Find and connect with academic supervisors, professors, and scholars for your research journey.
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Assistant Professor
Ryan M. Richard is Assistant Adjunct Professor and Ames Scientist II at Iowa State University, specializing in computational chemistry software development. His research focuses on fragment-based methods, machine learning, and high-performance computing for quantum chemistry simulations. As chief architect of NWChemEx, he pioneers exascale-ready frameworks for chemical modeling.
Researcher
Yong Han is a Research Scientist at the Ames National Laboratory (U.S. Department of Energy) and the Department of Physics and Astronomy at Iowa State University, where he has been employed since 2011. He holds a Ph.D. in Materials Science and Engineering (2007) and an M.S. in Physics (2004) from the University of Utah. His professional trajectory includes positions as a Postdoctoral Research Associate at Ames Laboratory (2007–2011) and Graduate Research/Teaching Assistant roles at the University of Utah. Dr. Han's research integrates computational simulation and physical modeling across atomic to mesoscopic scales. Key focus areas include: Thermodynamic/kinetic properties of bulk materials, surfaces, and interfaces Growth mechanisms of nanofilms and self-assembly of nanostructures Quantum effects in graphene, topological insulators, and silica nanopores Electronic structure analysis using density functional theory, kinetic Monte Carlo, and molecular dynamics His work frequently collaborates with experimental groups utilizing scanning tunneling microscopy. Analysis of recent publications (2023–2025) reveals dominant themes in computational materials science, including intercalation chemistry in 2D materials, metal nanocluster dynamics, surface diffusion phenomena, and method development for nanostructure simulation. Research consistently bridges theoretical frameworks with experimental validations. Dr. Han contributes to major projects including Development of Exascale Software for Heterogeneous & Interfacial Catalysis and Theoretical & Computational Tools for Modeling Energy-Relevant Catalysis . He maintains active collaborations with national laboratories and experimental research teams.
Associate Professor
Qiqi Wang is an Associate Professor of Aeronautics and Astronautics at MIT, specializing in computational methods for chaotic systems and high-fidelity fluid dynamics simulations. He leads research in numerical methods for exascale computing, unsteady aerodynamics, and design optimization under uncertainty. Education: Ph.D. (2009) & M.S. (2008) in Computational and Mathematical Engineering from Stanford University, B.S. (2004) in Mathematics from USTC. Prior roles include Quantitative Analyst at Two Sigma and Postdoc at Stanford. Research focuses on engineering design of chaotic systems, turbulence modeling, and adjoint-based sensitivity analysis. Key contributions include the Flow360 CFD solver, novel Jacobi iteration algorithms, and methods for sensitivity computation in chaotic flows. Key Projects: Exascale numerical methods for CFD Uncertainty quantification in aerodynamic design LES and RANS modeling for rotorcraft Awards: 2007 Stanford Computer Graphics Rendering Competition (Grand Prize) 2005 SIAM Academic Excellence Award 2003 Mathematical Contest in Modeling (Meritorious) Active in MIT's Aerospace Computational Science & Engineering Lab and Gas Turbine Lab. Teaches graduate courses in fluid dynamics and numerical analysis.
Researcher
David Clark is a Senior Research Scientist at the Massachusetts Institute of Technology's Computer Science and Artificial Intelligence Lab (CSAIL) , where he has been instrumental in shaping internet architecture since the 1970s. He served as Chief Protocol Architect (1981-1989) and chaired the Internet Activities Board, focusing on the intersection of technology, economics, and policy. Research Interests : His work spans internet security, large-scale network measurement, architectural redesign, and policy analysis for mitigating malicious applications. Recent projects include Trust Zones, data-driven routing security, and congestion inference frameworks like Jitterbug. Scientific Contributions : Coined foundational principles for internet architecture Developed tussle framework for network protocol design Advocated for policy-aware network research Scientific Recognition : Fellow of the National Academy of Engineering Fellow of the American Academy of Arts and Sciences Student Mentorship : Supervised 25+ graduate theses on topics ranging from routing security to network economics and quantum computing, including advisors for key studies on BGP hijacking and broadband policy. Leadership Roles : Leads MIT's Internet Policy Research Initiative and has chaired the Computer Science and Telecommunications Board of the National Academies, influencing national and international standards for internet governance.
Lecturer
Amir Kamil is a Lecturer at the University of Michigan's College of Engineering, teaching programming and computer science courses including EECS 280 (Programming & Data Structures) and EECS 390 (Programming Paradigms). His research focuses on parallel programming models, program analysis, and educational methodologies in computer science. Research Interests: Develops programming models for parallel systems and investigates pedagogical approaches to computer science education. Current work includes UPC++ for distributed C++ applications and improving student understanding of programming concepts. Teaching: Creates comprehensive educational materials including online textbooks for programming languages and data structures. Supervises undergraduate research and develops innovative teaching methods for computational theory. Students: Mentors graduate and undergraduate researchers in programming languages and parallel computing. Recent collaborators include PhD candidates and industry researchers at Microsoft, Amazon, and Apple.
Researcher
Bernd Mohr is a senior scientist and Division Head of the 'Application Support' division at the Jülich Supercomputing Centre (JSC) , part of the Institute for Advanced Simulation (IAS) at Forschungszentrum Jülich. He leads the Scalasca performance tools project in collaboration with Prof. Felix Wolf (TU Darmstadt) and oversees user support, performance analysis, and training at JSC. Previously, he served as deputy head of the division for 15 years and held a postdoctoral position at the University of Oregon, where he developed the foundational TAU performance analysis framework . Education: Diploma thesis and Ph.D. at the University of Erlangen (Germany), focusing on performance analysis tools for parallel computing. Research Expertise: Specializes in parallel programming, HPC performance optimization, and benchmarking. His work supports exascale computing initiatives, including leadership roles in the International Exascale Software Project (IESP/BDEC), European Exascale Software Initiative 2 (EESI2), and Jülich’s EIC and ECL projects. He has authored dozens of articles on parallel program performance analysis and tuning. Professional Involvement: Served on steering committees for SC and ISC conference series. Team leader of the 'Programming Environments and Performance Analysis' group from 2000 to 2024. Labs/Teams: Heads the ATML Parallel Performance team and contributes to the Scalasca collaboration. His work bridges tool development, user support, and large-scale computational challenges.
Professor
Jonathan Cook is a Professor in the Department of Computer Science at New Mexico State University (NMSU). He specializes in software process improvement, reliable component-based systems, and high-performance computing (HPC) performance analysis. His work includes developing tools and methodologies for monitoring HPC applications, optimizing memory systems, and validating proxy applications against real-world software. Education: Cook holds a Ph.D. in Computer Science from the University of Colorado at Boulder (1996), an M.S. in Computer Engineering from Case Western Reserve University (1991), and a B.S. in Computer Engineering from the same institution (1988). Research Interests: His expertise spans HPC performance analysis, runtime monitoring systems, compiler optimization, and software engineering environments. He focuses on improving the reliability and efficiency of large software systems through empirical methods and tool development. Recent Work Trends: His articles emphasize HPC monitoring (e.g., heartbeat data analysis, proxy application validation), novel memory architectures (scratchpad memory, 3D PIM NoCs), and compiler-driven performance optimization. His work bridges theoretical models with practical deployment in production environments. Grants and Advising: While specific grants or student advisees are not listed, his research actively involves experimental validation through collaborative projects with institutions like the Exascale Computing Project (ECP). Labs/Teams: His contributions align with NMSU’s broader efforts in HPC and software engineering, though no specific lab names are mentioned in the provided text.
Research Professor
Dr. Kai Polsterer is the Scientific Director of the Heidelberg Institute for Theoretical Studies (HITS) since January 2025, succeeding Tilmann Gneiting. He has been a leading researcher at HITS since 2013, heading Europe's first astroinformatics research group. His work focuses on developing machine learning methods to handle exponential data growth in astrophysics, including projects like the ERC Synergy Grant for universe mapping and exascale computing initiatives (SPACE). He collaborates across disciplines with statisticians and physicians to advance weather forecasting and cardiological analysis. Polsterer is actively involved in international organizations such as the International Astroinformatics Association (IAIA, President since 2023), IEEE Task Force on Mining Complex Astronomical Data, and the German Physical Society's AI working group. His research spans astroinformatics, data science, and interdisciplinary applications of AI. His expertise includes photometric redshift estimation, galaxy classification, and unsupervised learning techniques. Polsterer has pioneered tools like PINK (Parallelized Kohonen Maps) and contributed to projects like the LUCIFER instrument for near-infrared spectroscopy. He emphasizes open science and collaborative frameworks, such as the HiPS ecosystem for astronomical data visualization. His current role as Scientific Director reflects his leadership in advancing theoretical studies through computational and data-driven approaches. Polsterer’s contributions include over 50 peer-reviewed articles, spanning astroinformatics, machine learning applications in astronomy, and computational methodologies. He advocates for interdisciplinary research, bridging astrophysics, computer science, and medical data analysis. His ERC Synergy Grant project exemplifies his commitment to large-scale, collaborative science addressing fundamental questions in cosmology and data science.
Professor
Professor Maurizio Piai is a faculty member in the Physics Department at Swansea University, part of the Faculty of Science and Engineering. His research focuses on theoretical particle physics, particularly exploring physics beyond the Standard Model, lattice gauge theories, and holographic models. He has contributed extensively to studies involving symplectic gauge theories, composite Higgs models, and the application of holography to understand confinement and phase transitions. Piai's work includes investigations into meson and baryon spectroscopy, dilaton physics, and non-perturbative dynamics using advanced lattice techniques. He collaborates widely, leading projects on topics like the density of states method and the conformal window in gauge theories. His research frequently addresses implications for beyond Standard Model physics and dark matter candidates. Education details are not explicitly provided in the text but given his position, likely holds a PhD in Theoretical Physics from a leading institution. Supervision includes current and past PhD students focused on lattice field theory, holography, and matrix models. His work has been published in top journals like Physical Review D and Journal of High Energy Physics , with recent emphasis on Sp(N) gauge theories and spectral density analyses. Grants and funding details are not detailed here, but his involvement in large-scale projects like lattice simulations at the Exascale suggests significant research support. Piai is affiliated with the Morgan Advanced Studies Institute (MASI) and contributes to collaborative networks in theoretical physics. His office is located at 515B Vivian Building, Singleton Campus.
Researcher
Vincent Moureau is a CNRS Research Fellow (HDR) at the CORIA laboratory, specializing in advanced computational fluid dynamics and combustion modeling. His research focuses on Large-Eddy Simulation (LES) of turbulent flows, spray dynamics, and thermo-acoustic instabilities in complex geometries. He is a core developer of the YALES2 solver, a high-order unstructured code for multiphase reactive flows. Positions: Research Fellow at CORIA, HDR, and affiliated with INSA de Rouen for teaching. Key Expertise: LES in gas turbines, piston engines, and wind turbines; numerical methods for HPC systems. He has taught courses on numerical methods, aerodynamics, and CFD software training. His work earned awards including the 2018 Grand Prix ONERA and the Digital Simulation Collaboration Award. His research includes industrial collaborations with SAFRAN and INRIA. Labs/Teams: Leads the YALES2 development team and contributes to the SIAME project for exascale computing. Active in the SIAME and MATI projects for aero-thermal systems and combustion modeling.
Researcher
Ricardo Jorge Bessa is the Coordinator of the Center for Power and Energy Systems at INESC TEC. He holds a Licenciado in Electrical and Computer Engineering (2006, FEUP), M.Sc. in Data Analysis (2008, FEP), and Ph.D. in Sustainable Energy Systems (2013, MIT Portugal Program). His research focuses on renewable energy integration, smart grids, and decarbonization strategies. He leads European projects such as Horizon 2020 UPGRID and collaborates with Argonne National Laboratory. As an IEEE Senior Member and Associate Editor of IEEE Transactions on Sustainable Energy, he has authored over 60 journal papers and 120 conference papers. His work addresses challenges in energy storage, AI-driven forecasting, and carbon-aware infrastructure design. **Education**: Licenciado (5-year), Electrical and Computer Engineering, FEUP (2006) M.Sc., Data Analysis and Decision Support Systems, FEP (2008) Ph.D., Sustainable Energy Systems (MIT Portugal), FEUP (2013) **Research Interests**: Renewable energy forecasting and market mechanisms Smart grid flexibility and decarbonization High-performance computing sustainability Electric vehicle infrastructure optimization **Key Projects**: European FP6/FP7/Horizon 2020 initiatives, Argonne collaboration, and national energy storage consulting. **Awards**: ESIG Excellence Award (2022). **Advising**: Supervised 8+ theses on energy systems optimization and sustainability. **Labs/Teams**: Leads the INESC TEC Power and Energy Systems team, collaborating with academia and industry on grid resilience and green hydrogen production.
Professor
Professor Andreas Juttner is a Professor of Theoretical Physics at the University of Southampton, affiliated with the Department of Physics and Astronomy. His research focuses on lattice Quantum Chromodynamics (QCD), particle physics, and high-energy phenomena, with particular emphasis on semileptonic decays and computational methods in theoretical physics. He leads or co-leads multiple international research projects funded by the EPSRC, STFC, and the European Union, including the EXA-LAT project exploring lattice field theory at the exascale and the ERC-funded NEWPHYSICSHPC initiative. His work spans lattice calculations of form factors, systematic error analysis in inclusive decays, and interdisciplinary collaborations on quantum gravity via holography. Current PhD students under his supervision include Ahmed Elgaziari (PhD Physics & Astronomy), Rajnandini Mukherjee (PhD Physics), and Callum James Radley-Scott (PhD Physics). He is a member of the Southampton High Energy Physics (SHEP) group and the STAG Research Centre. Recent publications emphasize precision studies of B and D meson decays, lattice QCD benchmarking (FLAG Review 2024), and Bayesian methods for form factor analysis. Research projects include exploring exascale computing's role in advancing lattice field theory and probing new physics through collider and gravitational wave observables.
Professor
Florina M. Ciorba is a Professor in the field of High-Performance Computing (HPC), affiliated with the University of Basel. Her research focuses on parallel algorithms, fault-tolerant systems, dynamic load balancing, and energy-efficient computing. She has contributed extensively to HPC workflows, scheduling techniques, and resilient numerical methods for extreme-scale simulations. Key research areas include: Parallel and distributed systems Load balancing and scheduling algorithms Fault tolerance mechanisms GPU and heterogeneous computing Energy-aware HPC applications Recent work emphasizes scalable particle simulations, application classification using ML, and optimizing astrophysics workflows. She collaborates with international teams on standards like SPEChpc 2021 benchmarks and HPC operational autonomy loops. Publications span top venues including IEEE Transactions on Parallel and Distributed Systems, Euro-Par, and Cluster conferences. Her work addresses both algorithmic innovations and software implementations for next-generation HPC platforms.
Professor
George Bosilca is a Professor at the University of Tennessee, Knoxville, specializing in high-performance computing and parallel systems. With over two decades of research contributions, he has established himself as a leading expert in task-based runtime systems, distributed computing, and MPI implementations. His research focuses on developing and optimizing task-based runtime systems for extreme-scale computing environments, with particular emphasis on fault tolerance, performance optimization, and scalability. Bosilca's work spans multiple domains including scientific computing, climate modeling, and deep learning applications. He has made significant contributions to the PaRSEC runtime system and has extensively researched MPI optimization techniques for modern HPC architectures. The trend in Bosilca's recent publications demonstrates a strong focus on addressing challenges in exascale computing, including fault tolerance in distributed systems, GPU acceleration for scientific workloads, and energy-efficient computing techniques. His work bridges theoretical computer science with practical implementations for real-world scientific applications across various domains. Bosilca maintains extensive collaborations with leading researchers in the HPC community, most notably with Jack J. Dongarra (103 co-publications), Aurelien Bouteiller (60 co-publications), and Thomas Hérault (54 co-publications). These collaborations have resulted in numerous publications at top-tier conferences including SC, IPDPS, and EuroMPI, as well as in prestigious journals such as IEEE Transactions on Parallel and Distributed Systems and the International Journal of High Performance Computing Applications.
Researcher
Thomas J. Naughton is a researcher affiliated with the University of Reading and Oak Ridge National Laboratory. He specializes in High Performance Computing (HPC), focusing on fault tolerance, quantum computing integration, and distributed systems. Research Interests: His work bridges HPC and quantum computing, develops fault-tolerant systems, and explores computational models through optical computing. Recent Publications: His 2026-2024 papers address quantum-HPC convergence software stacks, virtualization performance, and fault injection frameworks. Educational Contributions: He co-developed Bebras-inspired computational thinking resources for K-12 education, emphasizing task-based learning.
