Summary
Overview
Work History
Education
Skills
Certification
Languages
Affiliations
publications
academic achievements & services
Timeline
Generic

SANJAY DAS

Richardson,TX

Summary

Motivated student currently working towards PhD degree in Computer Engineering. Self-motivated professional with excellent communication, planning and problem solving abilities with Extensive background in investigating reliability in deep learning systems.

Overview

4
4
years of professional experience
1
1
Certification

Work History

Graduate Research Assistant

The University Of Texas At Dallas
08.2022 - Current
  • Investigating the reliability of deep learning systems
  • Formulating approaches to mitigate these challenges to ensure operational functional safety (FuSa).
  • Tools & technologies used: Python, C++, PyTorch, TensorFlow, Machine Learning, Deep Neural Networks, Large Language Models (e.g. Transformer-based models).

Graduate Research Assistant

North Dakota State University
01.2022 - 05.2022
  • Explored unique design possibilities using emerging devices.
  • Utilized devices: Ferro-electric Field Effect Transistors (FeFET), Quantum Anomalous Hall Effect (QAHE) memories.
  • Designed an adaptable multilevel voltage to binary converter using FeFET.
  • Designed ternary In-Memory computing algorithms (e.g. balanced scaler multiplication, dot product) using QAHE memories.
  • Tools & technologies used: MATLAB, Cadence Virtuoso, HSPICE, Python.

Graduate Teaching Assistant

North Dakota State University
08.2021 - 05.2022
  • Lab instructor for ECE 173 (Introduction to Computing) consisting 70 undergraduate students and ECE 375 (Digital Design 2) consisting 30 undergraduate students.
  • Assisted undergraduate students in developing a conceptual understanding of their projects and provided guidance in implementation and debugging process.

System Engineer (Role: Software developer)

Tata Consultancy Services
09.2019 - 08.2021
  • Delivered customized IFS applications based on client requirements in a timely manner.
  • Leveraged C# with Microsoft Visual Studio for front-end development and employed PLSQL for backend operations on the Oracle database.
  • Utilized Microsoft Azure to create virtual environments and customized IFS applications for efficient and client-specific adaptations.
  • Tools & Technologies used: C#, Microsoft visual studio, PLSQL, Oracle database, Microsoft Azure, IFS application.

Education

Ph.D. - Computer Engineering

University of Texas At Dallas
Richardson, TX
12.2025

Master of Science - Electrical and Computer Engineering

North Dakota State University
08.2022

Bachelor's - Electrical Engineering

RCC Institute of Information Technology
05.2019

Skills

  • Python, C/C
  • SQL/PLSQL
  • VHDL, Verilog
  • Chisel
  • Deep Learning/Artificial Intelligence
  • Transformer-based model (eg Large Language Models)
  • PyTorch/TensorFlow
  • Analytical Thinking
  • Presentation Skills
  • Journal Publication
  • Research and Analysis

Certification

IFS Learning Achievement - IFS Applications 10 Essentials for Developers was issued by IFS.

Languages

English
Full Professional
Bengali
Native or Bilingual
Hindi
Full Professional

Affiliations

  • Soccer, Racquetball, Badminton, Swimming, Exercise, Cooking.

publications

  • Kundu, Shamik, Navnil Choudhury, Sanjay Das, et al. "QNAD: Quantum Noise Injection for Adversarial Defense in Deep Neural Networks." in 2024 IEEE International Symposium on Hardware Oriented Security and Trust (HOST), 2024.
  • Das, Sanjay, Shamik Kundu, Anand Menon, et al. "Analysing and Mitigating Circuit Aging Effects in Deep Learning Accelerators." in 2024 VLSI Test Symposium (VTS), 2024.
  • Das, Sanjay, Shamik Kundu, Kanad Basu. "Bottlenecks in Secure Adoption of Deep Neural Networks in Safety-Critical Applications." in 2023 Midwest Symposium on Circuits and Systems (MWSCAS), 2023.
  • Arunachalam, Ayush, Sanjay Das, Monikka Rajan, et al. "Enhanced ML-Based Approach for Functional Safety Improvement in Automotive AMS Circuits." In 2023 IEEE International Test Conference (ITC), pp. 266-275. IEEE, 2023.
  • Govindankutty, Arun, Shamiul Alam, Sanjay Das, et al. "Cryogenic In-memory Binary Multiplier Using Quantum Anomalous Hall Effect Memories." In 2023 24th International Symposium on Quality Electronic Design (ISQED), pp. 1-7. IEEE, 2023.
  • Das, Sanjay, Arun Govindankutty, Shan Deng, et al. "Adaptable Multi-level Voltage to Binary Converter Using Ferroelectric FETs." In 2022 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), pp. 116-121. IEEE, 2022.
  • Das, Sanjay. "Exploration of Mutli-Threshold Ferro-Electric FET Based Designs." PhD diss., North Dakota State University, 2022.
  • Bal, Sandeep, Sanjay Das, Soumadeb Dutta, et al. "Hardware realisation of an intelligent medical image watermarking." International Journal of Nanoparticles 12, no. 1-2 (2020): 33-49.

academic achievements & services

  • Featured in the Conference spotlight of IEEE VLSI Circuits and Systems Letter, Volume 8 Issue 3, August edition, 2022.
  • Finalist in Logic Locking and Embedded Security Challenge at Cyber Security Awareness Week (CSAW), 2022.
  • "Adaptable Multi-level Voltage to Binary Converter Using Ferroelectric FETs" paper received the "Best Paper Award" at ISVLSI 2022.
  • "Hardware Implementation of a Fragile Digital Image Watermarking Methodology" paper received a "Letter of Appreciation" at RCCIIT, 2019.
  • Active role as a reviewer for academic conferences including ASP-DAC, SOCC, ICPADS, ICCAD, VLSID, VTS.

Timeline

Graduate Research Assistant

The University Of Texas At Dallas
08.2022 - Current

Graduate Research Assistant

North Dakota State University
01.2022 - 05.2022

Graduate Teaching Assistant

North Dakota State University
08.2021 - 05.2022

System Engineer (Role: Software developer)

Tata Consultancy Services
09.2019 - 08.2021

Ph.D. - Computer Engineering

University of Texas At Dallas

Master of Science - Electrical and Computer Engineering

North Dakota State University

Bachelor's - Electrical Engineering

RCC Institute of Information Technology
SANJAY DAS