CV

A PDF version of my CV is available here.

Summary

Fifth-year Ph.D. candidate developing temporally robust learning, optimization, and control algorithms that remain reliable under non-stationarity and temporal drift. My research bridges distributed optimization, online system identification, and agentic AI, focusing on decision-making systems that stay stable, safe, and adaptive — from semidefinite optimization in power systems to memory safety and reasoning stability in large-language-model agents.

Education

• Ph.D., Electrical and Computer Engineering, Virginia Tech, Aug 2021 – Present
  • Advisor: Dr. Ming Jin
• M.S., Mechanical Engineering — Mechatronics, Jordan University of Science and Technology, Aug 2018 – May 2021
  • Thesis: Model Order Determination with Applications in System Identification, Image and Signal Processing
  • Advisor: Dr. Khaled F. Aljanaideh
  • GPA: 4.2 / 4.4
• B.Tech., Aeronautical Engineering, Jordan University of Science and Technology, Aug 2012 – Nov 2016
  • GPA: 86.7% — graduated top of class (1/40)

Academic Experience

• Graduate Research Assistant, ECE Department, Virginia Tech — Aug 2021 – Present
  • Mentor: Dr. Ming Jin
  • Developing temporally robust learning, optimization, and control algorithms resilient to non-stationarity — from distributed optimization to agentic AI.
• Research Assistant, Jordan University of Science and Technology — May 2021 – Aug 2021
  • Model order determination with applications in system identification.
• Research Assistant, Fuel Cell–Gas Turbine Hybrid Power & Autotronics, JUST — Jun 2017 – Aug 2018
  • Fuel cell–gas turbine hybrid power systems and automotive electronics.
• Research Assistant, Composite Materials Lab, JUST — Nov 2016 – Jun 2017
  • Interlaminar fracture toughness testing of composite laminates (Mode I opening, Mode II in-plane shear, End-Notched Flexure test).

Ongoing Research Projects

• Memory safety and stability in long-horizon agentic systems. This project studies how state, memory, and model structure shape behavior over time. The goal is to build diagnostics and guarantees for long-horizon operation. We treat memory and context as evolving internal states and analyze when they lead to failures such as incorrect commitments, disclosure, or inconsistent decisions. The work develops measurable predictors from retrieval-time signals and uses them to monitor risk before generation in agentic AI systems.

Publications

Remembering More, Risking More: Longitudinal Safety Risks in Memory-Equipped LLM Agents

Ahmad Al-Tawaha, Ruoxi Jia, and Ming Jin. "Remembering More, Risking More: Longitudinal Safety Risks in Memory-Equipped LLM Agents." *Under review at NeurIPS*.

Finite-Time Identification of LTI Systems Using Non-Causal FIR Models: A Unified Framework for Stable and Unstable Systems

Ahmad Al-Tawaha, Ming Jin, and Khaled F. Aljanaideh. "Finite-Time Identification of LTI Systems Using Non-Causal FIR Models: A Unified Framework for Stable and Unstable Systems." *Under review*.

A Dynamic Penalization Framework for Online Rank-1 Semidefinite Programming Relaxations

Ahmad Al-Tawaha, Javad Lavaei, and Ming Jin. "A Dynamic Penalization Framework for Online Rank-1 Semidefinite Programming Relaxations." In *Proceedings of the 7th Annual Learning for Dynamics & Control Conference (L4DC)*, pp. 1012–1024, 2025.

An Analytical Approach to Signal Denoising Based on Singular Value Decomposition

Ahmad Al-Tawaha, Khaled Aljanaideh, and coauthors. "An Analytical Approach to Signal Denoising Based on Singular Value Decomposition." In *Proceedings of the American Control Conference (ACC)*, 2025.

Monte Carlo Grid Dynamic Programming: Almost Sure Convergence and Probability Constraints

Mohammad S. Ramadan, Ahmad Al-Tawaha, Mohamed Shouman, Ahmed Atallah, and Ming Jin. "Monte Carlo Grid Dynamic Programming: Almost Sure Convergence and Probability Constraints." In *Proceedings of the American Control Conference (ACC)*, 2025.

Defense against Joint Poison and Evasion Attacks: A Case Study of DERMS

Ahmad Al-Tawaha*, Zain Ul-Abdeen*, Padmaksha Roy*, Ruoxi Jia, Laura Freeman, Peter Beling, Chen-Ching Liu, Alberto Sangiovanni-Vincentelli, and Ming Jin. "Defense against Joint Poison and Evasion Attacks: A Case Study of DERMS." *AAAI 2025 Workshop*.

Distributed Optimization and Learning: A Paradigm Shift for Power Systems

A. Al-Tawaha, E. Cibaku, S. Park, J. Lavaei, and M. Jin. "Distributed Optimization and Learning: A Paradigm Shift for Power Systems." IEEE Systems Journal, accepted, 2025.

A Nonheuristic Singular Value Thresholding Algorithm for Order Estimation

Ahmad Al-Tawaha, A. Alshorman, and Khaled F. Aljanaideh. "A Nonheuristic Singular Value Thresholding Algorithm for Order Estimation." Journal of Dynamic Systems, Measurement, and Control (ASME), vol. 147, no. 5, 2025.

Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models

Bilgehan Sel, Ahmad Al-Tawaha, Vanshaj Khattar, Ruoxi Jia, and Ming Jin. "Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models." In *Proceedings of the International Conference on Machine Learning (ICML)*, 2024.

Does Online Gradient Descent (and Variants) Still Work with Biased Gradient and Variance?

Ahmad Al-Tawaha and Ming Jin. "Does Online Gradient Descent (and Variants) Still Work with Biased Gradient and Variance?" In *Proceedings of the American Control Conference (ACC)*, 2024.

Decision-Focused Learning for Inverse Noncooperative Games: Generalization Bounds and Convergence Analysis

Ahmad Al-Tawaha, Harshal Kaushik, Bilgehan Sel, Ruoxi Jia, and Ming Jin. "Decision-Focused Learning for Inverse Noncooperative Games: Generalization Bounds and Convergence Analysis." *IFAC-PapersOnLine*, 56(2):9336–9341, 2023.

Learning-to-Learn to Guide Random Search: Derivative-Free Meta Blackbox Optimization on Manifold

Bilgehan Sel, Ahmad Al-Tawaha, Yuhao Ding, Ruoxi Jia, Bo Ji, Javad Lavaei, and Ming Jin. "Learning-to-Learn to Guide Random Search: Derivative-Free Meta Blackbox Optimization on Manifold." In *Proceedings of the Learning for Dynamics & Control Conference (L4DC)*, 2023.

A Singular Value Thresholding Algorithm for Order Estimation

Ahmad Al-Tawaha, Khaled F. Aljanaideh, and A. Alshorman. "A Singular Value Thresholding Algorithm for Order Estimation." In *Proceedings of the American Control Conference (ACC)*, 2023.

Awards & Scholarships

• 2026 — Gold Reviewer, ICML 2026 (top reviewers; complimentary registration)
• 2026 — Pratt Fellowship, Virginia Tech, Department of Electrical and Computer Engineering (Spring 2026)
• 2024 — ACC 2024 Travel Scholarship
• 2012–2018 — Full Scholarship (B.Sc. & M.Sc.), Ministry of Education, Jordan

Technical Skills

• Programming languages & tools: Python, MATLAB & Simulink, C++, LaTeX, Mathematica, ANSYS, Pro-Engineer
• Frameworks: PyTorch, TensorFlow, CVX, CVXPY, Cvxpylayer, Gurobi, NumPy, Pandas, Scikit-learn; experience with HPC

Service

• Conference reviewer: ICML 2026 (Gold Reviewer); ICLR 2025; ACC 2024, 2025, 2026; CDC 2025; IFAC 2023, 2025; IEEE Transactions on Control of Network Systems
• Tutorials: Distributed Control Strategies for Resilient Power Grids, SmartGridComm 2024