جست‌وجوی استاد و پژوهشگر

Abhishek Jainمشاهده پروفایل

دانشیار

• Cryptography
• Computer Security
• Privacy
• +۵ مورد دیگر

Abhishek Jain is an Associate Professor in the Department of Computer Science at Johns Hopkins University and a Senior Scientist at NTT Research. He is affiliated with the Data Science and AI Institute, the Information Security Institute, and the Algorithms and Complexity group. University: Johns Hopkins University Department: Computer Science Academic Rank: Associate Professor Institutional Roles: Co-director of the Advanced Research in Cryptography group, member of the Theory Group, and co-leader of the Cryptography Group Education: Ph.D. in Computer Science from the University of California Los Angeles (2012), advised by Amit Sahai and Rafail Ostrovsky. Recipient of the Symantec Outstanding Graduate Student Award during his Ph.D. Research Interests Cryptography Secure computation Proof systems Program obfuscation Privacy Blockchain Theoretical computer science Research Trends: His recent publications emphasize cryptographic protocols for homomorphic encryption, zero-knowledge proofs, and secure multi-party computation, alongside applications in blockchain and privacy-preserving systems. Key themes include scalability, verifiable evaluation, and adapting cryptographic techniques to dynamic and distributed environments. Scientific Awards 2020 NSF CAREER Award Best Paper Awards at Eurocrypt and the International Conference on the Theory and Applications of Cryptographic Techniques Advising & Grants: Mentors Ph.D. students and interns/postdocs at NTT Research. Research funded by NSF, DARPA, JP Morgan, Ethereum Foundation, Stellar, Cisco, Samsung, and JHU Catalyst awards. Labs & Teams: Co-leads the Cryptography Group at Johns Hopkins, participates in the DC Area Crypto Day, and organizes the weekly Theory Seminar. Collaborates with institutions including MIT CSAIL, BUSEC, and Microsoft Research New England.

• Distributed Systems
• Cryptocurrencies
• Computer Security
• +۷ مورد دیگر

David Mazières is a Professor at Stanford University , affiliated with the School of Engineering and the Department of Computer Science . He serves as a software engineer at the Stellar Development Foundation . His work bridges academic research and industry applications in distributed systems and security. University: Stanford University Academic Rank: Professor Email: dm@scs.stanford.edu Research Interests: David Mazières' research focuses on distributed systems , cryptocurrencies , and computer security . Key areas include consensus protocols (e.g., Stellar ), low-latency scheduling ( Syrup , Shinjuku ), and cryptographic techniques for privacy and security ( SafetyPin , CCFI ). Key Achievements: His notable works include: TCP-ENO (RFC 8547) for secure transport protocols Stellar Consensus Protocol for decentralized finance SOSP 1999 Best Paper for 'Separating key management from file system security' Teaching Contributions: He has taught core and advanced courses at Stanford since 2005, including CS212 (Operating Systems) , CS240h (Functional Systems in Haskell) , and CS251 (Cryptocurrencies and Blockchain Technologies) . Previously taught courses at NYU (2001-2005).

Simon Birrerمشاهده پروفایل

استادیار

• Cosmology
• Gravitational Lensing
• Dark Matter
• +۲ مورد دیگر

Simon Birrer is an Assistant Professor in Physics and Astronomy at Stony Brook University, specializing in cosmology and gravitational lensing. He holds a PhD from ETH Zurich (2016) and previously served as Kavli Fellow at Stanford University. Birrer leads research probing dark matter and dark energy using gravitational lensing phenomena. His group develops computational tools for analyzing strong gravitational lensing data to study cosmic expansion and dark matter distribution. Research areas include time-delay cosmography, Hubble constant measurements, and machine learning applications in astrophysics. Recent publications focus on multi-messenger gravitational lensing (2025), LSST survey applications (2025), and AI-powered lens modeling pipelines (2025). His work consistently addresses fundamental cosmological tensions like the Hubble constant discrepancy. Awards: Kavli Postdoctoral Fellowship (2019-2022) Kugelpyramide Lifetime Achievement Award Experimental Innovation Award (ETH Zurich) Research Group: Leads the SBU Strong Lensing group with 9+ graduate students and postdocs. The group participates in major collaborations including LSST Strong Lensing Science Collaboration (co-chair), LSST Dark Energy Science Collaboration, and TDCOSMO.

Alexandre Bouchard-Côtéمشاهده پروفایل

استاد

• Computational Statistics
• Bayesian Inference
• Monte Carlo Methods
• +۴ مورد دیگر

Alexandre Bouchard-Côté is a Professor of Statistics at the University of British Columbia (UBC), affiliated with the Department of Statistics within the Faculty of Science. His research focuses on computational statistics, Bayesian methods, and Monte Carlo techniques, with applications in evolutionary biology, cancer genomics, and computational linguistics. Education : PhD in Computer Science (with Designated Emphasis in Statistics) from UC Berkeley (2010), BSc in Mathematics and Computer Science from McGill University (2005). Affiliations : Director of the Blang probabilistic programming project and leader of the Bouncy Particle Sampler research group. Research Interests : Bouchard-Côté develops scalable Bayesian computational methods, including non-reversible Monte Carlo algorithms like the Bouncy Particle Sampler, and applies these to problems in cancer phylogenetics, evolutionary dynamics, and historical linguistics. His work emphasizes bridging theoretical foundations with practical tools for data science. Publications Trends : Recent work spans distributed sampling frameworks (e.g., Pigeons.jl), variational phylogenetic inference, and cancer clonal evolution modeling. His articles often address algorithmic scalability and interdisciplinary applications in biology and astronomy. Awards : CRM-SSC Prize in Statistics (2024) PIMS-UBC Mathematical Sciences Young Faculty Award (2018) Tweedie New Researcher Award (2016) Advising & Grants : Supervises graduate students (e.g., Son Luu, Nikola Surjanovic) and leads funded projects on distributed MCMC and cancer genomics. Collaborates with institutions like the Simons Foundation and the Canadian Statistical Sciences Institute (CANSSI). Labs/Teams : Core member of the UBC Statistical Machine Learning group, contributing to open-source tools like Blang and the Bouncy Particle Sampler implementation.

David Bindelمشاهده پروفایل

دانشیار

• Applied Numerical Linear Algebra
• Eigenvalue Problems
• Network Analysis
• +۵ مورد دیگر

David Bindel is an Associate Professor in the Department of Mathematics at Cornell University, affiliated with the College of Arts and Sciences, College of Engineering, and Cornell Ann S. Bowers College of Computing and Information Science. He earned his Ph.D. in Mathematics from the University of California, Berkeley in 2006. His research focuses on applied numerical linear algebra, eigenvalue problems, and their applications in plasma physics, network analysis, and nonlinear systems. He develops methods for analyzing complex systems, including magnetic confinement in stellarators, stability of MHD systems, and community detection in networks. His work bridges theoretical foundations with practical computational tools, such as formal verification of linear algebra algorithms and scalable Gaussian process models. Bindel’s research explores the interplay between structure and computation, leveraging eigenvalue analysis to address challenges in computer vision, opinion dynamics, and engineering design. He has contributed to advancements in numerical methods for large-scale systems, including iterative solvers, spectral approximation techniques, and stochastic optimization. His interdisciplinary approach spans applied mathematics, computer science, and physics, with applications in fusion energy, machine learning, and network science. Recent work highlights include high-order expansions for magnetic confinement, adaptive filtering for dynamical systems, and Bayesian optimization strategies. His publications emphasize rigorous analysis alongside computational scalability, addressing both theoretical and practical aspects of modern scientific computing. Despite no explicitly listed awards, his contributions reflect significant impact in his fields.

Marilyn J Smithمشاهده پروفایل

استاد

• Unsteady Aerodynamics
• Computational Aeroelasticity
• Computational Fluid Dynamics (CFD)
• +۳ مورد دیگر

Marilyn J Smith is the David S. Lewis Professor and Director of the Vertical Lift Research Center of Excellence (VLRCOE) at the Georgia Institute of Technology's Daniel Guggenheim School of Aerospace Engineering. She leads a seven-university consortium conducting vertical lift research for the U.S. Army, Navy, and NASA, and has secured over $200 million in collaborative research funding. Computational Nonlinear Computational Aeroelasticity Lab Director NASA FUN3D development team contributor Aerospace Systems Design Lab (ASDL) affiliate Her research spans unsteady aerodynamics, computational aeroelasticity, and sustainable energy applications across rotary-wing, fixed-wing, and launch vehicles. She serves on the Vertical Lift Consortium (VLC) Board of Directors and Vertical Flight Society (VFS) Board, while acting as VFS Deputy Technical Director for Aeromechanics and leading international NATO AVT panels on UAV aerodynamics. Recent publications focus on galaxy cluster cosmology, ship-helicopter dynamic interface modeling, and Type Ia supernova analysis. She has won prestigious awards including the AIAA Aerodynamics Award and multiple American Helicopter Society honors for research, mentoring, and service. 2022 AIAA Aerodynamics Award 2015 Best Paper Awards at AHS Forum 2014 & 2012 AHS Agusta-Westland International Fellowships Her laboratory work integrates high-performance computing with aerospace design and develops advanced turbulence models through partnerships with Georgia Tech Research Institute (GTRI). She contributes to public science communication with appearances on National Geographic, PBS, NPR, and local media.

• Data Visualization
• Visual Data Analysis
• Data Science
• +۳ مورد دیگر

Univ.-Prof. Torsten Möller, PhD is a Professor at the University of Vienna and serves as Head of the Research Group Visualization and Data Analysis and Head of the Research Network Data Science. His work spans data visualization, visual analytics, and human-computer interaction, with a focus on biomedical, environmental, and societal data applications. Academic rank: Professor Research group: Visualization and Data Analysis Network: Data Science Email: torsten.moeller@univie.ac.at Research interests include: Visual data analysis for complex systems Interdisciplinary applications in climate science and medicine Human-computer interaction in data exploration Image processing and computer graphics Recent publication trends show expertise in: Visualizing climate change and pandemic data Multi-volumetric and network analysis Algorithmic transparency and user-centered design Interdisciplinary collaborations (e.g., astrophysics, medical imaging) Statistical and uncertainty visualization Design frameworks for visualization recommendation Teaching includes courses in: Computer graphics and visualization Image processing and analysis Human-computer interaction Data analysis projects Doctoral research seminars

Qiang Tangمشاهده پروفایل

دانشیار

• Cryptography
• Blockchain Technology
• Computer Security
• +۳ مورد دیگر

Qiang Tang is currently an Associate Professor (Level D) at the School of Computer Science of The University of Sydney. Previously, he was a Senior Lecturer (2021.1-2024.12) at USYD and an Assistant Professor at the Computer Science Department of New Jersey Institute of Technology (2016.8-2021.1), where he co-directed the JACOBI Blockchain Lab with Prof. Jian Pei and Prof. Zhenfeng Zhang. He completed his PhD at the University of Connecticut under Prof. Aggelos Kiayias and Prof. Alexander Russell, following postdoctoral research at Cornell University with Prof. Elaine Shi. His research spans applied and theoretical cryptography, blockchain technology, privacy, and computer security. His work is supported by ARC, Google, Ethereum Foundation, Stellar Foundation, Protocol Labs, Algorand Foundation, Oracle, and USYD. Previous funding includes NSF, JD.com, AFRL, DoE, and Particl Foundation. His research has led to significant contributions in consensus protocols, distributed randomness generation, secure multi-party computation, and privacy-preserving technologies. Tang's publications reveal a strong focus on practical cryptographic solutions for blockchain and distributed systems. His recent work demonstrates expertise in asynchronous consensus, optimal protocol design, and secure implementations for real-world applications. His research shows consistent innovation in improving efficiency, security, and scalability of distributed systems. Scientific Awards: 2025 DSN Best Paper Award 2024 ICDCS Distinguished Paper Award 2023 SOAR Prize, USYD 2023 Oracle for Research Award 2022 Stellar Foundation Research Awards 2022 Ethereum Academic Award 2019 MIT Technical Review, 35 Chinese Innovators Under 35 Tang actively mentors PhD and Master's students, with several alumni now holding faculty positions or research roles at institutions like City University Hong Kong, Chinese Academy of Sciences, and A*STAR Singapore. He has received significant research funding including a multi-year Google project on End-to-End Secure Cloud and an ARC DP grant on Order Fairness in Decentralized Systems. He leads the research in his lab focusing on blockchain protocols and cryptographic applications, with strong industry connections through collaborations with Google, Ethereum Foundation, Stellar Foundation, and Protocol Labs. His team regularly publishes in top security and cryptography venues including CRYPTO, CCS, USENIX Security, and S&P.

Oliver Schmitzمشاهده پروفایل

استاد

• Plasma Edge Physics
• Plasma Wall Interaction
• Three-Dimensional Plasma Edge Transport
• +۶ مورد دیگر

Oliver Schmitz is a Professor in the Department of Nuclear Engineering & Engineering Physics at the University of Wisconsin-Madison, where he leads research in plasma edge physics for magnetic confinement fusion and next-generation particle accelerators. His work bridges experimental plasma science, computational modeling, and diagnostic development with applications in both tokamaks and stellarators. Education: PhD (2006), Heinrich-Heine-Universität Diploma (2003), Rheinische Friedrich-Wilhelms-Universität Professor Schmitz's research focuses on 3D plasma edge transport phenomena, plasma-wall interactions, and helicon plasma generation for wakefield accelerators. His group employs advanced computational tools like EMC3-EIRENE for 3D plasma edge modeling and develops active spectroscopic diagnostics to measure plasma parameters through atomic emission analysis. Key themes include resonant magnetic perturbation effects in tokamaks, inherent 3D physics in stellarators, and high-density plasma sustainment for accelerator applications. He actively develops atomic models to interpret spectroscopic data and operates helicon plasma test stands for fundamental process studies. Recent publications reveal strong emphasis on experimental-computational integration for fusion boundary physics, with significant contributions to ITER divertor solutions, stellarator exhaust optimization, and plasma-facing materials. The work shows growing focus on wakefield accelerator diagnostics through helicon plasma sources and advanced spectroscopy, alongside persistent innovation in 3D modeling of plasma-material interfaces. Scientific Awards: 2020 Thomas and Suzanne Werner Chair Professorship 2018 UW Madison Teaching Academy Fellow 2017 ITER Science Fellowship & Vilas Mid-Career Award 2015 DOE Early Career Award & NSF CAREER Award 2011 Torkil Jensen Award (General Atomics) 2007 Günther-Leibfried-Preis (Jülich) Professor Schmitz directs multiple DOE/NSF-funded research programs including his UW Madison laboratory and AWAKE project contributions at CERN. He mentors graduate students through NE 890/990 thesis research courses and has developed nationally recognized K-12 outreach including the "Plasma Show" for elementary schools and "Plasma Academy" for high-school educators developing AP Physics curriculum modules. His leadership extends to university governance through the Kaufman seminar on academic leadership. His research group operates helicon plasma test stands and computational facilities for EMC3-EIRENE simulations, with current efforts focused on high-density plasma sources for accelerators and resilient divertor solutions for stellarators. The group maintains strong international collaborations with ITER, CERN, and major fusion facilities worldwide.

James Shorterمشاهده پروفایل

استاد

• Protein Folding and Proteostasis
• Neurodegenerative Diseases
• Prion and Amyloid Biology
• +۷ مورد دیگر

James Shorter is a Professor of Biochemistry and Biophysics at the Perelman School of Medicine, University of Pennsylvania. He is affiliated with multiple prestigious institutes, including the Institute on Aging (IOA), the Institute for Translational Medicine and Therapeutics (ITMAT), the Penn Center for AIDS Research (CFAR), the Chemistry-Biology Interface (CBI), and the Penn Institute for RNA Innovation. He mentors several training programs such as the Penn Summer Undergraduate Internship Program (SUIP), PennPREP, and the Translational Research Immersion Program (TRIP), and serves as a Primary Trainer at the Center for Neurodegenerative Research (CNDR). Ph.D. in Cell Biology, University of London, 2000 M.A. in Biology, University of Oxford, 1995 Dr. Shorter’s research focuses on protein homeostasis, particularly the mechanisms of protein disaggregation and the role of prion-like domains in neurodegenerative diseases such as ALS, Alzheimer’s, Parkinson’s, and frontotemporal lobar degeneration. His lab investigates the Hsp104 disaggregase from yeast and has engineered variants to combat human proteinopathies. They also identified the mammalian disaggregase system (Hsp110/Hsp70/Hsp40) and explore how small molecules and nuclear import receptors can reverse pathological phase transitions of RNA-binding proteins like TDP-43 and FUS. His work bridges structural biology, genetics, and translational neuroscience. His recent publications highlight trends in targeting TDP-43 and FUS proteinopathies, engineering Hsp104 for selective detoxification, understanding mitochondrial disaggregases like Skd3, and modulating phase transitions with nuclear import receptors. His research spans from fundamental mechanisms of protein folding to therapeutic development for neurodegenerative diseases. Faculty Member, Institute on Aging (IOA) Faculty Member, Institute for Translational Medicine and Therapeutics (ITMAT) Mentor, Penn Summer Undergraduate Internship Program (SUIP) Primary Trainer, Center for Neurodegenerative Research (CNDR) Faculty Member, Penn Center for AIDS Research (CFAR) Member, Penn Institute for RNA Innovation Mentor, Translational Research Immersion Program (TRIP) Dr. Shorter advises numerous graduate students and postdoctoral researchers through the Biochemistry and Molecular Biophysics, Pharmacology, Neuroscience, and Cell and Molecular Biology graduate groups. His lab receives funding from NIH and other sources to support research on protein disaggregation, phase separation, and neurodegenerative disease mechanisms. He has trained many scientists now active in academia and biotech. His lab, located in Stellar-Chance Laboratories, operates at the intersection of biochemistry, cell biology, and translational medicine, with active projects on Hsp104 engineering, mitochondrial proteostasis, and the role of RNA-binding proteins in disease. The lab collaborates widely across Penn and with international partners to advance understanding and treatment of protein misfolding disorders.

August Evrardمشاهده پروفایل

استاد

• Cosmology
• Astrophysics
• Galaxy Clusters
• +۲ مورد دیگر

Professor August Evrard is a distinguished academic at the University of Michigan, holding the Arthur F. Thurnau Professorship in Physics and Astronomy. He is affiliated with the Department of Physics within the College of Literature, Science, and the Arts. Known for his contributions to cosmology and astrophysics, he pioneered the Problem Roulette tool, recognized with the Provost's Teaching Innovation Prize. His research focuses on galaxy clusters, dark matter, and cosmological surveys like the Dark Energy Survey (DES) and XXL Survey. He has been honored as an AAS Fellow (2025) and has contributed to advancements in physics education through innovative teaching methods and technologies. In research, Prof. Evrard explores topics such as dark matter halo dynamics, galaxy cluster properties, and weak lensing analyses. His work spans observational cosmology, computational modeling, and multi-wavelength astronomy. Notable projects include studies on galaxy cluster mass distributions, the relationship between X-ray emissions and velocity dispersions, and the application of machine learning to astrophysical data analysis. His contributions to education highlight the integration of AI-driven tools to enhance learning, as seen in initiatives like the Problem Roulette and course recommendation systems. Prof. Evrard's awards include the Provost's Teaching Innovation Prize for Problem Roulette and his AAS Fellowship. His academic leadership and innovative approaches to both research and education solidify his role as a pivotal figure in astrophysics and STEM pedagogy.

Alyson M. Brooksمشاهده پروفایل

دانشیار

• Galaxy Formation and Evolution
• Galactic Structure
• Cosmological Simulations
• +۵ مورد دیگر

Alyson M. Brooks is an Associate Professor in the Department of Physics and Astronomy at Rutgers University, part of the School of Arts and Sciences. Her research focuses on galaxy formation and evolution, particularly using cosmological simulations to study dark matter dynamics, stellar abundances, and galactic structures. She holds a PhD in Astronomy from the University of Washington (2008) and has held prestigious fellowships, including the Sherman Fairchild Fellowship at Caltech and the Grainger Postdoctoral Fellowship at UW-Madison. Brooks has been recognized with awards such as the 2015 Alfred P. Sloan Research Fellowship and the 2019 Maria Goeppert Mayer Award from the American Physical Society. Her educational background includes a B.A. in Physics with Astronomy from Macalester College (2000) and an M.S. in Astronomy from the University of Washington (2004). Her research interests span topics like the interplay between baryonic processes and dark matter, chemical evolution in dwarf galaxies, and the role of feedback mechanisms in galaxy formation. Brooks is actively involved in outreach, including founding the RU-PREP program to support undergraduate research and mentoring initiatives. Brooks has authored over 100 refereed publications, with recent work exploring the resolved stellar populations of dwarf galaxies using the James Webb Space Telescope and analyzing dark matter halo properties through simulations. Her scientific contributions have advanced understanding of galaxy kinematics, dark matter interactions, and the evolution of galactic structures across cosmic time.

Dan McCammonمشاهده پروفایل

استاد

• X-ray Astronomy
• Astrophysics
• Diffuse X-ray Background
• +۵ مورد دیگر

Dan McCammon is a Professor in the Department of Physics at the University of Wisconsin-Madison, affiliated with the College of Letters & Science. His research focuses on X-ray astronomy, including studies of the diffuse X-ray background, interstellar and intergalactic media, and the development of advanced X-ray instrumentation. He is a key contributor to the XRISM (X-ray Imaging and Spectroscopy Mission) satellite, leading efforts in high-resolution X-ray spectroscopy and mission operations. McCammon's work emphasizes understanding cosmic plasma dynamics, galaxy cluster physics, and supernova remnant evolution through cutting-edge observational techniques and detector technology. His research interests span multiple subfields, including the thermodynamic properties of galactic clusters, charge-exchange processes in astrophysical plasmas, and the design of cryogenic microcalorimeters for space-based observatories. He has pioneered advancements in transition-edge sensors (TES) and superconducting detectors, enhancing the precision of X-ray spectral measurements. McCammon has contributed to numerous sounding rocket missions, such as Micro-X, and has been instrumental in the development of the Line Emission Mapper (LEM) probe concept, aimed at mapping the soft X-ray sky with unprecedented resolution. His work on the Hitomi (ASTRO-H) satellite demonstrated breakthroughs in resolving the thermal and dynamic properties of cosmic plasmas, such as the Perseus galaxy cluster and the Crab Nebula. His publications highlight a focus on high-resolution X-ray spectroscopy of cosmic sources, including galaxy clusters, active galactic nuclei, and supernova remnants. He has explored topics like non-thermal pressure contributions in cluster cores, ionized plasma diagnostics, and the role of charge-exchange emissions in interpreting diffuse X-ray backgrounds. McCammon's instrumentation innovations have enabled breakthroughs in measuring spectral features with sub-eV resolution, advancing our understanding of astrophysical processes. Despite the absence of explicitly listed awards or grants in the provided text, his leadership in major space missions and pioneering detector technologies underscores his contributions to the field. His research team collaborates on international projects, such as XRISM and LEM, reflecting a commitment to advancing observational astrophysics through interdisciplinary collaboration.

Matt Nowinskiمشاهده پروفایل

دانشیار

• Aerospace Engineering
• Asteroid Dynamics
• Machine Learning
• +۵ مورد دیگر

Matt Nowinski is a Collegiate Associate Professor in the Department of Mechanical Engineering at Virginia Tech's College of Engineering. His professional roles include advisory board memberships and leadership positions within the department. He holds multiple degrees including a Ph.D. in Mechanical Engineering from ETH Zurich (1999), an M.S. in Computer Science from Syracuse University (2022), and prior mechanical/aerospace engineering degrees from Virginia Tech. His research focuses on asteroid dynamics (particularly D-type and V-type asteroids), gas turbine engines, aeroelasticity, and education technology. Notable areas include lightcurve analysis, surface mineralogy modeling, and machine learning applications in astronomy. His work bridges aerospace engineering with astrophysics, leveraging both experimental and computational methods. Dr. Nowinski has over 24 years of industry experience as a Boeing subject matter expert in military communications systems, complemented by academic roles at George Mason University and University of Chicago. He is a recipient of the John Jones Faculty Fellowship and Society of Distinguished Alumni honor. His research contributions span asteroid characterization, turbine blade flutter mechanisms, and telescope instrumentation. Current work emphasizes observational astronomy through the Stone Edge Observatory and Slack-based collaborative platforms. He actively contributes to advancing STEM education through innovative curricula and research integration.

• Computational Nuclear Engineering
• Nuclear Energy Systems
• Radiation Shielding
• +۹ مورد دیگر

Paul Wilson serves as the Grainger Professor of Nuclear Engineering and Chair of the Department of Nuclear Engineering & Engineering Physics at the University of Wisconsin-Madison. His research develops computational tools for modeling nuclear energy systems with applications in radiation shielding, waste management, non-proliferation, and energy policy. Education: PhD in Nuclear Engineering, University of Wisconsin-Madison (1999) Dr.-Ing in Mechanical Engineering, Technical University of Karlsruhe (1998) MS in Nuclear Engineering, University of Wisconsin-Madison (1995) B.A.Sc. in Engineering Science (Nuclear Power option), University of Toronto (1992) Wilson's research spans computational nuclear engineering with emphasis on Monte Carlo methods, nuclear fuel cycles, and proliferation analysis. His Computational Nuclear Engineering Research Group (CNERG) develops simulation tools for radiation transport, waste transmutation, and fusion systems. Key projects include the Infinity Two fusion pilot plant design and Cyclus nuclear fuel cycle simulator. Recent publications reveal strong focus on fusion energy systems (particularly stellarator-based designs like Infinity Two), machine learning applications in nuclear security, and advanced neutronics modeling. His work bridges computational methods with real-world nuclear challenges including waste management and non-proliferation. Scientific awards: Fellow of the American Nuclear Society (2023) American Nuclear Society Young Member Advancement Award (2019) American Nuclear Society Arthur Holly Compton Award (2018) Grainger Professor of Nuclear Engineering (2016) American Nuclear Society Presidential Citation (1996) Wilson advises graduate students through thesis research courses (N E 790/890/990) and has secured significant funding from the U.S. Department of Energy. His consultancy roles include work with CEA Saclay, Karlsruhe Institute of Technology, and the Blue Ribbon Commission on America’s Nuclear Energy Future. He previously served on the Generation IV Technology Roadmap Committee (2001-2003). He leads the Computational Nuclear Engineering Research Group (CNERG), which develops open-source tools including PyNE and Cyclus. The group's work spans fusion pilot plant design, nuclear security applications, and fuel cycle simulation for next-generation nuclear systems.