UC Davis · ASEEC Lab

ASIC Security Group

Advancing hardware security through |

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01 The Team

Researchers pushing the boundaries of hardware security

Houman Homayoun

Houman Homayoun

Principal Investigator

Leading the ASEEC ASIC Security Group, advancing hardware security through ML-driven approaches.

Kevin Immanuel Gubbi

Kevin Immanuel Gubbi

PhD Researcher

Researching ML-driven approaches for hardware security and ASIC design automation.

Navid Tarighat

Navid Tarighat

Ph.D. Student

AI for EDA and Design Verification.

Pavan Dheeraj Kota

Pavan Dheeraj Kota

MS Thesis

Working on advanced methodologies for ASIC design optimization and security assessment.

Yun-Gang Lee

Yun-Gang Lee

MS Researcher

Researching LLM agent-based methodologies for automated vulnerability detection and self-remediation in ASIC design.

Arvind Sudarshan

Arvind Sudarshan

AI/ML Engineer

Interested in use of AI in adjacent domains, agentic AI, data/infra platforms and full stack development.

Marcus Halm

Marcus Halm

MS Student

Interested in physical design, design verification, and AI/ML for EDA.

Brinda Puri

Brinda Puri

MS Researcher

ASIC Automation with GNN.

Yichen Liu

Yichen Liu

MS Researcher

Researching RL-based optimization methods for chip design and intelligent system automation.

Ishani Shah

Ishani Shah

Undergraduate Student

Researching optimization of digital architectures for secure automated systems.

Vandana Mansur

Vandana Mansur

MS Researcher

Interested in building intelligent systems leveraging AI and scalable cloud architectures across diverse domains.

Phone Yan

Phone Yan

Undergraduate Student

Interested in digital systems & ASICs and AI/ML for workflow automation.

Jiarao Zhang

Jiarao Zhang

MS Researcher

Researching reinforcement learning methods for timing closure and ECO optimization in ASIC physical design flows.

Alumni

Alumni 1

PhD Student

Alumni 2

MS Student

Alumni 3

MS Student

02 Research

Our focus areas at the intersection of ML and hardware

Reinforcement Learning for EDA

Applying RL agents to automate and optimize electronic design automation workflows, from floorplanning to place-and-route.

LLMs for Hardware Design

Leveraging large language models to generate, verify, and debug RTL code, improving designer productivity and design quality.

Hardware Security & Verification

Detecting hardware Trojans, side-channel vulnerabilities, and ensuring silicon integrity through ML-driven analysis.

Selected Publications

2025

RL-Driven Floorplanning for Secure ASIC Design

K. I. Gubbi, N. Tarighat, et al.

IEEE International Symposium on Hardware Security

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2024

LLM-Assisted RTL Generation with Security Constraints

N. Tarighat, K. I. Gubbi, P. D. Kota, et al.

Design Automation Conference (DAC)

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2024

Machine Learning Approaches for Hardware Trojan Detection

P. D. Kota, K. I. Gubbi, N. Tarighat, et al.

ACM Conference on Computer and Communications Security

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03 Blog

Insights and deep dives into hardware security and chip design

04 Deadlines

Upcoming conference paper submission deadlines

LAD 2026 IEEE International Conference on LLM-Aided Design Abstract: March 2, 2026
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ICCAD 2026 International Conference on Computer-Aided Design Abstract: April 7, 2026
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CCS 2026 ACM Conference on Computer and Communications Security (Cycle 2) Abstract: April 22, 2026
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ASP-DAC 2027 Asia and South Pacific Design Automation Conference Abstract: ~July 2026 (estimated)
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ISSCC 2027 International Solid-State Circuits Conference Paper: ~September 2026 (estimated)
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05 Projects

Tools, frameworks, and open-source contributions

SecureRL-EDA

A reinforcement learning framework for security-aware electronic design automation, integrating threat models into the optimization loop.

Python PyTorch RL

RTL-LLM Toolkit

An LLM-powered toolkit for generating, analyzing, and debugging Register Transfer Level hardware descriptions with built-in security checks.

Python LLM Verilog

TrojanNet Detector

A deep learning pipeline for detecting hardware Trojans in gate-level netlists using graph neural networks and anomaly detection.

Python GNN Security

06 Contact

Get in Touch

Interested in collaborating or joining the lab? We'd love to hear from you.

University of California, Davis
Department of Electrical & Computer Engineering