Dec. 28, 2016

Mihail Popescu

Mihail Popescu has received a MS in Medical Physics in 1995, a MS in Electrical Engineering in 1997 and a PhD in Computer Science in 2003 from the University of Missouri, Columbia, Missouri. Dr. Popescu has published seven articles in refereed journals, 20 conference papers, one book, and one book chapter. His research focus has been on eldercare technologies, medical decision making, and epigenetic pattern discovery.

Dec. 28, 2016

Satish Nair

Dr. Nair’s career commitment has been mathematical analysis & design of complex systems for a variety of applications including control, using both computational modeling and experimental techniques. His interests during the past eight years have been in the area of computational neuroscience, at the molecular, cellular, network, and behavioral levels. He has developed two new graduate courses (Theoretical Neuroscience I and II) that focus on intra- and inter-cellular neuronal modeling, and include usage of NEURON and GENESIS packages. Seeded by an NSF CCLI grant, he and biology colleagues Schulz and Schul, designed and have been team-teaching once a year, an…

Dec. 28, 2016

Chi-Ren Shyu

Chi-Ren Shyu (he/him/his) is Director of MUIDSI, Associate Dean for Graduate Education and Strategic Initiatives, and Chair of the Executive Committee for the Mizzou Quantum Innovation Center. Dr. Shyu has organized and chaired technical program committees for several IEEE conferences, including IEEE HealthCom, IEEE BigMM, IEEE BIBM, and IEEE BIBE. He represents MU on the Southeast Conference (SEC) Artificial Intelligence Consortium and the Missouri Department of Higher Education and Workforce Development’s Advisory Committee for Building Missouri’s AI Talent Pipeline (2026). He is the PI of Mizzou’s NSF CyberCorps SFS project ($3.6M). Since joining MU in 2000, Dr. Shyu has…

Dec. 28, 2016

Jianlin Cheng

Dr. Jianlin Cheng’s research is focused on bioinformatics, systems biology, machine learning and data mining. To date, his group has designed and developed a variety of cutting-edge computational methods for protein structure and function prediction, proteomics, genomics, biological network simulation, and general machine learning. His protein structure prediction methods were ranked among the best in the last three consecutive biannual Critical Assessment of Techniques for Protein Structure Prediction (CASP7, CASP8, and CASP9), from 2006 to 2010. The bioinformatics tools and web services produced by Dr. Cheng’s research are publicly available and used by life scientists from around the world.