About Me

I'm currently a 2nd-year PhD Student in computer science at the University of Maryland, advised by Prof. Furong Huang. I have experience doing research in deep learning, large language models (LLMs), agentic AI, security/privacy, and blockchains. My current research focuses on the intersection of security/privacy and machine learning, particularly in the context of large language models and agentic AI. I am always looking for new opportunities to collaborate on exciting research projects, so feel free to reach out if you have any ideas!

Publications
(☆ denotes equal contribution)

Skills

Programming

Python (Full Proficiency), Java (Full Proficiency), C/C++ (Full Proficiency), Rust (Intermediate Proficiency), Go (Intermediate Proficiency), Javascript (Intermediate Proficiency), Android (Java), Solidity (Intermediate Proficiency), Shell/Bash Scripting

Technologies

Docker, Virtualization, Parallel & Multi-Threaded Computing, Linux (RHEL/Fedora, Debian), Database Design, SQL, NoSQL, Kernel Development, CUDA, Git, SLURM, ROS (Robot Operating System), LaTeX

Deep Learning

PyTorch, TensorFlow, LLMs, Transformer Models, Model Quantization, Model Pruning, LLM Efficiency, Membership Inference Attacks, Security and trustworthiness, Microsoft Autogen, Agentic Frameworks

Networking & Security

Blockchains, Smart Contracts, zk-SNARKs, zk-STARKs, Elliptic Curves, Wireshark, Metasploit, Nmap, OWASP/MITRE Methodologies Analysis, Kali Linux

Soft Skills

Communication (Full Proficiency), Teamwork (Full Proficiency), Leadership (High-Intermediate Proficiency), Critical-Thinking (Full Proficiency), Problem-Solving (Full Proficiency), Adaptability (High-Intermediate Proficiency)

Research Experience

Graduate Research Assistant, University of Maryland

Aug 2023 - Present
Under Supervision of Prof. Furong Huang
horn-red News:
  • Submitted PropensityBench (equal-cont. first-author) to NeurIPS 2025.
  • AegisLLM (equal-cont. first-author) was presented at the ICLR Workshop on Building Trust (Apr 2025). Currently submitted to NeurIPS 2025.
  • Multiple NeurIPS 2025 position papers on the way.
  • Working on a project of surveying methods for enhancing robustness and adaptability for agentic AI.
  • Developing an AI system designed to automate the scientific research process, focusing on generating high-quality, publication-worthy research papers. This work addresses the significant limitations of existing AI research assistants by incorporating advanced techniques for knowledge access (web-based), synthesis, reasoning, and scientific writing, ultimately aiming to create an autonomous system capable of conducting original research and contributing meaningfully to the scientific community.

Research Intern, TU Graz and Universität Klagenfurt

June 2022 - Aug 2023
Under Supervision of Prof. Martin Gebser and Dr. Pierre Tassel

Developed a supervised approach to solving the RCPSP by using imitation learning for learning from CP schedules on smaller instances and generalizing to larger ones. This work is in continuation of Reinforcement Learning of Dispatching Strategies for Large-Scale Industrial Scheduling.

Research Assistant, Data Analysis Lab, University of Tehran

June 2021 - Oct 2022
Under Supervision of Prof. Behnam Bahrak

As part of the Crystalline project, designed and implemented RPoA, a flexible service-based alternative to the currently in-use consensus protocols, as mainly inspired by the drawbacks of PoA. Also, suggested and studied a novel node rewarding policy for full nodes in blockchain networks.

Research Intern, EMC Lab, EPFL

Nov 2021 - May 2022
Under Supervision of Dr. Hamidreza Karami

Studied acoustic source localization using single sensors by modeling using transformer models.

Research Intern, Robotics Lab, Arak University

June 2021 - Nov 2021
Under Supervision of Prof. Mohsen Rahmani

Studied a LiDAR-based context detection and planning problem for mapless autonomous driving using CNNs and UNets.