Find Academic Supervisors

Karen DowView profile

Associate Professor

• River Ice Engineering
• Hydraulics
• Fluid Mechanics
• +3 more

Dr. Karen Dow is an Associate Professor in the Department of Civil Engineering and Associate Dean (Undergraduate Programs) at the University of Manitoba's Price Faculty of Engineering. Her research focuses on river ice engineering and hydraulics, combining field monitoring, experimental investigations, and numerical modelling. She holds a Ph.D. (2009) and M.Sc. (2003) in Water Resources Engineering from the University of Alberta, and a B.Sc. (2001) in Civil Engineering from the University of Manitoba. Research Interests : River ice processes and hydraulics Experimental fluid mechanics Computational hydraulics Particle image velocimetry (PIV) Research Trends : Her publications emphasize understanding ice jam dynamics, turbulent flow behavior beneath ice covers, and numerical/experimental methods in hydraulics. Projects often involve fieldwork in Northern Manitoba and advanced PIV systems. Advising & Research Opportunities : She mentors students in hydraulics with a focus on theoretical fluid mechanics and teamwork. Current projects include ice jam database development and flow modeling under simulated ice conditions. Labs/Teams : Part of a collaborative research group in civil engineering, emphasizing experimental and computational hydraulics.

Gregory MatthewsView profile

Associate Professor

• Statistical Disclosure Control
• Missing Data Methods
• Statistical Genetics
• +3 more

Gregory Matthews is an Associate Professor in the Department of Mathematics and Statistics at Loyola University Chicago (LUC), serving as Director of the Center for Data Science and Consulting. He holds a Ph.D. in Statistics from the University of Connecticut (2011), with prior industry experience in predictive modeling (2004–2006) and postdoctoral research at the University of Massachusetts-Amherst (2011–2014). His research focuses on statistical disclosure control, missing data methodologies, statistical genetics, and sports analytics, with applications in anthropology, healthcare, and sports performance analysis. Dr. Matthews’ academic background includes a B.S. in Actuarial Science and M.S. in Applied Statistics from Worcester Polytechnic Institute. His work bridges theoretical statistics with practical applications, including developing imputation methods for aging curves in baseball, analyzing sports performance metrics, and addressing privacy challenges in data dissemination. He has contributed to open-source tools like the 'MixMAP' R package for genetic association studies and 'teamcolors' for sports data visualization. His publications span diverse topics such as dental morphology analysis in primates, predictive modeling for medical diagnostics, and methodological advancements in statistical disclosure limitation. He actively engages in interdisciplinary collaborations, particularly in paleontology, healthcare policy, and sports science. Dr. Matthews’ consulting work emphasizes ethical data practices, including privacy-preserving techniques for biomedical and social datasets. He has advised on projects ranging from emergency department protocols to optimizing NFL defensive strategies. His educational contributions include designing curricula for sports analytics and statistical methodologies.

Giusy LavecchiaView profile

Professor

• Structural Geology
• Tectonics
• Geodynamics
• +6 more

Giusy Lavecchia is a Full Professor in Structural Geology at Ud'A University, Chieti Scalo, Italy. She holds a Laurea cum laude in Geological Sciences from the University of Naples (1977) and has held multiple academic and administrative roles, including Head of the Laboratory of Geodynamics and Seismogenesis (1997–2011) and Vice-head of the Department of Psychology, Health and Territory (2014–2017). Her research focuses on structural geology, tectonics, seismotectonics, and magmatism, with a strong emphasis on 3D fault modeling and seismic hazard analysis. She has authored ~100 peer-reviewed papers, with an h-index of 21 and 1,800+ citations (SCOPUS, 2017). Notable contributions include pioneering studies on the Apennines' structural style and seismotectonic zoning. Her work integrates field geology, seismic data, and GIS tools to understand active deformation processes. Awards include a CNR scholarship (1978) and a NATO grant (1984). Her recent projects include synthesizing Quaternary fault data into 3D models for hazard assessments and exploring triggered seismicity mechanisms. She has supervised numerous graduate students and contributed to national seismic risk committees.

Gabriella R. SterneView profile

Assistant Professor

• Neuroscience
• Molecular Biology
• Genetics
• +3 more

Gabriella R. Sterne, Ph.D., is an Assistant Professor in the Department of Biomedical Genetics and the Department of Neuroscience at the University of Rochester School of Medicine and Dentistry (SMD). She holds joint appointments in both departments and leads the Sterne Lab, focused on understanding neural circuit mechanisms underlying feeding behaviors. Dr. Sterne earned her Ph.D. in Neuroscience from the University of Michigan (2016) and a B.A. in Biology from Whitman College (2010). Her research integrates experimental and computational approaches to study how neural circuits coordinate feeding motor programs, time feeding intervals, and store feeding-related memories using Drosophila as a model system. Key research themes include: Feeding Motor Sequences : How circuits orchestrate rhythmic motor actions like proboscis extension. Feeding Microstructure : Neural coding strategies for timing feeding rhythms across timescales. Feeding Memories : Circuit mechanisms linking taste experiences to long-term behavioral adaptations. Her lab collaborates extensively with neuroimaging and computational teams, contributing to projects like the Drosophila connectome mapping. Recent work includes computational brain models and neuroendocrine pathway discoveries influencing feeding behavior. Lab Members include postdoctoral scholars, graduate students (e.g., Gladys Leitch studying hunger modulation), and undergraduates involved in neuroanatomy visualization and synaptic quantification projects. The lab is affiliated with the Biomedical Genetics and Genomics, Neurobiology & Anatomy, and Neuroscience Ph.D. programs. Lab location: KMRB 2-9639, 601 Elmwood Ave, Rochester, NY 14642.

Sebastian PritzView profile

Researcher

• Database Systems
• Information Technology
• Data Management
• +3 more

Sebastian Pritz is a Researcher at the FH JOANNEUM University of Applied Sciences, affiliated with the Research Center Hagenberg, AIST Center of Excellence, TIMed Center, and Digital Media Lab. His focal area is ICT (Information & Communications Technology). He holds an M.Sc. and focuses on interdisciplinary research in database systems and environmental applications. Research interests include NewSQL/NoSQL database performance, time series data management, and vegetation analysis. He has published in conferences like ICECCME and contributed to projects like HCAI (Human-Centered AI) and CRISAM® Loop (AI-based risk management). He participated in the ICECCME 2023 conference and actively collaborates with interdisciplinary teams. His work bridges technical database solutions with ecological monitoring, reflecting a dual focus on ICT innovation and environmental science.

Meiqi NiuView profile

Researcher

• Neuroscience
• Cognitive Neuroscience
• Neuroimaging
• +3 more

Dr. Meiqi Niu is a Researcher at the Institute of Neuroscience and Medicine (INM-1) , Research Center Jülich GmbH, specializing in neuroimaging and brain architecture. Her work focuses on mapping cortical structures and receptor distributions in macaque and human brains, with applications in comparative neuroscience, bilingualism effects, and neurodegenerative disorders. She contributes to creating population-based brain atlases (e.g., MEBRAINS 1.0) and advancing neuroimaging techniques like 3D Polarized Light Imaging (PLI). Expertise: Brain mapping, receptor distribution analysis, computational neuroanatomy Techniques: 3D neuroimaging, machine learning, diffusion tensor imaging (DTI) Key Projects: Macaque brain atlases, somatosensory cortex organization, bilingualism impact studies Her research integrates cytoarchitectonic, receptor, and functional connectivity data to understand brain structure-function relationships. Recent work explores how neurotransmitter receptor gradients influence neural processing and how early language acquisition shapes brain networks. Labs/Teams: Active contributor to the Structural and Functional Organization of the Brain group (INM-1), collaborating on multimodal brain mapping initiatives.

Ulrike HammerbeckView profile

Research Fellow

• Stroke Rehabilitation
• Neurological Recovery
• Motor Learning
• +3 more

Ulrike Hammerbeck is an Honorary Research Fellow in the Division of Cardiovascular Sciences, focusing on recovery mechanisms after neurological insults, particularly stroke. Her research examines motor control, cortico-spinal connectivity, and rehabilitation strategies. She holds a PhD in Clinical Neuroscience from University College London (2015) and has conducted post-doctoral work funded by the Stroke Association. Key collaborations include institutions like the University of Manchester and University of Salford. Notable awards include the 2017 NeuroRehabilitation and Neural Repair Best Poster Prize (2nd place). Her work aligns with UN SDG goals for health and education. Education: PhD in Clinical Neuroscience, University College London (2015) MSc in Advanced Physiotherapy, University College London (2008) BPhysT in Physiotherapy, University of Pretoria (1995) Research Interests: Stroke rehabilitation, motor learning, brain stimulation, cortico-spinal connectivity, and movement kinematics. Her studies explore how training protocols influence recovery trajectories post-stroke and neuroimaging techniques for outcome prediction. Grants & Projects: Principal Investigator: "Can Early, High Repetition Arm Training Encourage New Connections from the Unaffected Hemisphere Post-Stroke?" (2015–2018) Labs/Teams: Active in interdisciplinary groups focused on stroke recovery and neuroimaging applications.

Robert RossView profile

Professor

• Exercise Physiology
• Cardiometabolic Health
• Obesity Management
• +3 more

Robert Ross, PhD, is a Professor in the Department of Kinesiology and Health Studies at Queen's University, cross-appointed to the School of Medicine and Department of Endocrinology and Metabolism. His research focuses on lifestyle interventions for obesity and cardiometabolic diseases, with a particular emphasis on exercise physiology and clinical outcomes. Ross holds a PhD from the University of Montreal and has authored over 200 peer-reviewed publications. His educational background includes: PhD in Exercise Physiology (University of Montreal) MSc in Exercise Physiology (University of Montreal) BEd in Physical Education (McGill University) Research priorities include randomized controlled trials evaluating exercise-based interventions for abdominal obesity, metabolic syndrome, and cardiovascular risk reduction. His laboratory operates within a 5000 sq ft facility equipped with MRI/CT imaging workstations, metabolic testing suites, and aerobic exercise equipment. Current funding includes a grant from the Canadian Institutes of Health Research (CIHR). Key research themes involve: Obesity pathophysiology and treatment Cardiometabolic risk biomarkers Physical activity guidelines development Exercise response variability Non-invasive body composition analysis Laboratory facilities include dedicated clinical spaces for hyperinsulinemic-euglycemic clamps, glucose tolerance testing, and DEXA scanning. Ross collaborates with Kingston General Hospital for advanced imaging access. His work emphasizes translating evidence-based interventions into clinical practice and public health policy.

Ira AssentView profile

Professor

• Machine Learning
• Data Mining
• Clustering Algorithms
• +5 more

Professor Ira Assent is affiliated with the Department of Computer Science at Aarhus University. Their research focuses on machine learning, data mining, and visualization, with applications in climate science, medical informatics, and computer vision. Professor Assent leads projects such as Light-IoT (analytics on compressed IoT data), WallViz (interactive visualization for massive datasets), and eData (anomaly detection in e-science). Their work emphasizes scalable algorithms, explainable AI, and interdisciplinary applications. Recent publications address rainfall prediction using deep learning, entity summarization via knowledge graphs, and efficient clustering techniques. Projects like RainAI demonstrate contributions to weather modeling and satellite data analysis. Collaborative efforts span academic and industrial domains, with a strong emphasis on practical, user-centric solutions. Selected research contributions include advancements in density-based clustering (e.g., AnyDBC, DISCO), parallel algorithms optimized for GPUs (HUNIPU), and visualization frameworks (AVID). Their work bridges theoretical computer science with real-world challenges, such as improving decision-making through interactive visualizations and enhancing medical information retrieval systems. Ongoing projects aim to address computational efficiency in large-scale data analytics while maintaining interpretability. Key areas of innovation include explainable AI (e.g., InteDisUX), climate modeling (DROPP), and hardware-accelerated algorithms (GPU-FAST-PROCLUS). These efforts reflect a commitment to advancing both foundational methods and applied technologies that impact diverse fields from environmental science to healthcare.

• Remote Sensing
• Earth Observation
• Biomass Burning
• +3 more

Dr. Tianran Zhang is a Researcher at King’s College London’s Department of Geography, part of the School of Global Affairs. She holds a PhD (2017) and MSc (2013) from King’s, and a BSc (completed in 3 years) from Ocean University of China. Her work focuses on advancing satellite-based fire monitoring, air quality analysis, and Earth observation techniques. Key projects include developing the Global Fire Assimilation System (GFAS) for Copernicus Atmosphere Monitoring Service (CAMS), and analyzing agricultural burning emissions in China. Education BSc in Environmental Science, Ocean University of China (2010-2013, 3-year program) MSc in Environmental Science, Ocean University of China (2013) PhD in Geography, King’s College London (2013-2017, supported by King’s China Award) Research Interests Remote sensing and Earth observation applications for fire detection Agricultural residue burning emissions and their atmospheric impacts Geostationary and polar-orbiting satellite data integration Deep learning for environmental data analysis Recent Work Highlights Recent studies include analyzing Australia’s 2019/20 Black Summer fires and improving CAMS fire emissions modeling through multi-sensor data fusion. Her work bridges satellite technology and environmental policy, with a focus on high-temporal resolution fire monitoring. Awards King’s China Award (PhD thesis support) Best Poster Prize at SOLAS Conference (2013) for aerosol iron solubility research Labs/Groups Active member of the Earth Observation and Environmental Sensing (EOES) Hub at King’s, focusing on interdisciplinary environmental sensing and societal impact studies.

• Critical Data Studies
• Digital Methods
• Digital Infrastructure
• +4 more

Dr. Jonathan W. Y. Gray is Reader in Critical Infrastructure Studies at the Department of Digital Humanities, King's College London. He also serves as Director of the Centre for Digital Culture and maintains research affiliations with the Digital Methods Initiative at the University of Amsterdam and the médialab at Sciences Po, Paris. Gray's research explores how digital data, methods, and infrastructures shape collective life. His work spans critical data studies, digital methods development, environmental data research, and critical technical practice. Key projects include forestscapes (examining forest-society relations through soundscapes), research on East and Southeast Asian communities in the UK, and investigations into data infrastructures for social justice. His recent publications reveal consistent thematic threads: the politics of data infrastructures, environmental data practices, and critical approaches to digital methods. The forthcoming book 'Public Data Cultures' (2025) and his co-edited works on data journalism demonstrate his commitment to making data practices more transparent and accountable. Gray has received recognition for collaborative research through the Public Data Lab, which he co-founded in 2017 as a distributed network for collective inquiry. His work bridges academic research with public engagement through projects like the forestscapes listening lab and collaborations with organizations including Amnesty International. As an educator, Gray focuses on critical and creative engagements with digital data, methods, and infrastructures. His approach emphasizes engaged, research-led teaching that brings together researchers, students, and external organizations as co-inquirers in addressing complex societal challenges.

• Health Informatics
• Distributed Decision Support
• Medical Imaging Analytics
• +3 more

Teresa Wu is a Professor and Associate Dean of Global Engagement at the Fulton Schools of Engineering, Arizona State University (ASU). She holds a joint appointment as a Professor in the School of Computing and Augmented Intelligence and serves as a Health Solutions Ambassador in the College of Health Solutions. Her expertise spans Health Informatics, Distributed Decision Support, and Medical Imaging Analytics. Wu earned her Ph.D. in Industrial Engineering from the University of Iowa and holds M.S. and B.S. degrees in Mechanical Engineering from Beihang University, China. Wu’s research focuses on medical imaging analytics, distributed decision systems, and information systems applications. She leads the ASU-Mayo Center for Innovative Imaging and has pioneered work in MRI-based kidney pathology tracking and headache classification using AI. Her awards include the NSF CAREER Award (2003) and recognition as an ASU Tenure and Promotion Exemplar (2006). Her grants include leadership roles in projects such as the $10M NIH-funded study on post-traumatic headache mechanisms and the NSF-funded CYDRES initiative securing smart buildings. She has advised numerous interdisciplinary collaborations, including work on sleep disorder monitoring and grid-interactive building cybersecurity. Education: Ph.D. Industrial Engineering (University of Iowa), M.S. & B.S. Mechanical Engineering (Beihang University). Awards: NSF CAREER Award, ASU Tenure Exemplar. Labs/Teams: ASU-Mayo Center for Innovative Imaging, CYDRES (Building Cyber Defense).

• Multimedia Quality of Experience
• Machine Learning
• Immersive Media
• +3 more

Dr. Helard Becerra is an Assistant Professor in the School of Computer Science at University College Dublin (UCD). He holds a PhD from the University of Brasília and has held postdoctoral roles at UCD's Insight Centre for Data Analytics and Samsung R&D Institute Brazil. His research focuses on multimedia quality assessment (audio/video/speech) and AI-driven healthcare solutions for stroke rehabilitation. Key contributions include developing NAViDAd (a deep learning-based quality metric) and predictive models for stroke recovery outcomes. Education: B.Sc. (UNSAAC, Peru, 2010); M.Sc. & Ph.D. (UnB, Brazil, 2013/2019). Professional experience includes roles at Samsung (2019), DIT (2017-2018), and leadership in EU projects like Precise4Q (Horizon 2020). Research interests span: 1) Perceived quality in multimedia systems, 2) Explainable AI for healthcare, 3) Predictive modeling in stroke rehabilitation. Notable work includes gradient boosting models for social risk prediction and Elo rating systems for personalized therapy. Teaching responsibilities include coordinating modules on Software Engineering, Parallel Computing, and Programming. He actively supervises graduate students and serves on UCD's Equality, Diversity & Inclusion Committee. Awards include the 2019 Best Student Paper Award at International Symposium on Electronic Imaging. He reviews for top conferences (ACM MMSys, IEEE ICIP) and journals (IEEE Access, IEEE Signal Processing Letters).

• Hearing Loss and Rehabilitation
• Stigma Associated with Hearing Loss
• Cochlear Implantation
• +5 more

Janet S. Choi, MD, MPH is a board-certified otolaryngology-head and neck surgeon and fellowship-trained otologist/neurotologist at Keck Medicine of USC. She serves as Assistant Professor of Clinical Otolaryngology-Head and Neck Surgery at the University of Southern California's Keck School of Medicine, specializing in ear-related disorders including chronic ear disease, cholesteatoma, cochlear implantation, perforated tympanic membrane, otosclerosis, vestibular disorders, and lateral skull base tumors such as acoustic neuromas/vestibular schwannomas and meningiomas. Dr. Choi earned her undergraduate degree with honors from University of California San Diego, medical degree from Johns Hopkins School of Medicine, completed her residency in Otolaryngology-Head and Neck Surgery at University of Southern California, and fellowship in otology, neurotology, and lateral skull base surgery at University of Minnesota. She is board-certified and fellowship-trained in her specialty. Her research centers on addressing stigma associated with hearing loss and hearing device use, improving utilization of hearing healthcare, and developing technology-based strategies to make medical and surgical hearing care accessible. Her work includes population-based studies examining hearing loss impact on health outcomes and AI-driven solutions for hearing care access. With over 50 peer-reviewed publications and regular invitations to national and international conferences, her scholarly impact is significant. Analysis of Dr. Choi's recent publications reveals a strong focus on hearing healthcare accessibility, with particular attention to demographic disparities, innovative delivery models like telemedicine, and the development of AI applications in audiology. Her research spans clinical otology, public health perspectives on hearing loss, and technological innovations in hearing care. Dr. Choi's unique perspective as both a physician and hearing aid user (experiencing left-sided conductive hearing loss since childhood) informs her compassionate, patient-centered approach. She is fluent in English and Korean and maintains clinical practices in multiple locations including Los Angeles, Beverly Hills, and Glendale.

• Migration Technologies
• Border Surveillance
• Human Rights Law
• +3 more

Petra Molnar is a lawyer and anthropologist at York University's Osgoode Hall Law School , serving as Associate Director of the Refugee Law Lab . She directs the global Migration and Technology Monitor project and holds a Faculty Associate position at Harvard's Berkman Klein Center. Her work bridges law, technology, and human rights, focusing on migration governance. As a Governor General's Literary Award finalist , she authored The Walls Have Eyes , analyzing AI's impact on border crossings across Mexico, Greece, and Palestine. Her current research explores community resistance to border technologies. Her key research areas include: Migration technologies and digital surveillance AI ethics in immigration enforcement Carceral technology critique Human rights impacts at borders Surveillance capitalism in asylum processes Techno-political collaboration with the US Her scientific engagement spans 15 recent publications analyzing: AI surveillance trends (2023-2025) Digital border walls and ecological impacts Crypto-rewarded border vigilantism (ICERAID) Biometric data in criminal databases UN human rights frameworks for tech governance Generative AI's role in migration control She has advocated for: Transparency in migration technology Centering lived experiences of migrants Accountability mechanisms for AI systems Decolonizing border tech discourse