CV

Summary

PhD research scientist with 10+ publications at NeurIPS, ICLR, and AISTATS (including two Spotlight awards) in mechanistic interpretability, LLM behavioral control, and adversarial robustness. Combines strong mathematical foundations with hands-on experience running large-scale LLM experiments.

Education

• Ph.D. in Electrical and Computer Engineering 2017 - 2024
  Northeastern University, Boston, USA. GPA: 4.0/4.0.
  Thesis: Making Deep Neural Networks Transparent.
• Ph.D. in Mathematics 2022 - 2025
  Northeastern University, Boston, USA. GPA: 4.0/4.0.
  Thesis: Poisson Geometry of Flag Varieties and Representation Theory of their Quantum Deformations.
• M.S. in Electrical and Computer Engineering 2017 - 2019
  Northeastern University, Boston, USA. GPA: 3.96/4.0.
• B.Sc. in Electrical Engineering 2012 - 2017
  Sharif University of Technology, Tehran, Iran. GPA: 3.7/4.0.

Experience

• Graduate Research Assistant 2017 - 2025
  ECE Department, Northeastern University, Boston, USA.
  • Led end-to-end research projects from ideation and implementation to evaluation and publication, producing 10+ papers at NeurIPS, ICLR, and AISTATS including two Spotlight awards (top 5%).
  • Designed and ran large-scale experiments on LLMs (LLaMA 3.1 8B, Gemma 2 9B) using HPC clusters (Slurm), iterating on mechanistic interpretability hypotheses across hundreds of ablations.
  • Collaborated across institutions and disciplines, with clinicians at Brigham and Women’s Hospital over multiple projects, translating genomic and spirometry data into model-ready pipelines and co-interpreting findings with medical domain experts.
  • Maintained 4.0 GPAs across two concurrent doctoral programs in ECE and Mathematics while maintaining a full publication record, demonstrating the ability to carry multiple deep, unrelated research threads in parallel without loss of rigor or output.

Skills

• LLM & Interpretability: activation steering, mechanistic interpretability, TransformerLens, LLM behavioral evaluation (LLM-as-a-Judge).
• Experiment Infrastructure: PyTorch, Hugging Face Transformers, 4-bit quantization, large-scale ablations, Version Control.
• Agentic & Generative Systems: LangChain, RAG pipelines, Vision-Language Models.
• ML & RL: feature attribution, Shapley-value methods, PPO & GRPO.
• Mathematics: Optimization, probability theory, Linear algebra, stochastic processes, PDEs, functional analysis.

Honors And Awards

• Best Ph.D. Thesis Award 2025
  Northeastern University.
• Ph.D. Spotlight 2024
  Northeastern University.