Find Academic Supervisors

Shibu YoosephView profile

Professor

• Computational Biology
• Genomics
• Bioinformatics
• +5 more

Shibu Yooseph is the Kravis Professor of Integrated Sciences in the Kravis Department of Integrated Sciences , specializing in computational biology, bioinformatics, and microbiome research. His career includes roles as Professor of Computer Science at the University of Central Florida (2016–2023), Senior Director of Bioinformatics at Human Longevity Inc., and leadership positions at the J. Craig Venter Institute, where he contributed to major genome projects like the Human Genome and Sorcerer II expeditions. Education: Ph.D. in Computer and Information Science (1997), University of Pennsylvania; B.Tech. in Computer Science (1992), Indian Institute of Technology, Banaras Hindu University. Research Focus: Algorithm design, machine learning, computational genomics, and microbiome analysis. Key projects include microbial network modeling, host-microbiome interactions, and applications in disease (e.g., inflammatory bowel disease, colorectal cancer). His work leverages computational tools like GRASP2 and SFA-SPA for metagenomic data analysis. Publications Trends: Recent work emphasizes oral and gut microbiome dynamics in clinical settings, microbial network inference , and computational methods for genomic assembly . Contributions span biotechnology, environmental microbiology, and translational medicine. Awards: Not explicitly listed in available texts. Leadership & Grants: Directed informatics teams at multiple institutions, led the Genomics and Bioinformatics Cluster at UCF, and contributed to major NIH-funded projects. Grants and funding details are not detailed in the provided text. Labs & Teams: Affiliated with the Kravis Department’s integrated sciences team and previously with the J. Craig Venter Institute’s informatics group.

Francesco FerraroView profile

Lecturer

• Respiratory Physiology
• Geriatric Rehabilitation
• Public Health
• +5 more

Francesco Ferraro is a Lecturer in Sport Therapy and Rehabilitation affiliated with the College of Science and Engineering. His research focuses on respiratory muscle training interventions, long-term post-viral syndromes (particularly Long-COVID), geriatric rehabilitation, and educational strategies during pandemics. He has published extensively on topics such as the efficacy of inspiratory muscle training in older adults, the impact of Long-COVID on quality of life, and the role of artistic sports in improving academic outcomes among vulnerable youth. His work integrates clinical practice with technological innovation, as seen in studies exploring AI applications in clinical vision and embodied cognition frameworks. Ferraro has conducted randomized controlled trials evaluating interventions like Tai Chi for respiratory health and Latino dance for child self-efficacy. He collaborates internationally, with studies in Pakistan, China, and across European countries. Key areas of contribution include: Developing rehabilitation protocols for orthopedic recovery through respiratory training Advocating for redefined biomarker standards in post-COVID patient assessment Designing pedagogical interventions to address pandemic-related educational gaps Ferraro’s research often bridges clinical, educational, and social domains, emphasizing holistic health strategies for marginalized groups such as left-behind children and individuals with chronic conditions.

• Computational Chemistry
• Medicinal Chemistry
• Computer-Aided Drug Design
• +4 more

Donald B. Boyd, Ph.D., serves as Research Professor of Chemistry at Indiana University - Purdue University Indianapolis (IUPUI) within the School of Science. His academic journey began in 1982 when he joined as Adjunct Professor while concurrently working as a Senior Research Scientist at Eli Lilly and Company, where he spent 25 years in computer-aided drug design. He was promoted to Research Professor in 1994, establishing himself as a leading figure in computational chemistry with over 100 refereed publications and significant editorial contributions. Dr. Boyd earned his B.S. from The Pennsylvania State University (1963), followed by an A.M. (1965) and Ph.D. (1968) from Harvard University, with NIH Postdoctoral training at Cornell University (1967-68). His research focuses on computational chemistry and medicinal chemistry, particularly the relationship between molecular structure and properties, with applications in pharmaceutical development. He pioneered computer-aided drug design methodologies that address the economic challenges of modern drug discovery, leveraging genomic insights for targeted therapeutic development. His publication record reveals consistent contributions to computational drug design, molecular modeling, and the historical evolution of computational chemistry. Early work centered on molecular simulations of drug-receptor interactions (1990s), evolving toward Alzheimer's disease therapeutics, HIV inhibitors, and pharmaceutical stress testing in recent years. The research demonstrates increasing integration of cheminformatics, machine learning, and industrial applications throughout his career. Spirit of Philanthropy Award from IUPUI (1996) Woodward Lecturer, Pennsylvania State University College of Medicine (2013) Sloan-C Award for Online Education (2012) Stanley C. Israel Regional Award (2011) James Flack Norris Award for Teaching Chemistry (2008) Multiple Prestigious External Award Recognition (PEAR) honors Dr. Boyd has advised numerous graduate students who now hold positions at major pharmaceutical companies and research institutions worldwide. His editorial leadership includes founding the Reviews in Computational Chemistry book series (18 volumes, 1990-2002) and serving as Editor of the Journal of Molecular Graphics and Modelling (1998-2001), where he increased submissions from 5 to 90 annually. He conceived the biennial Gordon Research Conferences on Computational Chemistry (1986-present) and the ACS Symposium on Emerging Technologies in Computational Chemistry. Through his Central Indiana Computational Chemistry Christmas Luncheons and leadership in professional organizations including the American Chemical Society's Division of Computers in Chemistry, Dr. Boyd has fostered collaborative research communities while maintaining active industry consultation roles with pharmaceutical and chemical companies.

Arup GhoshView profile

Associate Professor

• Human-Computer Interaction
• Digital Youth
• Social Computing
• +6 more

Dr. Arup Ghosh is an Associate Professor of Computer Science at Jacksonville State University (JSU), leading the Human-Technology Interaction Research Lab (HTIR Lab). His work focuses on Human-Computer Interaction (HCI), Digital Youth, and Social Computing, with a strong emphasis on improving adolescent online safety through value-sensitive design and AI integration. He teaches both undergraduate and graduate courses in Computer Science, including AI, HCI, and distributed systems. Dr. Ghosh has been honored with multiple awards, including Educator of the Year by the Engineering Council of Birmingham and IEEE Alabama, and serves in leadership roles within IEEE and ACM. Education: Ph.D. in Computer Science, University of Central Florida Graduate Certificate in Advanced Quantitative Methods, University of Central Florida M.S. in Computer Engineering, University of Central Florida B.S. in Information Technology, West Bengal University of Technology Research Interests: Dr. Ghosh’s research bridges technology and societal impact, particularly addressing online safety for adolescents and vulnerable populations. His work has been featured in Science Daily , NPR , and ABC News , highlighting innovations like privacy-preserving apps and ethical AI frameworks. He collaborates with industry and policymakers to translate research into actionable solutions, such as mitigating cyber risks for foster care youth and enhancing elderly care through AI. Publications & Impact: His peer-reviewed work spans HCI, cybersecurity, and education technology, with a focus on mobile safety and digital literacy. Recent studies explore AI-driven eldercare systems and mitigation strategies for online threats in education. Awards & Leadership: IEEE Eta Kappa Nu Honor Society Inductee (2024) ABET Computer Science Program Evaluator (2024–Present) Vice Chair, IEEE Alabama Section (2023–Present) Advising & Outreach: Dr. Ghosh advises JSU’s IEEE Student Branch and UPE Honor Society Chapter, fostering student engagement in tech competitions and conferences. He also contributes to institutional committees, including the JSU Technology Advisory Committee. Labs & Teams: The HTIR Lab develops solutions for safer digital experiences, with projects ranging from mobile safety apps to computational modeling of social behaviors.

Katarzyna ŚwiderekView profile

Associate Professor

• Computational Chemistry
• Biochemistry
• Enzyme Catalysis
• +4 more

Dr. Katarzyna Świderek is an Associate Professor at Universitat Jaume I (UJI) in Castelló, Spain, where she leads research at the Institute of Advanced Materials (INAM) within the Department of Physical and Analytical Chemistry. She serves as Senior Researcher in Computational Biochemistry group (RG9) and Project Leader for the DeProtCa initiative focused on enzyme design principles. Dr. Świderek earned her Master's (2007) and PhD (2011) degrees in Physical Chemistry from Lodz University of Technology, Poland, under Prof. P. Paneth. Her academic journey includes postdoctoral positions at University of Valencia (2011-2014), University Jaume I (2015 onward), and a visiting position at University of Bath (2017). In December 2024, she was promoted from Ramon y Cajal fellow to Associate Professor (Profesor Titular). Her research focuses on theoretical studies of reactivity in cellular processes , with three main interconnected areas: Origin of biocatalysis Inhibition and drug design Design of biocatalysts Most of her work employs molecular dynamics (MD) simulations with hybrid QM/MM potentials to investigate enzymatic mechanisms, with applications spanning pharmaceutical, medical, and industrial domains. Analysis of her recent publications reveals a strong emphasis on computational enzymology, particularly studying proteases (including SARS-CoV-2 Mpro), proteasome inhibition mechanisms, and enzyme design strategies. Her work increasingly integrates AI approaches with traditional computational methods, demonstrating evolution in the field toward more sophisticated predictive models for enzyme behavior. Dr. Świderek has secured multiple competitive research grants, including a recent Spanish Ministry of Science project (2025-2027) titled 'Deciphering the structural and kinetic principles of enzymes to design advanced protein-based catalysts for enhanced biocatalysis.' One of her studies on SARS-CoV-2 Mpro inhibition ranked in the top 5% of highly cited works from Royal Society of Chemistry Journals. She actively mentors graduate students including Carmen Ramos, Álvaro Serrano López de la Vieja, and Adrián Fernández de la Pradilla Ibáñez. Her research group collaborates internationally with institutions across Spain, Poland, USA, UK, Canada, and Italy, utilizing the T∙R∙I∙N∙I∙T∙Y computational cluster with 320 CPUs and multiple GPUs for their demanding simulations.

• Statistics
• Bioinformatics
• Epidemiology
• +3 more

Jose Ameijeiras Alonso is a Professor at the University of Santiago de Compostela, serving as General Coordinator and Coordinator within the Faculty of Mathematics. He holds a Ph.D. in Statistics and Operations Research and is affiliated with the Department of Statistics, Mathematical Analysis and Optimization. His research focuses on statistical methodologies with applications in epidemiology, bioinformatics, and environmental science. Key areas include circular data analysis, nonparametric estimation, and multimodality testing. He has developed statistical tools for analyzing protein structures, wildfire patterns, and disease outbreaks such as COVID-19. Notable contributions include the R package Multimode for mode assessment and the SPQEIR model for evaluating epidemic control strategies. His work bridges theoretical statistics with real-world applications in healthcare and environmental management.

• Emergency Medicine
• Infectious Diseases
• Critical Care Medicine
• +3 more

Luigi Mario Castello is an Associate Professor in the Department of Translational Medicine at the University of Eastern Piedmont Amedeo Avogadro. His research focuses on emergency medicine, infectious diseases, and critical care, with notable contributions to understanding sepsis management, viral reactivation in severe COVID-19, and pulmonary edema diagnostics. He leads the project 'Autoimmunity and Sepsis' and has published extensively on clinical practices in emergency settings. His work integrates machine learning for diagnostic accuracy, trauma care protocols, and primary care improvements. Key contributions include analyzing herpesvirus reactivation outcomes in hospitalized patients and refining sepsis scoring systems. Collaborations span multidisciplinary teams addressing urgent healthcare challenges.

• Infectious Disease Ecology
• Malaria Vector Ecology
• Vector-Borne Disease Control
• +5 more

Professor Heather M Ferguson is a leading researcher in infectious disease ecology at the University of Glasgow, specializing in malaria vector ecology and control. She holds a professorship within the Institute of Biodiversity, Animal Health and Comparative Medicine (BAHCM) in the College of Medical, Veterinary and Life Sciences. Her educational background includes a BSc (Honours) in Zoology from the University of Toronto, an MSc in Zoology (conservation biology) from the University of British Columbia, and a PhD from the University of Edinburgh focused on malaria vector-parasite interactions. She completed postdoctoral research at the University of Edinburgh and the Ifakara Health Institute in Tanzania before joining the University of Glasgow as a BBSRC David Philips Research Fellow in 2006. Professor Ferguson's research focuses on the ecology and behavior of African malaria vectors, surveillance and control of mosquito vectors of malaria and arboviruses, the impact of environmental change on vector-borne diseases, and assessing the risk of mosquito-borne disease emergence in Scotland. Her recent publications demonstrate a strong emphasis on vector genetics, insecticide resistance mechanisms, mosquito behavior, and innovative surveillance methods including spectroscopy and geospatial modeling. Her work spans multiple continents with significant research conducted in Tanzania, Ecuador, Malaysia, and Scotland. She maintains a close research partnership with the Ifakara Health Institute in Tanzania where she holds a Visiting Scientist appointment. Her research has significant implications for malaria control programs in endemic regions and contributes to understanding potential vector-borne disease risks in non-endemic areas like Scotland. Professor Ferguson's work bridges fundamental vector ecology with practical applications for disease control, making substantial contributions to both scientific understanding and public health practice.

Liam BrierleyView profile

Research Fellow

• Virology
• RNA Virus Ecology
• Computational Biology
• +7 more

Dr. Liam Brierley is a Research Fellow in Virology and Affiliate Researcher at the School of Biodiversity, One Health & Veterinary Medicine, University of Glasgow. His work focuses on applying computational methods to understand RNA virus cross-species transmission, leveraging statistical modeling, machine learning, and text mining tools. He holds a MRC Career Development Award (2024-2029) and previously received a MRC Skills Development Fellowship (2019-2022). His research spans ecological modeling of host-virus relationships, viral sequence analysis, and pandemic preparedness frameworks. Research interests include: Machine learning for RNA virus trait prediction (genotype-to-phenotype) Systematic data mining for host-virus relationship analysis Large-scale viral sequence analysis Ecological drivers of zoonotic transmission Key contributions include modeling RNA virus discovery patterns, preprint analysis during the pandemic, and computational tools for ctDNA variant detection. He has published over 20 peer-reviewed articles, including work in Proceedings of the Royal Society B , PLOS Pathogens , and Molecular Biology and Evolution . He serves on editorial boards for Scientific Data and Frontiers in Virology , and is a Fellow of the Royal Statistical Society. His outreach includes science communication through Edinburgh Fringe Festival performances and Bright Club Glasgow stand-up comedy events.

Youyi FongView profile

Academic

• Biostatistics
• Machine Learning
• Computer Vision
• +7 more

Youyi Fong is an Affiliate Professor in the Department of Biostatistics at the University of Washington. He holds a PhD in Biostatistics from the University of Washington and dual PhDs in Molecular, Cellular, and Developmental Biology and Computer Science from Indiana University. His research focuses on statistical methods for vaccine efficacy trials, immune correlates analysis, machine learning applications in medical imaging, and computational biology. He leads the Fong Group, developing tools for cell segmentation and phenotyping using deep learning and computer vision techniques. Key areas of research include analyzing clinical trial data for HIV, SARS-CoV-2, and dengue vaccines, as well as developing statistical frameworks for immune response modeling. His work integrates biostatistical methodologies with cutting-edge computational approaches, such as autoencoder-based unsupervised learning and kernel-based random effects models. Collaborations span infectious disease research, cell imaging analysis, and public health policy. Education: MS in Computer Science, Indiana University PhD in Molecular, Cellular, and Developmental Biology, Indiana University PhD in Biostatistics, University of Washington Research interests emphasize vaccine development, threshold regression models, and computational tools for biomedical imaging. His lab has contributed software like TSP (The Seattle Pipeline) for cell and tissue imaging analysis, which includes cell segmentation, spatial analysis, and statistical methods for multiplexed data. Publications span topics such as immune correlates of protection, vaccine durability, and statistical methodologies for clinical trials. His work bridges biostatistics, machine learning, and translational medicine to address global health challenges.

• Bioinformatics
• Systems Biology
• Biotechnology
• +3 more

ÓSCAR MANUEL LIMA DIAS is an Auxiliary Researcher at the University of Minho's Centre of Biological Engineering (CEB) since 2016 and CEO of OMNIUMAI, a company specializing in AI and data sciences. He holds a BSc in Biological Engineering, MSc in Informatics, and PhD in Chemical and Biological Engineering from the University of Minho. His academic roles include serving on the Steering Committee of the Master's in Bioinformatics and contributing to the Scientific Steering Committee of the Department of Biological Engineering. Roles: Auxiliary Researcher (2016–present), CEO of OMNIUMAI (2020–present), Member of Multiple Scientific Committees Education: PhD (2013), MSc (2008), BSc (2005) from the University of Minho Research Interests: Bioinformatics, Systems Biology, Metabolic Modeling, Machine Learning applications in biology, and Biotechnology. His work spans microbial metabolism, synthetic biology, and computational tools for metabolic network analysis. Publications & Projects: Over 57 peer-reviewed publications, leading roles in projects like iPlants.pt and Methane Mitigation Strategies. Collaborations with institutions in Denmark, Germany, Netherlands, Spain, UK, and USA. Labs & Teams: Active in the Centre of Biological Engineering, Labbels, and the Associate Laboratory on Biotechnology. Contributions to frameworks like merlin and TranSyT for metabolic modeling.

Yongmann ChungView profile

Associate Professor

• Computational Fluid Dynamics
• Turbulence Modeling
• Flow Control and Drag Reduction
• +4 more

Yongmann Chung is an Associate Professor at the School of Engineering, University of Warwick. His research focuses on Computational Fluid Dynamics (CFD), turbulence modeling, and flow control with applications in aerospace engineering and electrochemistry. He specializes in Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS) of complex flows, including micro-fluid dynamics in electrochemical systems and drag reduction strategies. His work spans unsteady turbulent flows, heat transfer, and aerodynamic phenomena in systems like flying cars and quadcopters. Teaching interests include fluid mechanics (ES2A7), computational fluid dynamics (ES440), and scientific computing (MA5P9). Recent publications explore battery health prediction using graph neural networks, vortex ring state analysis, and computational models for droplet dispersion in public spaces. Chung’s research also addresses industrial challenges such as cavitation erosion monitoring and turbulent flow control via Lorentz force actuation. Office hours are Fridays 10 am–12 pm during term time. He advises projects and grants in fluid dynamics and thermal engineering, with a focus on both fundamental turbulence research and applied energy systems. His work extends to bio-inspired design, exemplified by studies on dolphin kick swimmers, and environmental health modeling for airborne disease transmission.

• Adaptive Immunity
• Bioinformatics
• Computational Biology
• +5 more

Lindsay Cowell is a Professor in the Department of Population and Data Sciences at UT Southwestern Medical Center, with a secondary appointment in the Department of Immunology within the School of Biomedical Sciences. She directs research in adaptive immunity and bioinformatics, affiliated with the Immunology, Cancer Biology, and Computational and Systems Biology graduate programs. Her educational background includes an M.S. in Biomathematics (1995) and Ph.D. in Biomathematics (2000), both from North Carolina State University, followed by a postdoctoral fellowship at Duke University Medical Center. She joined UT Southwestern in 2010 after serving as an Assistant Professor in Duke's Department of Biostatistics and Bioinformatics. Dr. Cowell's research focuses on adaptive immune receptor repertoires, leveraging high-throughput sequencing and computational methods to study immune responses in cancer, autoimmune diseases (e.g., multiple sclerosis), and infections (e.g., HIV, SARS-CoV-2). Her group develops innovative approaches for representing immune repertoires as antigen specificity landscapes and detecting diagnostic patterns. Recent work emphasizes clinical applications through projects like VDJServer and AIRR Community initiatives. Analysis of her 15 most recent publications reveals a strong trend toward translational immunology, with significant contributions to SARS-CoV-2 complications, cancer biomarker discovery, and immune repertoire data standards. Her work bridges computational biology with clinical immunology, particularly in HPV-related cancers and autoimmune diagnostics. As a principal investigator, she leads collaborative projects across multiple institutions and serves on editorial boards for immunoinformatics resources. Her lab maintains active involvement in the AIRR Community, driving standards for immune repertoire data sharing and analysis.

Farnoush FarahpourView profile

Researcher

• Computational Biology
• Immunology
• Microbial Ecology
• +3 more

Dr. Farnoush Farahpour is a Researcher at the University of Duisburg-Essen, affiliated with the Faculty of Biology and Faculty of Medicine. She leads the Junior Group Farahpour Lab, focusing on computational methods to understand complex biological systems. Her research integrates data analysis and mathematical modeling to study microbial communities, T-cell receptor repertoires, and immune responses in diseases like cancer and diabetes. Key areas include developing tools for interaction inference and multi-level modeling of systems biology problems. Research Interests: Overcoming complexity in biological systems through computational approaches, microbial ecology, immune system dynamics, systems biology, and the application of stochastic models. Recent work explores gut microbiota’s role in HIV, SARS-CoV-2 pathogenesis, and therapeutic effects of BRAF/MEK inhibitors in melanoma. Recent Trends in Publications: Dr. Farahpour’s work emphasizes computational tools (e.g., scBubbletree for single-cell RNA-seq visualization) and microbiome studies, linking microbial diversity to disease outcomes. Her publications reflect a focus on translational research, bridging computational biology with clinical applications in oncology and infectious diseases. Grants & Labs: Operates the Junior Group Farahpour Lab, actively involved in funded projects on oncology and immunology. Collaborates widely, evidenced by co-authorships across multidisciplinary teams. Ongoing projects aim to expand computational frameworks for analyzing complex biological interactions and their clinical implications.

Antonio Martinez SanchezView profile

Researcher

• Artificial Intelligence
• Bioinformatics
• Image Processing
• +5 more

Antonio Martinez Sanchez is a Ramón y Cajal Researcher at the University of Murcia's Faculty of Informatics, Department of Information and Communication Engineering. His research focuses on computational methods for cryo-electron tomography, artificial intelligence, and bioimaging. He holds a PhD from the University of Almería (2013), specializing in differential geometry-based computational techniques for electron tomography. Education : PhD in Computer Science, Universidad de Almería (2013) His research interests include deep learning applications in microscopy, membrane protein analysis, and high-performance computing for 3D imaging. Recent work emphasizes template matching, orientation estimation, and automated pipelines for cryo-electron tomography. He leads the AIKE (Artificial Intelligence and Knowledge Engineering) research group and contributes to tools like ScipionTomo and MemBrain. Articles highlight advancements in computational methods for structural biology, such as fast cross-correlation algorithms and deep learning-driven orientation estimation. These techniques address challenges in analyzing cellular architecture and viral interactions. His work bridges computer science and biology, advancing tools for subcellular imaging and data reproducibility. Labs/Teams : AIKE: Artificial Intelligence and Knowledge Engineering research group.