Patrick Gunning is a Professor at the University of Toronto (Mississauga campus), specializing in Biological Chemistry and Organic Chemistry. His research focuses on developing small molecule architectures to manipulate protein complexation events, particularly targeting aberrant protein interactions in diseases like cancer. Key areas include STAT3/STAT5 inhibition, histone deacetylase (HDAC) modulation, and molecular design strategies for cancer therapies. Research interests emphasize understanding protein-protein interaction 'hot spots' and designing drugs to suppress or enhance specific gene expressions. His work explores both organic and inorganic drug-like scaffolds to regulate cellular signaling pathways. Recent studies highlight novel treatments for leukemia, lymphoma, and brain metastases through targeted protein degradation and metabolic pathway manipulation. Over 50 publications demonstrate expertise in oncology, epigenetics, and drug discovery. Notable contributions include HDAC6-selective inhibitors, PROTAC-based degraders, and fluorine NMR methodologies for protein analysis. His interdisciplinary approach bridges organic chemistry, biochemistry, and clinical applications in precision medicine. Current projects investigate molecular mechanisms underlying cancer growth, with a focus on STAT signaling pathways and metabolic vulnerabilities. The lab also pioneers innovative drug delivery strategies using advanced spectroscopic techniques and chemical synthesis platforms.
MICHEL SANNER is a Professor of Molecular Biology at the Department of Integrative Structural and Computational Biology at Scripps Research. He holds a PhD in Computer Science from the University of Haute Alsace, France (1992). His research focuses on computational methods for molecular interactions, molecular graphics, and component-based software development. Notable contributions include the AutoDock suite (for molecular docking), PMV (a molecular visualization environment), and Vision (a visual programming tool). His research group develops tools like AutoDock CrankPep for peptide docking and F2Dock for protein-protein interactions. These tools are widely used in drug discovery and structural biology. His work emphasizes software engineering principles to create adaptable computational pipelines for analyzing macromolecular structures and simulating interactions. Publications span topics like peptide-docking methodologies, ligand-binding site prediction, and GPU-accelerated docking algorithms. His articles highlight advancements in computational methods for understanding protein-ligand interactions, with applications in anticoagulant research and HIV/FIV protease inhibition. Collaborations include work with Arthur J. Olson and David S. Goodsell on docking methodologies.
James R. Green is a Professor in the Department of Systems and Computer Engineering at Carleton University , where he has been a faculty member since 2005. He holds a PhD from Queen's University and is a licensed Professional Engineer (P.Eng.) and Senior Member of IEEE. His work integrates machine learning, biomedical informatics, and high-performance computing. His educational background includes: B.A.Sc. in Systems Design Engineering, University of Waterloo (1998) M.Sc.(Eng.), Queen's University (2000) PhD, Queen's University (2005) Dr. Green's research focuses on machine learning challenges in biomedical informatics , particularly class imbalance and rare event prediction. Key areas include protein structure, function, and interaction prediction; microRNA detection in unique species; non-contact neonatal monitoring; and accelerating scientific computing via parallel architectures like the Cell BE processor. His lab has developed several widely used bioinformatics tools such as PIPE, ProtDCal, and PCI-SUMO. His recent publications reflect a strong trend in computational biology and machine learning , with applications in proteomics, genomics, and medical diagnostics. He has published over 100 peer-reviewed papers and secured funding from NSERC, CIHR, CFI, ORF, OCE, MITACS, and IBM. Scientific and teaching recognitions include: Three teaching awards NSERC Best Project Award (twice: 2006-2007 and 2007-2008) Multiple student projects resulting in conference papers (e.g., CMBEC) He has supervised numerous undergraduate capstone projects in areas such as assistive technologies, robotic systems, and bioinformatics. His teaching portfolio includes courses in Pattern Classification, Machine Learning, Computer Architecture, and Biomedical Engineering. He leads an active research group that bridges computer engineering and life sciences, fostering interdisciplinary collaboration. Lab and research team initiatives include: Development of open-access web servers for protein analysis Collaborations with biologists and clinicians Integration of hardware and software for medical applications
Scott Bailey, PhD, is a Professor in the Department of Biochemistry and Molecular Biology at Johns Hopkins University, with joint affiliations in the School of Medicine and the Bloomberg School of Public Health. His research focuses on the structural and mechanistic basis of CRISPR-Cas systems and protein-nucleic acid interactions. Education: BSc, University of Sheffield, 1998 PhD, University of Sheffield, 2002 Dr. Bailey’s research centers on understanding how molecular machines recognize and modify nucleic acids, with an emphasis on CRISPR-mediated immunity. Using X-ray crystallography, his lab determines high-resolution structures of CRISPR complexes at various functional stages to derive mechanistic models. These models are tested through mutagenesis and biochemical assays to link structure with function. His work has elucidated mechanisms of Cas9, Type III-B, and Type V systems, contributing significantly to the field of genome editing. Recent publications highlight advancements in Cas9 engineering, genome imaging techniques, and the structural basis of CRISPR targeting. His research has broad implications for biotechnology and therapeutic development. Trends across his articles show a sustained focus on CRISPR mechanisms, structural biology, and nucleic acid biochemistry, with increasing applications in proteomics and imaging. Scientific Awards: Johns Hopkins Presidents Frontier Award - Winner (February 2016) Johns Hopkins Presidents Frontier Award - Finalist (January 2015) Shikani/El Hibri Prize for Discovery and Innovation - JHSPH (February 2015) Ho-Ching Yang Memorial Faculty Award - JHSPH (May 2010) Dr. Bailey advises graduate students and postdoctoral researchers in the Molecular Biophysics and Biochemistry programs. His lab has been supported by competitive grants, including the Johns Hopkins Discovery Awards (2020). He teaches advanced courses in molecular biology and gene editing, contributing to both PhD and Master’s level training. The Bailey Lab is an active research group that integrates structural biology, biochemistry, and molecular genetics to dissect CRISPR mechanisms. The team includes PhD students, postdoctoral fellows, and research staff who collaborate on projects spanning structural determination, functional assays, and novel method development.
Sriram Neelamegham is the UB Distinguished Professor of Chemical & Biological Engineering, Biomedical Engineering, and Medicine at the University at Buffalo, SUNY. His research focuses on applying engineering principles to study molecular mechanisms of blood cell interactions in diseases such as inflammation, thrombosis, and cancer. He leads the Bioengineering Laboratory within the School of Engineering and Applied Sciences. Education: PhD in Chemical/Biomedical Engineering, Rice University, 1996 B.Tech in Chemical Engineering, Indian Institute of Technology Delhi, 1991 Research Interests: Systems Glycobiology: Investigating glycan biosynthesis and its role in disease Leukocyte and Platelet Adhesion Dynamics under Fluid Flow Von Willebrand Factor (VWF) Structure-Function Relationships Engineering Glycoengineered Therapeutics and Diagnostic Tools Key Contributions: Developed computational models and experimental tools for glycosylation pathway analysis Discovered mechanisms of VWF conformational changes under shear stress Pioneered glycoengineering strategies for stem cell targeting Awards & Recognition: NIH Independent Scientist Award (2015) SUNY Chancellor's Award for Excellence (2015) AIMBE Fellow (2012) and BMES Fellow (2019) 2018 Schoellkopf Medal (ACS) Lab Activities: Recruitment of postdocs, full-time, and part-time research technicians Development of glycan-engineered technologies for drug delivery and diagnostics Collaborations with biomedical industries and academic institutions
Qi Chen is a Professor in the Department of Geography at the University of Hawaii at Mānoa, specializing in remote sensing and geospatial technologies. His office is located in Saunders Hall, and he teaches undergraduate and graduate courses including GEO 370 (UAV and Aerial Photography), GEO 388 (Introduction to GIS), GEO 470 (Remote Sensing), GEO 489 (Applied GIS), and GEO 762 (Research Seminar: Remote Sensing. His research focuses on transforming earth observation data into actionable knowledge for environmental monitoring. Primary interests include: LiDAR applications for vegetation analysis and biomass estimation Climate change impacts on land cover and coastal systems Machine learning integration with geospatial data High-resolution mapping of agricultural and forest ecosystems Drone and satellite-based environmental assessment Chen's recent publications (2020-2025) demonstrate a strong focus on advancing remote sensing methodologies, particularly through: AI-driven approaches (GANs for vegetation indices, deep learning for marine debris) Multi-sensor fusion (LiDAR with camera systems, hyperspectral-multispectral integration) Novel applications in precision agriculture and infrastructure monitoring Hawaii-specific environmental studies incorporating indigenous knowledge systems He leads the Smart Remote Sensing Lab (smartremotesensing.org) where he mentors graduate students in developing cutting-edge geospatial solutions for ecological and societal challenges.
Mogens Fosgerau is a Professor in the Department of Technology, Management and Economics at the Technical University of Denmark (DTU), where he conducts research in transport policy and transportation science. His work spans econometrics, travel behavior modeling, and transport economics, contributing to sustainable urban mobility and policy design. Institution: Technical University of Denmark Department: Department of Technology, Management and Economics Email: mogens.fosgerau@econ.ku.dk ORCID: https://orcid.org/0000-0002-6452-5215 His research focuses on discrete choice modeling, travel time valuation, scheduling preferences, and congestion pricing. He develops theoretical and empirical models to understand how individuals make travel decisions under uncertainty and how these behaviors affect urban transport systems. His work integrates economic theory with data-driven methods, often using large-scale datasets and advanced econometric techniques. The recent trend in his publications highlights innovations in perturbed utility models for route choice, stochastic traffic assignment, and the analysis of induced demand for cycling. His research bridges transportation science, behavioral economics, and operations research, with applications in urban planning and policy evaluation. Scientific awards received include: The International Choice Modeling Conference (ICMC) award for Most Innovative Application (2022) Best Overall Paper Award, ITEA Conference (2015) Best Paper Awards from BIVEC-GIVET (2007), Kuhmo-Nectar (2008) Hedorfs Fonds Pris for Transportforskning (2011) Mogens Fosgerau has supervised PhD students such as Fentie Abegaz and has been involved in multiple externally funded research projects, including URBAN (Innovation Fund Denmark), IRUC (Danish Council for Strategic Research), and Horizon 2020 initiatives. He has also served on review panels, including for the Norwegian Research Council, and contributed to peer review and editorial duties. He is actively engaged in research networks and has presented his work at international conferences. His projects often involve interdisciplinary collaboration with researchers in economics, engineering, and urban planning.
David Agard is a Professor in the Department of Biochemistry and Biophysics at the University of California San Francisco (UCSF), where he leads a research group focused on uncovering the structural basis of biological function at the molecular and cellular levels. His lab specializes in advanced cryo-electron microscopy (cryo-EM) and fluorescence light microscopy, developing novel imaging technologies to study dynamic cellular processes. His research interests span structural biology , molecular chaperone function (particularly Hsp90 and its role in disease), microtubule nucleation , centrosome and cilium structure , and the structure of phage-encoded tubulins . He is deeply involved in methodological innovations in cryo-EM data processing , including deconvolution, heterogeneous reconstruction, and tomography, enabling atomic-level insights into complex biological systems. Recent publications highlight his lab’s work on the structural mechanisms of Hsp90-client regulation, microtubule organization, phage nucleus formation, and high-resolution imaging techniques using functionalized graphene-oxide grids. His work increasingly integrates AI-driven structural modeling and in situ approaches to understand macromolecular complexes in their native cellular context. Dr. Agard has made seminal contributions to understanding the ATPase cycle of Hsp90, the architecture of the gamma-tubulin complex, and the structural dynamics of viral and cellular tubulins. His research bridges biochemistry, biophysics, and cell biology, with implications for cancer, neurodegeneration, and antimicrobial strategies.
Peter Brown is an Associate Professor in the School of Life Sciences at Anglia Ruskin University (ARU), Faculty of Science and Engineering. His research focuses on ladybird ecology, invasive species, and citizen science, with strong collaborations across the UK (especially the UK Centre for Ecology & Hydrology and University of Hull), Europe, and Chile. Education: PhD: The spread of the harlequin ladybird Harmonia axyridis (Coleoptera: Coccinellidae) in Europe and its effects on native ladybirds – Anglia Ruskin University (2010) BSc (Hons) Ecology and Conservation – Anglia Ruskin University (2004) Peter's research interests include ladybird ecology, the impacts of non-native species on native biodiversity, intraguild predation among arthropods using molecular tools, and the use of citizen science in ecological research, particularly through the UK Ladybird Survey and COST Action CA17122. He investigates the global spread and ecological effects of the harlequin ladybird (Harmonia axyridis) and evaluates the benefits and risks of exotic biological control agents. As director of the Citizen Science Research Group and member of the Applied Ecology Research Group, he emphasizes public engagement in science. His recent publications reveal a consistent focus on citizen science, invasive species monitoring, and conservation biology. Themes include volunteer motivations, digital tools for data collection, policy implications of alien species, and recovery strategies for native ladybirds. This body of work demonstrates a strong integration of field ecology, molecular techniques, and public participation. Scientific Awards and Memberships: Fellow, Royal Entomological Society Honorary Fellow, British Naturalists' Association Co-leader, UK Ladybird Survey Editorial board, Nature in Cambridgeshire Member, British Ecological Society Peter supervises postgraduate research in ladybird and insect ecology and welcomes PhD applications. He has secured collaborative research opportunities and leads projects involving citizen science data. He has also contributed to policy and management frameworks for invasive species in Europe. Peter leads the undergraduate module 'Invertebrate Biology' and postgraduate modules in conservation and biodiversity, including field-based learning. He directs the Citizen Science Research Group and is actively involved in public outreach, having appeared on BBC programs such as The One Show, Countryfile Diaries, and The Today Programme, enhancing public understanding of ecology and invasive species.
Leo Wanner is a prominent Professor at Universitat Pompeu Fabra's Department of Information and Communication Technologies, specializing in Natural Language Processing. With a research career spanning over three decades, he has made significant contributions to computational linguistics, particularly in natural language generation, collocations, and hate speech detection. He has served as editor for multiple editions of the International Conference on Computational Linguistics (COLING) including the 2025 edition. Wanner's research interests encompass a wide range of topics in computational linguistics, with recent work focusing on hate speech detection, multilingual processing, and the capabilities of large language models. His work bridges theoretical linguistics with practical applications, addressing challenges in lexical semantics, syntax, and discourse analysis. Notably, he has pioneered research in collocation processing and has contributed to the development of frameworks for analyzing thematic progression in texts. His publication record demonstrates consistent productivity with significant contributions across multiple subfields. Recent work shows a strong focus on contemporary challenges in NLP, particularly hate speech detection and the capabilities of large language models. His research often takes a multilingual perspective, addressing challenges across different language families including Romance and Slavic languages. Wanner has led significant research projects including the development of FORGe, a multilingual deep sentence generator based on the Meaning-Text Theory, which achieved top performance in the WebNLG challenge. His work on multilingual surface realization has established important benchmarks in the field through shared tasks that have engaged researchers worldwide. As an academic leader, Wanner has mentored numerous researchers and contributed to building research infrastructure through corpus development and annotation schema design. His work on collocation resources, thematic progression analysis, and hate speech detection frameworks has provided valuable resources for the broader NLP community.
Thien Nguyen is an Associate Professor in the Department of Computer Science at the University of Oregon, within the College of Arts and Sciences. His research focuses on natural language processing, information extraction, and deep learning, with an emphasis on multilingual and large-scale language models. Ph.D., Computer Science, New York University M.S., Computer Science, New York University B.S., Computer Science, Hanoi University of Science and Technology His research explores how computers can understand human language to perform cognitive tasks, particularly by distilling structured information from massive multilingual text. He is a pioneer in applying deep learning to information extraction and has developed influential models and datasets such as CulturaX , Vistral , and Okapi . His lab designs learning algorithms for NLP tasks including event detection, machine translation, and chatbots. The recent work centers on large language models, cross-lingual transfer, and continual learning. His 15 most recent publications reflect a strong trend in multilingual NLP , large language models , event and relation extraction , and active and continual learning . These works span dataset creation, model development, and evaluation frameworks, often leveraging transformer architectures and reinforcement learning. The research is highly interdisciplinary, combining data mining, machine learning, and linguistic analysis. NSF CAREER Award (2023) Best Demo Paper Award, EACL 2021 Outstanding Demo Paper Award, EACL 2021 IBM Ph.D. Fellowship (2016) Dean's Dissertation Fellowship, NYU Harold Grad Prize, NYU Dr. Nguyen advises multiple Ph.D. and M.S. students and has secured significant research funding from the NSF, IARPA, and Adobe Research. His lab, UO-NLP, is actively developing tools like Trankit and FourIE . He teaches courses in data structures, machine learning, and NLP, and serves on the program and senior committees of top-tier conferences such as ACL, EMNLP, and NeurIPS. He is deeply involved in advancing multilingual NLP and democratizing access to language technologies across diverse languages.
Matthew Kanan is a Professor in the Department of Chemistry at Stanford University, teaching core courses including CHEM 31E: Chemical Foundations and 21st Century Problems (Autumn) and CHEM 121: Understanding the Natural and Unnatural World through Chemistry (Spring). He actively mentors students through year-round independent studies (CHEM 90, CHEM 190) and research programs (MATSCI 300, CHEM 301, CHEM 200). His research pioneers sustainable solutions for carbon management, focusing on electrochemical CO 2 reduction, catalyst development for reverse water-gas shift reactions, and novel carbon capture technologies. Key innovations include carbonate-promoted carboxylation processes, membrane-free electrochemical systems for acid-base production, and metamaterial reactor designs for energy-efficient thermochemical conversion. His work bridges fundamental electrochemistry with scalable engineering for carbon-neutral chemical synthesis. Recent publications (2023-2025) demonstrate a cohesive research trajectory toward industrial-scale CO 2 utilization, with emphasis on energy efficiency, catalyst durability, and impurity tolerance. Dominant themes include electrochemical engineering for concentrated product streams, computational modeling of catalyst microenvironments, and thermal processes for mineral-based carbon removal. This integrated approach targets practical implementation in sustainable fuel and chemical production. Professor Kanan supervises undergraduate research (CHEM 190), directed instruction (CHEM 90), and Ph.D. candidates across chemistry and materials science. His research group likely secures substantial funding for projects addressing critical challenges in carbon conversion, though specific grants aren't detailed in the source material. Collaborative work spans electrochemical engineering, materials design, and process optimization for decarbonization.
Professor Joseph Baker is a faculty member at the School of Kinesiology and Health Science, York University, specializing in optimal human development and athlete expertise. His research examines psychosocial and environmental factors in athletic skill acquisition, talent identification, and aging in sports. Institution: York University School: School of Kinesiology and Health Science Academic Rank: Professor Research Interests His work spans high-performance athlete development , Masters athlete aging studies , relative age effects , and talent wastage . He investigates how environmental constraints and practice structures influence expertise, with applications in para-sport and life-long physical activity . Publication Trends Recent studies focus on early specialization in hockey, talent selection policies , and psychological drivers of athlete longevity. Collaborations include analyses of physical load in handball, self-regulated learning in training, and barriers to sports participation for older adults. Students & Funding He mentors 15+ graduate students and has secured funding from Social Sciences and Humanities Research Council of Canada , Sport Canada , and Canadian Institutes of Health Research . His team explores topics like paralympic pathways , coach decision-making , and genetic/environmental interactions in performance.
Nele Mentens is a full professor at both KU Leuven and Leiden University, where she leads cutting-edge research in applied cryptography, hardware security, and secure embedded systems. At KU Leuven, she is affiliated with the Faculty of Engineering Technology and the Electrical Engineering Department (ESAT), leading the Emerging Technologies, Systems & Security (ES&S) research group at the Diepenbeek campus. Simultaneously, she holds a full professorship at Leiden University’s Leiden Institute of Advanced Computer Science (LIACS), focusing on applied cryptography and security. She has been instrumental in numerous national and international research initiatives, including Horizon Europe and NWO-funded projects. Full Professor, KU Leuven (since 2023) Full Professor, Leiden University (since 2020) Associate Professor, KU Leuven (2014–2023) Post-doctoral Researcher & Lecturer, KHLim / KU Leuven (2007–2014) Ph.D. in Engineering Science, KU Leuven (2007) M.Sc. in Electrical Engineering, KU Leuven (2003) Her research focuses on secure and efficient hardware design, particularly for cryptographic applications on FPGAs, reconfigurable architectures, IoT security, and neuromorphic computing. She explores physical attack resistance, side-channel analysis protection, and trusted computing architectures, with applications in healthcare, industrial monitoring, and endpoint AI. Her work bridges theoretical cryptography with practical hardware implementations, emphasizing energy efficiency and real-time performance. The 15 most recent publications reflect a strong trend toward secure, energy-efficient, and intelligent embedded systems. Topics include neuromorphic AI accelerators, trusted IoT architectures, dynamic reconfiguration for side-channel protection, and secure medical data processing. These works span disciplines such as computer architecture, cybersecurity, digital design, and embedded systems, with a focus on hardware-software co-design and real-world deployment. Nele Mentens has received recognition for her contributions, including: Best Paper Award, DATE'16 Best Paper Nomination, AsianHOST'17 Best Paper Award, CHES'19 She has supervised over 15 Ph.D. students and post-docs, both current and former, and has served as principal investigator in approximately 25 funded research projects. Her work has attracted significant grants from Horizon Europe, NWO, FWO, and national innovation programs. She actively contributes to the academic community through editorial roles in top journals and leadership in major conferences. Nele Mentens leads the ES&S research group at KU Leuven and collaborates closely with LIACS at Leiden University. Her team includes Ph.D. students, post-docs, and research experts working on projects like NimbleAI, NeuroSoC, and TrustedIoT. She has also established secure electronics labs through infrastructure grants and maintains strong international ties with institutions such as EPFL, Ruhr University Bochum, and ETH Zurich.
David Aitken is a Professor of Organic Chemistry at the Institute of Molecular Chemistry and Materials of Orsay (ICMMO - UMR 8182) , University of Paris-Saclay. His research focuses on synthetic methodology , photochemistry , and the preparation of bioactive molecular scaffolds . He studied Chemistry at the University of Strathclyde (BSc 1983, PhD 1986), followed by a CNRS Researcher position at the University of Paris 5 before becoming a Professor at the University of Clermont-Ferrand 2 in 1998. Since 2006, he has led his research group at Orsay and currently serves as Director of ICMMO . Education : BSc and PhD in Chemistry (University of Strathclyde, Scotland) Research Interests : Synthetic methodology, photochemical transformations, hydrogen bonding in peptides, conformational control, and biologically relevant molecules Methodologies : Photochemistry, organocatalysis, tandem reactions, stereoselective synthesis, and computational modeling Structural Analysis : Hydrogen bonding, helical folding, and non-covalent interactions using spectroscopy and molecular modeling Current Role : Director of ICMMO research institute His recent publications highlight innovations in peptide helical folding , cyclobutane and cyclopropane synthesis , and enantioselective catalytic reactions . His work bridges organic synthesis with biological applications, particularly in protein interaction inhibitors and insulin-sensitizing molecules .
