Welcoming BIDS 2017 Data Science Fellows

July 26, 2017

We are thrilled to introduce our 2017 cohort of data science fellows! With diverse research backgrounds and experiences, the new fellows will help lead our community in driving data science innovations and enhancing collaborations across UC Berkeley and beyond.

This year, for the first time, in addition to our Moore/Sloan Data Science Environment fellows, we are thrilled to introduce a number of collaborative fellowships with our partner institutions, including the UCSF Institute for Computational Health Sciences (ICHS); Lawrence Livermore National Lab (LLNL); Biomedical Big Data Training Program (BBDT); Clean Energy Research Center for Water-Energy Technologies (CERC-WET); University Libraries and Data Science Education Program (DSEP).

Please join us in welcoming:

Maryana Alegro

Maryana Alegro

Postdoctoral Scholar, Neurology, UCSF
BIDS-ICHS Data Science Fellow, UC Berkeley/UCSF

Maryana uses her knowledge in image and signal processing for building computational tools to help improve the understanding of neurodegenerative diseases. Her major experience is in MRI and histological image processing and, more recently, polarized light imaging.

Yasmin AlNoamany

Yasmin AlNoamany

Postdoctoral Scholar, Software Curation, University Libraries
BIDS Data Science Fellow, University Libraries

Yasmin's research focuses on reproducibility and software curation. She works closely with the Research Data Management team at UC Berkeley on different projects to provide support for the research activities in the campus. 

Diya Das

Diya Das

PhD Candidate, Department of Molecular & Cell Biology
BIDS Data Science Fellow, Moore/Sloan

Diya studies regeneration in the olfactory epithelium, the tissue responsible for our sense of smell.  Diya also facilitates opportunities for fellow researchers to develop their data science skills.

Ryan Giordano

Ryan Giordano

PhD Student, Statistics
BIDS Data Science Fellow, Moore/Sloan

Ryan's interests include variational methods, robustness, scalable statistical inference, and the philosophy of science. His work experience includes engineering jobs at Google and HP and two years as an English and math teacher with the United States Peace Corps stationed in Kazakhstan.

Elena Glassman

Elena Glassman

Postdoctoral Scholar, Electrical Engineering and Computer Sciences
BIDS Data Science Fellow, Moore/Sloan

Elena works with the Berkeley Institute of Design working on systems that help people teach and learn. Previously she created scalable systems that analyze, visualize, and provide insight into the code of thousands of programming students. 

Christopher Hench

Christopher Hench

PhD Candidate, German
BIDS-DSEP Data Science Fellow, Moore/Sloan

Christopher is interested in computational approaches to the formal analysis of lyric and epic poetry, and is currently working on reading soundscapes. He is additionally the Program Development Lead for Digital Humanities and the D-Lab.

Chris Kennedy

Chris Kennedy

PhD Student, Biostatistics
BIDS-BBDT Data Science Fellow, Moore/Sloan

Chris's methodological interests include targeted machine learning, randomized trials, causal inference, and deep learning. His applications are primarily in precision medicine, public health, and election campaigns. He is also a consultant and instructor at D-Lab.

Sören R. Künzel

Sören R. Künzel

PhD Student, Statistics
BIDS Data Science Fellow, Moore/Sloan

Sören is interested in Causal Inference, Machine Learning and Experimental Design, he enjoys solving real world problems, and analyzing asymptotic behavior of statistical estimators. He is currently developing a new version of random forests which is in particularly well suited for statistical inference.

Ciera Martinez

Ciera Martinez

Postdoctoral Fellow, Molecular and Cell Biology
BIDS Data Science Fellow, Moore/Sloan

Ciera is a computational biologist interested in the function and evolution of genomes, especially the mysterious non-coding regions of genomes. She has been active in promoting, establishing, and teaching computational reproducibility in the sciences.

Scott Paul McGinnis

Scott Paul McGinnis

PhD Candidate, History
BIDS Data Science Fellow, Moore/Sloan

Scott specializes in early China where his research explores the intersection of technical disciplines and historical practices during the Han period (206 BCE - 220 CE). Scott also teaches and coordinates activities in Digital Humanities and Data Science.

Jarrod Millman

Jarrod Millman

PhD Student, Biostatistics
BIDS Data Science Fellow, Moore/Sloan

Jarrod's current interests include graph analysis in neuroimaging. He has a BA in mathematics and computer science from Cornell University.

Henry Pinkard

Henry Pinkard

PhD Student, Computational Biology
BIDS-ICHS Data Science Fellow, UC Berkeley/UCSF

Henry works on inventing techniques to extract and exploit information from images of biological systems in order to tackle previously intractable challenges in research, medicine, and global health. He has helped develop Micro-Manager, an open-source software for the control of motorized microscopes.

Marla Stuart

Marla Stuart

Postdoctoral Scholar, Social Welfare
BIDS Data Science Fellow, Moore/Sloan

Marla's research concentrates on understanding the applicability of data science approaches in social welfare research and practice settings. She is also a fellow with the Guizhou Berkeley Big Data Innovation Research Center (GBIC), a research hub based in Guizhou Province, China that is dedicated to improving the health and well-being of China’s population.

Deborah Sunter

Deborah Sunter

Postdoctoral Scholar, Energy & Resources Group
BIDS Data Science Fellow, Moore/Sloan

Deborah's research interests include data science for sustainability, national energy planning, city-integrated renewable energy systems, environmental justice, and clean technology innovation. Specializing in computational modeling of thermo​physics in multiphase systems, she previously developed a novel solar absorber tube.

Maryam Vareth

Maryam Vareth

Associate Specialist, Radiology and Biomedical Imaging, UCSF
BIDS-LLNL Data Science Fellow

Maryam is an advocate for “data-driven” medicine and keen on meaningfully extracting clinically relevant insights from large-scale medical data, more specifically to directly link medical imaging data to medical diagnostics and therapeutics and moving her community towards open source and open research practices.

Zexuan Xu

Zexuan Xu

Postdoctoral Scholar, Climate and Ecosystem Science Division, LBNL
BIDS-CERC-WET Data Science Fellow, Moore/Sloan

Zexuan's current research focuses on assessing the accuracy of global and regional climate models compared to observational data, developing statistical corrections, and providing these inputs to hydrologic models and water resource studies.

Andreas Zoglauer

Andreas Zoglauer

Assistant Researcher, Space Sciences Laboratory
BIDS-LLNL Data Science Fellow

Andreas works at the intersection between Astrophysics & Data Science. He is currently working on the development of new data analysis tools and their application to hard X-ray and gamma-ray telescopes.



Featured Fellows

Maryana Alegro

Neurology, UCSF

Yasmin AlNoamany

University Libraries
DATA SCIENCE FELLOW

Diya Das

Molecular & Cell Biology
DATA SCIENCE FELLOW

Ryan Giordano

Statistics
DATA SCIENCE FELLOW

Elena Glassman

Electrical Engineering and Computer Sciences
DATA SCIENCE FELLOW

Christopher Hench

German, Digital Humanities, D-Lab, DSEP
DATA SCIENCE FELLOW

Chris Kennedy

Biostatistics

Sören Künzel

Statistics

Ciera Martinez

Molecular and Cell Biology

Scott Paul McGinnis

History
DATA SCIENCE FELLOW

Jarrod Millman

Biostatistics

Henry Pinkard

Computational Biology

Marla Stuart

Social Welfare, Guizhou Berkeley Big Data Innovation Research Center (GBIC)
DATA SCIENCE FELLOW

Deborah Sunter

Energy & Resources Group
DATA SCIENCE FELLOW

Maryam Vareth

Radiology and Biomedical Imaging, UCSF

Zexuan Xu

Climate and Ecosystem Science Division, LBNL

Andreas Zoglauer

Space Sciences Laboratory