Paul E. Hand is an Associate Professor of Mathematics and Computer Science at Northeastern University, affiliated with both the College of Science and the Khoury College of Computer Sciences. He holds a Bachelor of Science in Applied and Computational Mathematics from the California Institute of Technology (2004) and a PhD in Mathematics from the Courant Institute at New York University (2009), where he received the Kurt O. Friedrichs Prize for outstanding dissertation. PhD in Mathematics, Courant Institute, NYU (2009) BS in Applied and Computational Mathematics, Caltech (2004) His research focuses on developing theoretical frameworks and algorithms for machine learning and artificial intelligence, particularly in signal recovery, phase retrieval, and vision/imaging. He also explores intersections of deep learning with convex optimization and has contributed to bilinear recovery problems. Recent publications emphasize generative models, inverse problems, and robust optimization techniques. Key themes include deep learning with provable recovery guarantees , convex programming for signal inversion , and manifold-based optimization . Kurt O. Friedrichs Prize for Outstanding Dissertation (2009) NSF CAREER Grant DMS-1848087 He has taught courses on Deep Learning, Machine Learning, and Signal Processing at Northeastern University since 2016, previously holding academic roles at Rice University (2016-2018) and MIT (2009-2016). He directs educational outreach initiatives and developed the educational resource Leading Lesson for multivariable calculus problem-solving.
Professor Fredros Okumu is a leading researcher in vector biology and infectious disease ecology at the University of Glasgow's School of Biodiversity, One Health & Veterinary Medicine. He holds a PhD in Infectious Diseases from the London School of Hygiene and Tropical Medicine and an MBA in International Health Management from the University of Basel. His work focuses on malaria vector control, insecticide resistance, and ecological management of vector-borne diseases. Okumu leads research programs at the Ifakara Health Institute in Tanzania, collaborating internationally to advance surveillance and intervention strategies. Education: Public Health (Moi University), Applied Parasitology (University of Nairobi), Geo-Information Sciences (Lund University), PhD (London School of Hygiene & Tropical Medicine), MBA (University of Basel) Research: Mosquito biology, malaria transmission dynamics, genomics of Anopheles species, insecticide resistance mechanisms, and innovative control tools like mid-infrared spectroscopy and spatial repellents Awards: Howard Hughes Medical Institute–Gates Award, Wellcome Trust Fellowship, and WHO advisory roles His recent work includes genomic studies of Anopheles funestus resistance patterns, AI-driven mosquito age grading, and spatial modeling of vector habitats. Okumu's research bridges basic science with public health applications, emphasizing African-led R&D ecosystems.
Professor Maria Paola Canevini holds the position of Full Professor of Child Neuropsychiatry and directs the Developmental Neurology - Regional Epilepsy Center at ASST Santi Paolo e Carlo in Milan. Her academic work focuses on epilepsy, neurodevelopmental disorders, and genetic studies in neurological conditions. She graduated in Medicine and Surgery from the University of Milan and specialized in Neurology, with over 300 scientific publications to her name. Her research spans epilepsy therapy optimization (e.g., brivaracetam, cannabidiol), neurogenetic syndromes (Rett syndrome, Tuberous Sclerosis Complex), and sleep neuroscience in neurologic populations. She leads projects on inclusion of people with disabilities and adolescent mental health , addressing transitions to adulthood for patients with ADHD or epilepsy. Collaborative efforts include the BRIVAFIRST epilepsy drug study and CRISIS AFAR pandemic impact analysis. Her work integrates machine learning (e.g., predicting perinatal depression) and innovative wearable technologies for chronic disease monitoring. She has contributed to multinational studies on epilepsy genetics and participates in EU-funded sustainability initiatives (MUSA project).
Professor David Towers is the Head of the School of Engineering at the University of Warwick and holds the position of Professor of Mechanical Engineering. With over 30 years of combined academic and industry experience, he leads a dynamic research group focused on optical sensing technologies, fluid mechanics, and structural assessment. His work bridges engineering, biology, and clinical practice, with significant contributions to malaria control strategies through mosquito behavior analysis. Education: BSc (1st Class) in Mechanical Engineering Science from the University of Warwick PhD in Optical Engineering from the University of Warwick Royal Society Fellowship at ETH Zürich Research Interests: Professor Towers’ research spans three core areas: fluid mechanics (turbulent flows, sprays, multi-phase mixing), structural assessment (optical interferometry for deformation and stress measurement), and clinical optical systems (mosquito tracking for malaria intervention). His multi-disciplinary approach emphasizes collaboration with end-users, particularly in developing novel optical instruments for industrial and healthcare applications. Grants & Projects: AI for Mosquito Trajectory Understanding (£X, 2022–Present) Bill & Melinda Gates Foundation: Next-Gen LLIN Development (£X, 2019–2023) MRC: Indoor Mosquito Behavior Mapping (£X, 2019–2022) Awards: Athena SWAN Silver Award (2021) for promoting gender equality in STEM. Labs & Teams: Leads the Applied Optics Laboratory and collaborates with the Vector Control Research Group, focusing on AI-driven solutions for vector-borne disease control.
Professor Ralph Fyfe, currently at the University of Plymouth , serves as Professor in Geospatial Information and Associate Dean of Research for Science and Engineering. His research focuses on reconstructing past environmental change, with applications to conservation and climate change mitigation. Interdisciplinary expertise in archaeology, ecology, and climate science Lead Leverhulme Trust projects: "Deforesting Europe," "Transforming the Face of the Mediterranean," and "Reclaiming Exmoor" Contributed to over 115 academic papers and book chapters Ralph’s work combines pollen-landscape calibration datasets to quantify historical land cover changes, revealing human-driven transformations dating back to the Neolithic and Bronze Age periods. His research informs modern conservation strategies and has influenced UK National Park Authorities and COP26 climate policies. Recent publications highlight collaborations with international teams on Holocene vegetation dynamics, megafauna extinction impacts, and climate modeling. Key outlets include Global Change Biology and Scientific Reports . Fellow of the Royal Geographical Society Fellow of the Higher Education Academy Fellow of the Royal Society of Arts He teaches GIS skills , palaeoecology , and employability skills , integrating fieldwork and problem-based learning in locations like Iceland and Dartmoor.
Pengyu Hong is a Professor of Computer Science at Brandeis University's Michtom School of Computer Science and an affiliated faculty member at the Benjamin and Mae Volen National Center for Complex Systems. His expertise spans Machine Learning, Bioinformatics, Materials Science, and FinTech, with a focus on interdisciplinary applications in healthcare, molecular biology, and complex systems analysis. Education: Ph.D. in Computer Science, University of Illinois at Urbana-Champaign M.E. in Computer Science, Tsinghua University B.Eng. in Computer Science, Tsinghua University Research Interests: Hong's lab develops advanced machine learning techniques for analyzing heterogeneous data (images, text, financial data), with notable contributions in glycomaterials analysis, clinical outcome prediction, and active nematics modeling. His work bridges computational methods with biomedical and material science challenges, including NMR spectroscopy analysis and molecular property prediction. Publications: Recent work focuses on machine learning applications in glycan sequencing, fairness analysis in medical algorithms, and optical flow techniques for fluid dynamics. The lab also maintains benchmark datasets like GlycoNMR for carbohydrate analysis. Labs & Teams: Hong leads research at the Volen National Center for Complex Systems, integrating computational approaches with experimental systems biology and materials science.
Dr. Ngoc Nha Vi Tran is an Associate Professor of Computer Science at UiT The Arctic University of Norway. She holds a PhD from UiT and was a visiting scholar at Rutgers University, USA. Her research focuses on high-performance and energy-efficient computing, machine learning, and bioinformatics. She is a member of the NORA.startup Steering Group and leads the Arctic Green Computing Group. Education: PhD in Computer Science (UiT), M.Sc. in Software Engineering via Erasmus Mundus (Blekinge Institute of Technology, Sweden & Technical University of Kaiserslautern, Germany). Research interests include energy-efficient algorithms, bioinformatics tools (e.g., vCOMBAT), and applications of machine learning in healthcare and robotics. She teaches courses such as INF-2200 Computer Architecture, INF-2900 Software Engineering, and INF-2202 Concurrent Programming. Her work spans computational models for antibiotic target-binding, runtime energy optimization (REOH framework), and power models for embedded systems (RTHpower/ICE). She contributed to the EXCESS project on energy-efficient computing systems. Labs/Teams: Arctic Green Computing Group, EXCESS consortium.
Robert J. Doerksen is Professor of Medicinal Chemistry in the Department of BioMolecular Sciences at the University of Mississippi School of Pharmacy , Associate Dean of the Graduate School , and Research Professor in the Research Institute of Pharmaceutical Sciences . Since 2004 he has combined computational chemistry with experimental collaborations to advance drug discovery, particularly in glycoscience and cannabinoid research. Education: B.S. (Double First Class Honours) in Mathematics & Physics, University of New Brunswick, 1986 Graduate Diploma in Christian Studies, Regent College, Vancouver, 1996 Ph.D. in Chemistry, University of New Brunswick, 1998 (Advisor: Prof. Ajit Thakkar) Postdoctoral Fellow, UC Berkeley (with Prof. Martin Head-Gordon) Postdoctoral Fellow, University of Pennsylvania (with Prof. Michael Klein) Research Interests: Dr. Doerksen’s laboratory develops and applies computational medicinal chemistry approaches spanning chemoinformatics , molecular dynamics , virtual screening , and machine learning to understand how small molecules interact with proteins. Central themes include: Glycoscience : lectin–glycan interactions, glycosyltransferase regulation, glycomimetic design. Cannabinoids : CB1/CB2 receptor allosteric modulation, cannabidiol pharmacology, synthetic cannabinoid SAR. Neglected & Infectious Diseases : malaria, hepatitis B, tuberculosis, SARS-CoV-2, urinary-tract infections. Drug Delivery & Formulation : nanoparticle coatings, pharmacokinetic optimization, bioavailability enhancement. Publications Trend: Over 2023–2025 his 15 most recent papers reveal intense activity at the intersection of AI-driven discovery , glycobiology , and cannabinoid pharmacology , with emphasis on anti-infective, anticancer, and CNS-active agents. Key contributions include first-in-class MraY inhibitors for TB, cannabinoid-inspired antivirals against SARS-CoV-2, and glycomimetic antagonists of bacterial adhesins for UTI prevention. Scientific Awards & Honors: UM School of Pharmacy Faculty Service Award (2015–2016) UM School of Pharmacy Faculty Service Award (2010–2011) Editorial Boards: Molecules , AIMS Biophysics , Pharmaceutical Sciences , Perspectives in Medicinal Chemistry Repeated NIH, DoD, NSF, Wellcome Trust, and international grant-review panels (2010–present) Guest Editor for multiple special issues in Molecules and Frontiers journals Advising & Mentoring: As Associate Dean, Dr. Doerksen oversees University-wide graduate programs, chairs the Graduate Recruiting Fellowship and Scholarship Committee, and mentors students across disciplines. Faculty advisor for the UM chapters of the Christian Pharmacists Fellowship International (since 2005) and Taiwanese Student Association (2022–2025). He actively participates in PhD and MS thesis committees worldwide and has delivered NSF GRFP information sessions to support trainee funding. Laboratories & Teams: He directs research within the Computational Chemistry and Bioinformatics Research CORE (CCBRC) , fostering collaborative projects involving medicinal chemists, structural biologists, pharmacologists, and data scientists. The group leverages high-performance computing resources at the University of Mississippi to perform large-scale virtual screening, AI/ML model development, and integrative structural biology studies.
Prof. G.V. Shivashankar is a Full Professor of Mechano-Genomics at ETH Zurich and holds a joint appointment at the Paul Scherrer Institute (PSI), Switzerland. He previously served as Deputy Director of the Mechanobiology Institute (MBI) at the National University of Singapore (NUS), where he also held the IFOM-NUS Chair Professorship. His research focuses on nuclear mechanics, genome regulation, and cancer diagnostics, integrating optical imaging, machine learning, and functional genomics. Educated at The Rockefeller University (PhD, 1994–1999) and with postdoctoral training at NEC Research Institute, he has led groundbreaking studies on nuclear mechanogenomics and mechano-driven cell fate transitions. Awards include the Birla Science Prize (2006), Swarnajayanthi Fellowship (2007), and EMBO membership (2019). His work bridges disciplines, exploring how mechanical forces influence nuclear architecture and gene regulation. He leads the Laboratory of Multiscale Bioimaging at PSI, collaborating with IFOM in Milan. Current projects include developing nuclear biomechanical markers for early cancer diagnosis and AI-driven analysis of chromatin dynamics. Grants include support from the Mechanobiology Institute, Ministry of Education (Singapore), and the IFOM-MBI Joint Lab. Notable achievements include detecting chemoresistant cancer cells via chromatin biomarkers and reprogramming fibroblasts for tissue regeneration. His lab actively mentors students and collaborates globally on mechanobiology applications in health and disease.
Joseph Ibrahim is an Alumni Distinguished Professor in the Department of Biostatistics at the Gillings School of Global Public Health, University of North Carolina at Chapel Hill, where he has served since 2002. He currently holds dual leadership roles as Director of Graduate Studies for the Department of Biostatistics and Director of the Biostatistics for Research in Genomics and Training Grant. His methodological innovations in Bayesian survival analysis and missing data methodologies have significantly advanced public health research, particularly in cancer genomics applications. Professor Ibrahim's research program centers on developing statistical frameworks for complex clinical and genomic data. His seminal contributions include Bayesian cure rate models, prior elicitation techniques, and diagnostic tools for high-dimensional survival analysis. Current work focuses on integrating multi-omics data with longitudinal tumor burden metrics and refining adaptive clinical trial designs for biomarker-driven populations. These methodologies directly address critical challenges in precision oncology and pharmacovigilance, enabling more robust inference from real-world evidence. His 2025 publications reveal three dominant trends: (1) Advancements in cure rate modeling for joint longitudinal-survival data with change points, (2) Computational innovations for high-dimensional penalized models using autoencoders and R packages like hdbayes, and (3) Methodological refinements for Bayesian trial design incorporating historical controls. These works consistently bridge theoretical statistics with cancer research applications, particularly in tumor phylogeny inference and signal detection for adverse events. Scientific awards include: Samuel S. Wilks Memorial Award (2024) from the American Statistical Association for distinguished contributions to biostatistics Professor Ibrahim has mentored 48 pre-doctoral students and 8 postdoctoral fellows, with exceptional thesis publication records in top statistical journals. As principal investigator of the T32 Cancer Genomics Training Grant since 2004, he has secured funding for 35 doctoral students. His curriculum leadership includes modernizing eight graduate courses and establishing new data science computing sequences since 2015. Current advising focuses on Bayesian methodology development for cancer genomics applications. He directs the department's Biostatistics for Research in Genomics initiative and leads the T32 Cancer Genomics Training Grant team, which integrates statistical methodology development with translational cancer research across UNC's Lineberger Comprehensive Cancer Center and clinical partners.
Cary D. Troy is a Professor of Civil Engineering at Purdue University's Lyles School of Civil and Construction Engineering. He specializes in environmental fluid mechanics, with a focus on hydrodynamic processes in lakes and coastal systems, particularly Lake Michigan. His research integrates field experiments, numerical modeling (e.g., SUNTANS), and analytical methods to study circulation, thermal structure, and mixing in aquatic environments. Education: Ph.D. (2003), M.S. (1997), and B.S. (1995) in Civil Engineering from Stanford University, University of Illinois Urbana-Champaign, and Purdue University, respectively. Research interests include benthic boundary layer processes, river plume characterization, and the impacts of invasive species (e.g., quagga mussels) on water quality. His pedagogical work emphasizes active learning in engineering education, including flipped classrooms and writing-to-learn strategies. He has mentored over a dozen graduate students and received multiple teaching awards, including the Purdue University Bravo Award (2015) and Exceptional Early Career Teaching Award (2014). Awards include the Roy E. & Myrna G. Wansik Teaching Leadership Award (2016) and the American Society of Civil Engineers ExCEED Teaching Fellow designation (2009). His lab, the Burke Hydraulics and Hydrology Lab, focuses on advancing understanding of coastal and limnological systems through interdisciplinary approaches.
Max Staller is an Assistant Professor in the Department of Molecular and Cell Biology at the University of California, Berkeley, affiliated with the College of Letters & Science and the Center for Computational Biology. His lab focuses on understanding how transcriptional activation domains regulate gene expression through interdisciplinary approaches combining experimental, computational, and theoretical methods. Research Interests: Transcriptional regulation mechanisms in development and stress responses Functional analysis of intrinsically disordered protein domains Machine learning applications in protein sequence-function prediction Evolutionary dynamics of transcription factors Grants & Collaborations: Lead investigator on the NSF-funded PlantSynBio project (2021) for identifying transcriptional activation domains across plant species. Collaborates with the Cohen Lab (Washington University) on mutational scanning studies. Labs & Affiliations: Director of the Staller Lab, which integrates high-throughput experiments with computational modeling. Active in the Berkeley Bioscience community and the Center for Computational Biology.
J. Sean Humbert is a Professor at the University of Colorado Boulder, holding a courtesy appointment in the College of Engineering and Applied Science (AES). He serves as Director of the Robotics Program and Faculty Director for the Aerospace and Defense Western Colorado University Partnership Program. His research focuses on bio-inspired robotics, autonomous systems, and advanced control methodologies. Key research areas include flight dynamics, bio-inspired perception, micro-robotics, and soft robotics. He leads the Robotics and Systems Design group, affiliated with the Hypersonic Vehicles IRT. His work integrates bio-mimetic principles with engineering challenges, emphasizing robust control in unstructured environments. Recent publications span topics like soft robotic actuators, distributed sensing, and neural dynamics in robotics. His lab develops cutting-edge technologies for subterranean exploration, UAV navigation, and bio-inspired sensor systems. Collaborations include industry partnerships and interdisciplinary projects at the intersection of robotics, biology, and control theory. Awards and recognitions are not explicitly mentioned in the provided texts. Sean Humbert’s lab is located at ECES 1B14, with an office in ECES 146. His academic contributions bridge theory and application, addressing real-world challenges in autonomous systems and robotics innovation.
Professor Vicki Friesen is a faculty member in the Department of Biology at Queen's University, part of the Faculty of Arts and Science. Her research focuses on evolutionary and conservation genetics, particularly in seabirds, aiming to understand mechanisms of biodiversity generation and conservation applications. She holds a cross-appointment in the School of Environmental Studies. Her research interests include evolutionary genetics, conservation genetics, biodiversity origins, and the impacts of climate change on seabird populations. She uses next-generation sequencing to study local adaptation and genetic diversity in species such as seabirds, passerines, and fish. Education: Though not explicitly detailed here, her academic roles suggest advanced training in biology or genetics. Labs/Teams: Leads the Friesen Lab, focusing on Arctic ecology and conservation genomics. Advising: Supervises numerous graduate and undergraduate students in topics like migratory mechanisms, conservation genomics, and immunology. Her work emphasizes the application of genetic tools to conservation challenges, such as delineating conservation units and understanding hybridization dynamics in threatened species.
Professor Sandeep Reddy is a leading academic in healthcare management and digital health at Queensland University of Technology (QUT), where he heads disciplines in Healthcare Management, Health Information Management, and Health, Safety, and Environment. He co-leads the 'Health, Human Biology and MedTech' theme at QUT's Centre for Data Science. With a PhD in Healthcare Management and a medical degree, Reddy holds multiple professional fellowships, including the Australasian Institute of Digital Health and the UK Higher Education Academy. Roles: Professor, Academic Leader, Researcher, Editor Affiliations: QUT, WHO Digital Health Roster, European Academy of Translational Medicine Professionals His research focuses on AI integration in healthcare delivery, governance frameworks, and translational methodologies. Key areas include AI in chronic disease management, medical imaging, and facial recognition technology. Reddy has authored over 80 publications, including a 2024 textbook on translational AI applications. Reddy's work spans global health policy, having advised the WHO and participated in international panels. He teaches courses on health informatics, implementation science, and digital health, with over 20 years of academic and industry experience. Scientific awards and fellowships reflect his expertise: Fellow of AIDH, ACHSM, and Senior Fellow of the UK Higher Education Academy. His editorial roles include PLOS ONE, Computational and Structural Biotechnology Journal, and Frontiers in AI. Current research supervision focuses on AI in medical education, healthcare access, and explainability in AI systems. He advocates for equitable digital health solutions, addressing the rural-urban digital divide through empirical studies.
