Satwik Kundu  

Ph.D. Candidate @ Penn State — ML Systems

Satwik Kundu, Ph.D. Candidate @ Penn State

Hi! I am Satwik, currently a Ph.D. candidate in Computer Science and Engineering at Penn State, specializing in quantum computing, machine learning systems, and security. I am advised by Prof. Swaroop Ghosh.

My research focuses on making quantum computing more efficient and secure for real-world deployment. On the efficiency front, I work on optimization techniques to accelerate variational quantum algorithms while reducing quantum resource requirements. On the security front, I address vulnerabilities across the quantum software stack, from adversarial attacks on quantum neural networks (including model stealing and data poisoning) to confidentiality risks in quantum compilers.

My interests also span efficient ML systems and hardware-software co-design for AI, applying my background in optimization, parallel computing, and adversarial ML to bridge quantum & classical AI.

Before joining Penn State, I received my bachelor’s degree from Jadavpur University, where I worked on projects ranging from facial expression recognition to microarchitectural security in Docker containers.

News

Apr 2026 Awarded the Alumni Association Dissertation Award by Penn State!
Feb 2026 Our paper Efficient Optimization of Variational Quantum Algorithms via Gradient-Free Parameter Prediction has been accepted at IEEE Access!
Nov 2025 Gave an invited talk on Data Poisoning Attacks on Quantum Machine Learning at QCCS 2025.
Jul 2025 Awarded the Harvey and Geraldine Brush Graduate Fellowship in Engineering by Penn State!
Jun 2025 Awarded the 2024-25 Vice Provost and Dean of the Graduate School Student Persistence Scholarship by Penn State!
May 2025 Our paper STIQ received the Best Paper Award (1 of 140+ submissions) at IEEE HOST 2025!
Apr 2025 Our paper Inverse-Transpilation has been accepted at ACM GLSVLSI 2025 in the Advances in Security of Quantum Computing session!
Apr 2025 Our paper Adversarial Data Poisoning Attack on Quantum Machine Learning in the NISQ Era has been accepted for oral presentation at ACM GLSVLSI 2025!
Nov 2024 Our paper STIQ: Safeguarding Training and Inferencing of Quantum Neural Networks from Untrusted Cloud has been accepted at IEEE HOST 2025!
Oct 2024 Gave a talk on Security of Quantum Machine Learning at QCCS 2024.
Sep 2024 Our paper SoK: Security Concerns in Quantum Machine Learning as a Service has been accepted at ACM HASP 2024 (co-located with MICRO)!
Apr 2024 Passed my Ph.D. Comprehensive Exam!
Apr 2024 Our paper Evaluating Efficacy of Model Stealing Attacks and Defenses on Quantum Neural Networks has been accepted at ACM GLSVLSI 2024!
Mar 2024 Received $70,000 in IBM Quantum research credits for my work on improving the efficiency of variational quantum algorithms (VQAs)!

Selected Publications

  1. Access
    Efficient Optimization of Variational Quantum Algorithms via Gradient-Free Parameter Prediction
    Satwik Kundu, Debarshi Kundu, and Swaroop Ghosh
    IEEE Access, 2026
    URL arXiv Bib
  2. GLSVLSI
    Adversarial Data Poisoning Attack on Quantum Machine Learning in the NISQ Era
    Satwik Kundu, and Swaroop Ghosh
    Proceedings of the 35th IEEE/ACM Great Lakes Symposium on VLSI (GLSVLSI), 2025
    arXiv Bib
  3. HOST
    STIQ: Safeguarding Training and Inferencing of Quantum Neural Networks from Untrusted Cloud
    Satwik Kundu, and Swaroop Ghosh
    IEEE International Symposium on Hardware Oriented Security and Trust (HOST), 2025
    🏆 Best Paper Award 🏆
    arXiv Bib
  4. ASP-DAC
    Knowledge Distillation in Quantum Neural Network Using Approximate Synthesis
    Mahabubul Alam, Satwik Kundu, and Swaroop Ghosh
    In Proceedings of the 28th IEEE/ACM Asia and South Pacific Design Automation Conference (ASP-DAC), 2023
    URL Bib

Elsewhere