Researcher

Chethana
Prasad K

Hey, I'm Chethana 👋

Hi and Namaste! I'm humbled you dropped by. Before you explore the rest of my work, let me introduce myself.I'm Chethana Prasad Kabgere—or simply CPK. If I had to sum myself up in one sentence, I'd say I'm someone who enjoys building things. That's admittedly a broad description, but in my world, "things" usually mean machine learning models, research ideas, and technologies that solve meaningful problems.

Give me a challenging coding problem, an interesting research question, a new HCI idea, or an AI system that needs designing, and I'll happily disappear for hours trying to make it better.

What fascinates me most is the space where people and intelligent systems meet. I love exploring how AI can be more trustworthy, more interactive, and more useful — not just more accurate. Whether I'm writing code, designing user experiences, building machine learning models, or experimenting with distributed AI systems, I'm always asking one question: "How can we make this smarter, simpler, and more human?"

Research, for me, isn't just about publishing papers — it's about chasing ideas that keep me awake at night. Coding isn't just a skill — it's my favorite way of thinking. I enjoy turning abstract concepts into working systems, breaking things apart to understand them, and then rebuilding them better.

Over the years, I've explored everything from Human-Computer Interaction and AI systems to federated learning, graph neural networks, privacy-preserving machine learning, and agentic AI. But I don't like being boxed into one domain. The most exciting ideas usually happen at the intersection of disciplines.

Outside of work, you'll probably find me sketching product ideas, reading research papers that have nothing to do with my current project, or convincing myself that "one small code change" definitely won't take the next four hours.

I'm always learning, always building, and always looking for the next interesting problem to solve.

Welcome to my little corner of the internet.

Chethana Prasad K
Chethana Prasad K
IIIT-B · Georgia Tech · IISc
Open to PhD positions
Current Researcher, IIIT-B WSL Lab
MSCS Georgia Institute of Technology (HCI + AI)
M.Tech By Research (MS) Thesis Area: Federated Learning and PPML
Focus Federated ML, Knowledge-based AI systems,PPML
Location Bengaluru, Karnataka, India
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Research Areas

🧠
Federated Learning
Studying how aggregation behaves when client data is heterogeneous — mostly in the context of federated GNNs.
🔒
Differential Privacy
Adding formal privacy guarantees to aggregation and model-repair pipelines for federated IoT settings.
⚛️
Quantum ML (early-stage)
A smaller, exploratory thread on noise-resilient aggregation for NISQ devices — one accepted workshop paper so far.
📜
Data Governance
Currently building a consent-management prototype aligned to DPDP/GDPR, as part of a larger institutional project.
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Recent Highlights

2026 · arXiv preprint
Geometric Coherence of Global Aggregation in Federated GNN
Submitted to IJAI · arXiv:2602.15510 ↗
2026 · IEEE COMSNETS
DP-EMAR: Differentially Private Model Weight Repair
For federated IoT systems
2025 · WinTechCon
Noise-Resilient Quantum Aggregation on NISQ
Workshop paper, accepted
Since Sep 2025 · IIIT-B
Anumati — consent management prototype
In progress, with CDAC, IISc-CDPG and IUDX under MoHUA & MeitY
All Publications →