Co-Directors
Alin Deutsch
Co-Director
Professor
Computer Science & Engineering
Jacobs School of Engineering
University of California, San Diego
Dr. Alin Deutsch is interested in XML databases and XML query languages. He received his Ph.D. in computer science from the University of Pennsylvania in 2002. He received his M.S. in computer science from the Technical University of Darmstadt (Germany) in 1995 and his B.S. in computer engineering from the Bucharest Polytechnic University (Romania) in 1993 - graduating with honors from each institution. During his doctoral studies at the University of Pennsylvania, Deutsch worked as an intern at the AT&T Research Labs and Texas Instruments. As a teaching assistant at the University of Pennsylvania, he taught Java programming techniques and a tutorial on XML technologies. Due to his extensive experience, he is able to provide an effective mix of high-level technical detail and real-world interpretations - enabling him to interact with a wide variety of audiences. Deutsch's entrepreneurial skills have led to a patent in 2000 based on query optimization.
Ilkay Altintas de Callafon
Co-Director
Chief Data Science Officer
San Diego Supercomputer Center
University of California, San Diego
Dr. Ilkay Altintas is the Chief Data Science Officer at the San Diego Supercomputer Center (SDSC), UC San Diego, where she is also the Founder and Director for the Workflows for Data Science Center of Excellence. Since joining SDSC in 2001, she has worked on different aspects of scientific workflows as a principal investigator and in other leadership roles across a wide range of cross-disciplinary NSF, DOE, NIH and Moore Foundation projects. She is a co-initiator of and an active contributor to the popular open-source Kepler Scientific Workflow System, and the co-author of publications related to computational data science and e-Sciences at the intersection of scientific workflows, provenance, distributed computing, bioinformatics, observatory systems, conceptual data querying, and software modeling. Ilkay is the recipient of the first SDSC Pi Person of the Year in 2014, and the IEEE TCSC Award for Excellence in Scalable Computing for Early Career Researchers in 2015.
Faculty, Lecturers, and Visiting Faculty
Mai H. Nguyen
Lead for Data Analytics
San Diego Supercomputer Center
Lecturer
Computer Science & Engineering
Jacobs School of Engineering
University of California, San Diego
Dr. Mai Nguyen is the Associate Director for AI of the WIFIRE Lab and the Lead for Data Analytics at the San Diego Supercomputer Center at UC San Diego. Her research centers on applying artificial intelligence, deep/machine learning, and data science techniques to interdisciplinary problems. She has worked in many areas, including satellite image processing, medical image analysis, knowledge extraction from text, and object detection and data analysis for wildfire prevention and management. Prior to joining SDSC, she worked in industry on applications in remote sensing, image processing, speech recognition, and spacecraft autonomy. She received her M.S. and Ph.D. degrees in Computer Science from UCSD, with focus on machine learning.
Amarnath Gupta
Research Scientist
Associate Professor
Computer Science & Engineering
Jacobs School of Engineering
University of California, San Diego
Dr. Amarnath Gupta received his Ph.D. in Computer Science from Jadavpur University in India. He is currently a full Research Scientist at the San Diego Supercomputer Center of UC San Diego, and directs the Advanced Query Processing Lab. His primary areas of research include semantic information integration, large-scale graph databases, ontology management, event data management and query processing techniques. Before joining UC San Diego, he was the Chief Scientist at Virage, Inc., a startup company in multimedia information systems. Dr. Gupta has authored over 100 papers and a book on Event Modeling, holds 13 patents and is a recipient of the 2011 ACM Distinguished Scientist award.
Sanjoy Dasgupta
Lecturer
Computer Science & Engineering
Jacobs School of Engineering
University of California, San Diego
Dr. Sanjoy Dasgupta develops algorithms for the statistical analysis of high-dimensional data. Such data is now widespread, in domains ranging from environmental modeling to genomics to web search. The geometry of high-dimensional spaces presents unusual challenges; many traditional statistical procedures were developed with one- or two-dimensional data in mind and do not scale well to this modern context. Some of them are very inefficient; others give poor results because of counter-intuitive effects in high dimension. Dasgupta has developed the first provably correct, efficient algorithms for a variety of canonical statistical tasks, especially related to clustering (grouping) data. He is one of the few machine learning researchers whose work combines algorithmic theory with geometry and mathematical statistics. He adds a strong theoretical focus to UCSD's CSE artificial intelligence and bioinformatics groups. Prior to joining the UCSD Jacobs School in 2002, Sanjoy Dasgupta was a senior member of the technical staff at AT&T Labs-Research, where his work focused on algorithms for data mining, with applications to speech recognition and to the analysis of business data. Prof Dasgupta received a Ph.D. in Computer Science in 2000 from UC Berkeley and a B.A. in Computer Science from Harvard in 1993. He is a member of the editorial boards of the Journal of Machine Learning Research, the Journal of Artificial Intelligence Research, and the Machine Learning Journal.
Amit Chourasia
Sr. Visualization Scientist
San Diego Supercomputer Center
Lecturer
Computer Science & Engineering
Jacobs School of Engineering
University of California, San Diego
Amit Chourasia is a Sr. Visualization Scientist at the San Diego Supercomputer Center, UC San Diego where he leads the Visualization Group. His work is focused on leading the research, development and application of software tools and techniques for visualization. Key area of his work is to develop methods to represent data in a visual form that is clear, succinct and accurate (a challenging yet very exciting endeavor). He has had an opportunity to work with research groups in diverse science and engineering disciplines and contends that with the help of visualization, domain and data scientists can visually validate and investigate their data, explore and gain significant insights as well as share results within and outside their community.