Biography
Research Interests

Previously an associate professor of chemical & environmental engineering, biomedical engineering, and molecular biophysics and biochemistry at Yale University, Wilson joined Georgia Tech in 2016.   His research group focuses on establishing an integrated experimental and computational framework to translate our understanding of the fundamental principles of biophysics and biochemistry (i.e., the physicochemical properties that confer function) into useful processes, devices, therapies, and diagnostics that will benefit society.
Education
PhD, Rice University

Vida Jamali earned her Ph.D. in chemical and biomolecular engineering from Rice University under the guidance of Professor Matteo Pasquali and her B.S. in chemical engineering from Sharif University of Technology. Jamali was a postdoctoral researcher in Professor Paul Alivisato's lab at UC Berkeley and Kavli Energy Nanoscience Institute before joining Georgia Tech. The Jamali Research Group uses experimental, theoretical, and computational tools such as liquid phase transmission electron microscopy, rheology, statistical and colloidal thermodynamics, and machine learning to study the underlying physical principles that govern the dynamics, statistics, mechanics, and self-organization of nanostructured soft materials, in and out of thermal equilibrium, from both fundamental and technological aspects.

Anant Paravastu holds bachelors (MIT, 1998) and Ph.D. degrees (UC Berkeley, 2004) in chemical engineering. His Ph.D. research with Jeffrey Reimer focused on the use of lasers to control nuclear spin polarizations in the semiconductor GaAs. From 2004 to 2007, he worked as a postdoc at the Laboratory of Chemical Physics at NIH with Robert Tycko, where he learned to apply nuclear magnetic resonance to structural biology. Paravastu’s early structural biology work focused amyloid fibrils of the Alzheimer’s β-amyloid peptide. He was part of the team and community that showed that amyloid fibril formation is a complex phenomenon, with individual peptides exhibiting multiple aggregation pathways capable of producing multiple distinct aggregated structures. Between 2008 and 2015, Paravastu worked as an assistant professor at Florida State University and the National High Magnetic Field Laboratory. Paravastu started his present position at Georgia Tech in 2015. Paravastu’s laboratory presently focuses on 3 general lines of inquiry: 1) structural analysis of peptides that were rationally designed to assemble into nanostructured materials, 2) nonfibrillar aggregates of the Alzheimer’s β-amyloid peptide, and 3) aggregation due to misfolding of proteins driven away from their natural folds.

Ravi Kane is the Garry Betty/V Foundation Chair and GRA Eminent Scholar in Cancer Nanotechnology. He received a B.S. in Chemical Engineering from Stanford University in 1993. Also, he received an M.S. in Chemical Engineering Practice and a Ph.D. in Chemical Engineering from MIT, working with Bob Cohen and Bob Silbey. After postdoctoral research with George Whitesides in the Department of Chemistry and Chemical Biology at Harvard University, he joined Rensselaer Polytechnic Institute (RPI) as an assistant professor in 2001. He was promoted to associate professor in 2006, to full professor in 2007, and to the P.K. Lashmet Professor in 2008. He served as the head of RPI’s Howard P. Isermann Department of Chemical and Biological Engineering before moving to Georgia Tech in 2015. Prof. Kane has graduated 27 Ph.D students and contributed to over 130 scientific publications.

Nian Liu began as an Assistant Professor at Georgia Institute of Technology, School of Chemical and Biomolecular Engineering in January 2017. He received his B.S. in 2009 from Fudan University (China), and Ph.D. in 2014 from Stanford University, where he worked with Prof. Yi Cui on the structure design for Si anodes for high-energy Li-ion batteries. In 2014-2016, he worked with Prof. Steven Chu at Stanford University as a postdoc, where he developed in situ optical microscopy to probe beam-sensitive battery reactions. Dr. Liu 's lab at Georgia Tech is broadly interested in the combination of nanomaterials, electrochemistry, and light microscopy for understanding and addressing the global energy challenges. Dr. Liu is the recipient of the Electrochemical Society (ECS) Daniel Cubicciotti Award (2014) and American Chemical Society (ACS) Division of Inorganic Chemistry Young Investigator Award (2015).

Lily Cheung got her research start as a sophomore at Rutgers University, where she graduated Summa Cum Laude with a B.S. in Chemical Engineering in 2008. She then earned her Ph.D. in Chemical Engineering from Princeton University in 2013. Under the supervision of Stanislav Shvartsman, she characterized gene regulatory networks controlling the development of the model organism Drosophila melanogaster, using a combination of molecular biology, genetics, and reaction-diffusion modeling.

During her postdoctoral training with Wolf Frommer at the Carnegie Institution for Science, she designed biomolecular sensors to quantify sugar transport in plants. Her current interests include the use of high-throughput quantitative techniques and mathematical modeling to advance our understanding of how metabolic and gene regulatory networks interact to control plant growth.

Lily is the recipient of a NSF NPGI Postdoctoral Fellowship in Biology, a NSF CAREER Award, and a Human Frontier Science Program Early Career Award.

The Blazeck Lab tackles challenges at the interface of immunology, engineering, and metabolism to improve human health. We utilize our expertise in cellular and protein engineering to control biological function and to develop novel therapies to fight disease.

Synthetic Immune Systems

Our immune system uses very complex processes to make exquisitely specific receptors that recognize disease causing agents, and much of our ability to fight diseases is contingent upon the development of a diverse repertoire of immune receptors. Many questions remain unanswered about these immune receptors. For instance, at a population level, can we characterize the millions of receptors each person makes? And then further determine which of these millions of receptors is most important towards recognizing and targeting a pathogen? And can we control the generation of immune receptors to have desired properties? We are striving to answer these questions by harnessing our immune system’s power in a synthetic setting to improve understanding and treatment options for numerous diseases, while developing applications for vaccine design, personalized medicine, and enzyme engineering.

Engineering Cellular Therapies

Immunotherapies are treatments designed to modulate the immune response that have shown astounding clinical potential, yet there are no current treatments with guaranteed success. We are working to engineer cellular systems with controllable, enhanced, and non-native functions that improve their impact and capability. By developing high throughput technologies to interrogate immune function, we hope to translate our findings into improvements in the next generation of cellular therapeutics. 

Developing Proteins that Fight Cancer and Control Metabolism

It is widely accepted that cancer cells have a significantly altered genomic and metabolic makeup relative to normal cells, but how can we best target these differences? By combining our expertise in metabolism and therapeutic protein engineering, are working to engineer proteins to directly target and fight cancer. For instance, certain enzymes can control the metabolic environment around tumors to inhibit their growth or to stimulate a native anti-cancer immune response. We utilize directed evolution approaches to optimize protein function and efficacy.

Jeong Woo Lee is a member of the Parker H. Petit Institute for Bioengineering and Bioscience.

Grover’s research activities in process systems engineering focus on understanding macromolecular organization and the emergence of biological function. Discrete atoms and molecules interact to form macromolecules and even larger mesoscale assemblies, ultimately yielding macroscopic structures and properties. A quantitative relationship between the nanoscale discrete interactions and the macroscale properties is required to design, optimize, and control such systems; yet in many applications, predictive models do not exist or are computationally intractable.

The Grover group is dedicated to the development of tractable and practical approaches for the engineering of macroscale behavior via explicit consideration of molecular and atomic scale interactions. We focus on applications involving the kinetics of self-assembly, specifically those in which methods from non-equilibrium statistical mechanics do not provide closed form solutions. General approaches employed include stochastic modeling, model reduction, machine learning, experimental design, robust parameter design, and estimation.