CV
Education
Experience
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2023-Present Austin, TX
AI/ML Engineer
Polygraf AI
Building production-grade NLP systems for detecting AI-generated and manipulated content, privacy-preserving LLM infrastructure, and AI-powered document intelligence.
- Designed and deployed transformer-based PII detection pipelines (BERT variants) integrated into real-time product workflows.
- Built privacy-preserving LLM infrastructure that detects, redacts, and later restores sensitive entities while preserving semantic context.
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2016-2022 Austin, TX
Research Assistant
University of Texas at Austin
Research on combinatorial optimization problems arising in real-world large-scale systems; designed and analyzed efficient algorithms with provable performance guarantees. Published 3 journal articles and 9 conference proceedings.
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2018 Atlanta, GA
Visiting Summer Student
Georgia Institute of Technology
Research on minimizing electrical loss in electricity distribution networks. Advisor: Prof. Swati Gupta.
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2018 Berkeley, CA
Visiting Scholar
Simons Institute, University of California, Berkeley
Research on real-time decision-making problems arising in electricity networks.
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2014 Hong Kong
Research Intern
Hong Kong University of Science and Technology
Analyzed cache-induced asymmetric cooperation for MIMO cellular networks with limited backhaul.
Awards
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2023
2nd Place, Epson Innovation Challenge
Epson
Awarded for an AI-based secure print/scan system that prevents leakage of confidential data at physical document entry points.
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2018
Best Student Paper Award
IEEE ICASSP
For: Rasoul Shafipour, Ali Khodabakhsh, Gonzalo Mateos, Evdokia Nikolova, Digraph Fourier Transform via Spectral Dispersion Minimization, ICASSP, Calgary, 2018.
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2018
Best Paper Runner-Up
HICSS (Hawaii International Conference on System Sciences)
For: Ali Khodabakhsh, Ger Yang, Soumya Basu, Evdokia Nikolova, Michael C. Caramanis, Thanasis Lianeas, Emmanouil Pountourakis, A Submodular Approach for Electricity Distribution Network Reconfiguration, 51st HICSS, Hawaii, 2018.
Skills
Programming Languages: Python, Java, C++
ML/AI Frameworks: PyTorch, TensorFlow, Scikit-learn, Hugging Face, Transformers
Data, MLOps & Deployment: NumPy, Pandas, GCP, FastAPI, Gradio
Certificates
- Deep Learning Specialization - DeepLearning.AI (Andrew Ng) on Coursera (2022)