Over the last two years, the Institute for Data Engineering and Science (IDEaS) operations and research, and service portfolios have grown significantly. To accommodate this, IDEaS has taken steps to expand the current leadership team.
After a campuswide search, Xiaoming Huo is joining IDEaS as Associate Director for Research. New Thrust Lead positions were created positions to focus on and opportunistically expand capabilities in important areas. Joining IDEaS in this capacity are Jeffrey Skolnick as Thrust Lead for Precision Medicine and Drug Discovery and Umakishore Ramachandran as Thrust Lead for Cloud Computing.
In addition, IDEaS is increasingly being called upon to support data and cyber infrastructure technical design and management needs of large, center-scale projects. To adress these needs, senior research scientist Tony Pan will be assuming the role of Assistant Director for Data Infrastructure. David Sherrill, who is already serving as Associate Director for Research and Education, is taking on additional responsibility as Director of the Center for High Performance Computing (CHiPC).
Xiaoming Huo, Associate Director for Research
Xiaoming Huo is an A. Russell Chandler III Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. Dr. Huo's research interests include statistical theory, statistical computing, and issues related to data analytics. He has made numerous contributions on topics such as sparse representation, wavelets, and statistical problems in detectability. His papers appeared in top journals, and some of them are highly cited. He is a senior member of IEEE since May 2004.
In this new role, Huo brings experience in creating teams to tackle various challenges in science and society. He believes that nurturing and fusing teams within IDEaS will results in more funding opportunities, experience sharing, shaping future programs at the national level, and enhancing the visibility of IDEaS and Georgia Tech.
Jeffrey Skolnick, Thrust Lead for Precision Medicine and Drug Discovery
Jeffrey Skolnick, Regent’s Professor of Biological Sciences, research has focused
on health and life sciences, having developed novel AI approaches for precision medicine, disease mode of action prediction, and drug efficacy and side effect prediction that is at the state of-the-art. He has developed and applied algorithms to proteomes for the prediction of protein structure and function, the prediction of small molecule ligand-protein interactions with applications to drug discovery and the prediction of off-target uses of existing drugs with applications to aging, cancer and chronic fatigue syndrome, cancer metabolomics, precision medicine, fundamental studies on the nature and completeness of protein structure space and the exploration of the interplay between protein physics and evolution in determining protein structure and function, prediction of protein-protein and protein-DNA interactions, and molecular simulations of subcellular processes.
Skolnick hopes to catalyze the development of novel big data-based approaches to Precision Medicine and Drug discovery. In particular, he hopes to identify and catalyze teams that would to transformation research in these areas. Some representative projects include Cancer Multi-omics where the goal would be to stratify patients to predict which patients are likely to respond to specific drugs. Ideally, this would push the development of cancer therapeutics to treat currently intractable cancers such as pancreatic and triple negative breast cancer. Another area is neuroscience, with particular emphasis on Alzheimer’s Disease and Parkinson’s Disease, which currently lack effective, long term treatments. Here, the goal is to identify patient specific disease drivers and key mode of action proteins and non-coding regions responsible for disease onset and progression and then identify, and in collaboration with Emory, test predicted novel repurposed drugs in patients. The goal would also be to create a knowledgebase and website which would make the resulting tools widely available.
Umakishore Ramachandran, Thrust Lead for Cloud Computing
Kishore Ramachandran received his Ph.D. in Computer Science from the University of Wisconsin, Madison in 1986, and has been on the faculty of Georgia Tech since then. He led the definition of the curriculum and the implementation for an online MS program in Computer Science (OMSCS) using MOOC technology for the College of Computing, which is currently providing an opportunity for students world-wide (with an enrollment of over 10,000) to pursue a low-cost graduate education in computer science. He has served as the Director of STAR Center from 2007 to 2014, and as the Director of Korean Programs for the College of Computing from 2007 to 2011. Ramachandran has also served as the Chair of the Core Computing Division within the College of Computing. His research interests are in architectural design, programming, and analysis of parallel and distributed systems. Currently, he is leading a project that deals with large-scale situation awareness using distributed camera networks and multi-modal sensing with applications to surveillance, connected vehicles, and transportation. He is the recipient of an NSF PYI Award in 1990, the Georgia Tech doctoral thesis advisor award in 1993, the College of Computing Outstanding Senior Research Faculty award in 1996, the College of Computing Dean's Award in 2003 and 2014, the College of Computing William "Gus'' Baird Teaching Award in 2004, the "Peter A. Freeman Faculty Award" from the College of Computing in 2009 and in 2013, the Outstanding Faculty Mentor Award from the College of Computing in 2014, and became an IEEE Fellow in 2014.
Ramachandran will help establish a “Cloud Hub” at Georgia Tech partnering with Microsoft. The Cloud hub will provide Microsoft Azure resources for both education and research for faculty and students wishing to use the Cloud for their computational needs. While the Cloud hub will initially be started with support from Microsoft, the aspirational goals for the hub include expansion to include other Cloud providers who may want to partner with Georgia Tech. Further, Ramachandran hopes to use the experience with the Cloud hub to help evolve a Cloud strategy for Georgia Tech as a whole.
Tony Pan, Assistant Director for Data Infrastructure
Tony Pan joined the Institute for Data Engineering and Science in 2018 after graduating from Georgia Institute of Technology with a Ph.D. in Computational Science and Engineering. For over two decades, Pan has focused his research efforts on developing data science methods to enable large scale biomedical and bioinformatic studies, specifically through flexible and extensible data management, high performance computing (HPC) approaches, and efficient parallel algorithms. He is leading the data management infrastructure definition and implementation to support the NSF Engineering Research Center for Cell Manufacturing Technologies (CMaT) at Georgia Tech, and developing HPC algorithms for high-throughput sequencing data, gene networks, and single cell sequence analysis. Pan is also leading the development of data management infrastructure and gene association studies for the Arthrogryposis Registry in collaboration with Shriner’s Hospitals for Children.
In this role, Pan hopes to engage and support IDEaS members, partners, and collaborators in large scale, systematic data management and analysis efforts. Towards this end, he will focus on defining and implementing an IDEaS core data management strategy and corresponding infrastructure, as well as developing common optimization approaches and algorithms for large scale data analytics. Pan hope to foster an environment for data, knowledge, and best practice sharing between researchers, collaborators, and institutional support as part of IDEaS' data infrastructure efforts.
David Sherrill, Director, Center for High Performance Computing
Professor David Sherrill is the new Director for the Center for High Performance Computing (CHiPC). Sherrill is currently the assistant director for research and education in IDEaS. Sherrill is one of the co-PI's on the NSF MRI grant that funded the Georgia Tech Hive computer, and recently organized the Hive Supercomputer Symposium hosted by IDEaS. His background is in theoretical chemistry, and he develop new models in quantum chemistry, with a particular focus on biophysics, drug docking, and molecular crystals. Sherrill's group makes heavy use of high performance computing (HPC) resources, especially now, pioneering how to apply machine learning (ML) to intermolecular interactions. They are creating quantum chemistry datasets of unprecedented size to train these ML models. The existing quantum chemistry software is too slow for this, so they have developed their own very popular open-source program, Psi4.
In this new role, Sherrill hopes to strengthen connections between HPC users in science and engineering with HPC researchers in computing. One goal is to ensure Georgia Tech is prepared to respond to new national initiatives in which HPC may be a key component. Maintaining significant local HPC resources is a key part of that, and CHiPC should facilitate the organization of teams to compete for equipment grants. Sherrill plans to set up education and outreach workshops, and continue the excellent CHiPC efforts related to the student cluster competition and the Georgia Tech booth at Supercomputing.