About Me

Hey!, I’m Chethana — I design, analyze, and build intelligent systems, turning complex problems in machine learning into actionable frameworks for research and industry.I’m currently a Senior Research Associate at IIIT Bangalore. My journey was deeply shaped at IISc CDS, where I pursued my M.Tech (Research) thesis, immersing myself in the intersection of machine learning and security. Before that, I served as a Research Scholar Faculty at PES University, which set the stage for this work.Basically, a curious mind immersed in a world where machine learning meets security. My work focuses on building privacy-preserving AI systems — not the heavy, efficient alternatives that actually work in the real world. I’m also knee-deep in federated learning, cryptanalysis, and multi-modal sensor data fusion — yes, I love when multiple streams of data talk to each other to make smarter systems!

I’m currently pursuing a Master of Science in Computer Science (MSCS) at Georgia Tech, where I’m expanding my expertise in scalable AI systems and privacy-aware computation. Before this, I completed an MS(Research) in Machine Learning Engineering through PES University with guidence from IISc where i devoloped my thesis, which offered me an incredible platform to dive deep into real-world research problems. Earlier, I earned my Bachelor of Engineering in Electronics and Communication from VTU, Belgaum — the place where my fascination with the math and magic of technology truly began.

Before getting into full-time research, I worked at Infosys, where I handled functional testing in core banking systems, mainly Finacle. It was a crash course in how enterprise systems really work and how important robustness is. I also interned as a Research Engineer at HAL and BSNL, exploring practical engineering challenges in avionics and telecom.

Over time, my interests have naturally aligned toward making machine learning not just powerful but also responsible. That means secure, private, and ethical — all while being computationally efficient. No bloated models here!

I’ve always believed that research shouldn’t be locked away in labs or PDFs. It should be usable. Scalable. Deployable. My current projects revolve around just that — making machine learning systems smart and secure enough to survive in the wild.

So, whether I’m building federated frameworks for sensor-based terrain detection, analyzing encryption systems, or dreaming up the next efficient privacy layer, I’m here to contribute to tech that’s thoughtful, ethical, and future-ready.