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Curriculum Vitae. Use the buttons above to download a 1-page or 2-page PDF.

General Information

Full Name Nikhilesh Prabhakar
Location Richardson, TX
Languages English, Tamil, Hindi

Education

  • 2020 - Present
    Ph.D. / M.S. in Computer Science
    University of Texas at Dallas
    • Advisor: Dr. Sriraam Natarajan (StARLing Lab).
    • Jonsson School Graduate Fellowship.
    • Research focus: Neuro-symbolic AI, Interpretable Policy Learning, Reinforcement Learning.
  • 2016 - 2020
    B.Tech. in Computer Science
    Vellore Institute of Technology
    • CGPA - 9.23/10.

Coursework

Graduate (UT Dallas)
Machine Learning
Statistical Methods in AI / Probabilistic Graphical Models
Reinforcement Learning
Artificial Intelligence
Computational Logic
Advanced Algorithms
Theory of Computation
Undergraduate (VIT)
Data Structures and Algorithms
Operating Systems
Database Management Systems
Computer Networks
Theory of Computation
Compiler Design

Academic Interests

Neuro-symbolic AI
Interpretable Policy Learning
Reinforcement Learning
Sample-efficient Learning
Multi-agent Systems
Planning

Experience

Research
  • 2023 - Present
    Graduate Research Assistant
    StARLing Lab, University of Texas at Dallas

    Developed neuro-symbolic and relational RL frameworks for multi-agent systems, resulting in publications at AAMAS, AAAI, and FUSION.

Professional
  • 2024
    Workflow Chair
    AAAI-24, Vancouver

    Managed paper workflows for the 38th AAAI Conference.

  • Summer 2021
    ML Consultant
    Careband

    Activity recognition from accelerometer data for wearable deployment.

  • Summer 2018
    SDE Intern
    Referral Yogi Technologies

    Built a video transcription module using Ruby on Rails and the Google Speech API, integrated with batch sentiment and profile analysis.

Teaching
  • 2021 - 2023
    Graduate Teaching Assistant
    University of Texas at Dallas

    Machine Learning (CS6375); Digital Logic (CS4341).

  • Fall 2019
    Undergraduate Teaching Assistant
    Vellore Institute of Technology

    Introduction to Machine Learning (CSE4020).

Skills

  • Programming: Python, C++, PDDL, SQL, ASP (Clingo), Java, R
  • Libraries & Frameworks: PyTorch, BoostSRL, OpenAI Gymnasium, OpenCV, Scikit-learn, MuJoCo/MJX, JAX
  • Tools: Git, LaTeX