Fergus Boyles is a Researcher and Research Software Engineer at the University of Oxford, affiliated with the Department of Statistics and the Oxford Protein Informatics Group. He holds a DPhil in Systems Biology from Oxford, following a BSc in Mathematical Physics from the University of Edinburgh. His work focuses on integrating machine learning into computational biology, particularly in drug discovery and protein-ligand interaction modeling. Boyles specializes in developing robust software tools for research projects, including web applications and production-ready software packages. His research interests include predicting protein-ligand binding affinities, immunoinformatics, and improving scoring functions for structure-based virtual screening. Education: DPhil (Systems Biology), University of Oxford; BSc (Mathematical Physics), University of Edinburgh Key Projects: ANARCII database, immunoinformatics tools, scoring function development Collaborations: Oxford Protein Informatics Group, Department of Statistics His work emphasizes translating research into practical software solutions, with a focus on machine learning applications in drug discovery and computational biology.
Ricky Kiyotaka Taira is a Professor in the Department of Radiological Sciences within the David Geffen School of Medicine at the University of California Los Angeles (UCLA). With a distinguished career spanning over two decades, Dr. Taira has established himself as a leading researcher in medical informatics, specializing in natural language processing applications for healthcare data. Dr. Taira's research interests focus on medical informatics, natural language processing in clinical contexts, medical imaging informatics, radiology informatics, clinical decision support systems, electronic health records, and machine learning applications in healthcare. His work bridges the gap between computer science and clinical medicine, developing innovative solutions for processing and visualizing complex medical data. Analysis of Dr. Taira's publication history reveals a consistent trajectory focused on advancing medical informatics through natural language processing and data visualization techniques. His research spans diverse clinical domains including radiology, oncology, ophthalmology, and neurology, with particular emphasis on developing systems that improve clinical decision-making and patient care through better information organization and presentation. His work demonstrates evolving sophistication in handling medical language, from early foundational work on semantic structures to recent applications of large language models in clinical contexts. Dr. Taira has secured significant research funding, including NIH R01 grants as both Principal Investigator and Co-Principal Investigator. Notably, he served as Principal Investigator for the 'Data Structuring and Visualization System for Neuro-oncology' (R01LM009961, 2009-2013) and as Co-Principal Investigator for 'Predicting Diabetic Retinopathy from Risk Factor Data and Digital Retinal Images' (R01LM012309, 2016-2021). These grants reflect his expertise in developing informatics solutions for specific clinical challenges in neuro-oncology and diabetic eye disease. Throughout his career, Dr. Taira has maintained a productive research program, collaborating extensively with colleagues at UCLA including William Hsu, Alex Bui, Corey Arnold, and Suzie El-Saden. His work has contributed significantly to the fields of medical imaging informatics and clinical natural language processing, with numerous publications in top-tier informatics journals and conferences.
David Mendez is an Associate Professor of Technology and Operations at the Ross School of Business, University of Michigan. His research focuses on public health policy, substance use disorders, and tobacco control, with a particular emphasis on modeling smoking cessation trends, e-cigarette impacts, and policy interventions. He employs systems science and machine learning approaches to analyze population-level health behaviors and policy effectiveness. Key research interests include: Quantifying smoking-related mortality and policy impacts Adolescent substance use trajectories and e-cigarette effects Systems dynamics modeling of public health challenges Evaluating tobacco product regulations and harm reduction strategies His recent work examines the bidirectional relationship between e-cigarette and cannabis use among youth, the long-term consequences of menthol cigarette use in marginalized populations, and the application of Kalman filters to track smoking cessation dynamics. Dr. Mendez collaborates with policymakers to translate research findings into actionable public health strategies. Teaching includes Spreadsheet Modeling and Applications, emphasizing data-driven decision making in business contexts.
Adrià Martín-Mor is an Assistant Professor of Translation Studies at California State University, Long Beach (CSULB). Previously, he held positions including Serra-Húnter fellow at the Universitat Autònoma de Barcelona (UAB) and Visiting Professor at the University of Cagliari (Sardinia). He earned his Ph.D. in Translation Studies from UAB in 2011, focusing on translation technologies. His research emphasizes minoritized languages, particularly Catalan and Sardinian, exploring their political dimensions through technological interventions. Education: 2011: Ph.D., Translation Studies, UAB 2007: M.A., Translation, Interpreting and Intercultural Studies, UAB 2006: B.A., Translation and Interpreting, UAB Research Interests: Dr. Martín-Mor investigates translation technologies (CAT tools, MT), language preservation strategies for endangered languages, and the sociopolitical role of technology in language revitalization. He actively participates in projects like Sftware, a Sardinian volunteer group localizing free software (e.g., Telegram, Firefox) into Sardinian. His work bridges academia and activism, advocating for minority language digital presence. Awards & Grants: 2019: 'Si moves sa limba...' award for Sftware's Sardinian localization efforts 2011: Catalan government-funded research stay at Università di Bologna 2010: Spanish Ministry-funded stay at University of Limerick Labs/Teams: He co-founded Sftware and collaborates with the Tradumàtica research group. His work integrates translation technology into educational frameworks, exemplified by courses on statistical machine translation customization.
Jacob Daar is an Associate Professor in the Department of Psychological Science at Northern Michigan University's College of Arts and Sciences. Holding a Ph.D. from Southern Illinois University, he is a Board Certified Behavior Analyst at the Doctorate Level. Education: B.A./M.A. from University of South Florida, Ph.D. from Southern Illinois University Dr. Daar's research focuses on promoting emergent language repertoires, improving behavior assessment and treatment, and understanding gambling behavior through behavioral analysis frameworks. He directs the Behavior Education Assessment and Research (BEAR) Center, overseeing multiple service and practicum training programs for children with developmental disabilities. His recent work trends include: PEAK relational training system applications for autism intervention Stimulus equivalence and deictic framing in language acquisition Gambling behavior analysis through contingency confusion studies Relational Frame Theory in implicit social stereotyping Leadership & Advocacy Roles: Director of BEAR Center President of UP Association for Behavior Analysis Core Faculty, Michigan Leadership in Neurodevelopmental Disabilities (Mi-LEND) Member, Michigan Autism Council
Dr. Cheryl Quenneville is an Associate Professor in the Department of Mechanical Engineering at McMaster University and an Associate Member of the School of Biomedical Engineering. She specializes in biomechanics and biomedical engineering with a focus on injury tolerance criteria, orthopaedic device design, and computational modeling. Education: B.A.Sc. (Queen's University, 2003), M.Sc. (Western University, 2005), Ph.D. (Western University, 2009) Current Role: Associate Chair, Undergraduate, Mechanical Engineering Her research program integrates experimental testing and finite element modeling to advance understanding of bone fracture mechanics, develop injury risk functions, and validate synthetic surrogates for biomechanical research. Recent work has addressed hockey neck guard safety, forearm injury limits, and hip fracture risk prediction using DXA imaging. Key trends in her publications include injury biomechanics, computational modeling, and medical imaging applications. She has received the Petro-Canada-McMaster Young Innovator Award and collaborates with industry partners like Niko Apparel Systems. Her lab emphasizes trainee development and translation of findings to clinical and industrial partners. Scientific Awards: Petro-Canada-McMaster Young Innovator Award Dr. Quenneville teaches Current Topics in Orthopaedic Biomechanics (MECHENG 717/BIOMED 717) and actively accepts graduate students. The McMaster Injury Biomechanics Lab, which she leads, develops comprehensive injury limits for understudied events and translates findings through partnerships in healthcare and safety industries.
Neil Evans is an Associate Professor in the School of Engineering at the University of Warwick, affiliated with the Systems and Information Stream. He holds roles as Module Leader for Biomedical Systems Modelling (ES4A4) and Biomechanics (ES3H4/ES97E). His research focuses on systems modelling and control of biomedical processes, structural identifiability analysis, and applications in pharmacology, tumour growth, and biomechanical systems. He is a member of the Biomedical and Biological Engineering research group and the Biomedical Engineering Institute. Education: PhD in nonlinear control of infinite-dimensional systems from the Warwick Mathematics Institute (1999). Research Interests: Includes systems pharmacology, tumour growth modelling, immune system dynamics, and biomechanics of mobility and orthoses design. He has contributed to projects like the PROLIMB EPSRC-funded initiative for upper limb prosthetics and AstraZeneca’s oncology drug development analyses. His work emphasizes model selection, validation, and application in drug development and clinical settings. Grants & Projects: Includes EPSRC grants for sensorimotor prosthetics (PROLIMB), systems toxicology analysis, and mathematical engineering summer schools. Recent publications highlight advancements in machine learning for grasp analysis, pharmacokinetic models, and structural identifiability in mixed-effects systems. Awards: None listed. Labs/Teams: Active in the Biomedical Engineering Institute and collaborates with industry and healthcare groups on translational research.
František Váša is a Lecturer in Machine Learning and Computational Neuroscience at King's College London, based in the Department of Neuroimaging within the School of Neuroscience and the Institute of Psychiatry, Psychology & Neuroscience. His research focuses on developing quantitative methods for analyzing structural and functional brain imaging data, particularly using network science, machine learning, and deep learning techniques. Key areas include pre-processing and enhancement of ultra-low-field neuroimaging, null models for statistical inference in network neuroscience, and clinical applications of neuroimaging. He co-leads third-year modules on Machine Learning in Neuroscience and Computational Neuroscience for the BSc Neuroscience and Psychology program. His work emphasizes methodological rigor and translational impact, with recent contributions to super-resolution techniques for paediatric MRI and global neuroimaging initiatives like UNITY for low-resource settings. Collaborators include prominent figures such as Prof Robert Leech (King's College London), Prof Edward Bullmore (University of Cambridge), and Dr Bratislav Mišić (Montréal Neurological Institute). His research bridges theoretical frameworks with practical clinical applications, aiming to improve diagnostic tools and understand neurodevelopmental processes.
Alex Breen serves as Visiting Associate Professor at Bournemouth University's Faculty of Science and Technology and full-time Senior Research Fellow/Technology Lead at AECC University College. His research investigates mechanical aggravation of musculoskeletal conditions through quantitative fluoroscopy analysis of spinal motion, with emphasis on lumbar intervertebral dynamics and back pain mechanisms. His educational background includes: PhD in Prosthetics and Biomechanics (Bournemouth University, 2016) MSc in Medical Physics (Open University, 2012) BSc (Hons) in Physics with Medical Applications (Exeter University, 2005) Dr. Breen's research focuses on identifying biomechanical biomarkers for treatment-resistant chronic low back pain through quantitative assessment of intervertebral motion sharing patterns. He examines relationships between disc degeneration, spinal kinematics, and pain using fluoroscopic imaging, finite element modeling, and motion capture systems. Recent work explores microgravity effects on spinal geometry and spatio-temporal clustering of asymptomatic spinal motion. Analysis of his 2021-2025 publications reveals consistent emphasis on methodological validation (e.g., motion capture systems, fluoroscopy), clinical translation of biomechanical findings, and international collaboration in chiropractic research. Key themes include cervical/lumbar motion analysis, disc pressure modeling, and development of patient-specific spinal assessment protocols. His scientific recognition includes: 2019 NCMIC/JMPT RESEARCH AWARD Society for Back Pain Research Travel Fellowship (2016) Dr. Breen supervises PhD candidates Jacqueline Rix (biomechanical effects of spinal manipulation) and Terence McSweeney (quantitative imaging biomarkers). He has secured research funding including the Radiological Research Trust Travel Grant (2016) and serves on the Society for Back Pain Research executive committee (2018-present). His extensive peer review activities span journals including The Spine Journal, BMC Musculoskeletal Disorders, and Frontiers in Sports and Active Living. As AECC University College's Technology Lead, he directs biomechanical research infrastructure development and methodology innovation, particularly in spinal kinematics assessment and clinical translation of engineering approaches to musculoskeletal health.
Ethem Alpaydin is a Professor of Computer Science at Özyeğin University in Istanbul, Turkey. He is a prominent researcher in machine learning and artificial intelligence, with affiliations including membership in The Science Academy, Turkey, and Academia Europaea. He also holds a fellowship with the Asia-Pacific Artificial Intelligence Association. His research focuses on foundational aspects of machine learning, including statistical methods, neural networks, and deep learning. He has contributed to areas such as generative adversarial networks (GANs), decision pathways in neural networks, and distributed decision trees. His work bridges theoretical advancements with practical applications in domains like natural language processing and computer vision. Alpaydin has authored influential textbooks such as Introduction to Machine Learning and Maschinelles Lernen , which are widely used in academic curricula. His publications emphasize model interpretability, regularization techniques, and cross-lingual learning for languages like Turkish. Awards include recognition from leading scientific institutions for his contributions to AI and data science.
Herr Marc Masana Castrillo is a Researcher at the Institute of Computer Graphics and Vision within Graz University of Technology (College of Engineering). Holding a PhD in Computer Vision (cum laude) from Universitat Autònoma de Barcelona (2020), he specializes in Deep Learning , Continual Learning , and Neural Network Compression . His work addresses catastrophic forgetting in sequential tasks, out-of-distribution detection, and domain adaptation. PhD Thesis: "Lifelong Learning of Neural Networks: Detecting Novelty and Adapting to New Domains without Forgetting" MSc in Computer Vision (with Honours, 2015) BSc in Mathematics and Computer Science (2014) His research spans continual learning frameworks , feature disentanglement , and multimodal translation . Publications in top-tier venues like TPAMI , BMVC , and ICCV highlight his contributions. He co-developed Avalanche , an open-source PyTorch-based library for reproducible continual learning research. Scientific recognition includes the Best Master Thesis Project at UAB (2015) and the Business Track Award at Accenture Datathon (2016). His email addresses are mmasana@tugraz.at and marc.masana@icg.tugraz.at . He has reviewed for journals like TPAMI and conferences including CVPR and ICCV .
Prof. Niels Focke is a Professor of Epileptology at the University of Göttingen, leading the Translational Imaging group within the Department of Clinical Neurophysiology. He holds a dual affiliation as Hertie Faculty Member at the University of Tübingen (2014–present). His academic journey includes a Dr. med. from Göttingen (2005), Neurological Training across multiple departments (2005–2011), and a Habilitation (Venia legendi) from Tübingen (2014). Education: MD from University of Göttingen (2005) Board certification in Neurology (2011) Research focuses on structural and functional imaging of neurological diseases, particularly epilepsy. Techniques include MRI, HD-EEG/MEG, PET, and machine learning for biomarker development and automated lesion detection. Key interests involve identifying seizure origins via statistical MRI analysis and studying network connectivity disruptions in epilepsy. Methodologies: Voxel-based morphometry, diffusion imaging, fMRI Applications: Early diagnosis, clinical translation His work bridges basic science and clinical practice, with publications emphasizing multimodal imaging approaches. Affiliated with the Systems Neuroscience and Neurosciences (IMPRS) programs at Göttingen. No specific grants or awards explicitly listed, but his leadership roles reflect sustained academic contributions.
Professor Nektarios Panayiotis holds a dual role as a Professor in the Department of Floriculture and Landscape Architecture and Dean of the School of Agricultural Sciences at the Hellenic Mediterranean University (HMU). His academic journey includes a Diploma in Agriculture from the Agricultural University of Athens (1990) and a Diploma in Environmental Turfgrass Science from Cornell University, USA (1994). He leads the Laboratory of Quality and Safety of Agricultural Products, Landscape and Environment (QS AgriPLanE), focusing on sustainable urban greening solutions. His research emphasizes green roof systems urban landscape restoration plant biodiversity utilization sustainable agriculture with particular attention to Mediterranean ecosystems. Recent work explores salt-tolerant crops, substrate optimization for urban greenery, and the integration of native plants into urban planning. He has contributed to major projects like the Athens Concert Hall roof garden and adaptive green roof designs for arid climates. Over 150 peer-reviewed articles highlight his expertise in plant physiology under stress environmental impact assessments technological innovations in floriculture with a focus on translating research into practical solutions for urban sustainability. As a leader in horticultural science, his work bridges ecological principles with architectural design, aiming to enhance urban resilience through innovative landscaping practices.
Prof. Dr. Karl Gerald van den Boogaart is Head of the Modelling and Evaluation department at the Helmholtz Institute Freiberg for Resource Technology (HZDR). His work focuses on advancing geostatistical methods, compositional data analysis, and their applications in resource technology, mineral processing, and environmental geochemistry. He holds a leadership role in developing stochastic models for geological systems and has contributed significantly to the field of geometallurgy through interdisciplinary research. His research integrates advanced statistical techniques, such as multivariate analysis and Bayesian methods, with practical applications in mineral exploration, ore separation processes, and environmental assessment. Key areas of interest include the development of compositional data-driven tools for decision-making in resource management and the application of machine learning to materials science challenges. Prof. van den Boogaart has published extensively on topics ranging from geostatistical simulation and particle dynamics to organizational culture modeling. His work emphasizes bridging theoretical statistical advancements with real-world industrial and environmental challenges. Notable contributions include the Georges Matheron Lecturer of the Year 2014 award, recognizing his impactful research in mathematical geosciences. His current projects involve optimizing mineral processing techniques, enhancing ionospheric tomography via geostatistical inversion, and advancing compositional data analysis frameworks. He actively collaborates with academic and industrial partners to translate research into practical solutions for sustainable resource utilization and environmental stewardship.
Dr. Linda Baumbach is a Researcher at the University of Hamburg's Center for Bioinformatics (ZBH), affiliated with the Genome Informatics department. Her work focuses on bioinformatics applications in healthcare, particularly federated learning, privacy-preserving technologies, and osteoarthritis management. She investigates personalized medicine, physical activity impacts on chronic conditions, and healthcare system improvements. Research Interests Her interdisciplinary research spans federated machine learning for biomedical data, predictive modeling in osteoarthritis treatment outcomes, and leveraging AI for systematic literature analysis. She explores innovative approaches to data privacy in genomic studies and evaluates cost-effectiveness of physiotherapy interventions. Key Contributions Dr. Baumbach co-developed the FeatureCloud platform for federated learning, enabling collaborative research while adhering to data protection laws. Her studies on GLA:D® programs highlight exercise therapy benefits for knee osteoarthritis patients. She also addresses challenges in implementing personalized predictive models and advancing LLM-driven literature screening. Professional Activities She contributes to academic committees at the Center for Bioinformatics and collaborates internationally on projects like the GLA:D initiative and JIGSAW-E quality improvement program. Her work bridges computational methods with clinical needs, emphasizing translational research.
