β’ Reinforcement Learning β’ Spatial Data Mining
βπ PhD IIIT-Dβ|βπ Author: βReinforcement Learning Explainedβ
π¬ University of South Dakota AI Research Labβ|βπ Google Scholarβ|βπΌ LinkedIn
- Currently a Postdoctoral Researcher at the University of South Dakota (USD).
- Research interests: Reinforcement Learning (RL), Embodied AI, World Models, Machine Learning in Healthcare, and Pattern Mining.
- Author of the upcoming textbook:
Reinforcement Learning Fundamentals: From Theory to Practice (with companion code repo). - Passionate about teaching, mentoring, and community building in AI.
- βοΈ Writing a comprehensive RL textbook (LaTeX source + reproducible code).
- π Exploring world models and sample-efficient embodied RL.
- π Working on AI for biomedical computation with collaborators at USD.
- π€ Organizing academic events like the AI Symposium @ USD.
- π Reinforcement-Learning-Explained-Code β Companion code for my RL textbook.
- π AI-Symposium β Website for USD AI Symposium.
- π Research paper repositories and proposals (in progress).
- Languages: Python, LaTeX, SQL
- Libraries: PyTorch, TensorFlow, scikit-learn
- Tools: Overleaf, Git, Power Automate, HPC (Lawrence)
- Advanced world model architectures (DreamerV3, AdaWorld).
- Deep RL alignment techniques for LLMs.
- π Website: AI Research Lab @ USD
- πΌ LinkedIn: linkedin.com/in/srikanth-baride
- π Google Scholar: Scholar Profile
I enjoy teaching meditation π§ alongside AI research β helping people cultivate both clarity of mind and clarity of models.
βοΈ Check out my pinned repositories for active work!
