BIDS welcomes our 2018 cohort of Data Science Fellows! This year’s cohort joins our growing campus-wide community creating and applying talent, theory and tools for data-intensive discovery to advance interdisciplinary research and training.
Identifying electoral gerrymandering, reducing the spread of infectious diseases, and expanding our understanding of foundational statistical principles are just a few examples of the areas this year's Fellows are exploring. The BIDS fellowship program enables Fellows to pursue their individual fields of study with their home department advisors while working with an expanded community of researchers and collaborators from other fields. Fellows also take on specific projects to accelerate and sustain data science gains at Berkeley and for our stakeholders.
Since being established with support from the Gordon and Betty Moore Foundation and the Alfred P. Sloan Foundation in 2013, BIDS has welcomed postdoctoral scholars and graduate student researchers as Fellows through an annual competitive process. This year, they are supported by the Moore/Sloan Data Science Environment, by our partners at the UCSF Baker Computational Health Sciences Institute - BCSHI, and by a shared investment with UC Berkeley’s new Foundations of Data Analysis Institute - FODA.
Amir Gholami is a postdoctoral research fellow in the Berkeley Artificial Intelligence Research (BAIR) Lab who has extensive experience in statistical second-order optimization methods and large scale parallel computing, developing codes that have been scaled up to 200K cores. His current research includes large scale training of neural networks. Amir’s is a collaborative fellowship with FODA.
Francois Lanusse is a postdoctoral scholar at the Berkeley Center for Cosmological Physics exploring the intersection of cosmology, statistics, and machine learning. His research has focused on the gravitational lensing effect (in which distant galaxies appear distorted by the presence of massive structures along the line of sight), developing novel tools and methodologies. Francois’s is a collaborative fellowship with FODA.
Ivana Malenica is a PhD student in Biostatistics with research interests spanning various aspect of statistical theory and machine learning, as well as causal inference and high-dimensional statistics. Her work involves model selection criteria, individualized medical treatment, online learning, and use of health-monitoring devices.
Kevin Keys is a postdoctoral scholar at the UCSF School of Medicine studying the genetic basis of pediatric asthma. His biological and mathematical research interests include computational genomics, bioinformatics, and mathematical optimization. Kevin’s is a collaborative fellowship with BCHSI.
Richard Barnes, a graduate student in the Energy & Resources Group and in Electrical Engineering and Computer Sciences, draws on his background in computational science, ecology, and physics to develop new approaches to big data challenges in geomorphology, electoral gerrymandering, and genome sequencing. His most recent research focuses on large geospatial problems.
Sara Stoudt is a PhD student in Statistics interested in ecological applications of statistics. She is currently assessing the accuracy of statistical modeling applied to species distribution analysis. Sara is also involved in teaching writing for statistics.
Váleri Vásquez is a PhD student in the Energy and Resources Group who uses mathematical models to examine the environmental factors associated with infectious diseases, and how these drivers exacerbate the economic impacts of climate change. She is currently working on questions relevant to the control of malaria.
Wooseok Ha is a new postdoctoral scholar who works on statistical estimation and optimization for structured high-dimensional data. He has also collaborated on CT image reconstruction in medical imaging, and on inferring geographic structure from genetic data in population genetics. Woosek’s is a collaborative fellowship with FODA.
We at BIDS invite others to visit us at the Doe Memorial Library to connect with all 30 of our Data Science Fellows - and to learn more about the Institute, the broader Data Science Initiative at Berkeley, and our training, research and events.