Skip to main content

New Faculty — Year 2016-17

Annual Lists

Information on each faculty member is relevant to the year the faculty member joined the College of Engineering. Check the departments’ websites for more current information.

Department of Biological and Agricultural Engineering

Dr. Celso Castro-Bolinaga

Assistant Professor
Ph.D. (2016), Virginia Tech

Research Interests: River mechanics and sediment transport, environmental fluid mechanics, and computational fluid dynamics

Castro-Bolinaga received his M.S. and Ph.D. in civil engineering from Virginia Tech in December of 2012 and August of 2016, respectively. Castro-Bolinaga completed his undergraduate studies in January of 2009 at Universidad Católica Andrés Bello in Caracas, Venezuela, where he then worked for nearly two years as a hydraulic project engineer in a private consulting firm. His research focuses on the application of computational fluid dynamics to environmental fluid mechanics, and river hydrodynamics and morphodynamics. It encompasses natural processes that are primarily governed by the dynamic interactions among water flow, sediment transport and the geomorphic evolution of the riverbed. Specifically, his work aims to provide a better understanding of how the scales associated with these interactions govern the propagation of large amounts of loose sediment that are suddenly deposited within riverine environments, referred to as sediment pulses.

  • Castro-Bolinaga, C.F., and P. Diplas (2014), Hydraulic Modeling of Extreme Hydrologic Events: Case Study in Southern Virginia, Journal of Hydraulic Engineering, 05014007.
  • Castro-Bolinaga, C.F., E. Zavaleta, and P. Diplas (2014), A Coupled Modeling Effort to Study the Fate of Contaminated Sediments Downstream of the Coles Hill Deposit, Virginia, USA, in: Xu, Y.J. et al. (Eds.) IAHS Publication 367 Sediment Dynamics from the Summit to the Sea, proceedings of a symposium held in New Orleans, Louisiana, USA, 11-14 December 2014.
  • Castro-Bolinaga, C.F., P. Diplas, and R.J. Bodnar (2016), An Adaptive Morphodynamic Model for Water Flow, Sediment Transport, and Riverbed Evolution in Alluvial Rivers, Advances in Water Resources (under review).
  • Castro-Bolinaga, C.F., P. Diplas, and R.J. Bodnar (2016), Numerical Analysis of the Propagation of Fine-Grained Sediment Pulses in Alluvial Rivers, Environmental Fluid Mechanics (in preparation).
  • Castro-Bolinaga, C.F., E. Zavaleta, P. Diplas, and R.J. Bodnar (2016), Examining the Fate of Sediment Pulses Under Severe Hydrologic and Hydraulic Conditions, Journal of Hydraulic Research (in preparation).
Dr. Steven Hall

Associate Professor
Director, Marine Aquaculture Research Center (Marshallberg, NC)
Ph.D. (1998), Cornell University, Ithaca NY; PE (NY, LA)

Research Interests: Aquacultural engineering, coastal bioengineering, energy, water and resource efficiency in agricultural and aquacultural systems, automated systems in biological engineering, environmental sustainability engineering

Hall earned a B.S. in mechanical engineering from the State University of New York at Buffalo, an M.S. in agricultural engineering from the University of California at Davis and a Ph.D. in biological and agricultural engineering at Cornell University. He was the first postdoctoral fellow in Sustainable Agriculture at McGill University, Montreal, Canada. Prior to joining the NC State faculty, he was assistant, associate and full professor; and graduate chair at Louisiana State University (LSU) and the LSU AgCenter in Baton Rouge, Louisiana, where he held appointments in biological and agricultural engineering and was on the faculty at the LSU AgCenter Aquaculture Research Station. His current projects include engineering approaches to understanding effects of environmental variables including temperature, salinity and water quality on health of eastern oysters Crassostrea virginica, and design of bioengineered systems for culture of aquatic species for coastal protection and restoration, and for food and other resources. Other species of interest include sturgeon, tilapia, salmonids, crustaceans and aquatic plants. Designs and studies focus on biological, smart and automated solutions to aquacultural, environmental and coastal challenges with an interest in enhancing sustainability. He collaborates with a variety of academic, industrial and environmental professionals as director of the NC State University Marine Aquaculture Research Center at Marshallberg, with teaching, research and extension appointments. Hall is past president of the Aquacultural Engineering Society, Fellow of the American Scientific Affiliation, and has received numerous teaching, research and outreach awards.

  • Rybovich, M., M. LaPeyre, S. Hall, J. LaPeyre, 2016. Increased temperatures Combined with Lowered Salinities Differentially Impact Oyster Size Class Growth and Mortality. Shellfish Rsch. 35:1, 101-113.

UNC/NC State Joint Department of Biomedical Engineering

Dr. Derek Kamper

Associate Professor
Ph.D. (1997), Ohio State University

Research Interests: Upper extremity rehabilitation, hand neuromechanics and modeling, mechatronic devices and virtual reality for therapy

Kamper received a B.E. in electrical engineering from Dartmouth College, and M.S. and Ph.D. degrees in biomedical engineering from Ohio State University. He then completed a postdoctoral fellowship at Northwestern University and the Rehabilitation Institute of Chicago, where he subsequently worked as a research scientist. He later joined the faculty at the Illinois Institute of Technology, eventually becoming an associate professor. His research has focused on improving functional outcomes for individuals following neurological injury, such as spinal cord injury or stroke. In particular, Kamper has worked to understand the mechanisms leading to impairment, through both experiments and modeling. Knowledge obtained from these studies has led to the development of therapeutic interventions, including actuated orthotic gloves and virtual reality training environments.

  • Fisher H, Triandafilou K, Thielbar K, Ochoa J, Lazzaro E, Pacholski K, Kamper D. Use of a portable assistive glove to facilitate rehabilitation in stroke survivors with severe hand impairment. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2016; 24: 344-51.
  • Qian K, Traylor K, Lee SW, Ellis B, Weiss J, Kamper D. Mechanical properties vary for different regions of the finger extensor apparatus. Journal of Biomechanics 2014; 47: 3094-9.
  • Kamper DG, Fischer HC, Conrad MO, Towles JD, Rymer WZ, Triandafilou K. Fingerthumb coupling contributes to exaggerated thumb flexion in stroke survivors. Journal of Neurophysiology 2014; 111: 2665-2674.
  • Jones C, Wang F, Morrison R, Sarkar N, Kamper D. Design and development of a cable actuated finger exoskeleton for hand rehabilitation following stroke. IEEE/ASME Transactions on Mechatronics, 2012; 19: 131-140.
  • Lee SW, Wilson KM, Lock BA, Kamper DG. Subject-specific myoelectric pattern classification of functional hand movements for stroke survivors. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2011; 19: 558-66.
Dr. David Zaharoff

Associate Professor
Ph.D. (2002), Duke University

Research Interests: Cancer immunotherapy, immunoengineering, biomaterials-based delivery and immunomodulation

Zaharoff received his B.S. in mechanical engineering from the University of Illinois at Urbana-Champaign. He received his Ph.D. in biomedical engineering from Duke University. He was a Cancer Research Training Award and Ruth L. Kirschstein National Research Service Award postdoctoral fellow in the Laboratory for Tumor Immunology and Biology at the National Cancer Institute. Prior to joining NC State, he was interim head, associate professor and a founding faculty member of the Department of Biomedical Engineering at the University of Arkansas As an independent investigator, Zaharoff leverages his multidisciplinary training to engineer translatable biomaterials-based delivery systems to control the spatiotemporal distribution of immunomodulatory agents, with a particular interest in IL-12 family cytokines and immune checkpoint inhibitors.

  • Zaharoff DA et al. 2009, “Intravesical immunotherapy of superficial bladder cancer with chitosan/interleukin-12.” Cancer Res 69(15):6192-9.
  • Zaharoff DA et al. 2010, “Intratumoral immunotherapy of established solid tumors with chitosan/IL-12.” J Immunother 33(7):697-705.
  • Vo JL et al. 2014 “Neoadjuvant immunotherapy with chitosan and interleukin-12 to control breast cancer metastasis.” Oncoimmunology 3(12):e968001.
  • Koppolu BP et al. 2014, “Controlling chitosan-based encapsulation for protein and vaccine delivery.” Biomaterials 35(14):4382-9.
  • Smith SG et al. 2015, “Intravesical chitosan/interleukin-12 immunotherapy induces tumor-specific systemic immunity against murine bladder cancer.” Cancer Immunol Immunother 64(6):689-96.

Department of Chemical and Biomolecular Engineering

Dr. Milad Abolhasani

Assistant Professor
Ph.D. (2014), University of Toronto

Research Interests: Flow chemistry, microfluidics, microscale technologies for energy and environment, continuous nano-manufacturing, microscale transport phenomena

Abolhasani received his B.S. (2008) and M.A.Sc. (2010) in mechanical engineering from Sharif University of Technology and the University of British Columbia, respectively. He obtained a Ph.D. (2014) from the Department of Mechanical and Industrial Engineering at the University of Toronto. Over the course of his doctoral studies, he designed and developed a microfluidic platform for fundamental and applied studies of thermodynamic and mass transfer characteristics of gas-liquid reactions. Prior to joining NC State, he was an NSERC postdoctoral fellow in the Department of Chemical Engineering at MIT (Jensen group), where he developed a modular flow chemistry strategy for in-situ mass transfer and kinetic studies of single/ multi-phase chemical processes including bi-phasic cross-coupling reactions, colloidal synthesis and ligand exchange of semiconductor nanocrystals, and partition coefficient screening of pharmaceutical compounds. Currently, the Abolhasani lab is focused on the development of microscale flow chemistry technologies tailored for studies of (a) fundamental mechanisms involved in the solution-phase processing of organohalide lead perovskite nanocrystals for photovoltaic applications, (b) energy efficient photo-thermal recovery of captured carbon dioxide (CO2) from stationary sources, and (c) thermodynamic characteristics of CO2-triggered switchable solvents as a sustainable and green strategy for distillation-free solvent recovery.

  • M. Abolhasani and K. F. Jensen, “Oscillatory Multiphase Flow Strategy for Chemistry and Biology,” Lab on a Chip, 2016, 16 (15), 2775-2784.
  • M. Abolhasani, C. W. Coley, L. Xie, O. Chen, M. G. Bawendi, and K. F. Jensen, “Oscillatory Microprocessor for Growth and in Situ Characterization of Semiconductor Nanocrystals,” Chemistry of Materials, 2015, 27 (17), 6131–6138.
  • M. Abolhasani, N. C. Bruno, and K. F. Jensen, “Oscillatory Three-Phase Flow Reactor for Studies of Bi-Phasic Catalytic Reactions,” Chemical Communications, 2015, 51 (43), 8916-8919.
Dr. Lilian Hsiao

Assistant Professor
Ph.D. (2014), University of Michigan

Research Interests: Soft matter and colloids, complex fluids, biomimetic and responsive Materials

Hsiao earned her B.S. in chemical engineering from the University of Wisconsin-Madison (2007) and her Ph.D. in chemical engineering from the University of Michigan (2014). She studied nanoemulsion-filled responsive hydrogels during her postdoctoral research at MIT. She is the recipient of the Rackham Predoctoral Fellowship for outstanding doctoral dissertations. The Hsiao group seeks to apply the fundamental understanding of colloidal particles and their microscopic interactions to design soft matter with unusual macroscopic properties. Hsiao is interested in linking the flow and mechanical properties of soft materials to their microscale dynamics and structure. Much of her work will involve using experimental and modeling techniques to design systems for which there is complete control over the particle shape, surface chemistry and assembly kinetics. Anisotropic particles, multi-dimensional lithographic printing and a combination of highspeed confocal microscopy and rheological methods will be used to achieve optimal mechanical and functional properties in a broad class of bio-inspired materials.

  • C. Hsiao & P. S. Doyle. Sequential phase transitions in thermoresponsive nanoemulsions. Soft Matter 11, 8426-8431 (2015).
  • C. Hsiao, B. A. Schultz, J. Glaser, M. Engel, M. E. Szakasits, S. C. Glotzer & M. J. Solomon. Metastable orientational order of colloidal discoids. Nature Communications 6, 8507 (2015).
  • C. Hsiao, H. Kang*, K. H. Ahn & M. J. Solomon. Role of shear-induced dynamical heterogeneity in the nonlinear rheology of colloidal gels. Soft Matter 10, 9254-9259 (2014).
  • C. Hsiao, K. A. Whitaker*, M. J. Solomon & E. M. Furst. A model colloidal gel for coordinated measurements of force, structure, and rheology. Journal of Rheology 58(5), 1485-1505 (2014).
  • C. Hsiao, R. S. Newman, S. C. Glotzer & M. J. Solomon. Role of isostaticity and loadbearing microstructure in the elasticity of yielded colloidal gels. Proceedings of the National Academy of Sciences 109(40), 16029-16034 (2012).

Department of Civil, Construction, and Environmental Engineering

Dr. Ashly Cabas

Assistant Professor
Ph.D. (2016), Virginia Tech

Research Interests: Assessment of seismic hazards with a focus on near-surface effects on ground motions and their associated uncertainties, damping/attenuation characterization for seismic site response analyses and soil-structure interaction

Cabas received her M.S. and Ph.D. in the Department of Civil and Environmental Engineering at Virginia Tech. Cabas’ research focuses on geotechnical earthquake engineering, specifically on improving the assessment of site-specific seismic hazards by achieving better predictions of site response, and on quantifying the uncertainty resulting from common simplifying assumptions. Cabas completed her undergraduate studies at Universidad Católica Andrés Bello in Caracas, Venezuela, where she also worked as a civil engineer for nearly two years. She received first place at the Earthquake Engineering Research Institute (EERI) 2014 Graduate Student Paper Competition for her paper “Vs-ĸ Correction Factors for Input Ground Motions used in Seismic Site Response Analyses.” She recently served as curator of information on geotechnical impacts (specifically landslides and site effects) from the Nepal earthquake of April 25, 2015 as part of the EERI Learning from Earthquakes Program. The goal of her research program is to improve the assessment of seismic hazards by: (a) investigating different physical effects on ground motions, such as the near-surface seismic wave propagation phenomena as encompassed by site and topographic effects as well as soil nonlinear behavior, (b) studying their associated uncertainties; including spatial variability in soil properties, and (c) elucidating the correlation between ground motion parameters and structural response and damage. Her research program will be shaped by well-integrated interdisciplinary efforts and a continuous engagement with engineering practice.

  • Cabas, A. and Rodriguez-Marek, A. (2016), Vs-ĸ Correction Factors for Input Ground Motions used in Seismic Site Response Analyses, Earthquake Spectra (under review).
  • Cabas, A. and Rodriguez-Marek, A. (2017), What Can We Learn from Kappa to Achieve a Better Characterization of Damping in Geotechnical Site Response Models?, paper submitted to the Geotechnical Frontiers 2017 Conference, in Orlando, Florida, March 12-15, 2017.
Dr. Kevin Han

Assistant Professor
Ph.D. (2016), University of Illinois at Urbana Champaign

Research Interests: Visual data analytics for managing civil infrastructure systems. Subtopics to include: autonomous data collection using unmanned vehicles (i.e., UAV and UGV), computer vision algorithm development – 3D reconstruction, SLAM, localization, and object recognition – for automated civil structure detection and quality assessment

Han received his Ph.D. in civil engineering from the University of Illinois at Urbana-Champaign. While pursuing his doctoral degree, he received a Master of Computer Science and served as a part-time faculty member at Parkland Community College. He also received a M.S. in civil engineering and B.A. in architecture at the University of California at Berkeley. His work experience includes numerous internships (one of which is with Caterpillar Inc, where he has filed two patents), and full-time engineering experience as a design/field engineer at the Samsung Austin Semiconductor Plant in Texas.

  • Han, K., Cline, D., and Golparvar-Fard, M. (2015). Formalized Knowledge of Construction Sequencing for Visual Sensing-based Automated Progress Monitoring. Advanced Engineering Informatics.
  • Han, K., and Golparvar-Fard, M. (2015). Appearance-based Material Classification for Monitoring of Operation-level Construction Progress using 4D BIM and Site Photologs. Automation in Construction, Vol. 53. pg 44-57.
  • Han, K., Muthukumar, B. and Golparvar-Fard, M. (2016). Enhanced Appearance-based Material Classification for Monitoring of Operation-level Construction Progress through Removal of Occlusions, 2016 Construction Research Congress, San Juan, Puerto Rico, May 31 – Jun. 2, 2016.
  • Han, K., and Golparvar-Fard, M. (2015). Information Requirement for Model-based Construction Monitoring via Emerging Big Visual Data and BIM: A Case Study, 6th International Conference on Construction Engineering and Project Management, Busan, Korea, Oct. 11-14, 2015.
  • Han, K., and Golparvar-Fard, M. (2015). The Role of Integrated Plan and As-Built Models in Achieving Smooth Flow of Production in Construction, International Conference on Innovative Production and Construction (IPC 2015), Perth, Australia, July 28-31, 2015.

Department of Computer Science

Dr. Patrick Dreher

Research Professor
Ph.D. (1991), University of Illinois, Urbana

Research Interests: Cloud computing, scientific and high performance computing

Dreher is a research professor and member of the Graduate Faculty in the Department of Computer Science. In addition, he also holds a joint appointment as a research scientist at the Massachusetts Institute of Technology’s Computer Science and Artificial Intelligence Laboratory. Dreher has over 25 years of research and R&D management experience in both the application of high performance computing to science and engineering research and in the management of organizations and infrastructure focused on scientific computing. He has served on numerous peer review panels for the Department of Energy, the DoD HPC Modernization Program, and the National Science Foundation. His work in physics is centered on high energy and nuclear physics, especially in the computational aspects pursued within the U.S. Lattice QCD collaboration. Within computer science, he specializes in studying how to effectively apply high performance cloud computing to science and engineering research and works in the area of developing graph algorithms for big data parallel benchmarking. Dreher received his B.S. in physics from Rensselaer Polytechnic Institute, an M.S. in physics from the University of Chicago, and his Ph.D. in physics from the University of Illinois at Urbana. He also earned an M.B.A. from Rensselaer with a concentration in R&D management.

  • Dreher, P., Byun, C., Hill, C., Gadepally, V., Kuszmaul, B., Kepner, J., “PageRank Pipeline Benchmark: Proposal for a Holistic System Benchmark for Big-Data Platforms,” Graph Algorithms Building Blocks (GABB’2016), 30th IEEE International Parallel & Distributed Processing Symposium, IEEE Xplore Digital Library, May 2016.
  • Dreher, P., Vouk, M., “Embedding Cloud Computing Inside Supercomputer Architectures,” In Proceedings of the 6th International Conference on Cloud Computing and Services Science, ISBN 978-989-758-182-3, pages 296-301. DOI: 10.5220/0005912302960301, April 2016.
  • Dreher, P, Vouk, M., Scullin, W., “Toward a Proof of Concept Implementation of a Cloud Framework on Blue Gene Supercomputers for Computational Physics Applications,” Journal of Physics: Conference Series Vol 640 (2015).
Dr. Arnav Jhala

Associate Professor
Co-Director, Visual Narrative Cluster
Co-Director, Digital Games Research Initiative
Ph.D. (2009), NC State University

Research Interests: Computational models of narrative, artificial intelligence in games, visual aesthetics and computer supported game design, human-computer interaction

Jhala received his B.S. in computer engineering from Gujarat University (2001) and M.S. (2004) and Ph.D. (2009) in computer science from NC State University. Jhala’s research group investigates computational structures and methods that are useful in representing and mediating human interpretation and communication of narrative in interactive visual media, such as film and games. The Jhala research group uses symbolic and probabilistic tools to represent and construct coherent visual discourse and apply generative techniques for automated and semi-automated tools to interpret and collaboratively create visual narratives. Past projects include development of games for eliciting aesthetic and emotive preferences in domains such as photographic composition, aesthetics of play for highly skilled game players and gestural aesthetics of dance. Methods used in the lab vary from analysis of existing data sets (such as analysis of movies or game replays), development of games and systems to elicit specific type of behavior and development of novel designs to push the boundaries of creativity through computation.

  • Jhala A., Young R M., Cinematic Visual Discourse: Representation, Generation, and Evaluation, IEEE Transactions on Computational Intelligence and AI in Games 2 (2), 69-81.
  • Yannakakis G., Martínez H., Jhala A., Towards affective camera control in games, User Modeling and User-Adapted Interaction 20 (4), 313-340.
  • Swanson R., Escoffery D., Jhala A., Learning Visual Composition Preferences from an Annotated Corpus Generated Through Gameplay, IEEE Conference on Computational Intelligence in Games (CIG), 2012.
  • Weber B., John M., Mateas M., Jhala A., Modeling Player Retention in Madden NFL-11. AAAI Conference on Innovative Applications of Artificial Intelligence (IAAI), Deployed AI track, 2011.
Dr. Chris Martens

Assistant Professor
Ph.D. (2015), Carnegie Mellon University

Research Interests: Game design tools, programming languages, declarative modeling, interactive narrative, generative methods

Martens received her B.S. in computer science from Carnegie Mellon University in 2008, after which she joined the Ph.D. program at the same institution. She has done research internships at Google New York and INRIA, Palaiseau, France, on type systems and logical frameworks. Her thesis included the development of a new knowledge representation for generative narrative and a new programming language for game modeling called Ceptre. She was a postdoctoral researcher at the University of California, Santa Cruz, until July 2016, where she worked on generative game design. Her current research continues the thread of declarative, logic-based methods for modeling agents, simulations, and mechanics in games and interactive storytelling. She is interested in building more robust mathematical models and more collaborative programming environments for executing and analyzing expressive systems.

  • Chris Martens and Rogelio Cardona-Rivera. Discourse-driven Comic Generation. Proceedings of the International Conference on Interactive Digital Storytelling (ICIDS) 2016 (to appear).
  • Chris Martens, Adam Summerville, Michael Mateas, Sarah Harmon, Noah Wardrip- Fruin, and Arnav Jhala. Proceduralist Readings, Procedurally, Proceedings of the Experimental Al in Games Workshop (EXAG) 2016 (to appear).
  • Chris Martens. Ceptre: A Language for Modeling Generative Interactive Systems. Proceedings of the Artificial Intelligence in Interactive Digital Entertainment (AIIDE) 2015.
  • Chris Martens, Joao Ferreira, Anne-Gwenn Bosser, and Marc Cavazza. Generative Story Worlds as Linear Logic Programs. Proceedings of Intelligent Narrative Technologies (INT) 7, 2014.
  • Chris Martens, Anne-Gwenn Bosser, Joao F. Ferreira, and Marc Cavazza. Linear Logic Programming for Narrative Generation. Proceedings of Logic Programming and Nonmonotonic Reasoning (LPNMR) 2013.
Dr. Alessandra Scafuro

Assistant Professor
Ph.D. (2013), University of Slerno, Italy

Research Interests: Theoretical foundations, practical applications of cryptography

Scafuro received her B.S., M.S. and Ph.D. in computer science from the University of Salerno, in Italy. She was a postdoctoral researcher at the Computer Science Department at UCLA. Prior to joining NC State, she held a joint post-doctoral position at Boston University and Northeastern University. Presently, she studies the problem of designing protocols for secure computation. The goal of secure computation is to allow several parties to compute a function of their joint inputs in such a way that all participants learn the output of the function but do not learn the inputs of the other parties. This problem is relevant in scenarios where multiple parties are interested in evaluating function on sensitive data that must remain private, for example, running tests on medical records. While from a theoretical point of view, this problem has been extensively studied, the challenge today is to design protocols that are efficient and usable in real world applications, such as analysis of large data sets.

  • Hemenway, Z. Jafargholi, R. Ostrovsky, A. Scafuro, D. Wichs. “Adaptively Secure Garbled Circuits from One-Way Function,” Advances in Cryptology– CRYPTO 2016.
  • Garg, S. Lu, R. Ostroovsky, Alessandra Scafuro. “Garbled RAM From One-Way Functions,” Symposium on the Theory of Computing– STOC 2015.
  • Ostrovsky, S. Richelson, A. Scafuro. “Round-Optimal Black-Box Two-Party Computation,” Advances in Cryptology– CRYPTO 2015.
  • Goyal, R. Ostrovsky, A. Scafuro, I. Visconti. “Black-Box Non-black-Box Zero Knowledge,” Symposium on the Theory of Computing– STOC 2014.
  • Canetti, A. Jain, A. Scafuro. “Practical UC security with a Global Random Oracle,” Conference on Computer and Communications Security– CSS 2014.
Dr. Kathryn Stolee

Assistant Professor
Ph.D. (2013), University of Nebraska-Lincoln

Research Interests: Software engineering, program analysis, code search, crowd sourcing, program repair

Stolee received her B.S., M.S., and Ph.D. in computer science from the University of Nebraska-Lincoln. She was the Harpole- Pentair Assistant Professor of Software Engineering at Iowa State University from 2013–15 before starting at NC State as an assistant professor of computer science in January 2016. Currently, Stolee studies software developers, the tools they use, and the programs they write. She is currently exploring how developers use web search to assist with programming and software development activities, developing an approach to automated program repair through semantic code search and building a framework to support testing and analysis of regular expressions. This research all involves a blend of theory, empirical studies and tool development.

  • Carl Chapman, Kathryn T. Stolee, “Exploring regular expression usage and context in Python.” International Conference on Software Testing and Analysis (ISSTA) 2016: 282-293.
  • Yalin Ke, Kathryn T. Stolee, Claire Le Goues, Yuriy Brun, “Repairing Programs with Semantic Code Search.” Automated Software Engineering (ASE) 2015: 295-306.
  • Caitlin Sadowski, Kathryn T. Stolee, Sebastian G. Elbaum, “How developers search for code: a case study.” ESEC/SIGSOFT FSE 2015: 191-201.
  • Kathryn T. Stolee, Sebastian G. Elbaum, Daniel Dobos, “Solving the Search for Source Code.” ACM Trans. Software Engineering Methodology 23(3): 26 (2014).
  • Kathryn T. Stolee, Sebastian G. Elbaum, Matthew B. Dwyer, “Code search with input/ output queries: Generalizing, ranking, and assessment.” Journal of Systems and Software 116: 35-48 (2016).
Dr. Hung-Wei Tseng

Assistant Professor
Ph.D. (2014), University of California, San Diego

Research Interests: High-performance, energy-efficient heterogeneous computer architecture, intelligent fast, non-volatile storage systems, improving application performance through programming languages and compiling techniques

Tseng received his Ph.D. in the Department of Computer Science and Engineering at University of California, San Diego, under the advising of Professor Dean Tullsen. His thesis work, “Data-triggered threads” was selected by IEEE Micro “Top Picks from Computer Architecture” in 2012. Prior to joining NC State, Tseng was a postdoctoral researcher for the Non-Volatile Systems Laboratory of the Department of Computer Science and Engineering at University of California, San Diego working with Professor Steven Swanson. Tseng is interested in designing innovative computer architectures, storage systems and runtime systems for data-intensive applications. In addition to computer architecture, storage systems and runtime systems, Tseng also has research experience in various areas including programming languages, compilers, embedded systems, computer networks and bioinformatics.

  • Hung-Wei Tseng, Qianchen Zhao, Yuxiao Zhou, Mark Gahagan, and Steven Swanson. Morpheus: Creating application objects efficiently for heterogeneous computing. In 43rd International Symposium on Computer Architecture, ISCA 2016, 2016.
  • Hung-Wei Tseng and Dean M. Tullsen. CDTT: Compiler-generated data-triggered threads. In 20th International Symposium on High Performance Computer Architecture, HPCA 2014, pages 650–661, 2014.
  • Hung-Wei Tseng and Dean M. Tullsen. Software data-triggered threads. In ACM SIGPLAN 2012 Conference on Object-Oriented Programming, Systems, Languages and Applications, OOPSLA 2012, pages 703–716, 2012.
  • Hung-Wei Tseng and Dean M. Tullsen. Eliminating redundant computation and exposing parallelism through data-triggered threads. IEEE Micro, Special Issue on the Top Picks from Computer Architecture Conferences, volume 32:38–47, 2012.
  • Hung-Wei Tseng, Laura M. Grupp, and Steven Swanson. Understanding the impact of power loss on flash memory. In 48th Design Automation Conference, DAC 2011, pages 35–40, 2011.

Department of Electrical and Computer Engineering

Dr. Ismail Guvenc

Associate Professor
Ph.D. (2006), University of South Florida

Research Interests: 5G wireless systems, heterogeneous networks, wireless localization, UAV networks, visible light communications, public safety communications, detection and estimation

Guvenc received his Ph.D. in electrical engineering from University of South Florida (2006) with an outstanding dissertation award. He was with Mitsubishi Electric Research Labs during 2005, and with DOCOMO Innovations Inc. between 2006-12, working as a research engineer. Between August 2012 and August 2016, he has been an assistant professor with Florida International University. His recent research interests include heterogeneous wireless networks and 5G wireless systems. He has published more than 140 conference/journal papers and book chapters, and several standardization contributions. He co-authored/co-edited three books for Cambridge University Press, served as an editor for IEEE Communications Letters (2010-15) and IEEE Wireless Communications Letters (2011-present), and as a guest editor for several other journals. Guvenc is an inventor/coinventor in some 30 U.S. patents. He is a recipient of the 2014 Ralph E. Powe Junior Faculty Enhancement Award and the 2015 NSF CAREER Award.

  • Merwaday and I. Guvenc, “Handover Count Based Velocity Estimation and Mobility State Detection in Dense HetNets,” IEEE Trans. Wireless Commun., 2016.
  • Sahin, Y. S. Eroglu, I. Guvenc, N. Pala, M. Yuksel, “Hybrid 3D Localization for Visible Light Communication Systems,” IEEE J. Lightwave Technology, Nov. 2015.
  • Simsek, M. Bennis, and I. Guvenc, “Learning Based Frequency- and Time-Domain Inter-Cell Interference Coordination in HetNets,” IEEE Trans. Vehic. Technol., 2015.
  • Q. S. Quek, G. de la Roche, I. Guvenc, and M. Kountouris (Editors), “Small Cell Networks: Deployment, PHY Techniques,and Resource Management,” Cambridge University Press, April 2013.
  • Sahinoglu, S. Gezici, and I. Guvenc, “Ultra-Wideband Positioning Systems-Theoretical Limits, Ranging Algorithms, and Protocols,” Cambridge University Press, Aug. 2008.
Dr. Victor Veliadis

CTO, PowerAmerica
Ph.D. (1995), Johns Hopkins University

Research Interests: Wide bandgap power semiconductor devices and electronics

Veliadis received his Ph.D. in electrical engineering from Johns Hopkins University in 1995. From 1996 to 2000, he was with Nanocrystals Imaging Corporation where he developed quantum-dot phosphors for imaging applications. From 2000 to 2003, he designed InP-based tunable photonic integrated circuits for telecommunication applications at Lucent Technologies. In 2003, Veliadis was adjunct physics professor at Ursinus College and St. Joseph University. After a brief military service, he joined Northrop Grumman Electronic Systems in 2004 where he worked on wide bandgap semiconductor devices and circuits. As of May 2016, he is CTO of PowerAmerica and professor of electrical and computer engineering at NC State. Veliadis has authored 105 peer-reviewed technical articles and three book chapters and has 23 issued patents to his credit.

  • Veliadis, B. Steiner, K. Lawson, S. B. Bayne, D. Urciuoli, and H. C. Ha, “Suitability of N-ON recessed implanted gate vertical-channel SiC JFETs for optically triggered 1200 V solid-state-circuit-breakers,” accepted to Special Issue on Wide Bandgap Devices of the IEEE Journal of Emerging and Selected Topics in Power Electronics, 2016.
  • Veliadis, M. Snook, S. Woodruff, B. Nechay, H. Hearne, C. Lavoie, D. Giorgi, M. Ingram, “6.9-cm2 Active-area Interconnected Wafer 4 kV PiN Diode pulsed at 55 kA,” accepted for publication at Special Issue on Wide Bandgap Devices of the IEEE Journal of Emerging and Selected Topics in Power Electronics, 2016.
  • N. Pushpakaran, M. Hinojosa, S. B. Bayne, V. Veliadis, D. Urciuoli, N. El-Hinnawy, P. Borodulin, S. Gupta, and C. Scozzie, “Evaluation of SiC JFET Performance during Repetitive Pulsed Switching into an Unclamped Inductive Load,” IEEE Trans. on Plasma Science, vol. 42, No. 10, pp. 2968-2973, 2014.
  • Veliadis, B. Steiner, K. Lawson, S. B. Bayne, D. Urciuoli, H. C. Ha, N. El-Hinnawy, S. Gupta, P. Borodulin, R. S. Howell, and C. Scozzie, “Reliable Operation of SiC JFET Subjected to Over 2.4 Million 1200-V/115-A Hard Switch Stressing Events at 150 C,” IEEE Electron Dev. Lett., Vol. 34, No. 3, pp. 384-386, 2013.
  • Veliadis, H. Hearne, E. J. Stewart, M. Snook, W. Chang, J. D. Caldwell, H. C. Ha, N. El-Hinnawy, P. Borodulin, R. S. Howell, D. Urciuoli, and C. Scozzie, “Degradation and full recovery in high-voltage implanted-gate SiC JFETs subjected to bipolar-current stress,” IEEE Electron Dev. Lett., Vol. 33, No. 7, pp. 952-954, 2012.
Dr. Tianfu Wu

Assistant Professor
The NC State Visual Narrative Cluster
Ph.D. (2011), University of California, Los Angeles

Research Interests: Statistical learning, machine learning, big data; statistical inference, sequential hypothesis testing, decision policy; statistical theory, performance guarantee; computer vision, and pattern analysis

Wu received his two-year college in electronic engineering and information science from University of Science and Technology of China. He received his M.S. in signal and information processing from Hefei University of Technology, China, and Ph.D. in statistics from University of California, Los Angeles (UCLA). He was a postdoctoral researcher in the Department of Statistics at UCLA. Prior to joining the NC State faculty, he was research assistant professor of statistics in the Department of Statistics at UCLA. His research has been focused on computer vision and life-long communicative learning from the perspective of statistical modeling, inference and learning: (a) Statistical learning of large scale and highly expressive hierarchical and compositional models from visual big data (images and videos), (b) Statistical inference by learning near-optimal costsensitive decision policies, (c) Statistical theory of performance guaranteed learning algorithm and optimally scheduled inference procedure and (d) Statistical framework of visual Turing test and life-long communicative learning.

  • Tianfu Wu, Bo Li and Song-Chun Zhu, “Learning And-Or Models to Represent Context and Occlusion for Car Detection and Viewpoint Estimation,” IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI, Accepted), arXiv 1501.07359, 2016.
  • Hang Qi*, Tianfu Wu*, Mun Wai Lee and Song-Chun Zhu, “A Restricted Visual Turing Test for Deep Scene and Event Understanding”, arXiv 1512.01715, 2015 (*Equal Contribution).
  • Tianfu Wu and Song-Chun Zhu, “Learning Near-Optimal Cost-Sensitive Decision Policy for Object Detection,” IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 37(5): 1013-1027, 2014.
  • Adrian Barbu, Tianfu Wu and Ying Nian Wu, “Learning Mixtures of Bernoulli Templates by Two-Round EM with Performance Guarantee,” Electronic Journal of Statistics (EJS), vol.8, no.2, p.3004–3030, 2014.

Edward P. Fitts Department of Industrial and Systems Engineering

Dr. Karen Chen

Assistant Professor
Ph.D. (2015), University of Wisconsin-Madison

Research Interests: Human factors and ergonomics approaches to understand human performance of different populations, including but not limited to individuals with musculoskeletal conditions and older adults, use of virtual reality, and technologies to study safety and healthcare in various environments

Chen received her B.S. (2009), M.S. (2010), and Ph.D. (2015) in biomedical engineering from University of Wisconsin-Madison. Prior to joining the Edward P. Fitts Department of Industrial and Systems Engineering, she was a postdoctoral research associate at the Healthcare Systems Engineering Institute at Northeastern University in Boston, Massachusetts. Her recent research examines patient safety in healthcare systems, specifically examines some critical junctures between primary and specialty care using human factors frameworks and methods. Moreover, she studies human performance while individuals interact with different technologies. She explores the application of virtual reality for chronic neck pain rehabilitation and the interface design of touchscreens for individuals with physical disabilities. These research topics also highlight her experiences in experimental design.

  • Chen, K.B., Xu, X., Lin, J.-H., Radwin, R. G., Evaluation of Older Driver Head Functional Range of Motion using Portable Immersive Virtual Reality, Experimental Gerontology, 70: 150-156, 2015.
  • Xu, X., Chen, K. B., Lin, J.-H., Radwin, R. G., The accuracy of the Oculus Rift virtual reality head-mounted display during cervical spine mobility measurement, Journal of Biomechanics, 48(4): 721-724, 2015.
  • Chen, K. B., Ponto, K., Tredinnick, R. D., and Radwin, R. G., Virtual Exertions: Evoking the sense of exerting forces in virtual reality using gesture and muscle activity, Human Factors, 57(4): 658-673, 2015.
  • Chen, K. B., Kimmel, R. A., Bartholomew, A., Ponto, K., Gleicher, M. L. and Radwin, R. G., Manually locating physical and virtual reality objects using the hand, Human Factors, 56(6): 1163-76, 2014.
Dr. Xu Xu

Assistant Professor
Ph.D. (2008), NC State University

Research Interests: Human factors and ergonomics engineering, occupational biomechanics, optimization-based biomechanical modelling, data mining on human motion data, occupational musculoskeletal injury prevention

Xu received his B.S. in industrial engineering from Tsinghua University, Beijing, China. He received his M.S. and Ph.D. in industrial and systems engineering from NC State University. He was a postdoctoral research fellow in the School of Public Health at Harvard University. Prior to joining the NC State faculty, he was a research scientist in Liberty Mutual Research Institute for Safety. His research interests are generally in the areas of biomechanical modeling, optimization, simulation and data mining with respect to human daily activates to promote workplace and at-home injury prevention and driving safety.

  • Xu, X., Dickerson, C., McGorry, R.W. Lin, J.H. (2016). Evaluation of regression-based 3-D shoulder rhythms. Journal of Electromyography and Kinesiology 29, 28-33.
  • Xu, X., McGorry, R.W., Chou, L.S., Lin, J.H., Chang, C.C. (2015). Accuracy of the Microsoft KinectTM for measuring gait parameters during treadmill walking. Gait and Posture 42, 145-151.
  • Xu, X., Lin, J.H. (2015). The effects of working environment factors and user experiences on mechanical properties of upper extremity during powered hand tool use. IIE Transactions on Occupational Ergonomics and Human Factors 3, 81-90.
  • Xu, X., Qin, J., Catena, R. D., Faber, G. S., Lin, J.H. (2013). Effect of aging on inter-joint synergies during machine-paced assembly tasks. Experimental Brain Research 231, 249-256.
  • Xu, X., Faber, G.S., Kingma, I., Chang, C.C., Hsiang, S.M. (2013). The error of L5/S1 joint moment calculation in a body-centered non-inertial reference frame when the fictitious force is ignored. Journal of Biomechanics 46, 1943-1947.

Department of Forest Biomaterials

Dr. Yuan Yao

Assistant Professor of Sustainability Science and Engineering
College of Natural Resources
Ph.D. (2016), Northwestern University

Research Interests: Industrial ecology, sustainable engineering, and operations research life cycle assessment, industrial process modeling and process optimization

Yao received a B.S. in metallurgical engineering from Northeastern University, China, in 2011. She then joined Energy and Resource System Analysis Laboratory at Northwestern University, where she received a Ph.D. in chemical engineering in 2016. During that time, she was selected to the program of Management for Scientists and Engineers from Kellogg School of Management. Yao’s research focuses on building analytical models to quantify environmental/economic/social implications of emerging technologies in industrial systems, such as carbon capture, clean energy technologies, and incremental process improvements. Her work links fundamental engineering systems with scaled economic, environmental and social impacts. In particular, she develops decision support tools to analyze alternative scenarios and identify behavioral, technological and policy pathways toward a more sustainable future for manufacturing industries.

  • Yao, Y., et al. (2016). “Prospective Life Cycle Assessment of Emerging Technology Options for U.S. Ethylene Industry.” Industrial and Engineering Chemistry Research. 2016, 55 (12), pp 3493–3505.
  • Yao, Y., et al. (2015). “Understanding Variability to Reduce the Energy and GHG Footprints of U.S. Ethylene Production.” Environmental Science and Technology, 49, 14704.
  • Yao, Y., et al. (2014). “Greener Pathways to Energy-Intensive Commodity Chemicals: Opportunities and Challenges.” Current Opinion in Chemical Engineering, 6:90-98.
  • Yao, Y., et al. (2014). “A Hybrid Life-Cycle Inventory for Multi-crystalline Silicon PV Module Manufacturing in China.” Environmental Research Letters. 9:114001.
  • Gebreslassie, B.H., Yao, Y., and F. You (2012). “Design Under Uncertainty of Hydrocarbon Biorefinery Supply Chains: Multiobjective Stochastic Programming Models, Decomposition Algorithm, and a Comparison Between CVaR and Downside Risk.” AIChE Journal, 58: 2155-2179, 2012.

Department of Mechanical and Aerospace Engineering

Dr. Landon Grace

Assistant Professor
Ph.D. (2012), University of Oklahoma

Research Interests: Aerospace composite performance and longevity; nanoscale reinforcement of polymeric biomaterials; nanocomposites for sensing applications; diffusion phenomena in polymer and polymer composite materials; environmental degradation in composite materials; polymer composites in radar applications; dielectric property characterization of materials; polymer nanocomposite design, fabrication, and analysis

Grace received his B.S. in mechanical engineering from the University of Missouri and received his M.S. and Ph.D. in mechanical engineering from the University of Oklahoma. Prior to joining the NC State faculty, he spent four years as an assistant professor of mechanical and aerospace engineering with a secondary appointment in biomedical engineering at the University of Miami. Prior to joining the faculty at Miami in 2012, Grace spent five years as an aerospace engineer with the U.S. Air Force at Tinker Air Force Base in Oklahoma City. Currently, Grace studies the interaction of polymeric composites with their environment, and attempts to either (a) mitigate or prevent the long-term effects of environmental degradation due largely to fluid contamination or (b) exploit these interactions to achieve novel functionality. This research focus crosses into biomedical and civil/environmental engineering via nanocomposite-based sensors and in vivo degradation of polymeric implants. In the aerospace field, Grace studies diffusion kinetics in polymer composites and the effect of penetrants on both structural and electrical (radar) properties of aircraft/spacecraft composite structures. The majority of this research is experimental but significantly supplemented by theoretical techniques.

  • R. Grace, (2016), “Projecting long-term non-Fickian diffusion behavior in polymeric composites based on short-term data: a 5-year validation study,” J. Materials Science, 51(2), pp. 845-853.
  • Fittipaldi and L.R. Grace (2016), “Lipid diffusion and swelling in a phase separated biocompatible thermoplastic elastomer,” J Mech Behav Biomed Mater. 64: pp 1-9.
  • R. Grace (2015) “The effect of moisture contamination on the relative permittivity of polymeric composite radar-protecting structures at X-band,” Comp. Struct., 128, pp. 305-312.

Department of Nuclear Engineering

Dr. Jason Hou

Research Assistant Professor
Ph.D. (2013), The Pennsylvania State University

Research Interests: Multi-physics reactor simulation, advanced reactor design, in-core fuel management and fuel cycle analysis

Hou received his B.S. in engineering physics from Tsinghua University, China. He holds M.S. and Ph.D. degrees in nuclear engineering from the University of Michigan and Pennsylvania State University, respectively. Prior to joining the NC State faculty, he was a postdoctoral scholar in the Department of Nuclear Engineering at University of California, Berkeley. Hou considers himself an advocate of nuclear energy and the mission of his research is to promote nuclear energy by investigating advanced reactor designs and developing improved reactor modeling and simulation methods. In particular, he develops accurate yet efficient numerical models to improve the reactor design in various aspects including the economics, safety, proliferation resistance and sustainability. Currently, he also performs studies on the uncertainty quantification and sensitivity analysis in the nuclear system modeling and the improvement of high-fidelity reactor core simulator.

  • Hou, S. Qvist, R. Kellogg and E. Greenspan, “3D In-core Fuel Management Optimization for Breed-and-Burn Reactors,” Progress in Nuclear Energy, vol 88, pp. 58-74 (2016).
  • Hou, H. Choi and K. Ivanov, “Development of An Iterative Diffusion-Transport Method based on MICROX-2 Cross Section Libraries,” Annals of Nuclear Energy, vol 77, pp. 335-342 (2015).
Dr. Djamel Kaoumi

Associate Professor
Ph.D. (2007), The Pennsylvania State University

Research Interests: Nuclear materials; effect of irradiation, temperature, and mechanical stress on the microstructure of materials

Kaoumi received his B.S. in physics from the Institut polytechnique de Grenoble (France). He received his M.S. in nuclear engineering with a minor in materials science from the University of Florida, and a Ph.D. in nuclear engineering from the Pennsylvania State University. Then, he was a postdoctoral researcher for PSU/ ANL in the Division of Nuclear Engineering. Prior to joining the NC State faculty, he was an associate professor of nuclear engineering in the Mechanical Engineering Department at the University of South Carolina. Kaoumi’s goal is to develop a mechanistic understanding of microstructureproperty relationships, with an emphasis on microstructure evolution under harsh environment (i.e. irradiation, high temperature, and mechanical stress) and how it can impact the macroscopic properties and performance. Understanding the basic mechanisms of degradation of materials at the nanostructure level is necessary for the development of predictive models of the materials performance and for the design and development of better materials. Materials of interest include advanced alloys for structural and cladding applications in advanced nuclear systems (e.g. austenitic steels, advanced ferritic/martensitic steels, oxide-dispersion-strengthened (ODS) steels), high-temperature ni-based alloys, zirconium alloys and nanocrystalline metallic systems. Characterization techniques of predilection include both in-situ and ex-situ techniques e.g. in-situ irradiation in TEM, in-situ straining in a TEM, electron microscopy techniques, XRD, and synchrotron XRD.

  • Kaoumi, T. Gautier, J. Adamson, M. Kirk, 2015, “Using In-Situ TEM to characterize the Microstructure evolution of Metallic Systems under External Solicitation,” Microscopy and Microanalysis, V. 21 S3.
  • R.Allen, D. Kaoumi, et al., 2015, “Characterization of Microstructure and Property Evolution in Advanced Cladding and Duct: Materials exposed to High Dose and Elevated Temperature,” Journal of Materials Research, v 30, n 9, p 1246-1274.

Department of Textile Engineering, Chemistry and Science

Dr. Eunkyoung Shim

Assistant Professor
Ph.D. (2001), NC State University

Research Interests: Mechanism of nonwoven manufacturing process and process-structureproperty relationship, high surface area nonwovens-production, functionalization and applications, bulk and surface modification of nonwovens and fibers, fiber formation and the role of additives during melt spinning and spunbond process, and nonwoven Filter media

Shim received her B.S. and M.S. in clothing and textiles from Seoul National University. She received her Ph.D. in fiber and polymer science from NC State University. She joined the Department of Textile Engineering as an assistant professor in 2016. This appointment followed 15 years of experience in the Nonwovens Institute as a research assistant professor and research associate. Shim studies fundamental mechanism of nonwoven processes and applies this knowledge to control structures and properties of nonwovens as engineered products. This includes visualization and analysis of complex 2D and 3D fibrous structures of nonwovens to study their forming mechanism as well as how these structures influence performance and functionality of nonwovens. Her research also includes functionalizing nonwovens to impart unique properties for various applications. Filtration is one application area of her research. Her major focus on nonwoven filter media research is electrostatic charging mechanism and controlling structure of nonwoven filter media to achieve high efficiency at low resistance. Fiber formations is another area of her research. She studies effects of polymer properties on spinnability and polymer crystalline structure formation and uses various melt additives during the spinning to impart functionality on fibers.

  • Shim, B. Pourdeyhimi, D. Shiffler (2016), Process-structure- property relationship of melt spun poly (lactic acid ) fiber produced in the spunbond process, DOI: 10.1002/ app.4422.
  • Kilic, E. Shim & B. Pourdeyhimi, Electrostatic Capture Efficiency Enhancement of Polypropylene Electret Filters with Barium Titanate, Aerosol Science and Technology, 49(8):666-673 (2015).
  • Amirnasr, E. Shim, B. Y. Yeom, and B. Pourdeyhimi, Basis weight uniformity analysis in nonwovens, Journal of Textile Institute, 105(4), 444-453 (2014).