B.Tech CSE @ VTU | Undergraduate Researcher | AI/ML • Deep Learning • Reinforcement Learning • Scientific Computing
I’m a Computer Science undergraduate at Visvesvaraya Technological University (VTU) working on research-oriented problems across AI/ML, sequential decision-making, probabilistic modeling, Bayesian inference, and intelligent systems.
I enjoy combining mathematical ideas with practical implementations, experiments, and reproducible software.
- 🤖 Artificial Intelligence & Machine Learning
- 🧠 Deep Learning & Transformer Architectures
- 🎲 Probabilistic & Bayesian Inference
- 🔄 Reinforcement Learning
- 📈 Sequential Decision-Making
- 🧮 Scientific & Mathematical Computing
- 🌐 Dynamical & State-Space Models
- 🔍 Retrieval Evaluation & Representation Learning
Probabilistic Attack Regime Detection in Network Traffic via Switching State-Space Models Submitted to NeurIPS — currently awaiting the final decision.
Identifiability of Regime Structure in Switching Dynamical Systems Submitted to NeurIPS — currently awaiting the final decision.
Path-Space Bayesian Inference for Stochastic Differential Equations via Girsanov Likelihoods and Gaussian Process Priors
Measure-Valued Reinforcement Learning: Policies Over Posterior Distributions
Regret-Aware Policy Optimization: Provably Suppressing Harmful Replay Through Environment-Level Memory
ECG-TransNet: A Multi-Dataset CNN–Transformer Framework for Robust and Explainable Arrhythmia Detection ✅ Completed research project 📌 Currently looking for a suitable conference for submission.
Retrieval Evaluation Beyond Downstream Outputs: A Latent-Task-State Framework 🔄 Ongoing research project.
A multi-dataset CNN–Transformer framework for robust and explainable ECG arrhythmia detection.
A research-oriented project exploring Bayesian inference for stochastic systems using Girsanov likelihoods, Gaussian Process priors, and function-space methods.
An ongoing project exploring Bayesian and dynamical modeling approaches.
AI/ML · Deep Learning · Bayesian Methods · Reinforcement Learning · Transformers · Scientific Computing · Dynamical Systems
- Strengthening Python and software engineering skills
- Mastering Data Structures & Algorithms
- Building and deploying real-world applications
- Developing reproducible AI/ML research projects
- Exploring advanced topics in probabilistic modeling and sequential decision-making
- Preparing research projects for conference submission
- 🆔 ORCID: 0009-0008-6686-9223
- 📄 OpenReview: PeerAhammad M Bagawan
- 💻 GitHub: @PeerAhammad
I use GitHub to document my research, experiments, implementations, and software projects.
Research → Implement → Experiment → Evaluate → Improve
For research, collaboration, or technical discussions, feel free to connect through my ORCID, OpenReview, or GitHub profiles.