Find Academic Supervisors

Páraic Ó'SúilleabháinView profile

Associate Professor

• Personality Psychology
• Health Psychology
• Mortality Risk Analysis
• +3 more

Páraic Ó'Súilleabháin is an Associate Professor of Psychology at the University of Limerick, affiliated with the Department of Psychology and the Ageing Research Centre. He serves as Research Coordinator on the Doctoral Programme in Clinical Psychology and directs the Personality, Individual Differences, and Biobehavioural Health Laboratory (PathLab). His research focuses on personality traits, loneliness, adversity, and their associations with health outcomes across the lifespan, including mortality risk. His work bridges psychology with biological processes and biobehavioural factors. Education: PhD in Psychology (2017), NUI Galway; Post Graduate Certificate in Teaching and Learning (2018); BA (Hons) in Psychology (2012), NUI Galway. Prior to academia, he worked in med-tech and IT industries. Research interests include lifespan health, psychophysiological mechanisms, and the societal impacts of personality differences. His projects involve collaborations with institutions like Florida State University and University College London. Recent studies address loneliness in youth, cognitive decline in aging populations, and large-scale mortality analyses. Awards: 2025 APS Rising Star designation. Over 46 peer-reviewed publications, including systematic reviews and meta-analyses on loneliness and health. Advising & Grants: Leads PathLab and oversees doctoral training. Collaborations span transnational studies on global health issues. Active in UN Sustainable Development Goals related to health and well-being.

Xiao LiView profile

Assistant Professor

• Blockchain Technology
• Distributed Systems
• Machine Learning
• +7 more

Dr. Xiao Li is an Assistant Professor in the Department of Computer Science and Engineering at Santa Clara University, School of Engineering. His research focuses on blockchain technology applications in distributed systems (Edge Computing, IoT, Federated Learning), machine learning, and privacy-preserving frameworks. He has a Ph.D. in Computer Science from The University of Texas at Dallas (2024) and was awarded the Jan P. Van der Ziel Engineering Fellowship there. Education: Ph.D. in Computer Science, The University of Texas at Dallas, 2024 Research interests include: Blockchain architecture optimization in resource-constrained environments Machine learning model development for cryptocurrency analysis Cybersecurity disclosure sentiment analysis using unsupervised techniques Low-resource data challenges in psychiatric clinics Professional activities: Program Committee Member, IEEE International Workshop on Blockchain and Smart Contracts (IEEE BSC 2024) Recruitment of PhD/Master’s students specializing in blockchain, distributed machine learning, and edge computing Office Location: Bergin 206 Office Hours: Mon/Wed 4pm-5pm (Winter 2025)

B. Bradford BrownView profile

Professor

• Adolescent Peer Relations
• Social Media Effects
• Racial/Ethnic Identity
• +3 more

B. Bradford Brown is a Professor in the Human Development Area at the University of Wisconsin-Madison School of Education . With nearly 100 publications, his work focuses on adolescent peer relations, social media use, racial/ethnic identity, and college transitions. He has served as Editor of the Journal of Research on Adolescence and received the UW School of Education Distinguished Achievement Award. Current Research: Social media adaptation during middle school/high school transitions Racial Identity: Belonging and friendship formation in college settings Methodology: Meta-analyses, longitudinal studies, and qualitative analyses His publications highlight trends in adolescent development , digital peer interactions , and identity negotiation . Scientific awards include multiple Honored Instructor Awards from UW-Madison and a Teaching Academy induction. He actively mentors students and collaborates on studies of electronic intimacy, parental mediation, and peer group dynamics.

• Remote Sensing
• Geographic Information Systems (GIS)
• Environmental Monitoring
• +7 more

Giorgos Mountrakis is a Professor in the Department of Environmental Resources Engineering at SUNY College of Environmental Science and Forestry (ESF). His research focuses on environmental monitoring using remote sensing, environmental modeling through geographic methods, and decision support systems for ecological and urban challenges. He holds a Dipl. Eng. from the National Technical University of Athens (1998), an M.S. (2000), and Ph.D. (2004) from the University of Maine. His work integrates advanced technologies like satellite imagery, LiDAR, and machine learning to address land cover dynamics, climate impacts, and wildlife conservation. Current advisees include Atef Amriche (PhD candidate in Geospatial Information Science), Babak Haji Seyed asadollah (PhD in Environmental Resources Engineering), Ahmadreza Safaeinia (PhD in Environmental Resources Engineering), and Zhixin Wang (PhD in Geospatial Information Science). Key research themes include: land use/cover classification using deep neural networks, climate change impacts on forests and rangelands, and optimizing spatial-temporal models for large-scale environmental analysis. His projects span global datasets (e.g., Landsat, MODIS) and regional case studies in the US, Mongolia, and Algeria. Publications emphasize methodological advancements in remote sensing, such as fusion of multisensor data, accuracy assessment frameworks, and applications in biodiversity conservation. His work bridges technical innovation with practical environmental decision-making, addressing issues like urban growth prediction and wildlife-vehicle collision mitigation.

Elliot J. CrowleyView profile

Senior Lecturer

• Machine Learning
• Automated Machine Learning
• Low-Resource Deep Learning
• +3 more

Dr Elliot J. Crowley is a Senior Lecturer in Electronics and Electrical Engineering at the University of Edinburgh, serving as Discipline Programme Manager. He co-leads the Bayesian and Neural Systems research group. His research focuses on simplifying machine learning, automated ML, low-resource deep learning, and engineering applications. He holds an MEng in Engineering Science and a DPhil (PhD) from the University of Oxford, with postdoctoral experience at Edinburgh's School of Informatics. He leads the EPSRC New Investigator Award and participates in the dAIEdge Horizon Network. Notable contributions include foundational work in neural architecture search (NAS), probabilistic methods for model efficiency, and applications in computer vision. His courses, such as the Data Analysis and Machine Learning module, emphasize practical Python-based learning for engineering students. Key awards include an EPSRC grant and recognition through distinguished papers at ASPLOS 2021. His team includes current PhD students (Linus Ericsson, Miguel Espinosa) and former advisees (Chenhongyi Yang at Meta, Jack Turner at Qualcomm). Research spans from NAS algorithms to ethical machine learning practices, with a focus on bridging theoretical advances and real-world engineering challenges.

• Children's Literature
• Picturebooks
• Young Adult Literature
• +6 more

Professor Evelyn Arizpe is the Solana Professor of Children's Literature (Culture, Literacies, Inclusion & Pedagogy) at the University of Glasgow's School of Education. She leads the Erasmus Mundus Joint Master's Program in Children's Literature, Media and Culture (IMCLMC). Her career spans over 25 years, beginning with research on Mexican children's literature at the Universidad Iberoamericana (Mexico City) and doctoral work on adolescent readers at the University of Cambridge. She co-pioneered research on children’s responses to picturebooks and visual literacy, notably in the classic Children Reading Picturebooks: Interpreting Visual Texts (2003/2016). Her current research focuses on migration, displacement, and intercultural communities, including projects like Visual Journeys and the Salas de Lectura program in Mexico. She has collaborated internationally, particularly in Latin America, Spain, and the U.S., emphasizing bridges between theory and practice in education and culture. She sits on the jury for the Hans Christian Andersen Award (2022, 2024) and chairs global research networks such as the AHRC-GCRF project on children’s literature in crisis contexts. Education: Bachelor's in Literature, Universidad Iberoamericana (Mexico City) PhD in Education, University of Cambridge Research Interests: Children’s literature and literacies, picturebooks, YA literature, reader-response theory, migration studies, intercultural education, and educational peacebuilding in conflict zones like Medellín and Acapulco. Her work spans critical analysis of visual texts, cultural mediation, and policy advocacy for inclusive education. Grants & Collaborations: British Academy GCRF Grant: Educational Peacebuilding in Medellín and Acapulco AHRC-GCRF Network: Children’s Literature in Critical Contexts of Displacement International partnerships with institutions in Mexico, Colombia, Spain, and Vietnam Labs/Teams: Leads the Glasgow-based Children’s Literature Research Group and collaborates with global networks like the Salas de Lectura initiative in Mexico’s Ministry of Culture.

Inga ProkopenkoView profile

Professor

• Genetic Epidemiology
• Multi-Omics Analysis
• Type 2 Diabetes
• +5 more

Professor Inga Prokopenko is a faculty member at the University of Surrey's School of Biosciences (Faculty of Health and Medical Sciences), specializing in e-One Health and leading the Statistical Multi-Omics group. Her research focuses on genetic epidemiology, multi-omics approaches, and the comorbidity between metabolic disorders like type 2 diabetes and conditions such as cardiovascular disease, cancer, and mental health disorders. She leads studies on genetic determinants of blood glucose regulation, obesity-related risks, and shared pathophysiological pathways between diseases. Key research areas include: Genetic links between type 2 diabetes and cancers (breast, pancreatic, etc.) Mechanisms of GLP-1 receptor signaling in diabetes treatment Causal relationships between depression and diabetes using Mendelian randomization Role of abdominal obesity in cancer susceptibility She supervises PhD/MSc students in biosciences and medicine programs and develops computational tools like comorbidPRS for polygenic risk score analysis. Her work integrates large-scale genomic data from cohorts like the UK Biobank and EPIC studies to uncover shared genetic mechanisms across diseases. Recent work highlights include: Systematic reviews on flavan-3-ols and cardiovascular health Meta-analyses of trans-ethnic diabetes GWAS data Epigenetic studies linking blood metabolites to cancer risk Her research bridges statistical genetics with clinical applications, emphasizing precision medicine strategies for complex diseases.

Alexander MinnaertView profile

Professor

• Inclusive Education
• Special Education
• Motivation and Academic Emotions
• +7 more

Prof. Alexander Minnaert is a Professor in Inclusion and Special Needs Education & Clinical Educational Sciences at the University of Groningen's Faculty of Behavioural and Social Sciences. He leads research on Specific Learning Disorders and educational problems. His work focuses on motivation, social-emotional learning, giftedness, and autism spectrum disorders, aiming to improve inclusive education systems. Minnaert holds a PhD from KU Leuven and has held roles including Director of Research at the Department of Education (2014–2016) and Scientific Advisor to the Academy of Finland (2022–2029). He teaches in Master’s programs like Special Needs Education and coordinates research initiatives such as the 'Learning and Giftedness' workshop at Windesheim Applied University. His research spans three clusters: specific learning disabilities, motivation/emotion/self-regulation, and student/teacher support in inclusive settings. Over 30 PhD students have been supervised, contributing to fields like deafblindness communication, twice-exceptionality, and educational policy. Notable awards include the 2013 Best Teacher Award and Ubbo Emmius Colleghie award (2012). He chairs the Dutch Youth Institute's Youth Intervention Committee and advises on national education reforms. His projects address challenges like autism inclusion, gifted education, and early school leaving.

Claudio De PersisView profile

Professor

• Automatic Control
• Data-driven Control
• Cyber-Physical Systems
• +4 more

Claudio De Persis is a Professor in the Faculty of Science and Engineering at the University of Groningen, Netherlands. He holds a Laurea degree (cum laude) in Electrical Engineering from the University of Rome La Sapienza (1996) and a PhD in Control Systems (2000) from the same institution. His research focuses on automatic control, particularly data-driven control, nonlinear systems, cyber-physical systems, and energy systems. He has held academic positions at the University of Rome La Sapienza (2002–2011), the University of Twente (2009–2011), and currently leads the Groningen Center for Systems and Control within the Engineering and Technology Institute. His expertise includes fault detection in nonlinear systems, resilient control under Denial-of-Service attacks, and distributed control of energy networks. He has authored over 250 publications, including seminal works on quantized control and cyber-physical systems. He serves on editorial boards of journals like Automatica and IEEE Transactions on Automatic Control . De Persis has received two IEEE Outstanding Paper Awards for contributions to control theory. His research integrates control theory with data science, addressing challenges in smart grids and distributed systems. He holds patents for energy system control and collaborates on interdisciplinary projects, such as data center optimization and resilient networked systems. His current research emphasizes data-driven methods for controller synthesis, leveraging convex optimization and system identification to ensure stability and performance. He also explores privacy-preserving distributed control algorithms for power networks and aggregative games.

Ferrante NeriView profile

Professor

• Machine Learning
• Artificial Intelligence
• Optimization
• +5 more

Professor Ferrante Neri is a faculty member at the University of Surrey, holding the positions of Professor of Machine Learning and Artificial Intelligence and Associate Dean (International) for the Faculty of Engineering and Physical Sciences (FEPS). He is affiliated with the Nature Inspired Computing and Engineering Research Group, Surrey Institute for People-Centred AI (PAI), and the Computer Science Research Centre within the School of Computer Science and Electronic Engineering. His research focuses on optimization, explainable AI, and machine learning, with contributions to memetic computing and differential evolution. Since 2010, he has chaired the IEEE Task Force on Memetic Computing. He advises PhD students in topics like dynamic multi-objective optimization and AI-driven applications. His teaching expertise includes mathematical foundations for computer science. He has supervised students such as Aisha E S E Saeid and Pengjin Wu. Notable research areas include evolutionary algorithms, neural architecture search, and applications in robotics and environmental monitoring. Labs and teams include the Nature Inspired Computing group, which explores AI-driven solutions for complex problems. His work bridges theoretical advancements and practical applications in fields like autonomous systems and deep learning.

• Urban Computing
• Spatiotemporal Data Management
• Artificial Intelligence
• +3 more

Associate Professor Ke Deng is affiliated with the School of Computing Technologies at RMIT University. His research focuses on urban computing, spatiotemporal data analysis, and social networks, with expertise in data mining and artificial intelligence. He holds a PhD in Computer Science from The University of Queensland (2007), a Master's in Information and Communication Technology (2001), and a Bachelor's in Electrical Engineering (1994). Previously, he was a postdoctoral researcher at CSIRO ICT Centre and a researcher at Huawei Noah's Ark Lab. His work emphasizes practical applications of AI, such as fairness-aware recommendation systems, traffic scenario modeling, and energy-efficient protocols for IoT. Dr. Deng's career includes roles as an acting lecturer at The University of Queensland and co-supervisor of a PhD student. He has supervised numerous research projects, including advancements in quantum annealing for recommenders, fake news mitigation via reinforcement learning, and smart human sensing using millimeter-wave radar. His research outputs span journals like ACM Transactions on Information Systems and IEEE Transactions on Knowledge and Data Engineering. Education: PhD in Computer Science, The University of Queensland (2007) MSc in Information and Communication Technology (2001) BEng in Electrical Engineering (1994) Key Research Themes: Urban computing and smart cities Mechanisms for fair AI systems Energy-efficient IoT protocols Spatiotemporal data mining Grants and Collaborations: ARC Australian Postdoctoral Fellowship (2010–2012) Research at Huawei Noah's Ark Lab (2013) His recent projects highlight interdisciplinary innovation, such as quantum computing for feature selection and self-supervised networks for traffic scenario clustering. Dr. Deng is actively involved in mentoring PhD/Masters students and contributes to RMIT’s research initiatives in AI and urban informatics.

• Complementary and Alternative Medicine
• Clinical Sciences
• Acupuncture
• +3 more

Dr. Suzi Mansu is a Senior Lecturer in the Department of Health and Biomedical Sciences at RMIT University, located at the Bundoora West campus. Her research focuses on Complementary and Alternative Medicine and Clinical Sciences, with a particular emphasis on acupuncture safety, herbal medicine efficacy, and systematic reviews in dermatology and infectious diseases. She has contributed to studies on birth-related trauma support, acne vulgaris treatments, and respiratory disorder management through traditional Chinese medicine frameworks. Education : No formal educational details provided in the text. Her research interests span acupuncture safety assessments, herbal formulations for skin and infectious conditions, and integrating digital tools into medical education. Recent work includes a 2025 scoping review on midwifery practices for birth-related trauma and a 2018 meta-analysis on acupuncture for acne vulgaris. Dr. Mansu is open to supervising Masters and PhD students in relevant fields. She has collaborated on interdisciplinary projects, including the SOPE educational model for online herbal medicine training.

Kelvin Kam-fai TSOI蔡錦輝View profile

Associate Professor

• Hypertension and Cardiovascular Diseases
• Cognitive Impairment and Dementia
• Digital Health
• +4 more

Prof. Kelvin Kam-fai TSOI is an Associate Professor at the JC School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong (CUHK). He holds courtesy appointments at the Stanley Ho Big Data Decision Analytics Research Centre and The Jockey Club Institute of Ageing. A Visiting Associate Professor at Nanyang Technological University’s Lee Kong Chian School of Medicine and Visiting Professor at Shenzhen Institutes of Advanced Technology, he specializes in Digital Health and Epidemiology. Education: BSc in Statistics and PhD in Public Health from CUHK. Postdoctoral training in Gastroenterology and Hepatology at CUHK’s Department of Medicine and Therapeutics. Served as Director of the CUHK JC Bowel Cancer Education Centre and worked in the Hospital Authority on chronic disease management projects. Research interests focus on digital innovations for chronic disease management, including AI in hypertension, cognitive screening technologies, and wearable health devices. His work combines traditional epidemiology with big data analytics, emphasizing interdisciplinary collaboration between medicine and engineering. Key projects include developing a mobile blood pressure management platform via DeepHealth Limited, a social enterprise he founded in 2019. Current research explores seasonal effects on blood pressure variability and AI applications in healthcare. He co-founded the International Society for Digital Health and organizes global symposiums on digital health innovation. Grants & Awards: Supported by CUHK’s Sustainable Knowledge Transfer Fund (SKPF). Awards include IBM Honorarium Award (2020) and President’s Prize for Best Paper Presentation (2017).

Cristian Román-PalaciosView profile

Assistant Professor

• Phylogenetics
• Biodiversity Drivers
• Paleoclimatic Reconstructions
• +7 more

Cristian Román-Palacios is an Assistant Professor in the Department of Ecology and Evolutionary Biology at the University of Arizona, where he also serves as Coordinator and Advisor for the Master of Science in Data Science (MSDS) and Master of Science in Information Systems (MSIS) programs. He is a core faculty member in Artificial Intelligence and Machine Learning, Data Management, Analysis and Visualization, and Environmental, Health and Biological Sciences. Education: PhD in Ecology and Evolutionary Biology, University of Arizona (2020) BS in Biology, Universidad del Valle, Colombia (2015) His research lies at the intersection of phylogenetics, biodiversity modeling, and machine learning, focusing on large-scale biodiversity patterns, the impacts of climate change on species survival, and the development of statistical tools for paleoclimatic reconstructions. He employs computational and data-intensive methods to explore evolutionary and ecological questions across diverse taxa. His recent publications (2024–2025) demonstrate a strong trend toward interdisciplinary research, combining computational biology, geochemistry, climate science, and open-source software development. Key themes include biodiversity informatics (e.g., Animal Culture Database), paleoclimatic modeling (e.g., clumped isotope thermometry), reproducibility in science, and tools for collaborative research (e.g., LabOps, SSARP). His work increasingly integrates data science with biological and environmental applications. Scientific Contributions: Published over 25 peer-reviewed papers, many as first author Research featured in Science News, Popular Science, CNN, USA Today Developed open-source tools: phruta , treedata.table , SSARP , LabOps Cristian advises graduate students through the infosci-msadvise@arizona.edu email and Calendly appointments. He was previously a staff researcher at UCLA’s Tripati Lab. He leads initiatives such as the Southwest Center on Resilience for Climate Change and Health and promotes inclusive, collaborative science through online toolkits and leadership ecosystems aimed at addressing climate and social inequities. His lab, the Román-Palacios Lab, and involvement with the Data Diversity Lab reflect his commitment to open, reproducible, and equitable research practices in data-intensive biology.

Frank Van OverwalleView profile

Professor

• Social Neuroscience
• Cerebellum Research
• Social Cognition
• +3 more

Frank Van Overwalle is a Professor of Psychology at Brussels University, affiliated with the Consultation Center Brain, Body and Cognition. His research focuses on Social Connectionism and Social Neuroscience, particularly the neural mechanisms underlying social cognition, mentalizing, and cerebellar contributions to social and cognitive processes. He has led over 40 research projects and published 214 peer-reviewed articles, including works on cerebellar sequencing, mentalizing, and neuroimaging techniques. His research highlights the cerebellum's role in social action prediction, implicit learning, and emotional processing. Notable projects include investigations into cerebellar tDCS effects on social cognition and collaborations on the neural basis of group stereotypes and Theory of Mind. Van Overwalle received the Tobie Jonckheere Award in 1989 for his doctoral work on educational psychology. He has participated in numerous conferences and serves on the boards of the Cognitive Neuroscience Society and Organization for Human Brain Mapping. His work bridges cognitive models with empirical neuroimaging data, emphasizing cerebellar contributions to higher-order social functions.