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Ilkay Altintas
Chief Data Science Officer, HDSI Founding Faculty Fellow
CHIEF DATA SCIENCE OFFICER, SDSC

Ilkay Altintas is a Fellow of Halıcıoğlu Data Science Institute (HDSI) as well as San Diego Supercomputer Center’s Chief Data Science Officer. She has played a huge role in the stewardship of HDSI cyberinfrastructure (CI) resources and services.

She will continue to work with UC San Diego faculty, industry partners, and students at all levels. In addition to her CDSO responsibilities at SDSC, an Organized Research Unit of UC San Diego, Altintas is an associate research scientist and director of the Workflows for Data Science (WoRDS) Center of Excellence at SDSC. WoRDS specializes in developing scientific workflows and solution architectures used throughout data and computational science.
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Mikhail Belkin
Professor

Mikhail Belkin received his Ph.D. in 2003 from the Department of Mathematics at the University of Chicago. His research interests are in theory and  applications of machine learning and data analysis. Some of his well-known work includes widely used Laplacian Eigenmaps, Graph Regularization and Manifold Regularization algorithms, which brought ideas from classical differential geometry and spectral analysis to data science. His recent work has been concerned with understanding remarkable mathematical and statistical phenomena observed in deep learning. This empirical evidence necessitated revisiting some of the basic concepts in statistics and optimization.  One of his key recent findings is the “double descent” risk curve that extends the textbook U-shaped bias-variance trade-off curve beyond the point of interpolation.

Mikhail Belkin is a recipient of a NSF Career Award and a number of best paper and other awards. He has served on the editorial boards of the Journal of Machine Learning Research, IEEE Pattern Analysis and Machine Intelligence and SIAM Journal on Mathematics of Data Science.

Post-Doctoral Fellow: Preetum Nakkiran

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Henrik Christensen
Director/CRI

Henrik Christensen is the director of the UC San Diego Contextual Robotics Institute and a professor in the Department of Computer Science and Engineering at the Jacobs School of Engineering. Christensen came to UC San Diego after serving, most recently, as executive director of the Institute for Robotics and Intelligent Machines at the Georgia Institute of Technology.

Christensen was initially trained in mechanical engineering and worked subsequently with MAN/BW Diesel. He earned a master’s and Ph.D. in electrical engineering from Aalborg University in Denmark, in 1987 and 1990, respectively.

 

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Rajesh Gupta
Distinguished Professor, HDSI Founding Director

Professor Gupta’s research interests span topics in embedded and cyber-physical systems with a focus on energy efficiency from algorithms, devices to systems that scale from IC chips, and data centers to built environments such as commercial buildings.

Gupta received a Bachelor of Technology in electrical engineering from IIT Kanpur, India; a Master of Science in EECS from University of California, Berkeley; and a PhD in electrical engineering from Stanford University, US. Gupta is a Fellow of the IEEE, the ACM and the American Association for the Advancement of Science.

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Zhiting Hu
Assistant Professor

Zhiting Hu is an Assistant Professor in Halicioglu Data Science Institute at UC San Diego. He received his Bachelor’s degree in Computer Science from Peking University in 2014, and his Ph.D. in Machine Learning from Carnegie Mellon University in 2020. His research interests lie in the broad area of machine learning, natural language processing, ML systems, healthcare and other application domains. In particular, He is interested in principles, methodologies, and systems of training AI agents with all types of experiences (data, knowledge, rewards, adversaries, lifelong interplay, etc). His research was recognized with best demo nomination at ACL2019 and outstanding paper award at ACL2016.

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Arun Kumar
Assistant Professor, HDSI Faculty Fellow

Kumar is a member of the Database Lab and Center for Networked Systems and an affiliate member of the AI Group, specializing in artificial intelligence. Systems and ideas based on his research have been released as part of the MADlib open-source library, shipped as part of products from EMC, Oracle, Cloudera, and IBM, and used internally by Facebook, LogicBlox, Microsoft, and other companies. His current work focuses on simplifying and accelerating the processes of data preparation, model selection, and model deployment – complementing his primary research interests in data management and software systems for machine learning/artificial intelligence-based data analytics.

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Babak Salimi
Assistant Professor

Babak Salimi is an assistant professor in HDSI at UC San Diego. Before joining UC San Diego, he was a postdoctoral research associate in the Department of Computer Science and Engineering, University of Washington where he worked with Prof. Dan Suciu and the database group. He received his Ph.D. from the School of Computer Science at Carleton University, advised by Prof. Leopoldo Bertossi.  His research seeks to unify techniques from theoretical data management, causal inference and machine learning to develop a new generation of decision-support systems that help people with heterogeneous background to interpret data. His ongoing work in causal relational learning aims to develop the necessary conceptual foundations to make causal inference from complex relational data. Further, his research in the area of responsible data science develops needed foundations for ensuring fairness and accountability in the era of data-driven decisions. His research contributions have been recognized with a Research Highlight Award in ACM SIGMOD, a Best Demonstration Paper Award at VLDB and a Best Paper Award in ACM SIGMOD.

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Jingbo Shang
Assistant Professor

Jingbo Shang is an Assistant Professor in CSE and HDSI at UC San Diego. He obtained his Ph.D. from CS@UIUC. He received his B.E. from Shanghai Jiao Tong University, China. He is broadly interested in data mining, natural language processing, and machine learning. His research about mining and constructing structured knowledge from massive text corpora with minimum human effort has been recognized by many prestigious awards, including the Grand Prize of Yelp Dataset Challenge in 2015 and Google Ph.D. Fellowship in Structured Data and Database Management in 2017.

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Frank Wuerthwein
Professor

Wuerthwein is the Distributed High-Throughput Computing Lead at San Diego Supercomputer Center and executive director of the Open Science Grid (OSG), a national cyberinfrastructure to advance the sharing of resources, software and knowledge. His research focuses on distributed high-throughput computing with large data volumes. His research in experimental particle physics research includes searching for new phenomena at the high-energy frontier with the CMS detector (Compact Muon Solenoid) at the Large Hadron Collider at CERN in Geneva. He worked on the team that discovered the Higgs Boson, popularly known as the God particle.