The School of Engineering welcomes our seven new faculty members to the University. Hailing from several distinguished institutions, these new instructors bring extensive experience to Rutgers, having performed research in several exciting fields. We look forward to their continued growth and innovation as part of the Rutgers Engineering faculty.
Maryam Dehnavi recently worked as a postdoctoral researcher at the Massachusetts Institute of Technology, where she worked on machine learning and stencil computations. Her research included improving previous methods for finite-element method computations and other algorithms. Her goal is to create more efficient methods by which data-heavy or otherwise large-scale computations are performed by parallel systems. Previously she worked at Qualcomm Incorporated, where she developed and optimized code to improve applications. She has also been a visiting scholar at the University of California Berkeley and Irvine, where she likewise studied methods of improving software to work more effectively with hardware. She has been granted multiple scholarships and grants by the Natural Sciences and Engineering Research Council of Canada, and most recently earned a postdoctoral fellowship by the Quebec Research Fund.
Weihong Guo’s chief research interest is in statistical monitoring of manufacturing processes to ensure optimum product quality. As a researcher at the University of Michigan she has also studied data fusion for system improvement, sensing, modeling, and monitoring of profile data, and quality-oriented design. Her previous work has included battery manufacturing quality control, monitoring of ultrasonic welding processes, resource allocation, and surgical treatment prediction methods. Her work on the latter earned her first place in the 2014 Institute for Operations Research and the Management Sciences Minority Issues Forum Poster Competition. She has also been a Rackham Predoctoral Fellowship recipient.
Vishal Patel’s key research interests are in machine learning, signal/image processing, computer vision processing, and security and privacy. He is a co-principal investigator on a Defense Advanced Research Projects Agency (DARPA) study analyzing fingerprints as a security feature for mobile devices. After earning his doctorate studying visual and atomic representations of signals, he worked and taught at the University of Maryland’s Center for Automation Research. Other research areas include approximation theory with wavelets, face recognition by computers, and biometrics. He is the principal investigator on a LADAR imaging study hosted by an Army Research Laboratory with General Dynamics. He was the recipient of a 2015 Computer Vision and Pattern Recognition Outstanding Reviewer Award.
Jonathan Singer’s primary research interest is the generation of hierarchically structured materials via scalable micro/nanomanufacturing processes to incorporate the extraordinary properties of nanostructures into complex geometries. This is accomplished through combinations of “bottom-up” and “top-down” lithographic techniques. Such hybrid techniques shift the burden of high resolution patterning to a high- throughput process, while retaining a sufficient degree of control for targeted applications in, for example, alternative energy, microrobotics, and medical implants. Previously, Jonathan conducted his doctoral research at MIT’s Department of Materials Science and Engineering focusing on hybrid laser direct write lithography for phoxonic metamaterials and completed a Postdoctoral Associateship at Yale University’s Department of Chemical and Environmental Engineering primarily researching the nanoimprint of photovoltaic materials and bulk metallic glass alloys. He has been recognized by the Materials Research Society through their Silver Graduate Student Award and was recently named a Yale Scientific Teaching Fellow.
Jay Sy’s research interests include advancing medical technology by applying biological chemistry to new devices. He earned his Ph.D. while studying methods to deliver medication to the human heart. Prior to that, he studied bioengineering at the University of Pennsylvania, focusing on tissue engineering. Before joining Rutgers, he was a postdoctoral fellow at the Massachusetts Institute of Technology, studying drug delivery to rodent brains to treat brain cancer. In 2013 he received the National Institutes of Health’s Pathway to Independence Award, to help him become a faculty member from being just a research associate. He has also previously been granted fellowships by the National Science Foundation and the Department of Homeland Security.
George Tsilomelekis joins the Department of Chemical and Biochemical Engineering with extensive experience studying catalytic materials. His research interests focuses on the rational implementation of spectroscopic methods under realistic reaction conditions toward understanding complex catalytic reactions in the broad field of the conversion of renewable and alternative energy sources. Previously he was a postdoctoral research associate with the University of Delaware, studying solvent effects in biomass processing. As a graduate student he studied the molecular structure of catalytic systems based on supported metal oxides and established structure-reactivity relationships via Operando spectroscopy and vibrational isotope effects.
Haoran Zhang’s research includes metabolic engineering, synthetic biology, natural product biosynthesis, and applied microbiology. He most recently worked with the Massachusetts Institute of Technology’s Laboratory for Bioinformatics and Metabolic Engineering. Some of his other research has involved creating biochemical products, particularly through the use of Escherichia coli bacteria for use in various processes. He received his doctorate after studying E. coli products and their uses. In 2012 he was honored by Xiamen University as a Distinguished Alumnus. His other work includes metal bio-reduction, or the formation of metals by distilling them from plant products.