Person

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Rod Albuyeh
Lecturer

Albuyeh is Principal Data Scientist at Figure and part-time lecturer at the Halıcıoğlu Data Science Institute at UC San Diego.  He received his Ph.D. in Political Science at USC in 2016.  His specialties lie in anomaly detection for tabular time-series data and machine learning systems–with applications in marketing, fraud, and credit risk.  He is also interested in applying enterprise machine learning approaches to solve problems in the social sciences.

Research Interests: Machine Learning, Deployment, Scalable Systems

Categories: Faculty, Lecturers
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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.
Photo of Mikio Aoi
Mikio Aoi
Assistant Professor

Dr. Aoi is a computational neuroscientist interested in studying how populations of neurons coordinate their activity to perform computations. In particular, his interests are in understanding how the dynamics of neural computations impact behavior and in developing principled approaches to data analysis in close collaboration with experimentalists.

Before pursuing an interest in neuroscience he earned a bachelor’s degree in Kinesiology from California State University, Long Beach and a PhD in Mathematical Biology from North Carolina State University studying the dynamics of cerebrovascular function in stroke patients.  As postdoctoral associate in the Department of Mathematics at Boston University he developed statistical methods for characterizing rhythmic synchrony in neuronal populations. He then moved to Princeton University, where he continued his postdoctoral training with Jonathan Pillow, developing scalable methods for analyzing high dimensional datasets of neuronal activity in animals performing perceptual decision making tasks.

As a native of Southern California, Dr. Aoi is thrilled to return to California to join the outstanding students and faculty at UCSD in the Halıcıoğlu Data Science Institute and The Department of Neurobiology – Division of Biology.

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Bijan Arbab
Industry Fellow Intel

Bijan Arbab is the Director of Telemetry and Data Science at Intel Corporation. As an Industry Fellow Dr. Arbab is making impactful contributions to HDSI and the data science community at UC San Diego. In addition to enabling a significant data sharing agreement between Intel and the University that has become the foundation for successful collaborations between faculty and industry practitioners, he is also actively engaged in the mentorship of our data science students through the senior capstone program and undergraduate research projects.

Categories: Industry Fellows
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Ery Arias-Castro
Professor

Ery Arias-Castro received his Ph.D. in Statistics from Stanford University in 2004. He then took a postdoctoral position at the Institute for Pure and Applied Mathematics (IPAM), where he participated in the program on Multiscale Geometry and Analysis in High Dimensions. After that, he took a postdoctoral position at the Mathematical Sciences Research Institute (MSRI), where he participated in the program on  Mathematical, Computational and Statistical Aspects of Image Analysis. He joined the faculty in the mathematics department at UCSD in 2005.  His research interests are in high-dimensional statistics, machine learning, spatial statistics, image processing, and applied probability.

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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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Jelena Bradic
Professor

Bradic is an Associate Professor of Statistics, and winner of multiple teaching awards. She directs the Statistical Lab for Learning Large-Scale and Complex Data. Her interests include ensemble learning, robust statistics and survival analysis. Her application areas include gene-knockout experiments, understanding cell cycles, developing new policies or detecting effects of treatments onto survival, Her research also reaches into the area of causal inference and developing new learning algorithms that can make new scientific discoveries but also quantify uncertainty with which these discoveries are being made. Her multidisciplinary expertise in handling data has expanded her research into multidisciplinary fields that include political science, marketing, engineering, public health as well as biomedical sciences.

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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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Alex Cloninger
Assistant Professor

Alex Cloninger is an Assistant Professor in Mathematics and the Halıcıoğlu Data Science Institute at UC San Diego. He received his PhD in Applied Mathematics and Scientific Computation from the University of Maryland in 2014, and was then an NSF Postdoc and Gibbs Assistant Professor of Mathematics at Yale University until 2017, when he joined UCSD.  Alex researches problems in the area of geometric data analysis and applied harmonic analysis.  He focuses on approaches that model the data as being locally lower dimensional, including data concentrated near manifolds or subspaces.    The techniques developed have led to research in a number of machine learning and statistical algorithms, including deep learning, network analysis, signal processing, and measuring distances between probability distributions.  This has also led to collaborations on problems in several scientific disciplines, including imaging, medicine, and artificial intelligence.

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David Danks

Professor Danks conducts research at the intersection of machine learning, philosophy, and cognitive science. He examines the ethical, psychological, and policy issues around AI and robotics across a range of sectors. He has also developed multiple novel causal discovery algorithms for complex types of observational and experimental data, and done significant research in computational cognitive science

Danks received an A.B. in Philosophy from Princeton University, and a Ph.D. in Philosophy from University of California, San Diego. He is the recipient of a James S. McDonnell Foundation Scholar Award, as well as an Andrew Carnegie Fellowship.

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Whitney Davis
Undergraduate Intake Advisor

Whitney (she/her/hers) joined the Halıcıoğlu Data Science Institute in February 2020 and is still in her current role as the DSC Intake Advisor. Whitney received her B.A. in Liberal Studies from San Diego State University. She loves helping others, and enjoys working with students and faculty members within the growing field of Data Science!

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Virginia de Sa
Professor, HDSI Associate Director Cognitive Science

Associate Director de Sa is a leader in the fields of cognitive science, neuroscience, computer science, engineering, and data science. Her research utilizes multiple approaches to increase our understanding of  how humans and machines learn to perceive the world around them.

She earned her Ph.D. and master’s in Computer Science from the University of Rochester, and a bachelor’s degree in Mathematics and Engineering from Canada’s Queen’s University.

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Justin Eldridge
Assistant Teaching Professor

Justin Eldridge is an assistant teaching professor in HDSI. He obtained his PhD in computer science at The Ohio State University as a Presidential Fellow, along with BS degrees in physics and applied math. His research focus lies in statistical machine learning theory, with an emphasis on unsupervised learning and clustering in particular. His research while a PhD student received the best student paper award at COLT 2015 and a full oral presentation at NeurIPS 2016. Justin joined HDSI in 2018, where he develops and teaches courses in both the theoretical and practical foundations of data science and machine learning.

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Shannon Ellis
Assistant Teaching Professor

Shannon Ellis is an Assistant Teaching Professor in Cognitive Science and HDSI at UC San Diego. She obtained her Ph.D. in Human Genetics from Johns Hopkins School of Medicine. Her primary focus at UC San Diego is to foster and promote data science education. To this end, she teaches undergraduate programming and data science courses and pursues projects that help provide access and educational materials to individuals who have historically lacked access to an education in data science.

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Jeff Elman
Founding Co-Director

Dr. Elman left a legacy from his pioneering work in artificial neural networks, and as an internationally recognized scholar in the field of language processing and learning. His early TRACE model of speech perception, with Jay McClelland, remains one of the major theories in the field. In 1990, he developed the Simple Recurrent Network architecture (the so-called “Elman net”) that is today widely used in many fields to model behaviors that unfold over time. In his last research, he used a wide range of scientific methods, including computational simulations, neuroimaging, and behavioral measures. Elman earned his bachelor’s degree in social relations from Harvard and his Ph.D. in linguistics from the University of Texas at Austin. A member of the UC San Diego faculty since 1977, Elman was a founding member of the Department of Cognitive Science, the first of its kind in the world, as well as founding director of the Center for Research in Language. He was founding co-director of the university’s Kavli Institute for Brain and Mind. He served as dean of the Division of Social Sciences from 2006 – 2014. Among his honors is the prestigious David E. Rumelhart Prize, which he received in 2007 in recognition of his groundbreaking contributions to the theoretical foundations of cognitive science. Elman was elected a Member of the American Academy of Arts and Sciences in 2016.

The Cognitive Society established Jeffrey L. Elman Prize in his honor in 2020.

Categories: In Memoriam
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James Fowler
Professor
Professor Fowler’s work lies at the intersection of the natural and social sciences, with a focus on social networks, behavior, evolution, politics, genetics, and big data.  He is a founding faculty member of HDSI, and author of the international best-selling book Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives.
Fowler has been named a Fellow of the John Simon Guggenheim Foundation, one of Foreign Policy’s Top 100 Global Thinkers, TechCrunch’s Top 20 Most Innovative People, Politico’s 50 Key Thinkers, Doers, and Dreamers, and Most Original Thinker of the year by The McLaughlin Group.
Categories: Uncategorized
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Aaron Fraenkel
Assistant Teaching Professor

Fraenkel uses machine learning and experimental design to study large-scale abusive behaviors on the internet, particularly events driven by robots (known as bots). His teaching expertise is in the end-to-end practice of data science, drawing from his industry experience with cybersecurity, anti-fraud, and anti-abuse systems. He is one of the leaders developing and teaching the university’s foundational data science curriculum and major program overseen the Halıcıoğlu Data Science Institute.

Before joining UC San Diego in 2018, Fraenkel worked as a senior scientist at Amazon, with a focus on machine learning. Having worked as a data scientist at work in industry, he chose to return to academia and work at the root of instruction, helping shape student learning and critical thinking.

He earned his Ph.D. and undergraduate degrees in mathematics from UC Berkeley, and worked in postdoctoral faculty appointments in mathematics at Boston College and Pennsylvania State University. At HDSI, his curriculum development of the path-breaking data science program includes creating projects using real-world datasets and challenges.

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Rebecca Fraenkel
Post-Doctoral Fellow

Becky Fraenkel received her PhD in Economics from UCSD in 2020. Her research focuses on the provision of local public goods and the effects of environmental pollutants. She studies how these forces shape communities through property taxation, education, housing, and energy generation. Her research uses causal inference and machine learning to answer economic and policy-relevant questions in complex data.

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Yoav Freund
Professor

Freund works on applications of machine learning algorithms in bioinformatics, computer vision, finance, network routing and high-performance computing. His current research focuses on machine learning to develop and analyze adaptive algorithms that change their behavior by learning from examples, rather than by re-programming.

He served as a senior research scientist at Columbia University in computational learning systems, and in machine learning development for AT&T Labs (formerly Bell Labs).

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R Stuart Geiger
Assistant Professor

Geiger studies the relationships between science, technology, and society — not only how science and technology have substantial impacts on society, but also how they are social institutions in themselves. He studies issues of fairness, accountability, transparency, responsibility, and contestability in machine learning, particularly in online content moderation. He has examined how values and biases are embedded in these technologies and how communities make decisions about how to use or not use them. Geiger also studies the development of data science as an academic and professional field, as well as the sustainability of free/open-source software and scientific cyberinfrastructure projects.

Geiger earned his Ph.D in 2015 at the UC Berkeley School of Information and the Berkeley Center for New Media, then was the staff ethnographer at the UC Berkeley Institute for Data Science. He joined UCSD in 2020, jointly appointed as faculty in the Department of Communication. Geiger is a methodological and disciplinary pluralist who collaborates across many different ways of knowing, but his work is often grounded in the fields of communication & media studies, science & technology studies, cultural anthropology, organizational sociology, human-computer interaction, and history and philosophy of science.

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Avishek Ghosh
Post-Doctoral Fellow

Avishek Ghosh is an HDSI (Data Science) Post-doctoral fellow at the University of California, San Diego. Prior to this, he completed his PhD from the Electrical Engg. and Computer Sciences (EECS) department of UC Berkeley, advised by Prof. Kannan Ramchandran and Prof. Aditya Guntuboyina. His research interests are broadly in Theoretical Machine Learning, including Federated Learning and multi-agent Reinforcement/Bandit Learning. In particular, Avishek is interested in theoretically understanding challenges in multi-agent systems, and competition/collaboration across agents. Before coming to Berkeley, Avishek completed his masters degree from Indian Institute of Science (IISc), Bangalore (in the Electrical Communication Engg. Dept) and prior to that, he completed his  bachelors degree from Jadavpur University, in the dept. of Electronics and Telecommunication Engineering.

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Bobby Gordon
Marketing & Communications Director

Bobby serves as the Institute’s Marketing & Communications Strategist. Before joining UC San Diego, he served higher education in a variety of marketing and strategic administrative roles at Arizona State University, University of Arizona, University of Akron, Kent State University and University of Phoenix. He serves as a professional consultant and volunteer in higher education and non-profit sectors, and also is a professional speaker. He earned his MBA from University of Arizona and his BA from Muskingum University.

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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.

Categories: Uncategorized
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Brittany Hewitt
Academic Personnel Manager

Brittany Hewitt is currently our Academic Personnel Analyst for Halıcıoğlu Data Science Institute (HDSI). Prior, Brittany worked as an Academic Personnel Analyst at the Academic Resource Center (ARC), at UC San Diego School of Medicine.

Her passion for connectivity and communication gives her the ability to understand organizational needs as well as individual needs and partner with each to meet and exceed their expectations. She prides herself on the ability to establish relationships and communicate effectively and efficiently with all business partners.

Categories: Executive Office, Staff
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Kyle Hofer-Mora
Assistant Director for External Relations and Strategic Initiatives

Kyle Hofer-Mora serves as Assistant Director for External Relations and Strategic Initiatives at Halıcıoğlu Data Science Institute (HDSI).  In this capacity, Kyle works with a talented team focused on industry partnerships, as well as with faculty members, to strategically grow new graduate and professional programs.  He is responsible for the development and implementation of strategies to promote and expand HDSI’s program offerings and overall reach.

Kyle joins HDSI after four years as the Director of Business Analytics Graduate Programs at California Polytechnic State University, where he was instrumental in the launch and growth of a master’s program in business analytics, as well as professional certificates offered through a partnership between the College of Business and Extended Education.   With responsibilities that included working with industry partners for student projects, organizing data analytics symposia, leading the Business Analytics Advisory Board, and serving as a member of the campus-wide Data Science Task Force,  Kyle has formulated ways to ensure program offerings stay at the forefront of trends in this emerging and dynamic field and continue to meet the needs of the marketplace.

The bridge between academia and industry is a space in which Kyle is quite comfortable, having 10 years of experience in the financial services industry prior to joining the university setting.  He holds an MBA in Global Business from Pepperdine University and a B.A. in Finance from CSU Fullerton.

 

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Mike Holst
Professor

Holst is a leader in the Mathematical and Computational Physics Research Group, the Center for Computational Mathematics, and the Center for Astrophysics and Space Sciences. His interdisciplinary work at the university reaches into the fields of biochemistry and biophysics, computational fluid dynamics, computer graphics, materials science, and numerical algorithms relativity. A century after Einstein predicted the existence of gravitational waves, he has been part of a $600 million National Science Foundation collaboration working on detecting them.

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Albert Hsiao
Associate Professor

Albert Hsiao, MD, PhD is a cardiothoracic radiologist trained in engineering at Caltech and bioengineering and bioinformatics in the UC San Diego Medical Scientist Training Program (MSTP). He completed his residency and fellowships in Interventional Radiology and Cardiovascular Imaging at Stanford before returning to UC San Diego as faculty in Radiology, where he leads advanced cardiovascular imaging and the Augmented Imaging and Data Analytics (AiDA) research laboratory.  He also serves as co-director of the T32 clinician-scientist radiology research residency program and co-director of the MSTP SURF program. While a radiology resident himself at Stanford, he co-founded Arterys, a cloud-native software company to bring 4D Flow MRI and artificial intelligence technologies to market. He continues to partner with industry to develop and bring new imaging technologies to market to improve diagnosis and management of disease.

Website: https://profiles.ucsd.edu/albert.hsiao

Categories: Faculty Council
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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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Clarence Ip
Student Videographer

Clarence is the Halıcıoğlu Data Science Institute’s Video and Production Assistant. Before joining HDSI, he served the role as videographer and media producer for media crews and photography teams in New York and Hong Kong. He is currently studying at UC San Diego with the goal of earning a BA degree in International Studies.

Categories: Communications, Staff
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Tara Javidi
Professor, HDSI Faculty Fellow

Javidi founded and co-directs the Center for Machine-Integrated Computing and Security at UC San Diego. Among her projects is DetecDrone Target Search Technology, what she calls drones that think. Her research focus is on stochastic analysis, design, and control of information collection, processing, and transfer in modern communication and networked systems. Interests include: Information acquisition and utilization (such as active hypothesis testing and variable length coding over channels with feedback); optimal routing in wireless mesh networks; cognitive and delay-sensitive communications and networking; and communications under application and/or secrecy constraints. Her work includes the applications of microeconomic theory and organizational science to the design of wireless networks.

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Young-Han Kim
Professor

Kim primarily works on two important challenges for high-speed, high-volume information processing systems — how to describe information efficiently, and how to transmit it reliably in the presence of noise and interference. He is a co-author of the textbook, Network Information Theory. Kim earned his bachelor’s degree with honors in electrical engineering from Seoul National University, receiving a GE Foundation Scholarship. Kim has served as a distinguished lecturer for the IEEE Information Theory Society, and as Associate Editor for the IEEE Transactions on Information Theory. He is a Fellow of the IEEE.

Categories: Faculty Council
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Rob Knight
Founding Director, Center for Microbiome Innovation; Professor, Pediatrics and Computer Science & Engineering

Rob Knight is the founding Director of the Center for Microbiome Innovation and Professor of Pediatrics, Bioengineering, and Computer Science & Engineering at UC San Diego. He was honored with the 2019 NIH Director’s Pioneer Award for his microbiome research and received the 2017 Massry Prize, often considered a predictor of the Nobel. His work has linked microbes to a range of health conditions including obesity and inflammatory bowel disease, has enhanced our understanding of microbes in environments ranging from the oceans to the tundra, and made high-throughput sequencing techniques accessible to thousands of researchers around the world. Dr. Knight can be followed on Twitter (@knightlabnews) or on his web site http://knightlab.ucsd.edu/.

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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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Stephanie Labou
Data Science Librarian

Stephanie Labou is the Data Science Librarian with the UC San Diego Library. Stephanie provides user assistance with datasets and data analysis through general reference, in-person consultations, and collection development of licensed and open access data. She also co-manages the library’s Data & GIS Lab, which supports the full data lifecycle of quantitative, qualitative, and geospatial data-intensive research at UC San Diego. Additionally, Stephanie provides instruction and short-form workshops on coding skills and best practices, including the popular Software and Data Carpentry workshops.

Marina Langlois
Teaching Professor
Categories: Teaching Faculty
Dean Lee
Industry Fellow NIWC Pacific

Dean Lee’s research is focused on finding and bounding the limitations of such datasets and whether they are sufficient for machine learning algorithms in their current state, and if not, defining a set of conditions so that data generated in future platforms can be used to extract actionable insights.

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Matthew Levy
Industry Fellow NIWC Pacific

Dr. Levy’s goal is helping find answers for projects fulfilling the needs of the U.S. Navy and learning more about the latest data science tools to bring back to NIWC. Since starting in Spring 2019, he’s been working on problems within the cybersecurity domain specifically analyzing how hackers behave in cyberspace, what they do when faced with deception and deterrent mechanisms, and the efficacy of the deception mechanisms themselves.

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Meredith Longo
Program Coordinator & Undergraduate Student Advisor Student Affairs

My name is Meredith Longo, one of the program coordinators and undergraduate student advisors at HDSI. I formerly worked as a student services advisor at UCSC in the Baskin School of Engineering, and was a high school math teacher. I also earned my B.A. in Math/Secondary Education and M.Ed. at UCSD. My favorite things in life are my husband, everything Disney, and anime! My goal is to connect with students on a personal and professional level to best prepare them to excel in the growing field of Data Science.

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Yian Ma
Assistant Professor

Yian Ma works on scalable inference methods and their theoretical guarantees, with a focus on time series data and sequential decision making. He has been developing new Bayesian inference algorithms for uncertainty quantification as well as deriving computational and statistical guarantees for them.

Prior to his appointment at UCSD, he worked as a post-doctoral fellow at UC Berkeley. He obtained his Ph.D. degree at University of Washington and his bachelor’s degree at Shanghai Jiao Tong University.

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Ray Major
Industry Fellow SANDAG

Ray Major serves as a Chief Analytics Officer for San Diego Association of Governments (SANDAG) and is currently leading efforts within SANDAG to become more data-driven and using data information to support decision-making and future planning efforts. During his 2-year term as an Industry Fellow, Major’s role will be important in forging important connections between the institute and data science-related industry in the goal of strengthening the data science ecosystem within San Diego.

Categories: Industry Fellows
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Arya Mazumdar
Associate Professor

Arya Mazumdar obtained his Ph.D. degree from University of Maryland, College Park (2011) specializing in information theory. Subsequently Arya was a postdoctoral scholar at Massachusetts Institute of Technology (2011-2012), an assistant professor in University of Minnesota (2013-2015), and an assistant followed by associate professor in University of Massachusetts Amherst (2015-2021). Arya is a recipient of multiple awards, including a Distinguished Dissertation Award for his Ph.D. thesis (2011), the NSF CAREER award (2015), an EURASIP JSAP Best Paper Award (2020), and the IEEE ISIT Jack K. Wolf Student Paper Award (2010). He is currently serving as an Associate Editor for the IEEE Transactions on Information Theory and as an Area editor for Now Publishers Foundation and Trends in Communication and Information Theory series. Arya’s research interests include coding theory (error-correcting codes and related combinatorics), information theory, statistical learning and distributed optimization.

Post-Doctoral Fellow: Avishek Ghosh

 

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Julian McAuley
Assistant Professor

McAuley is an assistant professor in CSE. His research focuses on the linguistic, temporal, and social dimensions of opinions and behavior in social networks and other online communities. He has harnessed data science tools to increase understanding the facets of people’s opinions, the processes that lead people to acquire taste for gourmet foods and beers, and even the visual dimensions of how they make fashion choices. He has gained academic, industry and media attention for his work analyzing massive volumes of user data from online social communities including Amazon, Yelp, Facebook and BeerAdvocate. His work includes using artificial intelligence in fashion choice, and data science in developing models that generate step-charts for the globally popular videogame, Dance Dance Revolution.

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Gal Mishne
Assistant Professor

Mishne’s research is at the intersection of signal processing and machine learning for graph-based modeling, processing and analysis of large-scale high-dimensional real-world data. She develops unsupervised and generalizable methods that allow the data to reveal its own story in an unbiased manner. Her research includes anomaly detection and clustering in remote sensing imagery, manifold learning on multiway data tensors with biomedical applications, and computationally efficient application of spectral methods. Most recently her research has focused on unsupervised data analysis in neuroscience, from processing of raw neuroimaging data through discovery of neural manifolds to visualization of learning in neural networks.

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Erik Mjoen
Industry Relations Manager

As Industry Relations Manager, Erik focuses on building partnerships and collaboration between industry and the Halıcıoğlu Data Science Institute, with an emphasis on Research & Innovation, Recruitment, Continued Learning, and Leadership.

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Jennifer Morgan
Chief Administrative Officer
Categories: Leadership, Staff
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Eran Mukamel
Assistant Professor

Mukamel is a computational neuroscientist focusing on modeling and analysis of large-scale data sets to understand complex biological networks of the brain. He uses large-scale genomic and epigenomic datasets to study how brain cells develop, and adapt throughout the lifespan.

He earned his physics Ph.D. from Stanford University, and his bachelor’s and master’s degrees in physics and mathematics from Harvard University, where he followed with a postdoctoral fellowship in theoretical neuroscience.

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Keith Muller
UC San Diego & Teradata

Dr. Keith Muller is an Adjunct Professor in Computer Science and Engineering at the University of California, San Diego. He is recently retired from Teradata where he served as a Senior Fellow and CTO and has worked on finding data sets and problems for HDSI undergraduate students that are representative of what they will encounter in industry and offer a rich breadth of opportunity to experience the practice of creativity in data science.

Categories: Industry Fellows
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Saura Naderi
K-14 Outreach Director

Saura Naderi ‘07 earned her engineering degree from UC San Diego Jacobs School just as the recession hit. Not satisfied by the opportunities available to her, she created her own. She volunteered, later becoming an employee, to create a program at UC San Diego where undergraduates and K-12 students could play and explore science and technology with art-themed engineering-based projects. After receiving the exemplary employee award at UC San Diego and the Athena Pinnacle award and invited to do a TEDx talk, she was recruited by Qualcomm to create a similar program named – Thinkabit Lab. Upon leaving Qualcomm, Thinkabit Lab engaged 14,000+ middle school students and has been replicated in many different environments from libraries and schools to universities and companies. Saura was also a contestant on SyFy’s Robot Combat League, was an “Adventure Person” on Nerdist, and is the color commentator for the world’s first giant robot fight held in Japan. One of the creative projects she is most proud of is envisioning, and leading a team of engineers and artists to create, a robotic dress that hugs people. Saura is leading efforts to broaden participation in Data Science by designing creative ways to engage a diverse population.

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Preetum Nakkiran
Post-Doctoral Fellow

Preetum Nakkiran is a postdoc at UCSD, in Misha Belkin’s group.

He obtained his PhD in the CS Theory group at Harvard, advised by Boaz Barak and Madhu Sudan. He did his undergraduate work in EECS at UC Berkeley.

He works on the empirical theory of machine learning: aiming to discover and characterize empirical behaviors, if not prove them formally. His past work includes understanding generalization in deep learning, robustness, double-descent, and overparameterization.

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Sonlong Nguyen
Program Coordinator & Undergraduate Advisor Student Affairs

Sonlong is a Program Coordinator and Undergraduate Student Advisor at HDSI. Previously, Sonlong has served as a coordinator and academic advisor at Thurgood Marshall College and Eleanor Roosevelt College at UCSD. He is also an alum of UCSD where he received a BA in Urban Studies & Planning before going on to SDSU to receive his MA in Postsecondary Educational Leadership.

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Lucila Ohno-Machado
Professor

Ohno-Machado, MD, PhD, focuses on making health data more accessible and usable, so patients and clinicians can make better informed, evidenced-based health decisions together. She is a founding faculty member of HDSI. She was the founding chair UC-wide initiative that allows researchers to search more than 15 million de-identified patient records from the five largest UC health systems with one query.

Madhusudan Parthasarathy
Visiting Scholar
Categories: Visiting Scholar
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Michael Pazzani
Distinguished Researcher

Michael Pazzani is a Distinguished Scientist at the Halıcıoğlu Data Science Institute at University of California, San Diego.  He conducts research in machine learning, explainable artificial intelligence, personalization, internet search, and recommendation systems.

Prior to UCSD, Dr. Pazzani was the Vice Chancellor for Research and Economic Development at University of California, Riverside where he was also a professor of computer science with additional appointments in statistics and psychology.

He received his Ph.D. in Computer Science from UCLA and was an assistant, associate and full professor at the University of California, Irvine, where he also served as Chair of Information and Computer Science.

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Dimitris Politis
Distinguished Professor, HDSI Associate Director

Associate Director Politis is an internationally known scholar in mathematics and economics, working on time series, bootstrap methods, and nonparametric estimation, and a researcher with authorship of more than 100 journal papers and monographs.

Politis earned his Ph.D. in statistics from Stanford University, and dual masters’ degrees from Stanford in statistics and mathematics. He also holds a master’s degree from Rensselaer Polytechnic Institute in computer and systems engineering, and his bachelor of science degree in electrical engineering from University of Patras in Greece.

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Suraj Rampure
Lecturer

Suraj Rampure is a Lecturer in the Halıcıoğlu Data Science Institute at UC San Diego. He received his BS and MS in Electrical Engineering and Computer Sciences from UC Berkeley in 2020 and 2021, respectively.

While at Berkeley, he helped create and teach multiple undergraduate computer science and data science courses, including the core upper-division course for data science majors and an introductory programming course for non-majors. There, he was the recipient of multiple teaching awards, including the departmental Distinguished Graduate Student Instructor Award in 2020 and the campus Extraordinary Teaching in Extraordinary Times award in 2021.

At UC San Diego, he will focus on the undergraduate experience for data science students and will be involved in data science education research.

For more information, see http://rampure.org.

Categories: Faculty, Lecturers
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Finn Reid
Student Graphic Designer
Categories: Communications, Staff
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Margaret “Molly” Roberts
Associate Professor

Roberts research lies at the intersection of political methodology and the politics of information, with a focus on methods of automated content analysis and the politics of censorship in China.  Roberts co-directs the China Data Lab, which is part of the 21st Century China Center at the School for Global Policy and Strategy.

She earned her Ph.D. in government from Harvard, and both her master’s in statistics and bachelor’s in international relations and economics from Stanford. She joined UC San Diego in 2014. Her recent book, Censored: Distraction and Diversion Inside China’s Great Firewall, was published in 2018 by Princeton University Press.

Post-Doctoral Fellow: Rebecca Fraenkel

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Rayan Saab
Associate Professor

Rayan’s work is on the mathematics of information, data, and signals. His research is broadly motivated by problems in the acquisition, digitization, and processing of data. For example, he is interested in sampling and quantization, compressed sensing, sparse  and low-dimensional representations of data, as well as inverse problems like phase retrieval and blind source separation.

Before joining UCSD as an assistant professor in 2013, he was a visiting assistant professor and a Banting postdoctoral fellow at Duke University (2011-2013). Before that, he completed his PhD at the University of British Columbia in 2010, where he was a member of the Institute of Applied Mathematics.

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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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Armin Schwartzman
Professor

Armin Schwartzman’s research encompasses theoretical and practical aspects of statistical signal and image analysis in a variety of scientific applications. These include spatio-temporal and high-dimensional data analysis, geometric statistics and smooth Gaussian random fields, with applications in biomedicine, the environment, neuroscience, genetics and cosmology.

Armin Schwartzman received his bachelor’s and master’s degrees in electrical engineering from the Technion – Israel Institute of Technology and the California Institute of Technology; and his PhD in Statistics from Stanford University. He was an R&D engineer at Rockwell Semiconductor and Biosense Webster, and has held faculty positions in Biostatistics at Harvard University and Statistics at North Carolina State University.

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Terry Sejnowski
Co Dir/INC

Terry Sejnowski received his Ph.D. in physics from Princeton University. He was a postdoctoral fellow in the Department of Neurobiology at Harvard Medical School before joining the faculty at Johns Hopkins, where he was a Professor of Biophysics.   He currently holds the Francis Crick Chair at The Salk Institute for Biological Studies, and is a Distinguished Professor of Biology and Computer Science and Engineering at the University of California, San Diego, where he is co-director of the Institute for Neural Computation.  He also is the founding editor-in-chief of Neural Computation.  His book on “The Computational Brain” introduced distributed representations in neural networks to a generation of neuroscientists.

Categories: Faculty Council
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Parth Shah
Web Administrator
Categories: Communications, Staff
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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.

Elina Shankar
Student Graphic Designer

Elina Shankar is the Halıcıoğlu Data Science Institute’s Graphic Designer. Before joining HDSI, she served as a graphic designer for the Massachusetts Department of Elementary and Secondary Education. She is currently studying at UC San Diego with the goal of earning a BS degree in Cognitive Science with a Specialization in Design and Interaction.

Categories: Communications, Staff
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Benjamin Smarr
Assistant Professor

Benjamin Smarr is an assistant professor at the Halicioğlu Data Science Institute and the Department of Bioengineering at the University of California, San Diego. As an NIH fellow at UC Berkeley he developed techniques for extracting health and performance predictors from repeated, longitudinal physiological measurements. Historically his work has focused on neuroendocrine control and women’s health, including demonstrations of pregnancy detection and outcome prediction, neural control of ovulation, and the importance of circadian rhythms in healthy in utero development. Pursuing these and other projects he has won many awards from NSF, NIH, and private organizations, and has founded relationships with patient communities such as Quantified Self. With the COVID-19 pandemic, he became the technical lead on TemPredict, a global collaboration combining physiological data, symptom reports, and diagnostic testing, seeking to build data models capable of early-onset detection, severity prediction, and recovery monitoring.

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Larry Smarr
Director/Professor, CSE

Professor Smarr is founding Director of the California Institute for Telecommunications and Information Technology (Calit2), a UC San Diego/UC Irvine partnership. His research includes pioneering work in advanced cyberinfrastructure and the quantified self movement. He currently serves as principal investigator on 3 National Science Foundation (NSF) grants: Pacific Research Platform, Toward a National Research Platform, and Cognitive Hardware and Software Ecosystem Community Infrastructure. His data science and cross-disciplinary scholarship and leadership are extensive, and he has held advisory positions with NASA, NSF and the National Institutes of Health. He is frequently interviewed by scientific and mainstream media, including Science, Nature, the New York Times, BBC and the Wall Street Journal

Categories: Uncategorized
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Eric Snee
Administrative Operations and Media Lead

Eric Snee is the Halıcıoğlu Data Science Institute’s Administrative Operations and Media Lead. Prior to joining HDSI in 2019, he worked as an Administrative Assistant in the Mechanical and Aerospace Engineering, Bioengineering, Athletics, and Math Departments. Before UC San Diego, Eric worked for the US Commission on International Religious Freedom in Washington, D.C.

Eric graduated from the University of Maryland, College Park in 2015 with a B.A. in Communication.

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Shankar Subramaniam
Professor

Subramaniam is the Joan and Irwin Jacobs Endowed Chair in Bioengineering and Systems Biology, and a Distinguished Scientist at the San Diego Supercomputer Center. He has served on advisory boards for several biotech and bioinformatics companies, universities, international governmental organizations, and the NIH.

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George Sugihara
Professor

Sugihara is a theoretical ecologist who has performed foundational work in the data analysis of complex systems from fisheries to medicine to finance. He gained renown for developing, with Lord Robert May, methods for forecasting chaotic systems, providing the first example of chaos in nature with the diatom populations at Scripps Pier. He has worked with the major institutions on questions of systemic risk and on detecting early warning signs of critical transitions, including the Federal Reserve Bank of New York and The Bank of England. He also worked with fisheries to develop a currently enacted market-based incentive plan for reducing wasteful bycatch and to improve forecasting of wild fish stocks. His current interest in neurobiology and genomics includes collaborations with the Salk Institute for Biological Studies to apply EDM to neurobiology and to problems in gene expression in cancer.

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Janine Tiefenbruck
Lecturer

Tiefenbruck focuses her mathematics background on developing strong foundations in the teaching of Data Science. She is a lecturer who serves as a core educator in the Data Science major and minor undergraduate education program through the Halıcıoğlu Data Science Institute. Her goal is educating students in the theoretical basis of math that will help them build a solid foundation for whatever direction they choose to take in data science, and other technology specializations. “What I like about the field of Data Science is that it’s so customizable, it’s not just: ‘Here’s a formula, plug it in.’ It’s such a broad field, it covers areas from sports to politics,” said Tiefenbruck. Her educational approach is to highlight the creative side of the academic discipline, and present students with lively projects to spark their imagination, like analyzing trends in the TV quiz show game “Jeopardy!” or predicting the genre of a song based on its lyrics.

Tiefenbruck earned her Ph.D. and master’s degrees in mathematics from UC San Diego, specializing in algebraic and enumerative combinatorics, and her bachelor’s from Loyola University, Maryland in both math and computer science. Among her academic awards include a GAANN Fellowship (federal support for scholars fulfilling a national need), a Goldwater Scholarship and a Best Teacher award from Jacobs School of Engineering. Contact: jlobue@ucsd.edu.

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Sophia Tran
Industry Relations Specialist
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Berk Ustun
Assistant Professor

Berk Ustun is an incoming Assistant Professor at the Halıcıoğlu Data Science Institute at UC San Diego. His research lies at the intersection of machine learning, optimization, and human-centered design. Specifically, he is interested in developing methods to promote the adoption and responsible use of machine learning in medicine, consumer finance, and criminal justice.

Prior to his appointment at UCSD, Ustun held research positions at Google AI and the Center for Research on Computation and Society at Harvard. He received a PhD in Electrical Engineering and Computer Science from MIT, an MS in Computation for Design and Optimization from MIT, and BS degrees in Operations Research and Economics from UC Berkeley. For more details, please see https://www.berkustun.com

 

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Brad Voytek
Associate Professor, HDSI Founding Faculty Fellow
DEPARTMENT OF COGNITIVE SCIENCE

Bradley Voytek is an Associate Professor in the Department of Cognitive Science, the Halıcıoğlu Data Science Institute, and the Neurosciences Graduate Program at UC San Diego. He is an Alfred P. Sloan Neuroscience Research Fellow and National Academies Kavli Fellow, as well as a founding faculty member of the UC San Diego Halıcıoğlu Data Science Institute and its undergraduate Data Science program, where he serves as Vice-chair.

His research program uses neural modeling and simulation, along with large-scale data mining and machine learning techniques, to understand the physiological basis of human cognition and age-related cognitive decline.

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Yusu Wang
Professor

Yusu Wang obtained her PhD degree from Duke University in 2004, and from 2004 – 2005, she was a was a post-doctoral fellow at Stanford University. Prior to joining UC San Diego, Yusu Wang is Professor of Computer Science and Engineering Department at the Ohio State University, where she also co-directed the Foundations of Data Science Research CoP (Community of Practice) at Translational Data Analytics Institute (TDAI@OSU) from 2018–2020.

Yusu Wang primarily works in the field of geometric and topological data analysis. She is particularly interested in developing effective and theoretically justified algorithms for data analysis using geometric and topological ideas and methods, as well as in applying them to practical domains. Very recently she has been exploring how to combine geometric and topological ideas with machine learning frameworks for modern data science.

Yusu Wang received the Best PhD Dissertation Award from the Computer Science Department at Duke University. She also received DOE Early Career Principal Investigator Award in 2006, and NSF Career Award in 2008. Her work received several best paper awards. She is currently on the editorial boards for SIAM Journal on Computing (SICOMP), Computational Geometry: Theory and Applications (CGTA), and Journal of Computational Geometry (JoCG). She is elected to serve on the Computational Geometry Steering Committee in 2020.

Website: yusu.belkin-wang.org

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Logan Weidenhoffer
Executive Assistant to the Director
Categories: Executive Office, Staff
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Lily Weng
Assistant Professor

Lily Weng is an Assistant Professor in the Halıcıoğlu Data Science Institute at UC San Diego. Her research interests focus on the intersection between machine learning, optimization and reinforcement learning, with applications in cybersecurity and healthcare. Specifically, her vision is to make the next generation AI systems and deep learning algorithms more robust, reliable, trustworthy and safer. She has worked on developing efficient algorithms as well as theoretical analysis to quantify robustness of deep neural networks. She received her PhD in Electrical Engineering and Computer Sciences (EECS) from MIT in August 2020, and her Bachelor and Master degree both in Electrical Engineering at National Taiwan University in 2011 and 2013. More details please see https://lilyweng.github.io/

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Ruth Williams
Professor

Ruth Williams is a Distinguished Professor of Mathematics and holds the Charles Lee Powell Chair in Mathematics I at the University of California, San Diego (UCSD). She is a mathematician who works in probability theory, especially on stochastic processes and their applications. Her current research includes the analysis and control of stochastic models for complex networks, e.g., those arising in Internet congestion control and systems biology.  Her research has been recognized with many honors, including election to the US National Academy of Sciences and as a Corresponding Member of the Australian Academy of Science, and award in 2016 of the John von Neumann Theory Prize. For further information see http://www.math.ucsd.edu/~williams/bio.html

Categories: Uncategorized
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Yvonne Wollmann
Student Affairs Manager

Bio coming soon!

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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.

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Ronghui (Lily) Xu
Professor

Xu earned her Ph.D. in Mathematics and a Master’s in Applied Mathematics from UC San Diego, and her Bachelor’s in Math from Nankai University, China.

After a year as Postgraduate Researcher at UC San Diego, she took up Assistant Professorship in Biostatistics at Harvard School of Public Health and Dana-Farber Cancer Institute in Boston, MA. She returned to UC San Diego in 2004 with a joint appointment from the main campus (Mathematics) and health sciences (Biostatistics and Bioinformatics). Among her academic honors are as a Fellow of the American Statistical Association (ASA), and a recipient of the ASA’s David P. Byar Young Investigator Award. Her current research interests include causal inference, survival analysis, and machine learning methods as applied to biomedicine.

Website: http://www.math.ucsd.edu/~rxu/

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Angela Yu
Associate Professor
Since 2008, Dr. Yu has directed the Computational Cognitive Neuroscience Laboratory at UCSD, which studies the computational problems faced by intelligent agents, as well as their algorithmic solutions in natural and artificial intelligence systems. Previously, Dr. Yu studied at MIT (B.S. in Brain & Cognitive Sciences, Mathematics, Computer Science), UCL Gatsby Unit (PhD in Computational Neuroscience), and received postdoctoral training at Princeton University (Center for the Brain, Mind, and Behavior). Currently, Dr. Yu is working on learning and decision-making under uncertainty, the contribution of volitional movement to representation learning, as well as social cognition.
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Rose Yu
Assistant Professor Computer Science and Engineering

Dr. Rose Yu is an Assistant Professor at the UC San Diego, Department of Computer Science and Engineering. She earned her Ph.D. in Computer Sciences at the University of Southern California in 2017. She was subsequently a Postdoctoral Fellow at the California Institute of Technology. She was an assistant professor at Northeastern University prior to her appointment at UC San Diego.

Her research focuses on advancing machine learning techniques for large-scale spatiotemporal data analysis, with applications to sustainability, health, and physical sciences. A particular emphasis of her research is on physics-guided AI which aims to integrate first-principles with data-driven models. Among her awards, she has won Google Faculty Research Award, Adobe Data Science Research Award, NSF CRII Award, Best Dissertation Award in USC, and was nominated as one of the ’MIT Rising Stars in EECS’.

Website: http://roseyu.com

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Haoqi Zhang
Visiting Scholar
Categories: Visiting Scholar
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Wenxin Zhou
Associate Professor Mathematics

Wenxin Zhou is an Associate Professor in the Department of Mathematics at UCSD. My research areas include high-dimensional statistical inference, nonparametric and robust statistics. The driving force is to address some of the key issues in big data, ranging from robustness, heterogeneity, model selection uncertainty, statistical and computational trade-offs, to inference under privacy-preserving or parallel and distributed computing platforms.