“Problems worthy of attack prove their worth by fighting back – Paul Erdos”

I am an Undergraduate Student Majoring in Mathematics with a Minor in Computer Science at IISER Berhampur. I am currently doing my Master’s Thesis Research work at IIT Hyderabad with Dr.Srijith P.K. at the intersection of Reinforcement Learning and Deep Generative Models.

Research, I am interested in working on Zero-shot Unsupervised Reinforcement Learning models that can adapt to downstream tasks with the prospect of developing Foundation Models for Decision Making Systems.

Outside Research, Alongside my primary research work, I have a particular interest in Machine Learning Systems(MLSys) with a focus on developing efficient deep learning models for the Edge Devices and builing better compute infrastructure for ML Model Training. I love Open Source and I spend time actively contributing to open source projects of my own and others (some of them are mentioned on the software page)

I am on the lookout for possible research opportunities in the field of Deep Reinforcement learning. Feel free to connect with me to discuss potential collaborations, research opportunities and Cool Open Source Project Ideas.

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Education:

• M.S. in Mathematics and Computer Science(Minor), IISER Berhampur, 2025(expected)
  • Thesis: Yet to be declared.
• B.S. in Mathematics and Computer Science(Minor), Indian Institute of Science Education and Research (IISER) Berhampur, INDIA

Research and Engineering Experience:(CV)

• Master’s Thesis Student(2024): Thesis Title: TBD
• REint AI Deep Learning Intern(2023): Worked on Computer Vision Deep learning models for Energy generation forecasting using spatiotemporal data
• Indian Academy of Sciences Summer Research Fellow(2023): Employed parameter-efficient fine-tuning techniques to refine LLaMA Foundation Models at IIT Ropar.
• Summer Research Intern (2022): Investigated Neural Differential Equations, particularly Neural PDE models, at IIT Hyderabad.
• NeuroImaging and Brain Research Lab, IISER Berhampur(2022): worked on brain tumor segmentation models and other deep learning models for Medical Imaging

Research Interests:

• Reinforcement learning and Sequential Decision-Making
• Neural Differential Equations/Continuous-Time Deep Learning
• Unsupervised Learning and Self-Supervised learning
• Foundation Models for Decision Making
• Machine Learning Systems (ML for Systems and Systems for ML)

Updates: