The purpose of IDRE Early Career Researchers (ECR) Group is to bring together scholars from a variety of disciplines and methodological perspectives interested in advancing cross-disciplinary research in computational and data sciences at UCLA. The group is managed by ECR committee, a dynamic group of early career Researchers and IDRE scholars, which meets every month to go over the management and planning of the meetings, seminars, and/or workshops aimed at creating synergy and encouraging interdisciplinary collaborations among early career researchers at UCLA. Any early career research faculty, postdoctoral researcher, or graduate student affiliated with UCLA can become part of the ECR group by subscribing the following ECR group mailing list:
ECR group members are further welcome to discuss and share their ideas among colleagues at UCLA by joining either or both of the following social media platforms:
- Coming soon
Past Committee Members:
IDRE Scholars are selected through an open call for proposals from postdoctoral researchers at UCLA working in areas related to the IDRE programs including projects involving high-performance computing, GPU and many core-based computing architectures, statistical computing and data informatics, GIS, data visualization, and 3D modeling. In addition to the partial support for their research, the IDRE scholars also receive direct access to technologists within the IDRE Research Technology Group and relevant IDRE affiliated faculty and researchers.
The following five outstanding postdoctoral researchers are the recipients of IDRE scholars 2019 award:
Past IDRE Scholars:
J. Harry Caufield is a postdoctoral fellow in the NIH HeartBD2K Center of Excellence at UCLA, where he works with Prof. Peipei Ping of UCLA’s departments of Physiology, Medicine, and Bioinformatics. Before joining UCLA, Dr. Caufield earned his PhD in Integrative Life Sciences at Virginia Commonwealth University, where he studied microbial protein interactions and developed intuitive methods for working with large protein interaction networks. He continues to have an active interest in learning about biological relationships hidden within disparate data sources, particularly those with a direct impact on human health and disease.
Matthew Jacobs was born and raised in Brooklyn, NY. He received a B.A. in math at Columbia University in 2011. Then received a Ph.D. in math from the University of Michigan in 2017. His thesis advisor was Selim Esedoglu. For the last two years, he has been a postdoc in the UCLA math department and his postdoc mentors are Stan Osher and Andrea Bertozzi.
Masaki Nakada obtained his Bachelor’s degree in applied physics in 2009 and his Master’s degree in pure and applied physics in 2011 from Waseda University in Tokyo, Japan. He then obtained his Ph.D. in computer science in 2017 from University of California Los Angeles, and his current research is centered on artificial life to create a virtual human with biomimetic human vision and a neuromuscular control system. His research has led to the development of a biomimetic human system as a bottom up approach, which gives us the ability to realize the complete human system in software and robots.
Zhi (Jackie) Yao is currently a postdoctoral researcher in the Electrical and Computer Engineering (ECE) Department at University of California, Los Angeles (UCLA). She obtained the M.S. degree in 2014 and the Ph.D. degree in 2017, both in the ECE Department at UCLA. Her main work during the graduate and postdoc researches is the development of a numerical solver unifying dynamic electromagnetics (EM), nonlinear magnetic spin dynamics, and acoustics. This solver is under progress of licensing and enabling public access, and is one of the key contributions to the sustainability of the NSF ERC center for Translational Applications of Nanoscale Multiferroic Systems (TANMS) headquartered at UCLA. Her work has been funded by sources such as NSF and DARPA.
She has received multiple academic honors, such as the 1st place Best Student Paper in International Microwave Symposium, IEEE Antennas and Propagation Society Doctoral Research Grant, Qualcomm Innovation Fellowship, Outstanding Master’s Thesis at ECE UCLA and 1st place in PhD exam at ECE UCLA.
Khalid Youssef is a postdoctoral researcher with a Ph.D. in Biomedical Engineering. His research involves developing new machine learning algorithms, and their application in a variety of interdisciplinary fields such as image & signal processing, robotics, control, fluid dynamics, and medical imaging. Some applications he developed include a new generation of bioreactors that utilize artificial neural networks to dynamically control mechanical forces in cell growth environment, state of the art medical image denoising capable of learning noise statistics from images, and data driven radio frequency transmitter identification. Khalid’s work has pushed the state of the art in 2nd order ANN training algorithms, and his ongoing research targets the implementation of novel 2nd order-based ANN training methods to large-scale and big-data applications.
Iris Chang is a PhD candidate in Professor Jaime Marian’s group in the department of Materials Science and Engineering at University of California, Los Angeles. She uses Molecular Dynamics (MD) and Monte Carlo (MC) method to study particle/laser interactions with materials. Her thesis work focuses on the computational study of resilient self-healing materials for the extreme environment of space electric propulsion and power. She also teaches courses in Science of Engineering Materials and Mechanical Behavior of Materials. Before joining UCLA, she received B.S. degree in Materials Science and Engineering at National Taiwan University in 2013.
Richard William Sportsman is a PhD candidate in the Chemistry & Biochemistry Department at UCLA in the lab of Professor William M. Gelbart. Richard’s thesis research focuses on studying the physical properties of plant viruses and how these properties affect the initial stages of a plant virus infection (yes, plants can catch a virus too!). The study of plant viruses has applications in preventing virus spread and using plant virus proteins as a shell to package genes for therapy in cancer and other debilitating human diseases as well. IDRE offers a unique opportunity to learn about interesting projects across UCLA and potentially acquire new skills and form collaborations which have been very helpful to his research.
Omar I. Asensio, Ph.D., is a postdoctoral fellow at UCLA’s Institute of the Environment & Sustainability and the Anderson School of Management Ziman Center. He uses field experiments and quantitative methods to address innovation challenges related to energy, transportation and urban sustainability. His forthcoming research on energy efficiency strategies in commercial buildings will be featured in Science – Editor’s choice section. He holds a doctorate in environmental science and engineering from UCLA and is a former National Science Foundation IGERT fellow with a topic in clean energy for green industry.
Nikhil Chandra Admal, Ph.D., is a postdoctoral fellow working with Prof. Jaime Marian in the Materials Science and Engineering department at UCLA. He is broadly interested in the multiscale modeling of materials at various length and times scales ranging from the atomic scale to the continuum scale. Currently, the focus of his research is on the study of recrystallization in refractory materials to increase their operating temperature, and development of first-principles strain gradient elastic models to include non-local effects relevant in micromechanical systems, and systems with defects.
Prior to joining UCLA, Dr. Admal obtained his PhD from the Department of Aerospace Engineering and Mechanics at the University of Minnesota.
Kristine Tanton, Ph.D., is a postdoctoral fellow and project manager for the collaborative project at UCLA, Paris Past and Present. Working with Prof. Meredith Cohen (PI, Department of Art History) and a team of graduate and undergraduate students, she manages project workflow and serves as a modeler for the project. To date, the team has completed 3D models for about a dozen buildings that were first constructed during the reign of Louis IX (Saint Louis).
Dr. Tanton received her Ph.D. in Art History from the University of Southern California in 2013. She integrates traditional and emerging methods to study the dynamic relationship among sculpture, architecture, and ritual activity in the Middle Ages. She is especially interested in how new media and information technology can transform research and pedagogy in the field of pre-modern art and architectural history. Using digital tools such as 3D reconstructions, animations to track ritual movements through architectural space, and databases to formally and quantitatively analyze large datasets, she has been able to reevaluate long-held assumptions about canonical sites to gain insights into medieval architectural design and construction methods.
Zhenman Fang, Ph.D., is a postdoctoral fellow in the Computer Science Department, UCLA, working with Prof. Jason Cong and Prof. Glenn Reinman. He is a member of the NSF/Intel funded multi-university Center for Domain-Specific Computing (CDSC) and the SRC/DARPA funded multi-university Center for Future Architectures Research (C-FAR). Zhenman received his PhD in June 2014 from Fudan University, China and spent the last 15 months of his PhD program visiting University of Minnesota at Twin Cities. Zhenman’s research lies at the boundary of big data workloads and systems, heterogeneous and energy-efficient accelerator-rich architectures and systems, and system-level design automation. He has published 10+ papers in top venues that span across computer architecture (HPCA, TACO, ICS), design automation (DAC, ICCAD, FCCM), and cloud computing (ACM SOCC). He received several awards, including a best paper nominee of HPCA 2017, a best demo award (3rd place) at the C-FAR center annual review. More details can be found in his personal website: https://sites.google.com/site/fangzhenman/.
- Epidemic Model Guided Machine Learning for COVID-19 Forecasts – Jun 5, 2020
- Knowledge Graphs, Natural Language Processing, and Standards for Unifying Unstructured Biomedical Data – Apr 22, 2020
- Early Career Research Day – Nov 20, 2019
- Scaling to Petascale Institute, June 2017
- Resurrecting Historical Monuments: 3D Models, Metadata, and the Case of the Lady Chapel at Saint-Germain-des-Prés, May 2017
- Accelerating Next-Generation DNA Sequencing, Apr 2017
- Polycrystalline crystal plasticity with grain boundary evolution, Mar 2017
- Big Data and Information Policies for Behavior Change, Feb 2017
- IDRE Early Career Researchers Lunch and Meeting, May 2016