Renata Rawlings-Goss
Renata Rawlings-Goss
IDEaS Director of Industry Engagement
Bioinformatics
IRI Connections:
Jacob Abernethy is an Associate Professor in the College of Computing at Georgia Tech. He started his faculty career in the Department of Electrical Engineering and Computer Science at the University of Michigan. He completed his Ph.D. in Computer Science at the University of California at Berkeley, and then spent two years as a Simons postdoctoral fellow at the CIS department at UPenn. Abernethy's primary interest is in Machine Learning, with a particular focus in sequential decision making, online learning, online algorithms and adversarial learning models. He did his Master's degree at TTI-C, and his Bachelor's Degree at MIT.
Srinivas Aluru is executive director of the Institute for Data Engineering and Science (IDEaS) and professor in the School of Computational Science and Engineering at Georgia Institute of Technology. He co-leads the NSF South Big Data Regional Innovation Hub which nurtures big data partnerships between organizations in the 16 Southern States and Washington D.C., and the NSF Transdisciplinary Research Institute for Advancing Data Science. Aluru conducts research in high performance computing, large-scale data analysis, bioinformatics and systems biology, combinatorial scientific computing, and applied algorithms. An early pioneer in big data, Aluru led one of the eight inaugural mid-scale NSF-NIH Big Data projects awarded in the first round of federal big data investments in 2012. He has contributed to NITRD and OSTP led white house workshops, and NSF and DOE led efforts to create and nurture research in big data and exascale computing. He is a recipient of the NSF Career award, IBM faculty award, Swarnajayanti Fellowship from the Government of India, the John. V. Atanasoff Discovery Award from Iowa State University, and the Outstanding Senior Faculty Research Award, Dean's award for faculty excellence, and the Outstanding Research Program Development Award at Georgia Tech. He is a Fellow of AAAS, IEEE, and SIAM, and is a recipient of the IEEE Computer Society Golden Core and Meritorious Service awards.
404.385.1486
Dr. Fang (Cherry) Liu is a Research Scientist at Partnership for Advanced Computing Environment (PACE) center at Georgia Tech. She actively provides expert diagnosis and resolution of complex technical issues with High Performance Computing (HPC) resources; leverages HPC software and application stack, including compilers, scientific libraries and user applications to effectively run on HPC environment; educates campus-wide HPC community, teaching courses including introduction to Linux, intermediate Linux, introduction to Python and Python for Data Analysis courses; and does on-going research on big data with school of computational science and engineering (CSE) faculties. She is awarded the title of Adjunct Associate Professor by CSE to better serve campus HPC community in both teaching and research.
Before joining Georgia Tech, she was an assistant scientist at mathematics and computational science division at Department of Energy (USDOE) Ames Laboratory, where she gained extensive experience with multi-disciplinary research team and worked closely with world-class domain scientists from physics, chemistry and fusion energy. The projects she participated in included scientific workflows and data management system for nuclear physics applications, GPU computing for large scale quantum chemistry applications, concurrent data processing for fusion simulation through distributed component infrastructure, and so much more.
Her research interests broadly span parallel/distributed scientific computing, software interface design for monolithic scientific applications, multi-physics and multi-code coupling, multilevel parallelism support for Multi-Physics coupling, data management and provenance for scientific applications, big data infrastructure design and implementation, and data analytics for large graph dataset.She has been served as program committee member for various conferences including HPC, ICCS, ICCSA, CBHPC, ICPP, and she also was vice program general chair, program general chair for HPC2012 and HPC2013, now she sits in program steering committee for HPC since 2014.
Currently her primary interest focuses on tackling big data issues with using Hadoop and Spark in graph database, security and streaming data, while she is closely working with professor Polo Chau's group.
Dr. Liu graduated from Indiana University at Bloomington in 2009 with a Ph.D. degree in Computer Science. Her dissertation titled, "Building Sparse Linear Solver Component for Large Scale Scientific Simulation and Multi-physics Coupling," and her Ph.D. advisor was Professor Randall Bramley.
Eric joined PACE in 2021, and currently leads the Research Computing Facilitation team, after having worked as a Cyberinfrastructure Architect and RCF. Before joining PACE, Eric could be found at Indiana University as a systems engineer with the XSEDE Campus Bridging team, providing HPC-oriented consultations to institutions across the US. He also worked closely with the Cyberinfrastructure Research Center at IU, providing support for several different science gateway projects. Prior to that, his research in condensed matter physics at Florida State University involved computational studies of the optical properties of strongly correlated materials.
Aaron joined the PACE team in May 2019 as a computing facilitator, and currently serves as the Scheduler Architect. Through supporting users, he grew to appreciate the opportunity to improve HPC workflows through scheduler and systems configurations that lower the barrier to entry and passively optimize code execution. Additionally, Aaron has been involved in the Vertically Integrated Projects (VIP) program since Spring 2020, mentoring multiple teams of students with the Team Phoenix VIP through international HPC competitions at the ISC-HPC and Supercomputing conferences and more recently, providing leadership for the Future Computing with the Rogues Gallery VIP as they research applications of novel compute architectures. Prior to joining PACE, Aaron studied free neutron and nuclear beta decay as a precision test of the Standard Model, which entailed a diverse range of activities, including particle simulation and detection, digital and analog signal processing, and algorithm optimization across x86, GPU, and FPGA architectures.