NYU Tandon graduate students bring a wealth of experience to Brooklyn

While no two NYU Tandon Ph.D. candidates are alike, they do share a few traits: intellectual rigor, perseverance, scientific curiosity, and a desire to do world-changing work. Meet a few of them below.

Luca Collini

Department of Electrical and Computer Engineering

How did you choose your field of study, and what led you to Tandon?

I’m from Italy, and one year I won a scholarship to study at the Academy at the Lakes, a high school in Florida. I had always loved problem-solving, so I spent a lot of time with the STEM club there and focused on computer science. I really appreciated that in computer science, there was a short feedback loop. When you tried something, it either worked or it didn’t work; you knew right away and then you could try something else if you had to.

When the year was over, I returned to Italy and finished my last year of high school before entering Politecnico di Milano, where I earned a bachelor’s degree in computer engineering in 2019 and a master’s in computer science and engineering two years later. I was the first in my immediate family to earn a college degree.

I arrived in Brooklyn in 2022, and I now work with Professor Ramesh Karri, who co-founded the NYU Center for Cyber Security.

Can you describe your work in simple terms?

Lately I have been focusing on the use of large language models to design microchips. We just wrote a paper on that. Previously, I was involved in studying logic-locking: that’s a technique in which gates are added to a circuit, which then produces the correct output only if the matching key is entered. It’s a way to prevent hackers from tampering with the fabrication process or stealing intellectual property. There are some drawbacks, however: it can affect the confidentiality of the data stored on the chip, so we’re also working on preventing that..

What has been the best part of studying at NYU and being in Brooklyn?

The Center for Cyber Security hosts an annual student-run event called CSAW that’s the biggest competition of its type in the world.We generally attract more than 3,000 participants. A highlight for me has been organizing the logic-locking challenge, which asks competitors to attempt to hack a chip of our design.

I was also the recipient of a Qualcomm Fellowship, so that was exciting.

What do you foresee for after graduation?

Many companies need people capable of designing safe, secure chips, so I’ll be focusing on a job in industry initially. I’ve already had internships at Synopsys and Qualcomm, and that’s definitely a path I’d like to follow.

Anubhav Jain

Department of Computer Science and Engineering

How did you choose your field of study, and what led you to Tandon?

I’ve always loved computer science, and during my undergraduate years at the Indraprastha Institute of Information Technology in Delhi, I got involved in Machine learning research and image forensics. That’s when I first read journal articles by Professor Nasir Memon, who did some pioneering work in the field of security and privacy. I was drawn to NYU Tandon for the chance to study with him. First though, I spent some time at Idiap Research Institute in Switzerland.

Now that I’m here I work with both Professor Memon and Professor Julius Togelius. If you put us on a Venn diagram, I would fall at the intersection of their work, since Professor Memon is focused on security and privacy, and Professor Togelius works with generative models.

I’m very lucky to have been awarded a Nokia Bell Labs fellowship, so I’m very grateful for that.

Can you describe your work in simple terms?

I was recently the lead author of a paper that addressed the systematic bias that can occur in facial recognition systems. We generated highly diverse and balanced synthetic face datasets that can train facial recognition AI models to produce more fair results when the systems are used for security purposes or to protect civil liberties.

Facial recognition is just one specific example. In general, I’m focused on making generative models more secure, fair, and privacy preserving without training data or weight updates. In a nutshell, I explore problems at the intersection of controllable generation and Responsible AI

What has been the best part of studying at NYU and being in Brooklyn?

Brooklyn is a wonderful borough, with lots to do and explore, and of course, it’s very easy to go to Manhattan whenever you want. If I had to pinpoint one great thing about being a doctoral student here it’s the massive computing power available to us; we have access to powerful processing resources.

What do you foresee for after graduation?

I hope to defend my dissertation by the end of 2025 and then seek work in industry that will enable me to apply my research skills to solve challenging problems.

Nandan Kumar Jha

Department of Electrical and Computer Engineering

How did you choose your field of study, and what led you to Tandon?

In India, by 10th grade, you decide whether you want to follow a track focused on the arts and humanities, commerce, or STEM. Within STEM you choose between biology and mathematics. My father was a teacher of physics and math, so I grew up with the idea that I would study STEM, and I chose mathematics, thinking that I would eventually study to be an engineer.

I earned my undergraduate degree in Electronics and Communications Engineering from the National Institute of Technology (NIT, Surat) and then worked for a time as a Project Research Assistant at the Indian Institute of Technology (IIT), Bombay. IIT Bombay is one of the most prestigious institutions in India, and many of the professors in the Electrical Engineering department earned their Ph.D.s from leading U.S. universities.

One of the moments that truly inspired me was attending a guest lecture by Manjul Bhargava, a Fields Medalist — often referred to as the Nobel Prize in Mathematics — during my time there. That exposure at IIT Bombay — both to world-class researchers and to an intellectually stimulating environment — planted the seed for my interest in pursuing higher education and research in the U.S.

I decided to work in industry for a while first, and from 2015 to 2017 I was an electrical design engineer at Seagate Technology, working on the development of Solid State Drive (SSD), a type of storage device. In 2017, I entered the Indian Institute of Technology, Hyderabad, for my master’s studies.

I began investigating programs that would allow me to focus on computer architecture and was leaning toward schools on the West Coast, when I happened to meet Ramesh Karri at the International Conference on Computer Design (ICCD) at NYU Abu Dhabi in 2019. He’s very widely known for his seminal work in hardware security, and he encouraged me to apply to NYU Tandon. Once he mentioned that Brandon Reagen would be joining the faculty soon, that decided me.

I was already familiar with Professor Reagen's work, having read his book Deep Learning for Computer Architects during my master's research. In our initial Zoom conversation, before I joined the Ph.D. program, he mentioned his ongoing work on Private Inference, which was still in its very early stages. I found the topic both fascinating and challenging. It also aligned with the common advice that it's ideal to begin a Ph.D. in a research area that is just starting to take shape — where there's room to explore, define problems, and make impactful contributions, and even though I got admitted to other schools, I wasn’t going to pass up the chance to work with him.

Can you describe your work in simple terms?

A lot of people are now familiar with AI platforms like ChatGPT and Claude now. They can be very useful. They do pose some privacy risks for users' sensitive data (such as medical records or credit card history) though. When users interact with artificially intelligent systems that are hosted in the cloud, sometimes that involves sending sensitive data and personal information that they’d prefer to keep private. On the other end, the server has a proprietary AI model that they presumably want to keep secure. So that’s the challenge. No one wants unencrypted data exposed.

I’m working in a very new area called Private Inference (PI), which combines cryptography and machine learning to perform computations on encrypted data. Right now, this takes enormous computing power (orders of magnitude slower than plaintext) and huge amounts of storage (hundreds of gigabytes), so it’s not efficient or cost-effective to do it on the massive amount of raw data that AI requires. I’m trying to develop better neural networks that can eliminate the bottlenecks in the process. It’s showing great promise. Professor Reagen and I just published a paper on the topic, “Entropy-Guided Attention for Private LLMs,” which is getting a lot of attention.

What has been the best part of studying at NYU and being in Brooklyn?

Of course, at the top of the list is getting to work with someone so respected in the field of computer architecture.

Professor Reagen is also notable in that he gives Ph.D. candidates a lot of freedom to explore the questions that are important to them. Private Inference is an exciting space to work in, because it’s so new that it presents a lot of challenges, and I’m getting a chance to make my own mark.

As far as what’s so great about Brooklyn, I really appreciate the chance to step outside my door and go running or cycling. Doing research like ours requires mental clarity and energy, and getting outside helps a lot.

What do you foresee for after graduation?

There are so many great companies leveraging Large Language Models now. It’s not just the big ones everyone knows like Google DeepMind; there are startups like OpenAI and Anthropic doing interesting things and making huge impacts. I’d like to return to the industry and get the end-to-end experience — seeing how ideas evolve from research to real-world impact. I’m especially motivated by the opportunity to create a tangible impact at scale, and eventually, I hope to channel that experience into launching a startup of my own. Considering the entrepreneurial spirit at NYU Tandon and throughout Brooklyn, I’m certainly in the right place to start thinking that way.

Jennifer Yeom

Department of Electrical and Computer Engineering

How did you choose your field of study, and what led you to Tandon?

My dad was a professor of computer science, so the idea of a career in STEM always seemed natural to me. During my first year of studying electrical engineering at the University of Washington, it struck me how expensive higher education was. One friend who was apparently savvier than I was had already signed up for Reserve Officers' Training Corps (ROTC), and when I found out they were offering full scholarships for engineering majors, that became an easy decision.

When I graduated in 2012 as a Second Lieutenant in the Air Force, they sent me to earn a master’s degree at the Air Force Institute of Technology, where I focused on signal processing and machine learning.

Once I had earned my M.S., I tested navigation systems at a base in New Mexico for three years, and then I entered the Air Force’s Test Pilot School. You’ve probably seen F-16s fighter jets–the ones with the needle-like noses. After I finished school, my job was to go up with the test pilots and collect data and analyze the plane’s capabilities and performance. It was physically demanding but exciting. I was later moved to Colorado to test satellite systems, and I started to think about earning a doctoral degree so that maybe I could teach at the U.S. Air Force Academy.

I was very interested in robotics, because I saw a great need in the military for robotics expertise, but the Institute didn’t have a robotics program. The Air Force agreed that I could remain on active duty and take three years to earn a Ph.D. if I could find a university that would not only admit me but would award me a scholarship.

NYU Tandon came through for me. I’m now a Major, and I think I might be the first active-duty Air Force officer they’ve ever had as a doctoral student.

Can you describe your work in simple terms?

I work with Professor Giuseppe Loianno on drones. I’m interested in fault detection and safety assurance. You’re probably familiar with quadcopters, which are drones with four rotors. You see them a lot because they’re inexpensive, but that means they’re also somewhat unpredictable. I’m studying how best to prevent accidents if a propeller or motor fails.

What has been the best part of studying at NYU and being in Brooklyn?

I really have the best of both worlds here — remaining in the Air force and getting the chance to do academic research on a topic I find fascinating, all while getting to live in Brooklyn.

What do you foresee for after graduation?

With the military, nothing is left up to chance, so I don’t have to guess. I’ll be going to Nevada as a flight test engineer after I graduate, and when I’m done with that assignment, I’ll have the chance to join the faculty of the USAFA.