Find Academic Supervisors

• Directed Algebraic Topology
• Algebraic Topology
• Applied Mathematics
• +3 more

Sanjeevi Krishnan is an Associate Professor in the Department of Mathematics at The Ohio State University (OSU). He specializes in directed algebraic topology, focusing on spaces with time-like structures. His research bridges theoretical mathematics and applications in computer science and robotics. He currently teaches undergraduate Linear Algebra (Math 2568/4568) and has developed software tools like dat.py , cubcat.app , and practice: synthetic homotopy theory for topological computations. Key research interests include model structures, cubical approximations, and homotopy invariants in directed topology. His work has been published in journals like Algebraic & Geometric Topology , Journal of Pure and Applied Algebra , and Applied Categorical Structures . Notable contributions include foundational papers on covering spaces in directed topology and applications of topological duality in pursuit-evasion games. He collaborates with institutions globally, including work with Robert Ghrist on topological max-flow min-cut theorems and with Philippe North on dihomotopy type theory. His teaching and research emphasize practical implementations through computational tools and spectral sequence visualization.

Antoine MiechView profile

Researcher

• Computer Vision
• Machine Learning
• Natural Language Processing
• +7 more

Antoine Miech is a Researcher at DeepMind's Vision Group , with prior affiliations at Inria and Ecole Normale Supérieure where he completed his computer vision Ph.D. under Ivan Laptev and Josef Sivic . He has collaborated with researchers from Facebook AI and Google during his academic career. Research Interests span video understanding, weakly-supervised machine learning, and multimodal analysis. His work focuses on: Text-video embedding Self-supervised video representation Action localization Anticipatory video modeling Scalable multimodal learning Scientific Contributions include: HowTo100M - A massive dataset of narrated instructional videos MIL-NCE - A novel loss function for video-text alignment MEE - A model for handling heterogeneous data Context Gating - Learnable pooling architecture Awards & Recognition : Google Ph.D. Fellowship (2018) Technical Leadership : Created the LOUPE TensorFlow toolbox for feature pooling and maintained annotated video dataset catalogs. Organized the Data Science Game competition (2016-2017).

• Neurosciences
• Cognitive and computational psychology
• Biological psychology
• +3 more

Roni Maimon Mor is a Research Fellow at the Institute of Ophthalmology, University College London. Their work bridges neuroscience, cognitive psychology, and biomedical engineering, focusing on vision science, neural plasticity, and human-technology interaction. They investigate how sensory deprivation (e.g., congenital sight impairment) and interventions (e.g., gene therapy) reshape neural processes and perceptual abilities. Research interests include developmental vision, robotic prosthetics, and the cognitive embodiment of artificial limbs. Their studies explore how early life experiences influence motor learning and how neural systems adapt to sensory loss or technological augmentation. Mor’s interdisciplinary approach integrates neuroimaging (e.g., fMRI, EEG), behavioral experiments, and engineering solutions like gaze-tracking systems for pediatric diagnostics. Publications highlight advancements in gene therapy outcomes for retinal dystrophies, cortical plasticity in sensory-deprived populations, and neural correlates of prosthetic limb use. Their work contributes to clinical tools for vision assessment and theoretical models of body representation. No scientific awards explicitly listed. Research is supported by collaborations in ophthalmology, robotics, and cognitive science. Mor’s lab at UCL focuses on translating neural findings into therapeutic and assistive technologies.

Sonit SinghView profile

Lecturer

• Artificial Intelligence
• Computer Vision
• Natural Language Processing
• +7 more

Dr. Sonit Singh is a Lecturer at the School of Computer Science and Engineering at the University of New South Wales (UNSW), Sydney, Australia. Prior to this role, he served as a Postdoctoral Research Fellow at the same institution. He holds a PhD from Macquarie University, completed in collaboration with Macquarie. His research focuses on artificial intelligence, computer vision, natural language processing, and their applications in healthcare, particularly in medical imaging and diagnostic systems. Dr. Singh's academic background includes a strong emphasis on biomedical imaging, intelligent robotics, and computing education. His work bridges machine learning advancements with real-world clinical challenges, such as tumor segmentation, radiology report generation, and disease detection through imaging modalities like CT scans and ultrasound. His recent publications highlight innovations in 3D medical image localization, robust tumor segmentation networks, and clinical context-aware radiology report systems. These contributions underscore his expertise in integrating deep learning techniques with healthcare workflows. Dr. Singh collaborates with multidisciplinary teams, including medical professionals, to develop solutions for challenges like placenta segmentation and dietary intake monitoring using AI. While no specific awards or grants are explicitly listed, his extensive publication record reflects sustained academic engagement in high-impact areas. His research often addresses practical clinical needs, such as improving diagnostic accuracy and patient care through advanced computational methods.

Ariel GenadtView profile

Lecturer

• Modern and Contemporary Architecture
• Japanese Architecture
• Architectural Resilience
• +3 more

Ariel Genadt is a Lecturer in Architecture at the Stuart Weitzman School of Design, University of Pennsylvania. His work bridges research, teaching, and practice, focusing on modern and contemporary Japanese architecture, architectural resilience, and the intersection of technology, sustainability, and cultural expression. He holds a PhD in Architecture from the University of Pennsylvania (2016), with certificates in Ecological Architecture and University Teaching, alongside degrees from the Architectural Association (London) and Technion (Israel). Education: PhD in Architecture, University of Pennsylvania (2016) Master of Arts in Histories and Theories, Architectural Association, London (2004) Bachelor of Architecture, Technion, Israel (1997, cum laude) Research Interests: Japanese architectural history and practice Sustainable and resilient design Material innovation and tectonic expression Cultural preservation and reinterpretation Genadt's publications and exhibitions explore themes like architectural resilience in Japan, material assemblies, and cultural narratives in urban spaces. His curatorial work includes the Critical Abstractions: Modern Architecture in Japan exhibition (2018) and the 50 Years in Books by Penn Architecture PhDs database (2016). He has practiced globally, collaborating on projects in France, Israel, China, and beyond, and has taught at institutions including Swarthmore College and the Technion. His teaching spans courses on architectural theory, climate-responsive design, and Japanese modern architecture. Notable courses include ARCH 7120: Architectural Envelopes and ARCH 7110: Modern Architecture in Japan . He has advised the Master of Architecture thesis program and led design-build workshops at Tokyo University. Genadt’s professional affiliations include roles as a Fellow Researcher at the Japan Society for the Promotion of Science (Kengo Kuma Lab, 2012) and a visiting scholar at Fondazione Renzo Piano (2013). His work emphasizes cross-cultural dialogue and the role of architecture in addressing environmental and social challenges.

Ulrica NylenView profile

Associate Professor

• Management
• Organizational Behavior
• Leadership Studies
• +4 more

Ulrica Nylen is an Associate Professor in Business Administration (Management) at Umeå School of Business, Economics and Statistics (USBE), Umeå University. Her work focuses on teaching organizational behavior, leadership, and qualitative research methods, while actively collaborating with societal actors on applied research projects. Research Interests: She investigates professional identity development, particularly among Swedish police officers in international roles; interprofessional teamwork in human services sectors; and collaboration dynamics across organizations. Her methodological focus includes advancing qualitative research techniques. Current projects include studies on women entrepreneurship in Västerbotten and university-society partnerships. Awards: Nordeas thesis award (Diversity and Inclusion) Collaborations & Grants: Engages in multi-stakeholder projects with public agencies and NGOs, emphasizing applied research. Notable collaborations include evaluations of healthcare delivery systems and social service innovations. Labs/Teams: Works within interdisciplinary teams at USBE and partners with regional organizations like Västerbottens läns landsting to implement research into practice.

• Automation Engineering
• Mechanical Engineering
• Robotics
• +4 more

Pauli Mustalahti is a Research Fellow at Tampere University's Automation Technology and Mechanical Engineering department. His expertise lies in advanced control systems for heavy-duty robotic manipulators, hydraulic systems, and model-based control design. Mustalahti holds a Master of Science (Technology) in Automation Engineering from Tampere University (2016) and a Bachelor of Science (Technology) in the same field (2013). His research focuses on optimizing automated operations for industrial manipulators through innovative control strategies, including bilevel optimization frameworks, vision-aided positioning, and robust safety-constrained systems. Key contributions include improving long-reach manipulator accuracy via local calibration and enhancing electric linear actuator performance with safety protocols. Research interests: Robotics, Hydraulic Systems, Model-Based Control, Industrial Automation Notable achievements: Doctoral thesis on modular model-based control design for heavy-duty manipulators (2023) Collaborations: Global Fluid Power Society, IEEE, and international researchers in automation Mustalahti's work aligns with UN Sustainable Development Goals related to Industry, Innovation, and Infrastructure. His publications span peer-reviewed journals like IEEE Transactions on Automation Science and Engineering and conferences such as PEMC, addressing challenges in actuator safety, real-time control, and energy efficiency.

• Human Visual Perception
• Contour-Shape Processing
• Texture Perception
• +5 more

Dr. Elena Gheorghiu is an Associate Professor in the Department of Psychology at the University of Stirling, within the Faculty of Natural Sciences. She holds a PhD from Utrecht University (Netherlands) and has held post-doctoral positions at McGill University (Canada) and KU Leuven (Belgium). Her research focuses on human visual perception, specifically contour-shape processing, texture analysis, binocular vision, and visual illusions. She has received the prestigious 1st Prize at the Best Visual Illusion of the Year Contest (2007) for the 'Leaning Tower Illusion.' Education: PhD in Psychology, Utrecht University (Netherlands) Postdoctoral Fellowships: McGill University (Canada) and University of Leuven (Belgium) Research Interests: Contour/Texture Processing Stereopsis and Binocular Vision Symmetry and Regularity Perception EEG/ERP and Computational Modelling Her grants include funding from EPSRC (2024-2027), MOD-Dstl (2023), and Wellcome Trust (2015-2019). She has advised numerous postdoctoral researchers and students, including Dr. Rebecca Sharman (now at Abertay University) and Dr. Damien Wright (University of Edinburgh). Her lab explores topics such as mirror symmetry detection, contextual modulation effects, and temporal dynamics of visual perception. Key achievements include over 60 peer-reviewed articles and advancements in understanding visual perception mechanisms through psychophysical and neurophysiological methods.

Cynthia H. McColloughView profile

Professor

• Computed Tomography (CT) Imaging Technology
• Radiation Dose Management
• Material Composition Evaluation via CT
• +3 more

Cynthia H. McCollough, Ph.D., is a Professor of Biomedical Engineering and Medical Physics at Mayo Clinic, where she serves as a Consultant in the Department of Radiology. She leads the CT Clinical Innovation Center, focusing on advancing CT imaging technology and clinical applications. Her work emphasizes radiation dose reduction, quantitative material composition analysis (e.g., kidney stones, gout), and optimizing CT protocols for diagnostic accuracy while minimizing patient risk. Dr. McCollough holds leadership roles in national and international organizations, including the NIH Biomedical Imaging Technology Study Section and the American Association of Physicists in Medicine (AAPM). She has received numerous awards, including the Distinguished Investigator Award from Mayo Clinic and the William D. Coolidge Gold Medal from AAPM. Her research spans photon-counting CT, dual-energy CT, and translational imaging solutions for vascular and abdominal diseases. Dr. McCollough’s academic contributions include over 600 peer-reviewed publications and leadership in grant-funded projects such as the National Institute of Biomedical Imaging and Bioengineering initiatives. Education: PhD in Medical Physics from the University of Wisconsin-Madison, MS in Medical Physics from the University of Wisconsin-Madison, BS in Physics from Hope College. Research Highlights: Her lab develops tools for radiation dose estimation, non-invasive material characterization via CT, and optimizing CT parameters using human and model observers. Recent work includes improving kidney stone analysis, bone mineral density measurements using photon-counting CT, and reducing radiation exposure in pediatric imaging. Grants & Funding: Principal investigator on multiple NIH grants, including projects on coronary atherosclerosis characterization, urinary stone composition analysis, and photon-counting CT for vascular disease detection. Awards: Over 100 awards, including the Distinguished Mayo Clinic Investigator Award (2020), Honorary Doctorate from Linkoping University (2020), and AAPM’s highest honor, the William D. Coolidge Gold Medal (2024). Labs & Teams: Directs the CT Clinical Innovation Center and the X-Ray Imaging Research Core at Mayo Clinic, collaborating with multidisciplinary teams across radiology, biomedical engineering, and physics.

Norman Van RhijnView profile

Research Fellow

• Antimicrobial Resistance (AMR)
• Climate Change Impact on Fungal Pathogens
• One Health
• +3 more

Norman Van Rhijn is a Wellcome Trust Early Career Fellow at the University of Manchester's Division of Evolution, Infection and Genomics. His research focuses on microbial evolution with specific emphasis on fungal pathogens, particularly Aspergillus fumigatus . He leads work on antimicrobial resistance (AMR), climate change impacts on fungal diseases, and genetic tools for non-model organisms. He holds affiliations with MERman (Microbial Evolution Research Manchster) and the Manchester Fungal Infection Group (MFIG). Education: BSc Biology (Leiden University), MSc Medical Mycology (University of Manchester), PhD in Molecular Biology (University of Manchester). Research highlights include developing CRISPR-based genome editing methodologies, studying fungal adaptation to environmental pressures, and investigating dual-use fungicides. His work contributes to UN Sustainable Development Goals related to health and environmental sustainability. Award: Wellcome Trust Early Career Fellowship. Labs/Teams: PI in the MFIG project, editorial board member for mBio , and active in professional societies including the Microbiology Society and British Society for Medical Mycology.

Sarbeswar PraharajView profile

Assistant Professor

• Urban Sustainability
• Climate Resilience
• Geospatial Analysis
• +5 more

Sarbeswar Praharaj is an Assistant Professor in the Department of Geography and Sustainable Development at the University of Miami's College of Arts and Sciences. He also serves as Director of the MPS in Urban Sustainability and Resilience Program, Associate Dean of Graduate Education at the School of Architecture, and Affiliate Faculty at the Climate Resilience Academy. His work focuses on urban sustainability, climate resilience, geospatial analysis, and smart cities. Praharaj has contributed to global projects including case studies in Morocco and India, emphasizing participatory design and policy integration. His research explores multidimensional poverty measurement, flood susceptibility modeling, pandemic response strategies, and the role of geospatial tools in disaster management. He has published extensively on India's Smart Cities Mission, urban regeneration frameworks, and the socio-spatial impacts of climate change. Notable contributions include developing digital twin platforms for urban projects, co-design toolkits for poverty visualization, and dashboards to combat pandemic-related socioeconomic challenges. Praharaj advocates for inclusive urban policies and community-driven solutions to environmental and health crises.

Magnus BotnanView profile

Assistant Professor

• Topological Data Analysis
• Representation Theory of Quivers
• Computational Topology
• +3 more

Magnus Botnan is an Assistant Professor at the Department of Mathematics, Vrije Universiteit (VU) Amsterdam. He held a tenure-track position from 2018-2022, was a postdoc at TU Munich (2016-2018) under Ulrich Bauer, and earned his PhD at NTNU in 2015 under Nils A. Baas. His research spans topological data analysis, bridging pure mathematics (representation theory of quivers) with computational and applied aspects (persistent homology, data signatures). Education: PhD in Mathematics at Norwegian University of Science and Technology (NTNU) Research Grants: VIDI career grant (€850,000) Research Collaborations: with Mike Lesnick, Ulrich Bauer, S. Oppermann, and S. Oudot His recent work includes extremal Betti numbers, bottleneck stability, and signed barcodes for multiparameter persistence. He co-organized applied topology meetings in the Netherlands and supervises graduate students in computational topology. Key scientific contributions: Advances in Mathematics Journal of Applied and Computational Topology SoCG conference proceedings He teaches courses such as Calculus 2, Complex Analysis, and Topological Data Analysis at VU Amsterdam and Mastermath, with past courses in Differential Equations, Linear Algebra, and Modelling of Dynamical Systems.

Sam S. RamanujanView profile

Professor

• Big Data Architecture
• Visual Analytics
• Software Engineering
• +4 more

Dr. Sam S. Ramanujan is Professor of Computer Information Systems and Analytics at the University of Central Missouri , affiliated with the Harmon College of Business and Professional Studies . He teaches advanced object-oriented programming and software engineering courses, combining over two decades of academic expertise with substantial industry experience in complex system deployment. Doctor of Philosophy in Information Systems (University of Houston, 1995) MBA in CIS and Quantitative Analysis (University of Arkansas, 1989) PGDM in Information Systems (XLRI Institute of Management Studies, 1987) Bachelor of Arts (Hons) in Economics (University of Delhi, 1985) His research spans big data architecture , visual analytics , healthcare IT , and legal aspects of technology . He has published extensively on topics including software maintenance, e-commerce trust models, and cloud-based healthcare systems, with a focus on bridging technical and legal challenges in digital environments. Dr. Ramanujan's academic work shows a consistent focus on software engineering (1995–2017), healthcare IT (2004–2017), and legal-compliance frameworks (2000–2017). His publications demonstrate interdisciplinary expertise in merging technical systems with regulatory requirements . Best Paper Award , Journal of American Academy of Business, Cambridge (2006) He has contributed to pedagogical advancements in distributed computing curricula and collaborates with scholars like S. Kesh and S. Nerur. His industry experience informs real-world applications of his research in software maintenance and offshore operations.

Stefan DrechslerView profile

Researcher

• Old Norse philology
• Medieval manuscript studies
• Art history
• +5 more

Stefan Drechsler is a Researcher in Old Norse philology at the Department of Linguistic, Literary and Aesthetic Studies at the University of Bergen. His academic work focuses on interdisciplinary research into medieval Scandinavian manuscripts, particularly examining the intersection of textual analysis, codicology, and art history within the context of law manuscripts from medieval Norway and Iceland. Dr. Drechsler's research interests span a wide range of medieval studies topics including textual and codicological compilation strategies in Scandinavian law manuscripts, legal iconography in medieval European book painting, and social network analysis related to vernacular law texts. He has made significant contributions to understanding the literary and artistic exchange between western Scandinavian societies and other parts of Europe during the High Middle Ages. His work demonstrates how interdisciplinary approaches to vernacular manuscripts can reveal new information about cultural goods exchange and secular and ecclesiastical networks in the North Atlantic region. His publications show a consistent focus on manuscript production, particularly illuminated manuscripts from medieval Scandinavia. The most recent works examine paratextual elements in law manuscripts, iconography in Icelandic law manuscripts, and Norwegian manuscripts as European works of art, indicating a trend toward increasingly sophisticated analysis of the cultural context and artistic influences on medieval Scandinavian book production. Subjekt Award 2024 for 'The Laws of the Land 750 Years' exhibition at Bryggens Museum As Principal Investigator of two major research projects—'Nordic Law Books: The Production and Use of Vernacular Law Manuscripts in the North from 1100 to 1600' (NordicLaw) and 'Writing in Latin and in the Vernacular: Bilingual Scribal Practice in Norway ca. 1300–1350'—Drechsler has secured significant research funding. He has also organized a biannual public lecture series on medieval topics since 2020 and has been actively involved in multiple outreach projects including digital exhibitions. Dr. Drechsler is affiliated with the Research Group for Medieval Philology and the Research Group Images of Knowledge at the University of Bergen, where he contributes to the Medieval Research Cluster, a driving force in developing local and national dissemination of medieval knowledge.

Jeremy TeitelbaumView profile

Professor

• Algebra
• Number Theory
• Machine Learning
• +5 more

Jeremy Teitelbaum is a Professor in the Department of Mathematics at the University of Connecticut within the College of Liberal Arts and Sciences. He serves as Director of UConn's interdisciplinary Masters Program in Data Science, a one-year professional degree program. His academic career spans both pure mathematics and data science applications. Teitelbaum's research bridges classical algebraic number theory and modern machine learning. Initially focused on p-adic geometry, elliptic curves, modular forms, and p-adic L-functions , his work evolved significantly toward machine learning and data science . Current interests include bioinformatics, unsupervised learning (particularly clustering), and mathematical foundations of machine learning. He maintains active GitHub repositories documenting his computational work and lecture materials. His publication trends reveal a transition from pure number theory (2000s) toward machine learning applications (2020s), with consistent mathematical rigor throughout. Keywords across his work include algebraic geometry, representation theory, p-adic analysis, and statistical learning theory, reflecting both his foundational expertise and contemporary applications. Teitelbaum has held significant administrative roles including Dean of the College of Liberal Arts and Sciences (2008-2017) and interim Provost (2017-2018). He is a Certified Instructor for The Software Carpentry and develops extensive online educational materials, including complete video lecture series for Abstract Algebra and Transition to Higher Mathematics based on open-source textbooks. His teaching portfolio includes graduate courses like Fundamentals of Data Science (Grad 5100) and Mathematics of Machine Learning (Math 3094), alongside core mathematics courses such as Abstract Algebra and Linear Algebra. He maintains specialized interests in mathematical visualization tools, including Bokeh library applications and linear algebra pedagogy tools.