Students

Ph.D. Students

Zhouhan Chen: Zhouhan is a PhD student at the Center for Data Science, working with Professor Rajesh Ranganath. His current research focuses on advancing causal inference using generative models. Before coming to NYU, Zhouhan earned his Bachelor’s and Master’s degree in Computer Science at Rice University. His Master’s thesis on An Unsupervised Approach to Detect Spam Campaigns that Use Botnets on Twitter, was advised by Professor Devika Subramanian. Zhouhan has a broad interest in designing and applying machine learning algorithms in the fields of social network, cybersecurity and health care. Out of school, Zhouhan is also a longtime marathon runner and certified personal trainer.

Irina Espejo: Irina is a first year PhD student in Data Science and also a DeepMind fellow. She is interested in applications of data science to the logistics of cities as well as in physics and theoretical machine learning. At the moment, she is initiating her research with Kyle Cranmer. Irina graduated from Mathematics and Physics at Universitat Autonoma de Barcelona. During her studies, she collaborated in two research projects. The first one in Complex Systems trying to model the pairwise interactions of letters in texts. The second one was in experimental particle physics, which led to a summer internship at CERN with an analysis focused on the DMttbar signal. From her undergraduate merits, she was awarded a Fulbright Scholarship by the Spanish Fulbright Commission to pursue doctoral studies in the USA. She also obtained an MSc in Mathematical & Theoretical Physics at the University of Oxford.

Katrina Evtimova: Katrina is a PhD student at CDS advised by Yann LeCun. Her research interests lie in unsupervised learning, self-supervised learning, and deep learning theory. Katrina earned her Master’s degree in Data Science from CDS during which she collaborated with Kyunghyun Cho. Prior to starting her PhD, she worked as a research engineer at eBay NYC. Katrina holds a Bachelor’s degree in Mathematics from Harvard University.

William Falcon: William is a first year Ph.D. student and a Deepmind Fellow co-advised by Kyunghyun Cho at the CILVR lab and Eero Simoncelli at the LCV lab. His research interest is in the intersection of AI and neuroscience. His work focuses in developing biologically inspired deep learning and reinforcement learning techniques with applications to neuroscience, NLP and computer vision. In his spare time he writes about AI for Forbes. Prior to NYU, he worked on neural decoding from the brain and retina at Columbia University’s Center For Theoretical Neuroscience supervised by Liam Paninski. He was also the co-founder and CTO of AI startup NextGenVest to help students finance uni over SMS. Before that, he was a software engineer at Goldman Sachs and developed over 8 iOS apps. He started his career as a naval officer undergoing US Navy SEAL training (BUD/S class 277) where he was injured and finished his military service at NSW Special Reconnaissance Team One (SRT-1). He obtained a B.A (magna cum laude) from Columbia University in Computer Science and Statistics with a minor in Math.

Xintian Han: Xintian is currently a PhD student at the NYU Center for Data Science, co-advised by Professor Joan Bruna and Professor Carlos Fernandez-Granda. His main research interests are machine learning theory and methods with application in high dimensional and network data analysis. Before joining NYU, Xintian earned his bachelor degree in statistics from Peking University (PKU), where he worked with Professor Jinzhu Jia on high dimensional regression models and confidence intervals. He also explored unrolling optimization algorithms into neural networks with Professor Bin Dong. During the summer of 2016, Xintian visited Professor Karl Rohe at the University of Wisconsin-Madison, where he developed some theories and methods for network driven sampling.

Phu Mon Htut: Phu is a PhD student at the NYU Center for Data Science. She is also a member of the Machine Learning for Language (ML²) group where she is working with two amazing professors, Sam Bowman and Kyunghyun Cho. Phu is broadly interested in Machine Learning, Natural Language Processing and Information Retrieval. She earned her Bachelor’s degree in Computer Science from Nanyang Technological University in Singapore. Phu also worked as a research engineer for a couple years in Singapore before joining CDS.

Leslie Huang: Leslie is a PhD student in Data Science at the NYU Center for Data Science, where she is advised by Arthur Spirling. Her research is focused on NLP applications and text-as-data in political science. Leslie has a BA, summa cum laude, from Columbia University, and an MA from NYU, where she was a PhD student in political science prior to joining Data Science. 

Vladimir Kobzar: Vladimir Kobzar is PhD Candidate at the NYU Center for Data Science, where he is a part of the Math and Data Group. He completed an MS in Mathematics at the Courant Institute under the advisement of Afonso Bandeira, as well as a JD and LLM at the NYU School of Law. A copy of his master’s thesis is available here. His research interests include applications of convex optimization to problems that exhibit an algebraic structure. These include problems in cryo-electron microscopy, robotics, as well as computer and human vision. More broadly, Vladimir is interested in the development of computationally efficient, provably robust and interpretable algorithms for data science and machine learning, and in applying methods of mathematics to analyze, among other things, legal and regulatory ramifications of such algorithms.

Angela Lai: Angela is a first year Ph.D. student and a DeepMind Fellow. Before joining NYU, Angela was at the University of Rochester, where she earned a B.S. in data science, a B.A. in political science, and a math minor. She is currently working on research with Arthur Spirling and Rich Bonneau and is part of the Social Media and Political Participation lab. Her research interests include natural language processing, network analysis, and politics.

Sheng Liu: Sheng Liu is a Ph.D. student at the NYU Center for Data Science, co-advised by Professor Carlos Fernandez-Granda, Professor Brian Mcfee and Professor Narges Razavian. His research focuses on image, audio analysis for healthcare using techniques from deep learning, machine learning and mathematical optimization. Prior to joining CDS, Sheng received his M.S. in Data Science from NYU where he worked on inverse problems with applications to neuroscience, medical imaging, and healthcare. Before that, he earned a bachelor’s degree in mathematics from Shanghai University (SHU), with a thesis on metric learning.

Omar Mahmood: Omar is a PhD student at the NYU Center for Data Science (CDS), working with Kyunghyun Cho and Richard Bonneau. His current research focuses on predicting 3D molecular conformation from molecular graphs, and the prediction of protein function from amino acid sequence. Prior to starting at CDS, he pursued a master’s degree in machine learning at the University of Cambridge, where his dissertation project was on deep generative models for molecule design and optimisation, under the supervision of José Miguel Hernández-Lobato. Before this, Omar worked as a software engineer at a natural language processing startup, where he was responsible for successfully pitching the company’s product to a major US financial institution, and executing and coordinating the ensuing project. He also holds a Bachelor of Science, magna cum laude, in applied physics from Columbia University.

Sreyas Mohan: Sreyas a PhD student at the Center for Data Science, NYU working under the joint guidance of Prof. Eero P Simoncelli and Prof. Carlos Fernandez-Granda. He is also a part of Math and Data Group. He graduated in July 2017 with a Bachelors in Electrical Engineering from Indian Institute of Technology (IIT) Madras where his undergraduate thesis was supervised by Prof. Kaushik Mitra. Sreyas spent the summer of 2017 at the Institute of Science and Technology (IST), Austria working with Prof. Gasper Tkacik on deep learning models for a particular neuroscience application and the summer before that at the Simons Center for Data Analysis, NYC working with Dr. Dmitri Chklovskii in the intersection of unsupervised learning and computational neuroscience.

Nikita Nangia: Nikita is a PhD student at CDS, where she is advised by Sam Bowman. Broadly, her research is in machine learning and natural language processing. You can find her publications here. Prior to joining NYU, Nikita worked in R&D for a few years. She has a BA in Physics from the University of Chicago.

Yiqiu Shen: Yiqiu Shen is a PhD student at the Center for Data Science, co-advised by Prof. Kyunghyun Cho and Prof. Krzysztof J. Geras. His research interests primarily lie in Artificial Intelligence for healthcare and deep learning for medical image analysis. Prior to joining NYU, he was a software engineer at Two Sigma Investments where he maintained a platform that extracts trading signals from market sentiment. He earned a Bachelor degree in computer science from Rice University.

Harvineet Singh: Harvineet is a Ph.D. student in Data Science at New York University. His research interests include statistical modeling of structured data such as sequences and graphs, with applications in digital health and social sciences. Prior to joining NYU, he was a research engineer at Adobe Research in India, where he worked on methods for survival analysis, interactive recommendations, and sequence prediction. He has an Integrated Master’s degree from Indian Institute of Technology Delhi in Mathematics and Computing. His Master’s thesis work, advised by Prof. Amitabha Bagchi and Prof. Parag Singla, explored graph representation learning techniques for social network data. He did two summer internships at Adobe Research, focusing on customer behaviour prediction. Also, he was a visiting researcher at BME, Hungary. His other interests include traveling, playing basketball, and listening to music.

Nan Wu: Nan is a PhD student at the Center for Data Science, co-advised by Prof. Kyunghyun Cho and Prof. Krzysztof J. Geras. She is interested in data science with application in healthcare and now working on medical image analysis. Before joining NYU, she graduated from School of Gifted Young, University of Science and Technology and received her B.S in Statistics and B.A. in Business Administration. In her undergraduate thesis, she worked on applying machine learning in cognitive science research and neurofeedback protocols.

Yanli Zhou: Yanli is a Ph.D. student at the NYU Center for Data Science, working with Dr. Brenden Lake. Previously at NYU, she received her BA in Mathematics and Psychology in 2016 and an MS in Data Science in 2018. Before joining the Lake lab, she worked as a research assistant under the supervision of Dr. Wei Ji Ma at the Center for Neural Science and Department of Psychology where she built probabilistic models of visual decision-making tasks. She is broadly interested in incorporating insights from cognitive science into building AI systems that can efficiently and flexibly learn.

Leadership Circle

The CDS Leadership Circle is our student representative group that plans events and activities for students and acts as a representative of the Data Science student body. The mission of the group is to help improve the student community at CDS and to develop student leaders. If you have any suggestions for the Leadership Circle or want to get involved, please email cdsleadershipcircle@nyu.edu.