Find Academic Supervisors

Jonathan M. ReynoldsView profile

Professor

• Japanese Art
• Japanese Architecture
• Modern Japanese Architecture
• +1 more

Jonathan M. Reynolds is a Professor at Barnard College, affiliated with Columbia University's Department of East Asian Languages & Cultures. His research focuses on Japanese art and architecture, particularly modern Japanese architecture and photography. Education: PhD in Art History from Stanford University (1991) Research Interests: Reynolds explores the intersection of Japanese cultural identity, architecture, and photography from the 1940s to 1990s. His work examines modernist architectural movements and the pedagogical frameworks shaping contemporary architectural practice in Japan. Publications: His notable works include a monograph on tradition in Japanese visual culture and studies on Maekawa Kunio's contributions to modernist architecture. Recent publications trend toward interdisciplinary analyses of art, architecture, and photography's role in national identity formation.

Gareth BealeView profile

Lecturer

• Digital Archaeology
• Immersive Media
• Heritage Technology
• +3 more

Dr. Gareth Beale is a Lecturer in Digital Archaeology at the University of Glasgow's Archaeology department. His research focuses on the creative and critical use of technology in archaeology, particularly in immersive media and community-driven digital heritage projects. He co-directs the DiNAR project, which explores immersive experiences for heritage, including the award-winning VikingVR exhibition. He also leads the Discovering England's Burial Spaces initiative, developing tools for community-led burial site documentation. His work bridges archaeology with digital industries, emphasizing knowledge transfer and collaboration across academic, commercial, and third-sector partners. Key projects include the Basing House archaeological excavation (since 2012) and international fieldwork in Italy, Romania, and Hungary. Awards include the York Culture Award for Excellence in the Media Arts for VikingVR. His teaching and research span digital heritage, historical archaeology, and immersive technologies. Collaborations include the University of York’s Department of Theatre, Film and Television, and the Archaeology Data Service. Research Themes: Digital Archaeology, Immersive Media, Heritage Technology, Community Archaeology Collaborations: DiNAR Project, Basing House Project, Portus Project (Italy) Publications highlight innovative uses of digital tools in heritage preservation, such as RTI imaging for Norse runes and VR museum experiences. Current supervision includes projects on textile economies, digital memory theaters, and Gaelic language revitalization through heritage media.

Tricia SkolerView profile

Professor

• Developmental Psychology
• Neuroscience
• Infancy
• +6 more

Tricia Skoler is a Professor of Developmental Psychology at the School of Arts and Sciences, Hunter College (CUNY). Her research focuses on developmental trajectories, neuroscience, autism, and infant social cognition. She holds a PhD from Emory University and leads a lab emphasizing interdisciplinary approaches, requiring prospective students to read Doing Developmental Research (Guilford Press). She is currently accepting students for Spring 2025 courses (201 and 395). Her work spans neuroscience, architectural design, biophilia, and health psychology, integrating methodologies like EEG and statistical physics to study gaze processing, joint attention, and social-cognitive development in infants and children with ASD. Key contributions include understanding neural correlates of eye gaze in early infancy and contextual influences on social skills. Publications highlight themes such as gaze-following deficits in autism, the role of social cues in learning, and developmental neuroscience. Her research bridges basic science and applied contexts, including biophilic design and nutrition education. Lab inquiries must follow guidelines in Chapter 1 of her book. No explicit awards are listed, but her extensive publication record reflects recognition in developmental and cognitive neuroscience.

Oliver KennedyView profile

Associate Professor

• Databases
• Programming Languages
• Data Science
• +2 more

Dr. Oliver Kennedy is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo's School of Engineering and Applied Sciences. He serves as Co-Director of Graduate Studies and leads the Online Data Interactions (ODIn) Lab. His research focuses on databases, programming languages, and user interfaces for data science, with particular emphasis on scalable compilers and managing uncertainty in data. Kennedy holds a PhD in Computer Science from Cornell University (2011), MS from Cornell (2008), and dual BS degrees in Computer Science and Computer Engineering from NYU and Stevens Institute of Technology (2005). His work bridges theoretical computer science with practical data management challenges. His recent publications demonstrate a strong focus on improving database query processing, uncertainty management in data systems, and developing practical tools for data integration and exploration. Awarded the NSF CAREER Award in 2018, Kennedy's research has significant implications for efficient data processing in scientific and commercial applications.

Ramana VinjamuriView profile

Associate Professor

• Brain-Machine Interfaces
• Neuroprosthetics and Exoskeletons
• Machine Learning
• +4 more

Ramana Vinjamuri is an Associate Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC). He holds a secondary appointment as Visiting Professor at the Indian Institute of Technology, Hyderabad, India. His academic journey includes a Ph.D. in Electrical Engineering from the University of Pittsburgh (2008), M.S. in Bioinstrumentation from Villanova University (2004), and B.Tech. in Electrical and Electronics Engineering from Kakatiya University (2002). Dr. Vinjamuri's research focuses on Brain-Machine Interfaces (BMIs) for upper-limb prostheses control , neuroprosthetics and exoskeletons , machine learning in motor control , and neurophysiological signal processing . His work extends synergy-based models to control 37-dimensional hand movements, addresses human-robot interaction through emotionally intelligent systems, and develops neurotechnologies for substance use disorder using wearable sensors and AI. NSF CAREER Award (2019) NSF IUCRC BRAIN Center Planning Grant (2020) Harvey N Davis Distinguished Teaching Assistant Professor Award (2018) His publications demonstrate expertise in EEG and EMG signal analysis , deep learning for motor decoding , synergy modeling , and humanoid robot control . The Vinjamuri Lab at UMBC involves graduate, undergraduate, and high school researchers, with international collaborations in India and the US.

Vagelis PapalexakisView profile

Associate Professor

• Data Science
• Machine Learning
• Artificial Intelligence
• +3 more

Dr. Vagelis Papalexakis is an Associate Professor and Ross Family Chair in the Computer Science & Engineering Department at the University of California, Riverside. His research focuses on data science, machine learning, and tensor methods, with applications in multi-aspect/multi-modal data analysis. He holds a Ph.D. from Carnegie Mellon University and a Diploma/M.Sc. from the Technical University of Crete. Affiliations: Ross Family Chair, Bourns College of Engineering, UCR Education: Ph.D. in Computer Science, Carnegie Mellon University M.Sc./Diploma in Electronic & Computer Engineering, Technical University of Crete His work emphasizes interpretable insights from complex datasets, including tensor-based defenses against adversarial attacks, graph representation learning, and scalable algorithms for high-dimensional data. Notable awards include the NSF CAREER Award (2021), IEEE DSAA Next Generation Award (2021), and ICDM Tao Li Award (2022). Grants include NSF funding for railway safety (CISE MSI: RPEP CPS), USDOT transportation research, and NVIDIA GPU grants. He leads projects in AI ethics, misinformation detection, and gravitational wave analysis. His lab collaborates with industry (e.g., Cisco, Instacart) and national labs (e.g., Lawrence Livermore).

Lesia SemenovaView profile

Assistant Professor

• Machine Learning
• Responsible and Trustworthy AI
• Interpretability
• +4 more

Lesia Semenova is an incoming Assistant Professor in the Department of Computer Science at Rutgers University, set to join in Fall 2025. She currently serves as a postdoctoral researcher at Microsoft Research, NYC. Her research focuses on machine learning, responsible AI, interpretability, and healthcare applications. She holds a PhD from Duke University's Computer Science Department and prior degrees from Taras Shevchenko National University of Kyiv. Education Background: Ph.D., Computer Science, Duke University M.S. and B.S., Applied Mathematics, Taras Shevchenko National University of Kyiv Research Interests: Machine Learning Interpretability Responsible AI Frameworks Healthcare Applications of AI Reinforcement Learning Human-Centered Design Selected Awards and Recognition: 2024 Rising Stars in Computational and Data Sciences PhD Dissertation Award from Duke University Advising and Professional Activities: Semenova advises students such as Harry Chen and Dennis Tang. She has organized workshops at NeurIPS and presented at conferences like the International Joint Conference CFE-CMStatistics. Her work bridges theoretical machine learning with practical healthcare and policy applications. Professional Engagement: She is affiliated with the Artificial Intelligence and Machine Learning research groups at Rutgers, and has collaborated with institutions like the Johns Hopkins Applied Physics Lab.

Simon MasnouView profile

Professor

• Applied Mathematics
• Image Processing
• Shape Optimization
• +5 more

Simon Masnou is a Full Professor at Université Claude Bernard Lyon 1, affiliated with the Institut Camille Jordan (CNRS UMR 5208). He holds leadership roles as Head of the 'Applied Mathematics, Statistics' Master's degree and Head of the 'M2 Maths in Action' program. Previously, he served as Director of the Camille Jordan Institute (2018-2022). His research focuses on applied mathematics, image processing, shape optimization, and geometric measure theory, with contributions to variational models, geometric flows, and applications in computer vision and materials science. Education: PhD in Mathematics (1998, Paris Dauphine) and HDR (2008, Paris 6). Research projects include ANR STOIQUES (2024-2028), PEPR PDE-AI (2023-2028), and collaborations with industry on topics like defect prediction in aluminum production and high-dimensional data analysis. Teaching includes courses on linear algebra, optimization, and machine learning at undergraduate and graduate levels. Key contributions span phase field models, varifold-based surface approximation, and image inpainting. He supervises PhD students in geometric variational problems and computational methods. His work bridges theoretical mathematics with industrial challenges, addressing issues in materials science, medical imaging, and cultural heritage preservation.

Leah MeisterlinView profile

Adjunct Associate Professor

• Urban Planning
• Geospatial Analysis
• Spatial Justice
• +3 more

Leah Meisterlin is an Adjunct Associate Professor at The Cooper Union's Irwin S. Chanin School of Architecture, specializing in geospatial methodologies and urban history. Her work bridges cartography, spatial justice, and urban planning, with notable projects like Mapping Historical New York and Envisioning Seneca Village . She has held academic roles at Columbia University, Barnard College, and New York University, alongside research positions at the Temple Hoyne Buell Center and NYU's Center for Latino Adolescent and Family Health. Her research focuses on urban spatial analysis, historical GIS, and the intersection of technology with urban equity. Recent publications address 19th-century urban density patterns, spatial justice in zoning, and critical cartography. She leads Meisterlin Projects, a geospatial consultancy, and has contributed to exhibitions at MoMA and the Oslo Architecture Triennial. Teaching spans GIS, urban planning, and spatial justice, with courses at Columbia, Barnard, and Cooper Union. Her work emphasizes interdisciplinary methods, blending geography, architecture, and critical theory to address urban challenges.

Juliane HausView profile

Research Fellow

• Mobility
• Traffic
• Social Science Research Methods
• +4 more

Dr. Juliane Haus is a Research Fellow at WZB Berlin Social Science Center, affiliated with the Research Group Digital Mobility and Social Differentiation. Her work focuses on mobility transitions, social science research methods, ethnomethodology, and video analysis. She holds a PhD in Sociology from TU Berlin (2019). Her research integrates transdisciplinary approaches, emphasizing experimental design, policy evaluation, and visualization in urban mobility contexts. Key projects include BeNaMo (synthesizing sustainable urban mobility research), WiSEV (enhancing municipal traffic transition projects), and 'Verkehrswende erleben' (visualizing car-free urban spaces). Publications span edited handbooks, peer-reviewed articles on mobility policy nexus, and ethnographic studies of economic laboratories. Her work bridges theory and practice, addressing interdisciplinary collaboration between academia, policy, and industry. Awards: None explicitly listed. Advising: No students listed. Grants: Multiple BMBF-funded projects. Labs/Teams: Active in WZB research groups and external collaborations.

Kieran O'HalloranView profile

Associate Professor

• Critical Thinking
• Posthumanism
• Digital Humanities
• +4 more

Dr. Kieran O'Halloran is a Reader in Applied Linguistics at King's College London, based in the School of Education, Communication & Society within the Faculty of Social Science & Public Policy. He holds a BA from the University of Cambridge and a PhD in Applied Linguistics from University College London. His research focuses on critical thinking, posthumanism, and digital pedagogy, integrating corpus linguistics and posthumanist theory. Key interests include creative teaching methods, digital text analysis, and the intersection of technology with education. He teaches modules such as 'Critical Posthumanism, Digital Data' and 'Film, Poetry, Style' in the BA English Language and Linguistics program. O'Halloran's work emphasizes innovative approaches to literary interpretation using AI and digital tools, as seen in his recent articles on AI-driven creative analysis and posthumanist stylistics. He leads initiatives like the King’s Festival of Artificial Intelligence, exploring AI's role in education and creativity. His research is affiliated with the Research Centre for Language, Discourse & Communication, focusing on descriptive linguistics and applied linguistic practices. Publications include books like Posthumanism and Deconstructing Arguments (2017) and Posthumanism and Corpus Linguistics (2022), alongside peer-reviewed articles in Language and Literature and Discourse, Context & Media . His pedagogical contributions highlight digital literacy and creative problem-solving in higher education.

• Computer Science
• Data Visualization
• Scientific Visualization
• +3 more

Robert S. Laramee is a Professor at the University of Nottingham (previously at Swansea University), specializing in visualization research. His work focuses on data visualization, scientific visualization, and computational fluid dynamics. He has authored over 170 publications in top journals like IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum, and IEEE Computer Graphics and Applications. Research Interests: His research spans information visualization, flow visualization, visual literacy, and educational aspects of visualization. He emphasizes practical applications in fields like healthcare, digital humanities, and computational science. Recent Trends: Recent work includes studies on treemap literacy, educational frameworks for visualization, and interactive systems for clinical data. He has also contributed to visualization resources and surveys, aiming to bridge academic and industry needs. Grants & Collaborations: Collaborations include projects on visualization for smart cities, protein-lipid interactions, and quantum chromodynamics data analysis. No specific grant details are provided in the text. Labs & Teams: Affiliated with visualization research groups at Nottingham and Swansea, though specific lab names are not mentioned.

• Biomechanics
• Gerontology
• Chronic Obstructive Pulmonary Disease (COPD)
• +5 more

Dr. Jenna Yentes is an Associate Professor in the Department of Kinesiology and Sport Management at Texas A&M University, affiliated with the College of Education and Human Development. Her research focuses on functional resiliency in aging populations, biomechanics of chronic obstructive pulmonary disease (COPD), and nonlinear analysis of human movement. She leads studies on gait stability, respiratory-gait coupling, and exoskeleton-assisted walking. Notable contributions include quantifying locomotor reserve and exploring firefighter performance in protective gear. Education: Ph.D. in Biomechanics (University of Nebraska, 2013), M.S. in Kinesiology (California State University Fullerton, 2006), B.A. in Kinesiology (University of Northern Colorado, 2000). Research Interests: Reserve capacity in older adults' mobility and cognition Biomechanical adaptations in COPD patients Methodological rigor in nonlinear data analysis (e.g., entropy metrics) Firefighter physical performance under protective gear Recent Articles Trends: Focus on entropy-based gait analysis, COPD biomechanics, dual-task interference in aging, and exoskeleton effects on interlimb coordination. Methodological rigor in parameter selection for nonlinear algorithms is a recurring theme. Awards: 2023 Faculty Climate Award (Texas A&M), 2019 Promising Scientist Award (International Society of Posture and Gait Research), and 2019 Chancellor's Commission on the Status of Women Award (University of Nebraska). Advising & Grants: Mentors graduate students (noted in publications) and collaborates with TEEX Fire Academy and multiple Texas A&M research centers including the Huffines Institute for Sports Medicine and the Center for Population Health and Aging. Research supported by institutional and federal grants. Labs/Teams: Active in Texas A&M's Human Movement and Aging Lab, collaborating with interdisciplinary teams in sports medicine, rehabilitation engineering, and pulmonary research.

• Health Communication
• Digital Health
• AI
• +7 more

Prof. Julia van Weert is a Professor of Health Communication at the Faculty of Social and Behavioural Sciences of the University of Amsterdam. Her research focuses on improving patient-provider communication through digital health interventions, shared decision-making processes, and health equity. Specializing in areas such as AI applications in healthcare, cancer care communication, and falls prevention in older adults, her work bridges communication science with practical healthcare challenges. She leads projects like the SNOWDROP initiative, which uses big data to empower seniors in managing medication-related fall risks. Her studies frequently address barriers to effective communication in multicultural healthcare settings and the impact of online health information on patient outcomes. Key collaborations include work with Amsterdam UMC and ASCoR, emphasizing user-centered design for clinical decision support systems. Her expertise spans health literacy, pandemic communication during crises, and the role of mental wellbeing in health messaging. Notable projects include systematic reviews on decision aids for older adults and longitudinal studies on media consumption patterns during the COVID-19 pandemic. Prof van Weert’s research integrates qualitative and quantitative methods, often involving cross-disciplinary teams to address complex healthcare communication challenges. She has contributed to the development of clinical tools like the ADFICE_IT system for deprescribing fall-risk drugs and the Online Value Clarification Tool for early-phase clinical trials. Her work emphasizes translating academic findings into actionable strategies for improving healthcare delivery and patient empowerment across diverse populations.

Al BarrView profile

Professor

• Computer Graphics
• Predictive Modeling
• Scientific Visualization
• +5 more

Alan H. Barr is a Professor of Computer Science at the California Institute of Technology (Caltech), affiliated with the Division of Engineering and Applied Science and the Computation & Neural Systems (CNS) department. He is a founding member of the Caltech Computer Graphics Group and a leader in developing mathematically rigorous methods for computer graphics and predictive modeling. His research focuses on enhancing computational modeling accuracy through approaches like interval analysis and constraint-based systems. Notable contributions include deformable models, quaternion interpolation, and cellular simulation frameworks. He has advised over 20 graduate students, many of whom became industry leaders at Pixar, Microsoft Research, and academic institutions like NYU and Brown University. Awards include the ACM SIGGRAPH Achievement Award (1988) and ACM Fellow (1995). Research Interests: Predictive modeling with error bounds Scientific visualization and MRI data analysis Biophysical systems simulation (e.g., cellular organelles) Self-assembling robotic structures for space colonization Mathematically robust computer graphics techniques Key Collaborations: Caltech Biological Imaging Center (Beckman Institute) JPL (Jet Propulsion Laboratory) New computational substrates research (quantum/DNA computing) Recent Work: Expanding into computational biology, medical imaging optimization, and high-confidence systems for managing complex computational interactions. Active in interdisciplinary projects across Caltech divisions.