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Julia ZhangView profile

Associate Clinical Professor

• Medical Oncology
• Hematology
• Cancer Research
• +2 more

Julia Zhang, M.D., Ph.D., is an Academic Clinical Associate Professor in the Division of Hematology and Oncology at the University of Washington School of Medicine. She practices at the Fred Hutchinson Cancer Center at Overlake Cancer Center in Bellevue, Washington, where she provides specialized care in medical oncology and hematology. Dr. Zhang completed her M.D. and Ph.D. training at Sun Yat-Sen University and Washington State University, respectively. She furthered her medical education with a residency in Internal Medicine at SUNY Downstate Medical Center and a fellowship in Hematology-Oncology at the University of Arkansas for Medical Sciences. She is board certified by the American Board of Internal Medicine in Internal Medicine, Hematology, and Medical Oncology. Her clinical expertise encompasses general medical oncology and both benign and malignant hematology. Dr. Zhang's research interests span cancer biology, health disparities in oncology, autoimmune disorders, and liver diseases. She has contributed to significant research in areas including structural racism's impact on cancer mortality, autoimmune hepatitis manifestations related to COVID-19, and primary biliary cholangitis. Dr. Zhang's publication record shows consistent scholarly activity with recent contributions in 2024, 2023, and 2020, demonstrating her engagement with both clinical practice and research. Her work spans multiple disciplines including oncology, hematology, hepatology, and public health, reflecting a broad research portfolio that addresses both specialized medical conditions and broader health system issues. Board Certified in Internal Medicine, Hematology, and Medical Oncology Active researcher with publications in high-impact journals Specialized expertise in complex oncological and hematological conditions Dr. Zhang maintains an active clinical practice at the Fred Hutchinson Cancer Center while contributing to academic medicine through teaching and research. Her work bridges clinical care with scholarly investigation, particularly in areas where social determinants intersect with cancer outcomes.

• Scientific Software Development
• High Performance Computing
• Molecular Dynamics
• +3 more

Dr. Torsten Stuehn serves as IT Group Leader at the Max Planck Institute for Polymer Research (MPI-P) in Mainz, Germany, leading scientific software development and HPC infrastructure since joining in 2003. He oversees the ESPResSo++ simulation package and collaborates with the University of Mainz and Max Planck Compute and Data Facility (MPCDF). Education: Diploma in Physics, University of Mainz, 1999 Doctorate in Physics, University of Mainz, 2005 His research focuses on scientific software engineering for exascale computing, developing neural network-based force fields, adaptive resolution methods, and load balancing algorithms to advance molecular simulation capabilities. This work addresses critical challenges in maintaining computational leadership for soft matter physics. Recent publications reveal a clear evolution in ESPResSo++ toward exascale readiness, integrating machine learning with multiscale modeling and parallel computing innovations. The software's progression reflects broader trends in computational physics where AI-driven methods and heterogeneous architecture optimization are becoming indispensable. Stuehn directs MPI-P's computational infrastructure team and contributes to major initiatives including Transregio SFB 146 and the European E-CAM project, driving open-source scientific software development for the global research community.

• Phytochemical Research
• Cancer Therapeutics
• Cardiovascular Pharmacology
• +5 more

Dr. Matthew Jones is a Lecturer in Physiology at the University of Salford, School of Science, Engineering & Environment, specializing in Biomedicine. He serves as Deputy Programme Leader for the Biomedical Science Programme with emphasis on supporting level 4 students, and acts as Admissions Tutor for the Biomedicine suite of programmes including Biomedical Science, Human Biology and Infectious Diseases. His educational background includes a BSc in Biomedical Science with Professional Experience (2016), MSc by research (2017), and PhD (2021), all completed at the University of Salford. His PhD research investigated the chemical composition and anti-cancer potential of Boswellia carterii oleoresins under Professor David Greensmith. Dr. Jones's research spans two primary domains: phytochemical pharmacology and biomedical education. His pharmacological work focuses on understanding the therapeutic potential of novel phytochemicals for childhood brain cancers, cardiovascular disorders, and inflammatory conditions, with particular expertise in examining cardiotoxic effects at the single-cell level. His educational research investigates student transitions to higher education, awarding gaps, and active learning approaches in Biomedicine. He has developed innovative teaching methods including digital escape rooms and card games to enhance student engagement in laboratory settings. Analysis of his 42 research outputs (primarily from 2023-2025) reveals a strong dual focus: approximately 60% of his work centers on cancer pharmacology (particularly medulloblastoma and leukemia treatments using plant-derived compounds), while 40% addresses educational innovations in biomedical science teaching. His cancer research consistently examines pro-apoptotic and anti-migratory effects of phytochemicals, while his educational work emphasizes gamified and active learning approaches to improve student outcomes. As module leader for Biomedical Skills and Human Physiology, Dr. Jones teaches across all undergraduate levels in courses including Professional Skills, Human Systems Physiology, Translational Research Skills, and Advances in Pathophysiology. He actively supervises undergraduate and Master's research projects and is available for PhD supervision in areas including cardiotoxicity of phytochemicals, anti-cancer effects of novel phytochemicals, and impact of inflammatory dysregulation on cardiac function. His experimental expertise encompasses flow cytometry, various microscopy techniques, cell culture, molecular biology, and analytical chemistry including HPLC and mass spectrometry. Dr. Jones contributes to the UN Sustainable Development Goals focused on 'Ensure healthy lives and promote well-being for all at all ages' and 'Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all,' reflecting his dual commitment to biomedical research and educational excellence.

Rahmatullah RocheView profile

Assistant Professor

• Computational Biology
• Applied Machine Learning
• Data Science
• +1 more

Rahmatullah Roche serves as an Assistant Professor in the Department of Computer Science at Columbus State University's TSYS School of Computer Science, joining the tenure-track faculty in Fall 2024. His academic credentials include: Ph.D. in Computer Science and Applications from Virginia Tech (2024) M.S. in Computer Science and Software Engineering from Auburn University (2021) B.S. in Computer Science and Engineering from Bangladesh University of Engineering and Technology (2016) Dr. Roche's research spans Computational Biology , Applied Machine Learning , Data Science , and Human-Computer Interaction , with primary focus on macromolecular predictive modeling for intra- and inter-molecular interactions using cutting-edge AI techniques. His work bridges computer science and biology to solve complex structural bioinformatics challenges. Analysis of his 14 publications (2020-2025) reveals a consistent trajectory in applying deep learning—particularly transformer networks, equivariant graph neural networks, and biological language models—to protein-RNA complex prediction, protein-nucleic acid binding, and protein-protein interaction site identification, published in high-impact journals including Cell Systems and Nucleic Acids Research. Key scientific recognitions include: Pratt Fellowship Award (2023-2024) Turner College Research Award (2025) Professional Development Award for Core Course redesign (2025) Core Course Design Institute Professional Development Award (2024) 3rd place Flash Talk award at VT GPSS Symposium (2024) Best Poster Award at ACM-BCB 2020 YSEA Finalist Travel Award at MCBIOS 2024 Dr. Roche actively recruits undergraduate and graduate students for his research lab while securing resources through NSF ACCESS grants. His teaching portfolio includes Computer Science I, Computer Organization, and Graphical User Interface Development, complemented by service as Discipline Coordinator for Web Development and reviewer for top bioinformatics journals. His research group collaborates with Virginia Tech on advancing biomolecular modeling through interdisciplinary AI applications.

Stephen T. LamView profile

Assistant Professor

• Nuclear materials
• Advanced reactors
• Materials chemistry
• +10 more

Stephen T. Lam is an Assistant Professor of Chemical Engineering at the University of Massachusetts Lowell, where he also serves as Director of the Nuclear Engineering Program and RHSA Mentor within the Francis College of Engineering. His research focuses on accelerating materials development for nuclear and clean energy applications through computational methods. His educational background includes a Ph.D. in Nuclear Science and Engineering (2020) and an MS in Nuclear Science and Engineering (2017) from the Massachusetts Institute of Technology, and a BS in Chemical Engineering (2013) from the University of British Columbia. Prior to his academic career, Lam worked in the petroleum and chemical processing industries and holds a Professional Engineer license in Canada. Ph.D.: Nuclear Science and Engineering (2020), Massachusetts Institute of Technology MS: Nuclear Science and Engineering (2017), Massachusetts Institute of Technology BS: Chemical Engineering (2013), University of British Columbia Lam's research integrates multi-scale simulation, experimental validation, and data analytics to address materials challenges in nuclear and clean energy systems. His work spans molten salt chemistry for advanced reactors, neural network interatomic potentials, and fusion energy materials. He leads the Lam Research Group, which combines predictive simulation, data analytics, and experiments to accelerate materials development. His recent publications demonstrate expertise in molten salt structure, neural network potentials, and fusion materials, with emphasis on fluoride and chloride salt systems for nuclear applications. The research shows strong interdisciplinary collaboration across computational chemistry, materials science, and nuclear engineering. Among his notable recognitions are the Early Career Research Award (2024) from the U.S. Department of Energy and the Distinguished Faculty Advancement Award (2024) from the U.S. Nuclear Regulatory. He has also received multiple early-career research awards from national laboratories and professional societies. Early Career Research Award (2024), U.S. Department of Energy Distinguished Faculty Advancement Award (2024), U.S. Nuclear Regulatory Best Presentation (2017), Tokyo Institute of Technology Natural Sciences and Engineering Research Council of Canada Postgraduate Scholarship (2017) Lam actively mentors graduate students and postdoctoral researchers, with current advisees working on AI-assisted materials design, molten salt chemistry, and fusion energy applications. He teaches courses in nuclear materials, nuclear science and engineering, transport phenomena, and fundamentals of electricity. The Lam Research Group maintains strong collaborations with national laboratories and industry partners, focusing on developing computational tools to improve understanding of material properties and accelerate materials discovery for next-generation energy technologies.

Calvin TsayView profile

Lecturer

• Optimization Algorithms
• Process Control
• Machine Learning Optimization
• +2 more

Calvin Tsay is a Lecturer (Assistant Professor) in the Computational Optimisation Group at Imperial College London, holding the BASF/RAEng Senior Research Fellowship in Scale-Bridging Modelling. Education: PhD Chemical Engineering (UT Austin 2020), BS/BA (Rice University 2015). Research develops optimization methods bridging machine learning and process systems engineering. Specializes in mixed-integer programming for neural networks and Bayesian optimization for energy applications. Awards: President's Medal for Early Career Researcher RAEng Senior Research Fellowship CACE Best Paper (2023) COIN-OR Cup (2022) Leads research on AI-driven chemical process optimization. Supervises PhD students in ML optimization and process control. Collaborates with BASF on industrial applications.

Alexander BarnesView profile

Professor

• Magnetic Resonance
• Gyrotron Technology
• NMR Spectroscopy
• +3 more

Prof. Alexander Barnes is a Full Professor at the Department of Chemistry and Applied Biosciences and Head of the Institute of Molecular Physical Science at ETH Zürich. His research focuses on advanced magnetic resonance techniques, gyrotron technology, and biomolecular structural analysis. Key areas include high-power microwave source development for NMR applications, structural characterization of viral proteins (e.g., SARS-CoV-2), and cryogenic instrumentation for enhanced spectroscopy. Barnes has pioneered innovations in dynamic nuclear polarization (DNP) systems, frequency-agile gyrotrons, and miniaturized superconducting magnets. His work bridges fundamental physics with biomedical and materials science applications. Current projects address protein-membrane interactions, THz gyrotron design, and cryogenic NMR probe optimization. Barnes collaborates extensively with international research groups and industry partners to advance analytical instrumentation and disease-related molecular mechanisms. Publications reflect a sustained focus on experimental and computational methods for magnetic resonance, including breakthroughs in electron beam modeling, frequency-chirped DNP, and ultra-high-field magnet development. His engineering contributions include spherical rotor systems for magic-angle spinning and lightweight gyrotron cavities. Barnes also leads initiatives in solid-state NMR for drug discovery, particularly targeting protein kinase modulation in T-cells and viral assembly mechanisms.

Steven BoxerView profile

Professor

• Physical Chemistry
• Biophysical Chemistry
• Protein Electrostatics
• +7 more

Steven Boxer is the Camille Dreyfus Professor of Chemistry at Stanford University. His research focuses on the physical aspects of biological systems, with particular emphasis on protein electrostatics, membrane biophysics, and photosynthesis. He has made significant contributions to understanding the role of electric fields in enzyme catalysis and the photophysics of fluorescent proteins. Dr. Boxer received his PhD in Physical and Physical-Organic Chemistry from the University of Chicago in 1976 and his BS with Honors in Chemistry from Tufts University in 1969. His research program investigates several interconnected themes: Excited State Dynamics in GFP & Split GFP Electrostatics and Dynamics in Proteins Model Membranes Energy and Electron Transfer in Photosynthesis His lab develops innovative experimental methods including Stark spectroscopy to measure electric fields in proteins and has pioneered the use of vibrational probes to map electrostatic environments in biological systems. Recent publications demonstrate his continued leadership in applying physical chemistry approaches to biological problems, with particular focus on quantifying electric fields in enzyme active sites and their role in catalysis. His work bridges chemistry, physics, and biology to provide fundamental insights into biomolecular function. As the Camille Dreyfus Professor of Chemistry, Dr. Boxer has received significant recognition for his contributions to chemical research and education. Dr. Boxer leads an active research group that combines experimental and computational approaches to study biological systems with a strong physical perspective. His lab has developed numerous innovative techniques and continues to train the next generation of scientists at the interface of chemistry and biology. The Boxer Lab maintains a strong research presence with multiple ongoing projects exploring the physical basis of biological phenomena, including advanced instrumentation for measuring electric fields in proteins and developing novel membrane models.

Alan FershtView profile

Professor

• Chemistry
• Biophysics
• Molecular Biology
• +7 more

Alan R. Fersht is a distinguished academic and researcher, currently serving as the Herchel Smith Professor of Organic Chemistry at the University of Cambridge. He has held significant roles such as Director of the MRC Centre for Protein Engineering and Director of the MRC Unit for Protein Function and Design. His research focuses on protein folding, molecular biology, and structural biology, with contributions to understanding protein misfolding in diseases like cancer. Fersht's work integrates biochemical, biophysical, and computational methods to study protein dynamics and chaperone mechanisms. Key honors include Fellowship of the Royal Society (1983), the Copley Medal (2020), and membership in multiple prestigious academies. His awards span decades, recognizing his contributions to biochemistry, structural biology, and protein engineering. Fersht's publications explore protein folding pathways, molecular chaperones (e.g., GroEL), and the thermodynamics of protein stability. His research interests include protein design, folding initiation sites, and the role of electrostatic interactions in folding. Notable studies on barnase-barstar interactions and chaperone-assisted folding highlight his experimental and theoretical approaches to understanding protein behavior. Fersht's work bridges fundamental research and applications in biotechnology and medicine.

Clara Viñas TeixidorView profile

Research Professor

• Boron Chemistry
• Organometallic Chemistry
• Nanomaterials
• +9 more

Prof. Clara Viñas Teixidor (Membership Number: 5772) is a Research Professor at the Institute of Materials Science of Barcelona (ICMAB) , part of the Spanish National Research Council (CSIC) . With a career spanning over 45 years, she has published 359 original scientific papers, 20 book chapters, and co-edited Boron-Based Compounds: Potential and Emerging Applications in Medicine , selected by Wiley for the 2019 International Year of the Periodic Table. Her work bridges chemical and pharmaceutical disciplines, focusing on boron cluster chemistry. Degrees : Chemistry (UAB, 1975), Pharmacy (UB, 1980), PhD in Pharmacy (UB, 1990, supervised by F. Teixidor). Positions : 1991–present at CSIC (ICMAB), including Research Professor since 2006. Research Interests center on Boron chemistry , particularly icosahedral boron clusters , for applications in nanomedicine , catalysis , sensors , and environmental chemistry . Her work pioneers hybrid materials combining boron clusters with polymers, nanoparticles, and metallacarboranes. Scientific Contributions include collaborations with experts in Raman microscopy and radioimaging. Her 2016 Chemical Society Reviews article on boron clusters was highly cited (145 times) and featured on the journal’s cover. Scientific Awards : Medal at ICCC42 (2016), Member of Academia Europaea (2021).

V. MenkovskiView profile

Associate Professor

• Graph Neural Networks
• Machine Learning
• Deep Learning
• +7 more

Dr. V. Menkovski serves as an Associate Professor in Data Mining at Eindhoven University of Technology's Department of Mathematics and Computer Science. He also holds associate professor positions with EAISI Health and EAISI High Tech Systems, and is an ICMS Affiliated member. His work spans multiple domains of artificial intelligence and computational physics, with significant contributions to fusion energy research. Mathematics and Computer Science, Data Mining (Primary Appointment) EAISI Health (Associate Professor) EAISI High Tech Systems (Associate Professor) ICMS (Affiliated Member) Menkovski's research focuses on Graph Neural Networks, Machine Learning, Deep Learning, and their applications in diverse fields from plasma physics to metamaterials. His work demonstrates strong interdisciplinary connections, particularly between computer science and fusion energy research. He has developed novel approaches for crowd simulation, tokamak plasma monitoring, and metamaterials homogenization using advanced neural architectures. His fingerprint reveals expertise in Quality-of-Experience, Autoencoders, Neural Networks, Annotation, Graph Neural Networks, Video Streaming, Adversarial Machine Learning, and Anomaly Detection. Analysis of his recent publications (2023-2025) shows a clear trend toward applying Graph Neural Networks to complex physical systems, particularly in fusion energy research and materials science. His work increasingly integrates symmetry principles with neural architectures, as seen in his research on equivariant networks for metamaterials and symmetry-informed networks for zeolite analysis. There's also significant focus on practical applications in fake news detection, anomaly detection, and plasma state monitoring. Best Paper Award ICPM 2021 (with Sommers and Fahland) Best Paper Award of LoG 2022 (with multiple co-authors including Huang, Chen, Fang, Zhao, Yin, Pei, Mocanu, Wang, Pechenizkiy, and Liu) Menkovski teaches several advanced courses including Deep Learning, Advanced Topics in Artificial Intelligence, and Sociophysics 2, which runs through August 2025. His supervised work portfolio includes 79 projects, indicating substantial mentorship activity. He has received significant media attention for his research, including coverage by 11 news outlets, blog posts, and mentions on social media platforms. His work on 'Supervised Learning of Process Discovery Techniques Using Graph Neural Networks' was particularly noted in media coverage. His research involves collaboration with multiple institutions and teams, particularly in fusion energy research (Eurofusion Tokamak Exploitation Team, ASDEX-Upgrade team, EUROfusion MST1 Team). He works closely with researchers across disciplines, including physicists working on tokamak plasma and materials scientists studying metamaterials and zeolites.

• Mathematical Biology
• Computational Modeling
• Biophysics
• +3 more

Sabine Fischer is a Professor for Supramolecular and Cellular Simulations at the University of Würzburg’s Center for Computational and Theoretical Biology (CCTB). She holds a PhD in Mathematics from the University of Nottingham (2009) and completed postdoctoral research at the University of Cambridge (2009-2011) and the University of Frankfurt (2011-2017). Her work focuses on mathematical modeling and data-driven simulations of biological processes across subcellular, multicellular, and multi-tissue scales. Key research areas include agent-based modeling of parasite collective behavior (e.g., Project 7 of SPP 2332 PoP), cell-cell interactions, and morphological modeling with Blender. Her group develops tools for image analysis and applies methods ranging from classical statistics to machine learning. Education: Diploma in Mathematics, University of Würzburg PhD in Mathematical Biology, University of Nottingham (2009) Professional Experience: Postdoc, University of Cambridge (2009-2011) Postdoc, University of Frankfurt (2011-2017) Development Engineer, h.a.l.m. Elektronik GmbH (2017-2018) Professor, University of Würzburg (since 2018) Her research integrates experimental data with computational models to study processes like mouse blastocyst differentiation, tissue-level organization, and parasitic locomotion. Current projects emphasize agent-based modeling of Trypanosoma collective behavior and the development of open-source tools like VESNA for 3D vessel analysis.

• Health Economics
• Applied Microeconomics
• Industrial Organization

Assoc Prof Yang Zhang is an Associate Professor in the School of Economics at the National University of Singapore , Department of Economics. He has been affiliated with the university since 2012, progressing from Lecturer (2012-2015) to Senior Lecturer (2016-2021) and currently Associate Professor since 2022. Education: PhD in Managerial Economics and Strategy (Northwestern University, 2011) BA in Economics (Peking University, 2005) Research Interests: Health Economics Applied Microeconomics Industrial Organization Recent Research Trends focus on leveraging deep learning and structural biology tools for protein structure prediction, RNA modeling, and computational drug design. His work integrates advanced algorithms with large-scale metagenomic data to improve accuracy in complex biological system modeling.

Tony LELIEVREView profile

Professor

• Applied Mathematics
• Multiscale Modeling
• Molecular Simulation
• +7 more

Tony Lelièvre is a Professor of Applied Mathematics at the Ecole Nationale des Ponts et Chaussées, part of the Institut Polytechnique de Paris. He holds a PhD (2004) and Habilitation (2009), specializing in multiscale modeling, molecular simulation, and stochastic processes. His research focuses on free energy computations, numerical analysis of complex fluids, and computational statistical physics. He co-authored two books and over 100 papers, receiving significant awards like the ERC Consolidator Grant (2013-2019) and the Grand prix Alcan. Lelièvre has organized numerous international workshops and serves on editorial boards of journals like ESAIM:M2AN and SIAM/ASA Journal of Uncertainty Quantification. His work bridges applied mathematics, numerical analysis, and computational science with applications in materials science and industrial fluid dynamics. Education: PhD in Applied Mathematics, 2004 Habilitation à Diriger des Recherches, 2009 Research Interests: Multiscale modeling of complex fluids Molecular dynamics and free energy calculations Stochastic methods for metastable systems Numerical analysis of PDEs and SDEs Computational statistical physics Recent Contributions: His work on adaptive biasing force methods and hybrid Monte Carlo techniques has advanced the simulation of rare events and free energy landscapes. He contributed to variance reduction techniques in molecular simulations and mathematical analysis of parallel replica algorithms. Awards: ERC Consolidator Grant (2013-2019), Prix CS 2002, Grand prix Alcan (2010), Ordway Visiting Professorship (2012-2013), and several teaching awards. Professional Activities: Organized major conferences like CEMRACS 2013 and IPAM Long Program on Energy Landscapes (2017). Co-edits journals and authored influential textbooks on magnetohydrodynamics and free energy computations.

Emanuel GullView profile

Professor

• Quantum Physics
• Condensed Matter Physics
• Theoretical Physics
• +4 more

Professor Emanuel Gull is a theoretical physicist specializing in numerical methods for quantum many-body systems. He holds a professorship at the University of Warsaw's Faculty of Physics, where he relocated his laboratory from the University of Michigan to conduct research under an ERC Advanced Grant. His work focuses on predictive algorithms for simulating quantum materials, integrating quantum field theory, condensed matter theory, quantum Monte Carlo methods, applied mathematics, and machine learning. This interdisciplinary approach addresses phenomena like magnetism and superconductivity in materials critical to technologies such as MRI machines and electric car batteries. Professor Gull's ERC Advanced Grant, the first awarded to a foreign researcher hosted at the University of Warsaw, underscores the significance of his project. Collaborating with the Quantum Molecular Systems group at the Faculty, his methods support experimental advancements in ultracold matter research. His research aligns with the University's strategic focus on cutting-edge interdisciplinary science. His achievements include the prestigious ERC Advanced Grant, highlighting global recognition of his contributions. The project’s relocation of his laboratory reflects Warsaw's growing role as a hub for quantum research. Grants and institutional support from the University of Warsaw's BMPB office further enable his work, emphasizing collaboration and innovation. Professor Gull's research lab, now based in Warsaw, bridges theoretical and applied physics, fostering advancements in quantum technologies. His work exemplifies the intersection of fundamental science and technological application, with direct implications for energy storage and medical imaging technologies.