Curriculum Vitae

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PhD researcher in computer vision and machine learning, with publications at CVPR, ECCV and WACV and industry experience at CCC Intelligent Solutions and Mayo Clinic. I work on representation learning, generative modeling, and real-world vision systems at scale.

Education

• Ph.D. in Electrical Engineering, West Virginia University — Morgantown, WV, USA
  Aug 2021 – present · GPA 4.0/4.0 · Advisor: Prof. Nasser Nasrabadi
• M.Sc. in Biomedical Engineering, K. N. Toosi University of Technology — Tehran, Iran
  Sep 2017 – Sep 2020 · GPA 4.0/4.0
• B.Sc. in Electrical Engineering, K. N. Toosi University of Technology — Tehran, Iran
  Sep 2012 – Sep 2016 · GPA 3.5/4.0

Experience

• Data Science Intern, CCC Intelligent Solutions — Chicago, IL, USA
  Sep 2025 – Dec 2025
  • Flow-matching generative modeling; synthetic data generation
  • Vehicle image classification; gradient-informed representation learning
  • Adaptation of vision foundation models
• Data Science Intern, Mayo Clinic (AI & Informatics) — Rochester, MN, USA
  Jan 2025 – Aug 2025
  • Adaptation of vision foundation models to histopathology image analysis
  • Self-supervised, weakly supervised and representation learning
  • Cancer detection and subtyping; diffusion-based data augmentation
  • LLM-based information extraction from unstructured clinical text

Selected publications

• GIF: Generative Inspiration for Face Recognition at Scale — IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

• Decomposed Distribution Matching in Dataset Condensation — IEEE/CVF Winter Conference on Applications of Computer Vision, 2025

• ARoFace: Alignment Robustness to Improve Low-Quality Face Recognition — European Conference on Computer Vision, 2024

• Hyperspherical Classification with Dynamic Label-to-Prototype Assignment — IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

• Boosting Unconstrained Face Recognition with Targeted Style Adversary — IEEE International Joint Conference on Biometrics, 2024

• Deep Boosting Multi-Modal Ensemble Face Recognition with Sample-Level Weighting — IEEE International Joint Conference on Biometrics, 2023

• CCFace: Classification Consistency for Low-Resolution Face Recognition — IEEE International Joint Conference on Biometrics, 2023

See the full publication list →

Skills

• Learning paradigms: supervised, self-supervised, weakly supervised and unsupervised learning; deep representation and metric learning
• Generative modeling: diffusion models, flow matching
• Computer vision: classification, retrieval and recognition — face recognition, medical imaging, vehicle imagery
• Data at scale: large-scale, long-tail and noisy real-world datasets
• Engineering: distributed multi-GPU training with PyTorch; end-to-end ML pipelines; Python, PyTorch, Git

Projects

See Projects for research tools and side projects I build and maintain.

References

Available upon request.