Find Academic Supervisors

• Frontal Polymerization
• Composite Materials
• Additive Manufacturing
• +4 more

Philippe H Geubelle is a Professor of Aerospace Engineering, Mechanical Science and Engineering, and affiliated with the National Center for Supercomputing Applications (NCSA) and Beckman Institute for Advanced Science and Technology at the University of Illinois at Urbana-Champaign. He holds the Abel Bliss Professorship and serves as Executive Associate Dean of the Grainger College of Engineering. Geubelle's research focuses on advanced materials and manufacturing, particularly in frontal polymerization, composite materials, and additive manufacturing. His work integrates computational modeling, materials science, and mechanical engineering to develop energy-efficient manufacturing techniques and novel material systems. Key research areas include morphogenic composites, 3D printing innovations, and multiscale material design. He has received prestigious awards, including the ASME Fellow (2009) and NSF CAREER Award (1998). His contributions span over 250 publications, emphasizing numerical studies on polymerization processes, composite manufacturing optimization, and fluid dynamics in material systems. Geubelle collaborates extensively with industry and academic partners, driving advancements in sustainable manufacturing and smart materials. Affiliations: Grainger College of Engineering, NCSA, Beckman Institute Key Projects: Frontal polymerization-based manufacturing, microvascular composites, and AI-driven material design

• Deep Learning
• Finite Element Analysis
• Materials Processing
• +4 more

Seid Koric is an Adjunct Associate Professor in the Department of Mechanical Science and Engineering at the University of Illinois, affiliated with the National Center for Supercomputing Applications (NCSA) as Senior Technical Associate Director. He holds a PhD in Engineering from the University of Illinois. His research focuses on integrating artificial intelligence with high-performance computing (HPC), particularly in materials science, computational mechanics, and multiphysics modeling. Key research areas include deep learning for metamaterial design, finite element analysis, and real-time monitoring of complex systems using digital twins. He has pioneered applications of deep operator networks (DeepONets) for predicting solution fields in materials processing and additive manufacturing. His work bridges computational methods with industrial challenges, such as steel solidification and nuclear system monitoring. Notable achievements include the HPC Innovation Excellence Award (2011 and 2020), recognizing his contributions to HPC and AI integration. Collaborations span academia and industry, addressing challenges in aerospace, energy systems, and smart manufacturing. His lab develops scalable computational frameworks and open-source tools for exascale computing, emphasizing interdisciplinary problem-solving. Education: PhD in Engineering, University of Illinois Affiliations: NCSA (Senior Technical Associate Director), Mechanical Science and Engineering Department Labs/Teams: Leads computational research groups focused on AI-driven HPC applications at NCSA

• Machine Learning
• Computer Vision
• Reinforcement Learning
• +3 more

Alexander Gerhard Schwing is an Associate Professor at the University of Illinois at Urbana-Champaign, holding appointments in the Department of Electrical and Computer Engineering and the Siebel School of Computing and Data Science. He is also a W.J. “Jerry” Sanders III - Advanced Micro Devices, Inc Fellow. His research focuses on machine learning, computer vision, and reinforcement learning, with notable contributions to image segmentation, graphical models, and neural networks. Schwing leads interdisciplinary efforts at the Coordinated Science Lab and the National Center for Supercomputing Applications (NCSA). His research interests include developing algorithms for efficient human modeling from monocular video, neural network architectures like the Forward-Forward algorithm, and underwater geolocalization using transformers. He has received prestigious awards such as the Amazon Research Award (2019) and the NSF CAREER Award (2021). His work bridges theoretical advancements with practical applications in robotics and computer graphics. Schwing collaborates widely, with recent projects addressing challenges in 3D scene reconstruction (e.g., NeRFDeformer) and offline imitation learning. His publications reflect a strong emphasis on both foundational machine learning and applied vision tasks.

• Genomics
• Plant Genetics
• Soybean Cyst Nematode
• +3 more

Matthew Hudson is a Professor in Crop Sciences at the University of Illinois, with additional appointments at the National Center for Supercomputing Applications (NCSA) and as a Professor in Bioengineering. He is also an Affiliate at the Carl R. Woese Institute for Genomic Biology. His interdisciplinary work bridges plant genomics, computational biology, and agricultural science, leveraging high-performance computing to address critical challenges in crop improvement. Dr. Hudson's research focuses on plant genomics, particularly in soybean and other crops, with emphasis on understanding genetic resistance to pests like the soybean cyst nematode. His work spans multiple areas including genomics , plant-pathogen interactions , genome editing , and lipid metabolism in plants . He has made significant contributions to understanding the genetic basis of soybean cyst nematode resistance through studies of the Rhg1 locus and other quantitative trait loci. Analysis of Dr. Hudson's recent publications reveals a strong focus on applying advanced genomic technologies to crop improvement. His work increasingly integrates high-throughput genome engineering , automated phenotyping systems , and pangenome analyses to develop climate-resilient crops. A notable trend is the development of computational tools and databases like "FatPlants" that integrate genomic and metabolic pathway information to accelerate crop breeding. NACTA Educator Award (2010) While specific details about Dr. Hudson's advising and grant portfolio aren't explicitly mentioned in the available information, his extensive publication record (over 100 research outputs including articles, patents, and book chapters) suggests active mentorship of students and postdocs. His research likely involves significant grant funding given the computational and experimental scale of his projects, particularly those involving the National Center for Supercomputing Applications. Dr. Hudson's work appears to be highly collaborative, engaging with researchers across plant biology, computational science, and agricultural engineering. His affiliation with the National Center for Supercomputing Applications suggests involvement in developing and applying advanced computational approaches to genomic data analysis, potentially including machine learning and big data analytics for crop improvement.

Amy Marshall-ColonView profile

Associate Professor

• Systems Biology
• Plant Physiology
• Crop Science
• +4 more

Amy Marshall-Colon is an Associate Professor in the Department of Plant Biology at the University of Illinois, with additional roles as an Assistant Professor at the Institute for Sustainability, Energy, and Environment and an Affiliate at the National Center for Supercomputing Applications (NCSA) and Carl R. Woese Institute for Genomic Biology. She holds a B.S. from Lipscomb University (2000), M.S. from University of Florida (2002), Ph.D. from Purdue University (2009), and completed an NIH-NRSA Fellowship at New York University (2010–2013). Her research focuses on integrative systems biology approaches to study crop responses to environmental stresses, particularly nitrogen use efficiency (NUE) and climate change impacts. This includes analyzing cross-communication among signaling pathways and developing multiscale computational models to predict gene-by-environment interactions. Key areas span plant molecular mechanisms, metabolic pathways, and the design of virtual crop models for sustainable agriculture. Recent publications highlight work on bioenergy sorghum stem development, root architectural adaptations in Brachypodium, and CO2 response mechanisms in Arabidopsis. These studies emphasize spatial transcriptomics, gene regulatory networks, and computational tools for predicting crop resilience in changing climates. Awards : Friedrich Wilhelm Bessel Research Award (2021) Joseph B. Hawkes Research Award (University of Illinois) NCSA Faculty Fellowship List of Teachers Ranked Excellent by Students Teaching Tools in Plant Biology Competition Winner Her advising and grants narrative involves leading interdisciplinary teams at NCSA and the Carl R. Woese Institute, focusing on crop modeling and sustainable biomass production. Collaborations extend to global research networks, addressing nitrogen dynamics, abiotic stress, and computational plant science. She is part of the Crops In Silico initiative and actively contributes to labs investigating plant systems biology and genomic applications.

Paul RickerView profile

Professor

• Computational Astrophysics
• Galaxy Clusters
• Binary Stars
• +4 more

Paul Ricker is a Professor of Astronomy at the University of Illinois, affiliated with the National Center for Supercomputing Applications (NCSA) and the Department of Physics. His research focuses on computational astrophysics, leveraging large-scale numerical simulations to study galaxy evolution, clusters of galaxies, binary stars, supernovae, and computational methodologies like parallel algorithm development and cyberinfrastructure. He holds a PhD in Physics from the University of Chicago, following degrees from Pennsylvania State University. He teaches courses including ASTR 100, 210, 310, and advanced graduate-level classes. His work bridges astrophysics and computer science, with contributions to simulation software like Flash-X. Research highlights include modeling common envelope evolution in binary systems and exploring the interplay between active galactic nuclei and galaxy clusters. His affiliations include the Cosmological Simulation Group and collaborations with the LIGO-Virgo gravitational wave observatories. Teaching and mentoring are integral to his role, though no specific advisees are listed in available texts.

Kaiyu GuanView profile

Professor

• Environmental Science
• Agricultural Sustainability
• Remote Sensing
• +7 more

Dr. Kaiyu Guan is a Professor in the Department of Natural Resources and Environmental Sciences at the University of Illinois Urbana-Champaign with a joint appointment at the National Center for Supercomputing Applications (NCSA). He holds additional roles as a Blue Waters Professor, Siebel School of Computing and Data Science Professor, and Director of the Agroecology Sustainability Center. His research focuses on computational environmental science, particularly vegetation-hydrology interactions, climate change impacts on ecosystems, and agricultural sustainability. Dr. Guan utilizes satellite data, machine learning, and modeling to address challenges in crop productivity, water management, and food security. He has affiliations with multiple centers including the Institute for Sustainability, Energy, and Environment and the Center for Digital Agriculture. Education: PhD in Environmental Engineering (Princeton University, 2013); B.S. in Geography and Geoinformatics (Nanjing University, 2008). Research interests include ecohydrology, the water-food-energy nexus, and agroecosystem modeling. He explores innovations in remote sensing, soil carbon dynamics, and greenhouse gas mitigation strategies. Current projects emphasize climate resilience and adaptation in agricultural systems. Dr. Guan leads collaborative efforts to advance agrivoltaics, precision agriculture, and digital twins for farmland management. His work bridges computational science with real-world applications to enhance global sustainability. Publications highlight breakthroughs in crop monitoring, soil gas flux analysis, and carbon budget quantification. He actively recruits graduate students and postdocs in crop remote sensing and modeling. His grants and collaborations span federal agencies, industry, and international partners, driving advancements in climate-smart agricultural practices. Labs/Teams: Agroecology Sustainability Center, NCSA, and the Center for Digital Agriculture. These hubs foster interdisciplinary research in agroecosystems, computational tools, and sustainable agriculture solutions.

Xiaojia Shelly ZhangView profile

Associate Professor

• Topology Optimization
• Additive Manufacturing
• Structural Engineering
• +7 more

Dr. Xiaojia Shelly Zhang is an Associate Professor and David C. Crawford Faculty Scholar in the Department of Civil and Environmental Engineering at the University of Illinois at Urbana-Champaign's Grainger College of Engineering. She also holds affiliate appointments in Mechanical Science and Engineering and is a Faculty Fellow at the National Center for Supercomputing Applications (NCSA). Dr. Zhang directs the MISSION (Multi-functional Structures and Systems design Optimization) Laboratory, where she leads research at the intersection of computational mechanics, materials science, and structural engineering. Her educational background includes a B.S. (Honors) and M.S. in Civil Engineering from UIUC, followed by a Ph.D. in Structural Engineering from Georgia Tech. Dr. Zhang's research focuses on topology optimization, additive manufacturing, and multi-scale materials design, with applications spanning from civil infrastructure to soft robotics and metamaterials. Dr. Zhang's publication record demonstrates consistent excellence with numerous high-impact papers in Science Advances, Nature Communications, and top mechanics journals. Her work shows a clear progression toward increasingly complex multi-physics problems, integrating machine learning, uncertainty quantification, and sustainability considerations. Recent publications (2024-2025) emphasize practical applications in healthcare, sustainable infrastructure, and advanced manufacturing. National Science Foundation CAREER Award recipient DARPA Young Faculty Award and Director's Fellowship Multiple ASME/ASCE early career awards including Hughes Young Investigator and Leonardo da Vinci Award UIUC Campus Distinguished Promotion Award (2025) Consistent teaching excellence recognition since 2020 Dr. Zhang actively mentors students and postdocs in her MISSION Laboratory, with several advisees appearing as first authors on high-impact publications. Her research is supported by major grants from NSF, DARPA, AFOSR, and ARO. She serves on the Executive Committee of the International Society for Structural and Multidisciplinary Optimization and holds editorial positions for the Journal of Applied Mechanics and Structural and Multidisciplinary Optimization.

• High-Performance Computing
• Parallel Computing
• Distributed Systems
• +6 more

Marc Snir is a Professor at the University of Illinois’s Siebel School of Computing and Data Science. He has led significant research contributions in high-performance parallel computing, including work on the Message Passing Interface (MPI) and IBM’s SP scalable parallel system. As Department Head from 2001–2007, he oversaw the transition to the Siebel Center and expanded the department’s capabilities. He later served as the first director of the Illinois Informatics Institute, chief software architect for the Blue Waters supercomputer, and co-director of the Universal Parallel Computing Research Center (UPCRC). His research focuses on parallel computing systems, fault resilience, and I/O optimizations. He has been recognized with the 2014 Distinguished Alumni Service Award. His work spans exascale computing, distributed systems, and machine learning applications in HPC. He has contributed to projects like Argo (an exascale OS/runtime), Aluminum (a GPU-aware communication library), and LCI (Lightweight Communication Interface). His research emphasizes improving scalability, energy efficiency, and reliability in high-performance systems. He has advised numerous students (names not listed here) and led teams in advancing HPC tools and methodologies. His involvement in initiatives like UPCRC and the Blue Waters project underscores his commitment to bridging theoretical research and practical applications in computing.

• Computer Architectures
• Compilers
• Secure Systems
• +1 more

Pen-Chung Yew is a Professor in the Department of Computer Science and Engineering at the University of Minnesota at Twin Cities. He holds a PhD from the University of Illinois at Urbana-Champaign (UIUC) Computer Science Department, awarded in 1981. His research focuses on computer architectures, compilers, and secure/high-performance parallel systems. He was a key designer of the Cedar system at UIUC’s Center for Supercomputing Research and Development (CSRD) in the 1980s. Yew has held leadership roles, including Head of the University of Minnesota’s Department of Computer Science and Engineering, William Norris Land-Grant Chair Professor, and Director of the Institute of Information Science (IIS) in Taiwan. He served as NSF Program Director for the Microelectronic Systems Architecture (MSA) Program and Editor-in-Chief of IEEE Transactions on Parallel and Distributed Systems. He has chaired major conferences in computer architecture and systems. He received the 2023 Distinguished Academic Achievement Alumni Award and is an IEEE Life Fellow. His career spans academia, research leadership, and editorial roles in high-impact journals.

• High-Performance Computing (HPC)
• Grid Computing
• Parallel Programming
• +4 more

Professor Mark Baker is a faculty member at the University of Reading's Department of Computer Science, specializing in High-Performance Computing (HPC), Grid Computing, and Distributed Systems. His research focuses on optimizing parallel and distributed applications, virtualization technologies, and semantic web frameworks. He has contributed to projects like the VERA information environment for archaeological informatics and the MPJ Express messaging library for Java HPC. Research interests include para-virtualization performance analysis, cloud computing resource utilization, and scalable grid information services. He has published extensively on topics such as parallel programming models, distributed system architectures, and benchmarking methodologies. His work integrates semantic web technologies for profiling systems and enhancing collaborative environments in e-Science. Key contributions include the development of wide-area messaging frameworks (e.g., Tycho), cluster computing fundamentals, and grid portal technology. He has collaborated on projects involving supercomputing infrastructure (e.g., Thamesblue supercomputer) and cloud-based HPC applications. His research emphasizes practical applications of virtualization and distributed computing in academic and industrial contexts.

Terry DaviesView profile

Researcher

• Numerical Weather Prediction
• Meteorology
• Numerical modelling
• +4 more

Dr Terry Davies is an expert scientist at the Met Office and affiliated with the University of Reading's Department of Meteorology. He specializes in developing and maintaining the atmospheric dynamical core of the Met Office's Unified Model (UM), focusing on enhancing its performance across various configurations including global forecasts, climate models, and high-resolution regional models. His work emphasizes computational efficiency and adapting to future supercomputing architectures. Education: BSc in Applied Mathematics and Computer Science (Sheffield University, 1972); PhD in Heat and Mass Transfer in Fluid Flow (Liverpool University, 1975). Research interests include numerical weather prediction, fluid dynamics, and climate modeling. He has contributed significantly to the development of the UM's non-hydrostatic New Dynamics framework, a pioneering global model operational since 2002. Terry also holds roles in international collaborations such as SRNWP and the PDEs on the Sphere organizing committee. Awards: Recipient of the L G Groves Memorial Prize (1983 and 2002) and Fellow of the Royal Meteorological Society. His career spans over four decades, including key roles at the Met Office, ECMWF, and academic collaborations. Terry's work bridges meteorological research and operational forecasting, driving advancements in computational meteorology.

• Geostatistics
• Big Data Processing
• Computer Systems
• +6 more

Dr. John Zigman is an academic affiliated with the Faculty of Engineering at The University of Sydney. His research spans interdisciplinary fields including geostatistics, big data processing, and computer systems optimization. He has contributed to advancements in geological boundary modeling, memory management frameworks for hybrid systems, and Java performance analysis. Key research interests include: Geological modeling using Bayesian approaches and dynamic time warping Development of holistic memory management systems (e.g., Panthera framework) Optimization of parallel computing architectures and distributed garbage collection Integration of geophysical data with autonomous spatial modeling algorithms Recent work focuses on photonic integrated circuits (2025), Java performance re-engineering (2025), and large-scale geological boundary rectification (2023). His publications demonstrate expertise in both theoretical computer science and applied geosciences. Notable collaborations include work with Prof. Arman Melkumyan on geostatistical applications and Prof. Stephen Blackburn on persistent Java systems. His research bridges computational methods with earth sciences, addressing challenges in resource exploration and data-intensive systems.

• Quantum Computing
• Quantum Algorithms
• Quantum Error Correction
• +3 more

Gokul Ravi is a Professor in the Department of Computer Science and Engineering at the University of Michigan. His research focuses on quantum computing, quantum algorithms, compiler optimization for quantum systems, and computer architecture. He leads a research group emphasizing impactful research in quantum domains, with weekly one-on-one and group meetings fostering collaboration and community. Students benefit from lab lunches where they discuss projects, papers, and potential collaborations. He prioritizes clear communication, with expectations including 5-6 years of PhD tenure and 3+ top-tier publications. Research interests span variational quantum algorithms, error mitigation, quantum cloud computing, and hardware-software co-design. His work addresses challenges in fault-tolerant quantum computing, compiler passes for NISQ applications, and quantum-centric supercomputing for materials science. Recent publications highlight innovations in quantum algorithm design, error correction, and hybrid systems. Students receive weekly progress updates and yearly feedback. He supports internships (up to 2) aligned with research and facilitates conference attendance via travel grants. Vacation planning is flexible but avoids deadlines. His mentoring style adapts to individual student needs, balancing independence with mentorship, particularly in early PhD stages.

Evgenia SmirniView profile

Professor

• Performance Evaluation
• Reliability and Dependability
• Applied Machine Learning
• +8 more

Evgenia Smirni is the Sidney P. Chockley Professor of Computer Science at the College of William and Mary, leading research in performance evaluation, dependability, and applied machine learning. She holds prestigious titles as an IEEE Fellow and ACM Distinguished Scientist. Research Interests : Her work spans performance analysis, reliability engineering, analytical modeling, HPC systems, and cloud computing. Notable projects include GeoSpread for epidemic modeling and strategic resilience evaluation of neural networks in autonomous systems. Awards : Recognized as an IEEE Fellow (202X) and ACM Distinguished Scientist (202X), she also serves as an Associate Editor for IEEE Transactions on Computers and IEEE Transactions on Parallel and Distributed Systems. Service & Leadership : Recent roles include General Chair of SIGMETRICS 2023, Keynote Speaker at DSN 2023, and co-chair of multiple international conferences including DSN 2017 and HPDC 2019. She has organized panels on future research directions in performance evaluation. Software Tools : Developed widely-used tools like KPC ToolBox for modeling and MAMSolver for matrix-analytic solutions. Advising : Supervised over 20 graduate students, many now in prominent academic and industry roles. Notable advisees include Lishan Yang (George Mason), Feng Yan (University of Houston), and Giuliano Casale (Imperial College London).