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Peter OppeneerView profile

Professor

Uppsala UniversitySweden

Peter Oppeneer is a Professor in the Materials Theory group within the Department of Physics and Astronomy at Uppsala University, Sweden. His research program focuses on theoretical condensed matter physics with emphasis on ultrafast phenomena and magnetic materials. His research interests span femtosecond magnetism, ultrafast spin and orbital currents, out-of-equilibrium magnon and phonon dynamics, unconventional superconductivity, multipolar and hidden order parameters, and orbitronics. The group develops both analytical theories and numerical simulation codes, combining ab initio methods with model Hamiltonian approaches. Key research thrusts include ultrafast demagnetization mechanisms, spin-crossover materials, molecular spintronics, and topological quantum states in magnetic materials. Analysis of recent publications reveals strong focus on altermagnetism, terahertz spin dynamics, Dirac semimetals, and laser-induced phase transitions. The group's work bridges fundamental quantum theory with applications in next-generation spintronic devices and ultrafast magnetic switching technologies. Collaborative activities include work with experimental groups on ultrafast spectroscopy, X-ray magnetic circular dichroism, and terahertz emission studies. The group maintains active collaborations across Europe and internationally, particularly in the areas of femtosecond magnetism and topological materials. Research infrastructure includes development of specialized computational codes for Eliashberg theory, dynamical mean field theory, and ultrafast spin dynamics simulations. The group contributes to major international facilities including synchrotron and free-electron laser sources for time-resolved studies.

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Jerome LiangView profile

Professor

Stony Brook UniversityUnited States

Professor Jerome Liang is a distinguished faculty member at Stony Brook University's Renaissance School of Medicine, holding professorships in Radiology, Biomedical Engineering, Electrical and Computer Engineering, and Computer Science. He serves as Co-Director of Radiology Research and has established himself as a leading expert in medical imaging reconstruction techniques. Dr. Liang's educational background includes a Ph.D. in Physics from City University of New York, postdoctoral training at Duke University, and fellowship at Albert Einstein College of Medicine. His undergraduate degree in Modern Physics was obtained from Lanzhou University in China. His primary research interests focus on advanced medical imaging techniques, particularly low-dose computed tomography image reconstruction, quantitative SPECT reconstruction, high-resolution PET imaging, tissue segmentation from multi-spectral images, computer-aided diagnosis systems, and virtual colonoscopy development. His work bridges engineering principles with clinical applications to improve diagnostic imaging capabilities while reducing radiation exposure. Analysis of his recent publications reveals a strong focus on machine learning applications in medical imaging, particularly in polyp classification, dual-energy CT spectral analysis, and virtual endoscopy. His research consistently aims to enhance diagnostic accuracy while optimizing radiation dose and improving visualization techniques for various medical conditions. 1981 China-US Physics Examination and Application Program (CUSPEA) Winner (Top 25 among 250,000 candidates) 1990 NIH First Investigator Award 1996 American Heart Association Established Investigator Award 1996 Radiological Society of North America Certificate of Merit Award 2002 SUNY Chancellor's Entrepreneur Award 2007 IEEE Society Fellow 2011-2013 SBU, BNL and CSHL Certificates of Excellence in Research and Invention 2013 Stony Brook School of Medicine Award for Excellence in Translational Research Dr. Liang has secured significant research funding including NIH/NCI R01 grants for "Advanced Virtual Colonoscopy for Early Cancer Screening" and "Radiogenomics of Colorectal Polyps." He currently leads active protocols including IRB 93995-MODCR005 focused on integrating virtual and optical colonoscopies with pathological analysis. His laboratory (IRIS - Imaging Research and Informatics) continues to advance medical imaging technology while mentoring the next generation of researchers in this critical field.

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Sylvain CristolView profile

Professor

University of LilleFrance

Sylvain Cristol is a Professor at the University of Lille within the Heterogeneous Catalysis department and the Modeling and Spectroscopy (MODSPEC) group. He teaches quantum chemistry, chemical bonding, statistical physics , and X-ray absorption spectroscopy at the university’s European Master’s program. PhD in Molecular and Organic Chemistry (1997-2000, Université de Provence) Postdoctoral work at Davy-Faraday Research Lab, Royal Institution of Great Britain (2000-2002) His research focuses on modeling hydrodesulfurization and hydrodeoxygenation catalysts for biomass valorization, supported by ANR-PNRB project ECOHDOC (with Caen, Poitiers, and TOTAL). He pioneered operando X-ray absorption spectroscopy for characterizing supported oxides (Mo/Re on alumina/anatase) via the ANR SAXO project (Paris VI, Grenoble, SOLEIL). Collaborative work with Francesco Mauri (Paris VI) advanced NMR parameter modeling in solids. Publications span DFT studies , XANES spectroscopy , and solid-state NMR applied to catalysis. Scientific awards include the UCCS Thesis Prize (highest honors) for his work on dibenzothiophene reactivity on molybdenum sulfide.

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Alec M. WodtkeView profile

Professor

Max Planck Institute for Multidisciplinary SciencesGermany

Alec M. Wodtke serves as Director at the Max Planck Institute for Biophysical Chemistry and holds a Professorship at the University of Göttingen. He leads the Dynamics at Surfaces research group, which employs cutting-edge laser, molecular beam, and ultrahigh vacuum technologies to study molecular interactions at interfaces. His research focuses on understanding the fundamental rules governing energy conversion at molecular interfaces. Wodtke's work bridges macroscopic energy conversion phenomena with molecular-scale processes, investigating how energy transfers occur one molecule and one collision at a time. His group specializes in designing well-defined experiments that capture molecules in the act of reacting, providing benchmark measurements for theoretical advances in surface chemistry. Recent research trends show a strong focus on ultrafast molecular dynamics, with significant contributions to understanding hydrogen-graphene interactions, energy dissipation mechanisms at surfaces, and atomic-scale reaction kinetics. His work has important implications for developing heterogeneous catalysts, photovoltaics, and fuel cell technologies. Alexander von Humboldt Professorship (2011) ERC Synergy Grant worth 12 million euros (2024) Ertl Lecture Prize (2022) Somorjai Visiting Miller Research Professorship Moore Distinguished Scholar at Caltech Wodtke directs multiple project groups including Atom-surface scattering dynamics, Chemical dynamics using ultra-short atom pulses, First-principles simulations of molecule-surface dynamics, and Time-resolved spectroscopy of surface adsorbates. His research team has secured significant funding including Advanced ERC Grants and operates specialized facilities for surface science research.

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Possu HuangView profile

Assistant Professor

Stanford UniversityUnited States

Possu Huang serves as Assistant Professor of Bioengineering in the Department of Bioengineering at Stanford University's School of Engineering. His research group operates from the Shriram Center for Bioengineering, sharing laboratory space with the Bintu Lab while maintaining an active interdisciplinary program bridging computational and experimental protein engineering. His educational journey includes: B.A. in Molecular and Cell Biology (Biochemistry) from UC Berkeley Ph.D. in Biochemistry and Molecular Biophysics from Caltech Postdoctoral training as Senior Fellow at University of Washington Dr. Huang's research focuses on atomic-precision protein design through integrated computational-experimental approaches. His lab has pioneered breakthroughs including the first computationally designed protein-protein interface, TIM barrel fold design principles, and the eOD HIV immunogen. Current work leverages machine learning , structural biology , and library optimization to develop therapeutic proteins and nanotechnology platforms, with particular emphasis on achieving natural-level complexity in engineered systems. Analysis of his 2023-2025 publications reveals three dominant trends: (1) generative AI for all-atom protein design (e.g., Protpardelle, SHAPES), (2) immunology applications targeting MHC complexes for HIV vaccine development, and (3) optogenetic tools through engineered fluorescent proteins. These works consistently integrate deep learning with wet-lab validation to solve biomedical challenges. Dr. Huang has mentored nine graduate students to completion, including PhD candidates Carla (defended June 2025), Christian (defended May 2025), and master's students Shankara and Kirsten. His lab maintains active social media presence (@possuhuanglab) and regularly publishes high-impact research while training the next generation of protein engineers. The Huang Lab operates as a dynamic interdisciplinary hub where computational biologists collaborate with experimentalists to push the boundaries of protein design. Current projects include developing tetravalent nanobody platforms, photoswitchable binders for temporal protein control, and AI-driven solutions for HIV immunogen design, all conducted within Stanford's state-of-the-art bioengineering facilities.

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Noa MaromView profile

Associate Professor

Carnegie Mellon UniversityQatar

Noa Marom is an Associate Professor in the Department of Materials Science and Engineering at Carnegie Mellon University (CMU), holding courtesy appointments in Chemistry and Physics. She is a member of the Pittsburgh Quantum Institute (PQI) and an affiliate of the Wilton E. Scott Institute for Energy Innovation. Her research focuses on computational materials science, energy security, and quantum materials. Marom earned a B.A. in Physics and B.S. in Materials Engineering (cum laude) from the Technion-Israel Institute of Technology (2003) and a Ph.D. in Chemistry from the Weizmann Institute of Science (2010). She held postdoctoral positions at the University of Texas at Austin’s Institute for Computational Engineering and Sciences (ICES) before joining Tulane University as an Assistant Professor (2013–2016) and CMU in 2016. Her research interests include computational design of semiconductor materials, topological quantum computing, and crystal structure prediction. Key projects involve machine learning for materials discovery and quantum computing applications, such as optimizing semiconductor interfaces for stable qubits. Marom has received numerous awards, including the NSF CAREER Award (2016), DOE INCITE Awards (2017–2019), and the IUPAP Young Scientist Prize (2018). She serves as Associate Editor of npj Computational Materials. Her work spans collaborations with institutions like the Paul Scherrer Institute (Switzerland) and the Pittsburgh Supercomputing Center. Research highlights include computational studies of InAs/InSb semiconductors for quantum bits and machine learning-driven discovery of organic semiconductors.

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Jürgen KönigView profile

Professor

University of Duisburg-EssenGermany

Prof. Dr. Jürgen König is a Professor at the University of Duisburg-Essen , contributing to projects within the Collaborative Research Centre 1242. His research focuses on Charge Carrier Dynamics in Nanostructures (Project A02) and Unifying Theoretical Description of Relaxation in Electron Systems (Project B07). Contact details include email: koenig@thp.uni-due.de . Research interests span Condensed Matter Physics , Quantum Transport , Nanostructures , and Electron Dynamics . His work often employs theoretical modeling of quantum systems, with recent publications analyzing phase transitions in 2D Ising systems Floquet engineering in superconductors nonlocal thermoelectric correlations Lee-Yang zero analysis of transport . Articles from 2017-2024 highlight expertise in quantum dot systems , spin dynamics , surface physics , and full counting statistics .

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Nick MoseyView profile

Associate Professor

Queen's University at KingstonCanada

Nick Mosey is an Associate Professor in the Department of Chemistry and Associate Dean (Research) in the Faculty of Arts & Science at Queen’s University. He holds a PhD from the University of Western Ontario and completed postdoctoral research at Princeton University. His research focuses on computational and theoretical chemistry, particularly in developing simulation methods to study chemical reactions under mechanical stress and tribological conditions. Key areas include molecular dynamics, exact exchange calculations in periodic systems, and the design of electrocatalysts for fuel cells. His work integrates method development (e.g., contracted planewave basis functions, temporal QM/MM) with applied studies in tribology (e.g., friction modifiers, lubricants) and electrocatalysis (nickel-based materials for alkaline fuel cells). He has led interdisciplinary projects involving collaborations across chemistry, materials science, and engineering. Awards include the NSERC Doctoral Prize (2007), Early Researcher Award (2009-2014), and leadership in securing funding from NSERC and Ontario government programs. Mosey teaches courses in quantum mechanics and computational chemistry, with a focus on bridging theory and practical applications. His group has produced over 70 peer-reviewed publications and trained numerous graduate students and postdoctoral researchers. Current research emphasizes extending simulation time-scales for reactive systems and exploring novel materials for energy applications.

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Alex MironenkoView profile

Assistant Professor

University of Illinois Urbana-ChampaignUnited States

Dr. Alex Mironenko is an Assistant Professor in the Department of Chemical and Biomolecular Engineering at the University of Illinois at Urbana-Champaign. His research focuses on developing quantum mechanical methods to predict catalytic behaviors for renewable energy and chemical production. He leads the Mironenko Lab, which emphasizes computational models for heterogeneous catalysis, reactive force fields, and nanozyme design. Education: PhD in Chemical Engineering, University of Delaware (2018) Kadanoff-Rice Postdoctoral Scholar, University of Chicago (2018-2020) MS in Chemical Engineering, University of Kansas (2012) Diploma of Engineer, Omsk F.M. Dostoevsky State University, Russia (2009) Research Interests: Computational heterogeneous catalysis Reactive force fields derived from first principles Low-dimensional metal oxide catalysts Nanozymes and biomimetic catalysis Selective C-C coupling for CO₂ valorization Improving density functional theory accuracy Awards: ACS Petroleum Research Fund Doctoral Investigator Award (2021) Allan P. Colburn Outstanding Dissertation Prize (2019) Kadanoff-Rice Postdoctoral Fellowship (2018-2020) Advising and Grants: Advised PhD student Neil Tran (publication on methanol carbonylation mechanisms) Funded by NSF, ACS, and industry partnerships Labs/Teams: Mironenko Virtual Catalysis and Quantum Chemistry Lab Collaborations with institutions like University of Chicago and industry partners

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Gyeong HwangView profile

Professor

University of Texas at AustinUnited States

Gyeong Hwang is a Matthew Van Winkle Regents Professor of Chemical Engineering at The University of Texas at Austin. He leads the Hwang Research Group focused on computational materials discovery and design for energy and electronic applications. His work emphasizes multiscale modeling of nanostructured materials, with applications in energy storage/conversion, carbon capture, and semiconductor processing. Educational Qualifications: Ph.D., Chemical Engineering, California Institute of Technology (1999) M.S., Applied Physics, California Institute of Technology (1998) M.S., Chemical Engineering, Seoul National University (1993) B.S., Chemical Engineering, Seoul National University (1991) Research Interests: Hwang's research integrates first-principles modeling with experimental validation to address challenges in: - Surface chemistry and interfacial reactions - Nanostructured materials synthesis - Electrochemical device fabrication - CO₂ capture mechanisms His group develops computational tools for predicting material behaviors at atomic and continuum scales. Recent Publications Trends: Publications (2023-2025) focus on: - Solid-state battery interfaces - Plasma-enhanced material deposition - Ionic liquid interactions - Thermal/spatial transport phenomena - Electrochemical reaction mechanisms Awards: NSF CAREER Award (2005) Electrochemical Society's F.M. Becket Memorial Award (1999) Korean Chemical Engineering Service Award (2010) Advising & Grants: Leads interdisciplinary research funded by NSF, industry partnerships, and regents' endowments. Active in graduate student training through courses like ChE 379 (Molecular Simulation) and ChE 348 (Numerical Methods). Labs/Teams: The Hwang Research Group operates state-of-the-art computational facilities for quantum mechanics simulations and multiscale modeling. Collaborates with experimental groups globally on materials prototyping.

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Davide DonadioView profile

Professor

University of California, DavisUnited States

Davide Donadio is a Professor of Chemistry at the University of California, Davis. His research focuses on molecular modeling and simulations of materials, particularly in non-equilibrium processes, thermal transport, and nanostructure assembly. He leads the Naotheory Group, which develops predictive multiscale models for energy-related materials. Education : Habilitation in Materials Science, Italian Ministry for University and Research (2013) Ph.D. in Materials Science, University of Milano (2003) M.S. in Physics, University of Milano (1998) Research Interests : His work spans molecular-level understanding of energy conversion, thermal management, and nanostructure formation. Key areas include phononics, thermoelectrics, and interfacial phenomena in materials like ice surfaces, semiconductors, and clathrates. He employs machine learning and first-principles methods to bridge simulation and experiment. Awards : UC Davis Hellman Fellow (2017–2018) Young Scientist Award, Italian Institute for the Physics of Matter (1998) Grants & Labs : His funding and collaborations drive advancements in nanostructured materials and computational tools like PLUMED tutorials. The Naotheory Group actively publishes in high-impact journals and collaborates internationally on thermal transport and materials design.

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Laura FumagalliView profile

Associate Professor

The University of ManchesterUnited Kingdom

Laura Fumagalli is an Associate Professor (Reader) in Condensed Matter Physics at the University of Manchester's Department of Physics & Astronomy and a staff researcher at the National Graphene Institute. She holds a M.Sc. in Electronic Engineering (2002) from the Polytechnic University of Milan and École Supérieure d'Electricité, and a PhD in Physics (2006) from the Polytechnic University of Milan. Her research focuses on dielectric properties of nanoscale systems, including confined water, biomolecules, 2D materials, and the development of scanning dielectric microscopy (SDM). Key achievements include an ERC Consolidator Grant (2018) for the Liquid2DM project and a Royal Microscopical Society Medal (2021). Current research positions include leadership in the ERC-funded Liquid2DM project and supervision of postdoctoral researchers like Dr. Simone Benaglia. Ongoing funding includes the UKRI-MSCA fellowship (2023-2024) and Royal Society instrumentation grants. Past positions include lecturer roles at the University of Barcelona, where she earned prestigious fellowships (Juan de la Cierva, 2009; Ramon y Cajal, 2014). Teaching responsibilities include leading the Frontiers of Solid-State Physics course and tutoring foundational physics modules. Her lab (Schuster Building Lab 1.09 and NGI) hosts a dynamic team of PhD students and postdocs investigating confined liquids, biomolecules, and 2D heterostructures. Notable students include M. Souilamas (2020-2024) and H. Read (2019-2023), whose theses focused on confined water and biological surfaces. Publications span topics like interfacial water dynamics, lipid membrane structures, and ferroelectricity in 2D materials. Her work bridges materials science and biophysics, addressing fundamental questions in nanoscale dielectric behavior with applications in both fields.

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Xifan WuView profile

Professor

Temple UniversityUnited States

Xifan Wu is a Professor of Physics at Temple University, specializing in computational methods and materials science. His research focuses on first-principles computational approaches, particularly exploring the locality of Wannier orbitals to address physical problems in solids and liquids. Key interests include superlattice design and applications of order-N exact exchange functionals like PBE0 and GW quasi-particle approximations. He has authored numerous high-impact publications in journals such as Physical Review Letters and Physical Review B , covering topics like ferroelectric superlattices, X-ray absorption spectroscopy, and the dielectric properties of electrolyte solutions. His work bridges quantum mechanical models with machine learning potentials, advancing large-scale simulations of complex materials. Education/Background: Not explicitly detailed in the provided text. Grants/Awards: No specific awards listed, but his research is supported by Temple University’s Center for the Computational Design of Functional Layered Materials (CCDM). Labs/Teams: Collaborates with teams focused on computational design and materials modeling, possibly through Temple’s physics department and affiliated research centers. His recent work explores molecular-scale insights into electrical double layers at oxide-electrolyte interfaces and the impact of ions on X-ray spectra, demonstrating expertise in linking theoretical models with experimental phenomena.

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Victor VasquezView profile

Professor

University of Nevada, RenoUnited States

Victor Vasquez is a Professor and Chair of the Chemical and Materials Engineering Department at the University of Nevada, Reno (UNR). He holds a PhD in Chemical Engineering from UNR (1999) and focuses on thermodynamics, atomistic modeling, and process systems engineering for extreme materials. Key projects include Metal hexaboride research for neutron detection Reverse micellar systems for nanoparticle synthesis Lithium and cobalt supply chain analysis via complex networks Geothermal energy life cycle analysis Thermal pretreatment of lignocellulosic biomass Research keywords include: Materials Science Thermodynamic Modeling Molecular Dynamics Machine Learning Environmental Engineering Supply Chain Optimization Scientific awards: DELTA New Department Leaders Institute (2023) Faculty Academic Leadership Program (2019) He mentors graduate and undergraduate students, particularly from diverse backgrounds, and serves as adviser for UNR's AIChE and SHPE student chapters. Collaborations span UC San Diego, Alfred University, and Latin American institutions. Leadership roles include AIChE NORCAL section director (2010-2017) and ABET symposium participation (2021).

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Qiang CuiView profile

Professor

ETH ZurichSwitzerland

Qiang Cui is a Professor of Computational Chemistry at Boston University, specializing in developing and applying advanced computational methods to study complex biomolecular systems. His research focuses on understanding mechanisms of enzymes, biomolecular machines, and bio-material interactions through multi-scale simulations, including quantum mechanical/molecular mechanical (QM/MM) approaches and coarse-grained models. Education: B.S., Chemical Physics, University of Science & Technology of China (1993) Ph.D., Physical Chemistry, Emory University (1997) Postdoctoral Associate, Harvard University (1998-2001) Research Interests: Development of novel computational techniques for simulating complex systems Study of energy transduction in molecular machines (e.g., myosin, DNA repair enzymes) Investigation of biomaterial interfaces and nanotechnology applications Protein allostery and mutational effects using machine learning Labs/Teams: The Cui Group at Boston University advances computational methodologies and collaborates on projects spanning biophysics, material science, and molecular biology.

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