design Automation Conference (ASP-DAC)
  • A shallow hybrid classical–quantum spiking feedforward neural network for noise-robust image classification
    • Konar D.,Das Sarma A.,Bhandary S.,Bhattacharyya S.,Cangi A.,Aggarwal V.
    Elsevier Applied Soft Computing
  • Deep Spiking Quantum Neural Network for Noisy Image Classification
    • Konar D., Aggarwal V.,Das Sarma A.,Bhandary S.,Bhattacharyya S.,Cangi A.
    2023 International Joint Conference on Neural Networks (IJCNN)
  • On Quantum-Enhanced LDPC Decoding for Rayleigh Fading Channels
    • Majumder U., Das Sarma A., Vaidya V., Girish Chandra M.
    2023 IEEE/ACM Symposium on Edge Computing (SEC)