Engineering graduate student developing intelligent AI systems

Engineering graduate student developing intelligent AI systems

Aneesh Deshmukh is earning a master's degree in computer science

Artificial Intelligence is on the rise, and researchers are working harder than ever to understand, develop, and improve it. Aneesh Deshmukh, computer science M.S. student at the University of Cincinnati, is working on AI systems modeled after human brain functionality. Deshmukh's goal is to help these robots understand their surroundings and take this knowledge to navigate unfamiliar environments in the future. For this work, he has been named Graduate Student Engineer of the Month by the College of Engineering and Applied Science.

Why did you choose UC? What drew you here?

Why did you choose your field of study?

During my undergraduate studies in India, I was in a program like electrical and computer engineering and after graduating I worked as a software engineer at a mobile gaming company. I had always been fascinated by robotics, but it was during my undergraduate studies that I started developing a more serious academic interest in the field.

I got opportunities to explore robotics and AI through RoboWars, hackathons, personal projects, and a robotics course. These experiences made me realize that I wanted to learn much more before I could really consider pursuing robotics as a career. I also started to understand how multidisciplinary the field is with so many different areas and directions to explore.

What interested me most was being at the intersection of software and hardware-using software and intelligence to make physical systems do something meaningful in the real world. With that in mind, I decided to pursue computer science while focusing my research on robotics and AI, which was the combination that felt perfectly suited to me.

Briefly and simply describe your research work. Why does it interest you? What problems do you hope to solve?

I have always been amazed and inspired by nature, especially how we, as part of it, think, learn, and experience the world. I would often find myself wondering what was going on in another person's mind, and how their thoughts and interpretations of an experience might differ from mine. I find it fascinating to think about how people build memories, make connections, imagine things, and even have completely different personal experiences in the same situation. When broken down, so much of it comes from electrical and chemical signals moving through neurons in the brain, yet somehow it leads to the way we think, feel, remember, and perceive the world. The idea of complex behavior emerging from relatively simple interactions has always been something I found mystifying.

Ever since I was a teenager, YouTube has been one of my favorite ways to explore questions like these through various channels. I only learned the term "emergence" a few years ago, but the phenomenon itself was something I had been wondering about for much longer.

I was very fortunate to find Ali Minai, PhD, whose research aligned closely with these interests. My current work focuses on mimicking some of the functionality of the hippocampus using neural networks and combining that with vision and language systems. The goal is to help robots enter unfamiliar environments with little or no prior knowledge, learn what is around them, build memories of those environments, understand task-based instructions, and then use what they have learned to navigate and complete those tasks.

Through this research, I hope to better understand some of the principles behind how the human brain works while also using those ideas to build more capable robots. Ultimately, I would like to contribute toward robots that can assist people with everyday tasks, especially in situations where someone may have difficulty performing those tasks on their own.

What are some of the most impactful experiences during your time at UC?

What are a few accomplishments of which you are most proud?

A few accomplishments stand out to me because they each meant something different at the time.

My selection as Graduate Teaching Assistant in my department felt like a huge accomplishment to me. It was also a unique experience because it gave me the chance to see the other side of the classroom and better understand what goes into teaching, mentoring, and helping students understand difficult concepts.

I am especially proud to have published my first research paper. Alongside my internship in the summer of 2025, I was also working with Assistant Professor Tianyu Jiang on research involving Bayesian-inspired information seeking with large language models. The paper was published at the Empirical Methods in Natural Language Processing 2025 conference and seeing research that I had worked on reach publication was extremely rewarding.

My parents have always encouraged me to try and learn new things, which made me eager to keep expanding my skillset and explore things outside my usual academic work. UC's 1819 Innovation Hub is a great place for that. I learned how to do new things like knitting and using woodworking tools and machines. I value these experiences because I enjoy learning new skills even when they are completely outside my field of study.

When do you expect to graduate? What are your plans after earning your degree?

I expect to graduate in May 2027, after which I hope to pursue research and development roles in industry that allow me to continue working at the intersection of robotics and AI.

In the long term, I want to contribute to pushing the boundaries of both fields and developing technologies that can help us take better care of our planet while allowing people to spend less time on menial tasks and devote more time to creative, social, and intellectual fulfillment. In the future, I envision robots working alongside humans as capable partners, enabling people to devote more of their time and energy to such pursuits.

Do you have any other activities, hobbies, or involvements you'd like to share?

Featured Image at top: Aneesh Deshmukh is working on AI systems modeled after human brain functionality. Photo/Pixabay

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