Hello!

My name is Adithya. Nice to meet you!

Education

I recently graduated from the Georgia Institute of Technology with both a Bacherlor’s and Master’s degree in Computer Science. My specializations are in Machine Learning and Computer Systems, but I also have a background in mathematics, algorithms, and theoretical computer science.

Experience

Professional

I’ve interned at a couple companies during my time at Georgia Tech. I’ve worked two summers at AWS as a Software Development Engineer Intern, where I worked on the generative AI capabilities for AWS AppStudio. Before that, I interned at ServiceNow as a Software Engineering Intern, where I worked on the the MetricBase time-series database.

I’m currently open to full-time opportunities! I’m looking for software engineering roles in backend development, infrastructure, distributed systems, and machine learning, so if that’s you or your company, feel free to reach out through my Linkedin below,

If you want to learn more, feel free to check out my resume and my Linkedin.

Research

My research lies on deep learning inference on edge devices. More simply, it’s about trying to train and deploy neural networks that require as little computational power as possible to run on devices like laptops, smartphones, or even Raspberry Pis.

Most of my work is in post-training optimization for deep learning models. I even have a paper presented at NeurIPS 2024 about an algorithm I designed to improve the convergence of pruning-while-training algorithms for convolutional neural networks and transformer models. You can read the paper here.

In addition, I also have done work with others on improving the performance of foundational small language-vision models like LLAvA to get them to perform better on video captioning, annotation, and summarization. You can read about that and look at the code over here.

For Fun

Outside of work and research, I’ve worked on a couple fun projects and experiments. Some highlights include a series of neural networks that attempt to fill out the March Madness bracket every year (check it out here), and an 2nd-place best overall project from HackGT 2023, that attempted to flag a voice as potentially showing signs of Parkinson’s Disease using combination of audio processing and deep learning (check it out here).

You can find some of my other work at my GitHub.

Hobbies

Outside of work, I’m an avid sports fan. Though I mainly watch basketball (NBA, and men’s and women’s college, go Warriors and Yellow Jackets!), I do enjoy football (go 9ers), track and field, and recently picked up ice hockey as well (I’m an unfortunate Sharks fan). I’m also a big fan of role-playing video games, hiking, and skiing.

I also am a pretty big distance runner, having run a couple half-marathons, and plan to work up to a full marathon soon.

Thanks for stopping by!

Thanks for reading through everything! If there’s anything else you want to know, feel free to reach out through the links below. Have a great day!