Grant Brown is an Assistant Professor of Biostatistics in the College of Public Health at the University of Iowa. His primary area of research is spatiotemporal epidemic modeling, which draws on aspects of Bayesian hierarchical models, statistical computing, simulation, and data visualization. He is also interested in the analysis of correlated data more generally, and statistical learning techniques. Grant earned his PhD in Biostatistics from the University of Iowa in 2015, and has contributed to numerous research projects across campus. Among other pursuits and consulting work, he has evaluated a program to encourage patient engagement with pharmacists, contributed to the development of data entry and program management websites for programs promoting colorectal cancer screening and breast/cervical cancer screening programs in Iowa, and implemented predictive enrollment models for Enrollment Management at the university
Grant D Brown
Omar Haider Chowdhury is an Assistant Professor at the University of Iowa in the Department of Computer Science. He recently was a Post-Doctoral Research Associate in the Department of Computer Science at Purdue University. Before joining Purdue, he was a Post-Doctoral Research Associate in Cylab at Carnegie Mellon University. He received his Ph.D. in Computer Science from the University of Texas at San Antonio. His research interest broadly lies in investigating practically relevant problems of Computer Security and Privacy. His current research focuses on leveraging formal verification and program analysis techniques to check compliance of a system implementation, against well-defined policies, properties, and standards. He won the best paper award at the ACM SACMAT '12. He has also served as a program committee member of ACM SACMAT and ACM CCS.
Ibrahim Demir is an Assistant Professor at the Civil and Environmental Engineering department, and Associate Research Faculty Engineer at the IIHR – Hydroscience and Engineering. Dr. Demir has appointments at the Iowa Informatics Initiative and Department of Electrical and Computer Engineering at the University of Iowa. Dr. Demir received his PhD degree on Environmental Informatics at the University of Georgia. Dr. Demir’s research focuses on hydroinformatics, environmental information systems, scientific visualization, big data analytics, and information communication. Dr. Demir currently serve at Editorial Board of Environmental Modeling and Software journal (Elsevier), and various national and international informatics and cyberinfrastructure committees including the CUAHSI Informatics Committee, NSF EarthCube Technology and Architecture Committee, Unidata User Committee, and International Joint Committee on Hydroinformatics (IWA/IAHR/IAHS). He is the lead architect and developer of many novel research and operational information systems including Iowa Flood Information System, Iowa Water Quality Information System, NASA IFloodS and SMAP Satellite Mission Information Systems, Georgia Watershed Information System and many others.
Bryce J. Dietrich received his PhD in Political Science from the University of Illinois. He is currently an Assistant Professor of Social Science Informatics, holding appointments in the Department of Political Science and the Department of Sociology. His research uses novel quantitative, automated, and machine learning methods to analyze non-traditional data sources such as audio (or speech) data and video data. He uses these to understand the causes and consequences of elite emotional expression in a variety of institutional settings, with a particular emphasis on non-verbal cues, such as vocal pitch. His work has received grant support from Amazon, C-SPAN, and the Kinder Institute on Constitutional Democracy. His dissertation "It’s Not What You Say, But How You Say It" also won the Kathleen L. Burkholder Prize for best dissertation in political science from the University of Illinois.
Bin He is an assistant professor in the Biology Department at the University of Iowa. His research interest is in the evolution of Gene Regulatory Networks (GRNs). In particular, his lab studies how GRNs controlling stress response evolved in C. glabrata, a commensal and opportunistic pathogen yeast in human, as compared to its free-living relative, S. cerevisiae. The goal of the lab is to elucidate the evolutionary strategies used by the commensal yeast to adapt to the host environment, both to gain a genera understanding of gene regulatory network evolution, and also to provide insight into the treatment of commensal microbe associated infections. Before joining U of Iowa, Bin was a graduate student with Dr. Marty Kreitman in the Department of Ecology and Evolution at The University of Chicago, where his population genetics study elucidated the role of natural selection in transcription factor binding sites evolution in Drosophila enhancers; he also worked on a novel approach to identify disease modifying variation in a fly model of human neonatal diabetes. After getting his Ph.D., he joined Erin O’Shea’s lab at Harvard Center for Systems Biology, where he began his work on the evolution of stress response network in yeast. He was a visiting scholar at Princeton University in Julien Ayroles and Peter Andolfatto’s labs before coming to Iowa.
Hans J Johnson
Hans J. Johnson, Ph.D., Associate Professor Electrical and Computer Engineering (Primary), Biomedical Engineering, Psychiatry -- His primary research interest involves accelerating research discovery through the efficient analysis of large scale, heterogeneous, multi-site data collections using modern High Performance Computing (HPC) resources. Specifically, he directs research efforts that deploy software-engineered solutions that harness the power of modern HPC infrastructures (many-core laptops/accelerator cards, distributed storage solutions, centralized data repositories, and large cluster computing resources) so that well established single-user analysis tools can be repurposed and deployed for analysis and knowledge extraction from large data repositories. His current projects are interdisciplinary collaborations that have resulted in many funded grants. These collaborations allow him to be significantly involved in software engineering and informatics projects. His primary contributions to those efforts focus on developing and deploying the tools necessary to monitor, manage, analyze and foster collaborative data sharing for large-scale multi-site projects. His formal training in Biomedical, Electrical and Computer Engineering provide a solid foundation for his academic research objective of accelerating research by employing rigorous software engineering practices and leveraging high performance computing. His efforts have been widely acknowledged as he is the lead developer on 14 projects hosted by the Neuroinformatics Tools and Resources Clearing House, he is the most prolific contributor to the Insight Toolkit v4 package, and President of the Insight Software Consortium. He has also been elected to leadership roles on several international multi-site studies (PREDICT-HD, TRACK-HD, ITK). He is excited by the recent initiatives that that the University of Iowa has undertaken, and believe that the need for strong software engineering and informatics collaborations are necessary for their success. In particular, the Aging Mind and Brain, Genetics, and Water Sustainability cluster hires each have significant needs for managing the complexities of leveraging large data for the generation of new discoveries. The recent investment in HPC resources (Helium/Neon computational clusters, centralized storage solutions, and upgrades to core networking capabilities) provides a modern platform for conducting research. It is incredibly exciting to have skills at the nexus of these two initiatives where I can apply software engineering and informatics technologies to leverage the research infrastructure for solving the complex scientific problems of tomorrow.
Caglar Koylu is an Assistant Professor of GIScience with a joint appointment at the Iowa Informatics Initiative and the department of Geographical and Sustainability Sciences. He received his Ph.D. in Geography in 2014 from University of South Carolina (USC). Before joining UI, he worked as a Postdoctoral researcher at USC. While his research interests are in the broad areas of spatial data mining, space-time analysis and visualization, human-computer interaction and visual analytics, his particular focus is developing new theories, visual and computational approaches to understand complex patterns from large (Big) geo-social networks, i.e., networks embedded in geographic space and time such as migration, human mobility, networks of social media, commodity flows and information flows. Caglar has published in peer-review journals, presented at various conferences, and served as a reviewer for journals such as IJGIS and CaGIS.
Amaury Lendasse was born in 1972 in Belgium. He received a M.S degree in Mechanical Engineering from the Universite Catholique de Louvain (Belgium) in 1996, a M.S. in Control in 1997 and a Ph.D. in Applied Mathematics in 2003 from the same university. In 2003, he was a postdoctoral researcher in the Computational Neurodynamics Lab at the University of Memphis. From 2004 to 2014, he was a senior researcher and an Adjunct Professor in the Adaptive Informatics Research Centre in the Aalto University School of Science (better known as the Helsinki University of Technology) in Finland. He has created and lead the Environmental and Industrial Machine Learning at Aalto. He is now an Associate professor at The University of Iowa (USA) and a visiting Professor at Arcada University of Applied Sciences in Finland. He was the chairman of the annual ESTSP conference (European Symposium on Time Series Prediction) and member of the editorial board and program committee of several journals and conferences on machine learning. He is the author or coauthor of more than 200 scientific papers in international journals, books or communications to conferences with reviewing committee. His research includes Big Data, time series prediction, chemometrics, variable selection, noise variance estimation, determination of missing values in temporal databases, nonlinear approximation in financial problems, functional neural networks and classification.
Daniel K Sewell
Daniel Sewell received his PhD in statistics from the University of Illinois in 2015. He is currently an assistant professor of Biostatistics in the College of Public Health at the University of Iowa. His primary area of research is in statistical models and inference for network data, and in particular the statistical analysis of dynamic social networks. He has also contributed to other subfields of statistics, such as clustering and particle filtering, and holds interest in broad research topic areas such as Bayesian statistics and statistical computation. As a graduate student, he was selected as a student presenter at the Midwest Statistical Research Colloquium, was a finalist for the Norton Prize for Outstanding Doctoral Thesis in Statistics, and, along with his collaborators from the University of Illinois, won the Patrick J. Fett Award for best paper on the scientific study of Congress and the Presidency. He has collaborated with and provided consulting for a large number of researchers in over fifteen distinct fields of study. He has presented at various conferences and universities, acted as a reviewer for several statistical journals, is a member of the American Statistical Association, the Institute of Mathematical Statistics and the International Society for Bayesian Analysis.
M. Zubair Shafiq received his PhD degree in computer science from Michigan State University in 2014. He is an assistant professor of computer science at the University of Iowa. He is part of the Iowa Informatics Initiative. His research interests are in the broad areas of networking and security, with a focus on measurement and performance evaluation of wireless networks, content delivery networks, and online social networks. He received the best paper award from the 2012 IEEE International Conference on Network Protocols. He was also honored with the 2013 Fitch Beach Outstanding Graduate Research Award, which is the most prestigious award given annually for graduate research by the College of Engineering, Michigan State University.
Metal surfaces are ubiquitous in catalysts – from proton exchange membrane fuel cells to catalytic converters in car exhausts – and we rely on their ability to lower activation energy barriers for kinetically demanding transformations. To undertake catalysis, bonds between the metal surface and adsorbed molecules are made and broken. To design better catalysts, we need to understand where the electrons reside and how they behave during these reactions, i.e. their electronic structure.
Sanvesh Srivastava is an Assistant Professor the Department of Statistics and Actuarial Science and a member of Iowa Informatics Initiative. His research aims to develop flexible Bayesian methods and efficient computational algorithms for big data sets, tailored for both their complexity and size. Motivating examples include big data in genomics, medical imaging, and recommender systems. Simultaneously optimizing for the size and complexity is a challenge with current Bayesian methods. He is developing novel and computationally tractable Bayesian methods using principles from machine learning and optimal transportation. Before coming to the University of Iowa, Sanvesh received his Ph.D. in Statistics in August, 2013 from Purdue University, where he also won I.W. Burr Award for "promise of contribution to the profession as evidenced by academic excellence in courses and exams, by the quality of research, and by excellence in teaching and consulting." After Ph.D., he spent two years at Duke University and Statistical and Applied Mathematical Sciences Institute (SAMSI) as a postdoctoral researcher. He has extensive experience in collaborating with scientists and teaching statistics to students from diverse areas and varied expertise.
Fatima Toor is an Assistant Professor at the electrical and computer engineering department with a joint appointment at the Iowa Informatics Initiative and the Optical Science and Technology Center. Her current research involves the design, fabrication, and testing of cutting edge photonics devices for applications in the health, environment, and energy industries. Prior to the University of Iowa, she was a Research Analyst at Lux Research, a multinational technical advisory firm, where she helped global clients – Innovation 1000 corporations, leading institutional investors, utilities, and public policy makers – make better strategic decisions and monitor the ever changing global solar market. Before joining Lux, she was a Postdoctoral Researcher in the Silicon Materials and Devices group at the National Renewable Energy Lab (NREL). Professor Toor obtained her Ph.D. and M.A. in electrical engineering from Princeton University where she developed spectrally high performing InGaAs/InAlAs/InP based mid-infrared wavelength quantum cascade lasers (QCLs). Professor Toor is a member of APS, IEEE, OSA, Sigma Xi, and SWE. She has published in many peer-reviewed scientific journals, presented at various scientific conferences across the globe, and a reviewer for several APS, IEEE, OSA and ACS journals.
Jun Wang is a Professor in Department of Chemical and Biochemical Engineering with a joint appointment at the Iowa Informatics Initiative and the Center for Global and Regional Environmental Studies. Prior to joining University of Iowa, he worked in University of Nebraska – Lincoln (UNL) first as Assistant Professor and then Associate Professor with university-selected Rosowski professorship. His current research focuses on the integration of satellite remote sensing and chemistry transport model to study air quality, wildfires, and aerosol-cloud interaction. He also enjoys interdisciplinary research and has worked in in areas related to public health, agriculture, climate change, renewable (solar and wind) energy, supercomputing, visualization, data mining, and education in Earth Science. Jun Wang has authored or co-authored ~90 citable works in the peer-reviewed literature. He has been a science team member of several NASA missions, and a lead/co-lead for several projects funded by NOAA, DoD, USDA, and NSF. He received the NOAA Climate and Global Change Postdoctoral Fellowship in 2005, NASA’s New Investigator award in 2008, UNL’s “Academic Star” award in 2009 for ““taking the art of mentoring to new height”, and NASA’s Group Achievement award for Suomi-NPP in 2012 and TEMPO in 2013.
Tong Wang is an Assistant Professor of Management Sciences at the Tippie College of Business and a member of Iowa Informatics Initiative. She received her Ph.D. in Computer Science from the Massachusetts Institute of Technology in 2016. Her general research interests are in machine learning, data mining, and their application in computational criminology, healthcare, marketing, etc. Her research on crime data mining is the second place winder in "Doing Good with Good OR” at INFORMS 2015, and has been implemented by the New York Police Department. Her work on crime data mining has been reported in multiple media including Wikipedia.
Tianbao Yang joined the Computer Science Department at UI in 2014. He received his Ph. D. in Computer Science in 2012 from Michigan State University. Before joining UI, he worked as a researcher at NEC Laboratories America and GE Global Research. His research interests lie at the crossroads of machine learning and big data analytics. He has focused on several research topics, including deep learning, distributed optimization, stochastic optimization, and randomized algorithms in machine learning. He has published over 40 papers in prestigious machine learning conferences and journals. He has won the Mark Fulk Best student paper award at 25th Conference on Learning Theory (COLT) in 2012. Dr. Yang also served as (senior) program committee or reviewer for several conferences and journals, including AAAI, CIKM, UCAI, ACML, NIPS, TKDD, TKDE.
Xun Zhou is an Assistant Professor of Management Sciences at the Tippie College of Business, University of Iowa. Prior to joining UI, he received a Ph.D. in Computer Science from the University of Minnesota in June 2014. His general research interests are data mining and data management, with an emphasis on spatio-temporal big data analytics and mining, spatial database and Geographic Information Systems (GIS). Xun’s work has been recognized with best paper awards at international conferences and workshops such as BigSpatial’13 and SSTD’11. Xun served as program committee members in SSTDM’14, ACM SIGSPATIAL PhD Symposium’14. He also served as a reviewer for conferences and journals including IEEE TKDE, Geoinformatica, ACM KDD, IEEE ICDM, ACM SIGSPATIAL.
Andrea L Flaherty
Andrea Flaherty is the program coordinator for the university's graduate program in informatics (IGPI) and assistant to the director of UI3. She has extensive experience in program administration, event planning and conference management, and previously served as a program specialist in the Department of Mechanical and Industrial Engineering. A native of Davenport, she has a bachelors degree from the University of Iowa.
Spencer Kuhl serves the University of Iowa Informatics Initiative as an application developer, research consultant, and data visualization specialist. He exercises a dual appointment in the Office of the Vice President for Research and Economic Development as Dr. Daniel Reed’s research scientist where he explores data visualization technologies, high performance computing economics, radio frequency technologies, extreme-low-power sensors, and STEM educational outreach activities.
Before joining UI3, Mr. Kuhl was a research assistant, device engineer, and software developer at the WM Keck Dynamic Image Analysis Facility where he investigated 3D cellular reconstruction and morphometrics, monoclonal antibody cancer therapeutics, in-vitro 3D extracellular-matrix human primary tumor microenvironments, he also developed four dimensional long-term live-cell observational technologies, antibody micro-array printers, micro-fluidic and chaotic flow devices, novel microscope customizations and 3D morphometic analysis software.
Kang P Lee
Kang Lee serves as a data scientist at UI3 and ITS-RS. As a data scientist, or a data analytics consultant, he stands ready to help researchers on campus at every step of data analysis such as collecting, processing, analyzing data, and ultimately gaining meaningful insight from data. He earned his Ph.D. degree in Computer Science from Seoul National University. After graduation, he worked as a data scientist at Samsung Big Data Center, where he led a number of big data based market research projects.
Sai Kumar Ramadugu
Sai Ramadugu is hired as Informatics Consultant in UI3 and ITS- Research Services. Sai holds a doctoral degree from University of Iowa and has worked extensively in computational chemistry and biochemistry. In his current role Sai concentrates coordinating training and workshops opportunities for students, staff and faculty (OpenMP, MPI, Big Data, OpenACC from Pittsburgh Supercomputing Center and Data Science Institute from UI), 1-1 consultations for campus community regarding high performance computing applications, software installs, data/storage, etc. You can reach Sai via email.
Ben Rogers is the Associate Director for Informatics Services in UI3 and the Sr. Director for Research Services in Information Technology Services. Ben is responsible for setting strategic direction and coordinating the day to day operations of Research Services and the Services component of the Informatics initiative. Ben has experience working in high performance computing, data storage systems, medical imaging, clinical and translational science, and working with research projects in diverse disciplines. His undergraduate work was in Computer Science and Physics and he later earned an MBA, all from the University of Iowa.