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Eugene Bagdasarayan is a PhD student advised by Deborah Estrin at Cornell Tech. Prior to Cornell Tech, he received an Engineer’s Degree in Computer Science and a Bachelor of Science in Automatic Control Systems and Information from Bauman Moscow State Technical University and then worked for Cisco.

What are you currently working on?

I am currently working on a project that is based on the intersection of Machine Learning and Systems. We investigate ways for users to keep their data private but still access data-intensive services or contribute to training Machine Learning Models. Today, users produce multiple digital traces that can be extremely sensitive to exposure, however, these traces could possess great value for future progress like early disease detection or building next-generation chatbots.

What excites you most about your current research?

My current research tries to address important problems of data privacy that is now recognized as a critical issue when we try to build new services. Answering these questions would enable new types of applications that are based on the personal data and still preserve the privacy of users’ data.

What were you doing prior to Cornell Tech in terms of your research focus?

I was working for Cisco Systems R&D, where we were developing a new cloud platform — OpenStack — and configuring it for Cisco hardware. However, I always wanted to be one step closer to invention and prototyping which requires more creativity and deeper understanding of the subject. Cornell Tech offers the unique balance between academia and industry where your research project might find its way into a product that has tangible near termas well as long term value.

What’s surprised you most about Cornell Tech?

People. I never met such a talented and diverse set of people in my life. Being among students, faculty and staff inspires me every day and I try to satisfy this really high bar.

How do you think Cornell Tech differs from traditional academia?

Luckily, I see all ingredients from academia — research seminars, working style and student life. However the important difference is the mix of different research areas (CS, IS, ORIE, ECE, Business) that produce amazing cross-field projects and many collaborations established with startups and industry.


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