Find Academic Supervisors

• Qualitative Research Methodology
• Health Services Research
• Pediatric Musculoskeletal Medicine
• +3 more

Dr. Tim Rapley is a researcher at Newcastle University , affiliated with collaborators such as Professor Helen Foster, Dr. Anna Basu, and Professor Carl May. His work spans pediatrics, rheumatology, and health services research. Positions: Researcher, Qualitative Methodologist Collaborators: Professor Helen Foster (Emerita), Dr. Anna Basu, Professor Carl May Research Interests : Rapley specializes in qualitative research methodology, normalization process theory (NPT), and the implementation of complex healthcare interventions. His work focuses on pediatric musculoskeletal assessment (e.g., pGALS), clinical decision-making, and patient experiences in chronic conditions like Sjögren’s syndrome and juvenile idiopathic arthritis. Publication Trends : His recent articles address child neurology (cerebral palsy diagnosis, perinatal stroke interventions), patient-centered care (ventricular assist device communities, bronchiectasis resources), and methodological advancements (NoMAD survey tool, NPT applications). Themes include health equity, interdisciplinary collaboration, and evidence-based practice. Labs & Teams : Rapley collaborates extensively with pediatric rheumatologists, health services researchers, and multidisciplinary teams across Newcastle University and UK institutions, emphasizing community-based care models and stakeholder-informed intervention design.

• Physical Geography
• Human Geography
• Anthropocene Studies
• +6 more

Professor Nigel Clark is a leading scholar at the Lancaster Environment Centre , affiliated with the Faculty of Science and Technology at Lancaster University . His work bridges physical and human geography, focusing on the Anthropocene and humanity's role as a geological agent. Research Interests include: Anthropocene and Earth System dynamics Fire ecology and pyropolitics Planetary geology and critical temperature studies Climate justice and disaster ethics Material culture and stratigraphic politics His recent publications highlight planetary thresholds , geological agency , and fire as a transformative force across disciplines. Clark supervises PhD students Samantha Harrison , Ellie Moxham , and Lydia Parsons , contributing to debates on environmental ethics and planetary stewardship.

Fabian DennerView profile

Associate Professor

• Numerical analysis
• Modeling and simulation
• Multiphase systems
• +5 more

Fabian Denner is an Associate Professor at the Department of Mechanical Engineering, Polytechnique Montréal. His work focuses on modeling multiphase flows and related physical phenomena, including cavitation, acoustic wave dynamics, and high-performance computing (HPC). He develops advanced numerical methods and software tools for simulating incompressible and compressible flows, with applications in medicine, chemical engineering, and aerospace. His research group addresses challenges in predicting cavitation effects, liquid jet breakup, and acoustic modulation in accelerating flows. Education Dipl.-Eng. in Automotive Engineering, University of Stuttgart (2009) Ph.D. in Mechanical Engineering, Imperial College London (2013) Research Interests His expertise spans: Numerical modeling of multiphase flows Acoustic wave propagation and modulation Cavitation dynamics and biomedical applications High-performance computing (HPC) for fluid dynamics Liquid jet atomization and particle-laden flows Surface tension and interface reconstruction techniques Publications and Software Fabian has published extensively in leading journals like Physics of Fluids , Journal of Computational Physics , and Journal of Fluid Mechanics . He co-developed software frameworks such as Wave-DNA and APECSS for simulating complex fluid dynamics and acoustic phenomena. Scientific Recognition Margaret Fishenden Centenary Memorial Prize (2015) Leadership Roles Vice-director, Canadian Society for Mechanical Engineering - Fluid Engineering Technical Committee Co-director, Editorial Advisory Committee of Canadian Journal of Chemical Engineering Active contributor to international conferences (APS DFD, ICMF, IUTAM)

Marit SchoonhovenView profile

Associate Professor

• Statistical Process Control
• Lean Six Sigma
• Quality Management
• +4 more

Dr. Marit Schoonhoven is an Associate Professor at the University of Amsterdam , affiliated with the Faculty of Economics and Business and the Business Analytics department. Since 2007, she has been instrumental at IBIS UvA, delivering Lean Six Sigma Green Belt and Black Belt training while guiding process improvement projects for organizations including Zwitserleven, AEGON, Deventer Hospital, and the University Medical Center Utrecht. Research Focus : Her work centers on control charts and statistical process control, extending to applications in healthcare efficiency, educational analytics, and Bayesian modeling. She frequently publishes in journals like the Journal of Quality Technology and Technometrics . Key research areas: Statistical Process Control, Lean Six Sigma, Healthcare Operations, Bayesian Modeling Recent article trends: Bayesian graphical models for Alzheimer’s disease, multilevel monitoring in education, nonparametric control in dynamic systems

• Automatic speech recognition
• Language recognition
• Machine learning
• +5 more

Sandro Cumani is an Associate Professor in the Department of Control and Computer Engineering (DAUIN) at the Polytechnic University of Turin. He serves as a member of both the College of Electronic, Telecommunications and Physics Engineering and the College of Computer, Film and Mechatronics Engineering, demonstrating his cross-disciplinary impact across multiple academic programs. Dr. Cumani's research focuses on automatic speech and language processing with emphasis on speaker verification systems, machine learning for biometric authentication, and speech recognition technologies. His work integrates advanced machine learning techniques with practical applications in voice biometrics, addressing challenges such as domain mismatch, score calibration, and bias mitigation in speech models. His research interests include automatic speech recognition, language recognition, speaker recognition, speaker verification, and machine learning applications in biometric systems. His publication record shows a clear trajectory from foundational work on score distribution modeling and calibration techniques toward more sophisticated approaches addressing privacy preservation, bias mitigation, and subgroup performance analysis in speech recognition systems. The research consistently focuses on improving the reliability and fairness of speaker verification technologies through statistical modeling and machine learning innovations. Dr. Cumani leads the Speech Recognition Group (SRG) within DAUIN and has been the Scientific Responsible for multiple commercial research projects on speaker recognition and diarization from 2018 through 2025. He actively supervises PhD students, including Salvatore Sarni who completed his thesis on Speaker Verification and Language Recognition.

Theresa GeimanView profile

Associate Professor

• Epigenetics
• Stem Cells
• Cancer
• +4 more

Theresa Geiman serves as an Associate Professor in the Department of Biology at Loyola University Maryland, maintaining her office in Dorothy Day 051. Her research focuses on epigenetic mechanisms including chromatin remodeling, DNA methylation, and histone modifications that regulate gene expression during cellular differentiation, development, and cancer progression. Dr. Geiman investigates how epigenetic modifications control stem cell gene expression, particularly examining why failure to properly silence stem cell genes in differentiated cells can lead to cancer-like properties such as uncontrolled growth and cellular mobility. Her work explores the shared molecular pathways between normal stem cells and cancer cells, with emphasis on how epigenetic dysregulation contributes to disease states. Utilizing molecular, biochemical, and cellular techniques across multiple model systems—including mouse embryonic stem cells, genetically modified mice, and human cancer cell lines—her laboratory studies epigenetic modifier proteins by generating knockout models to observe developmental and disease phenotypes. This research provides critical insights into normal cellular homeostasis and pathological conditions like cancer. Analysis of her publication history reveals sustained focus on the Lsh/HELLS protein family and their roles in DNA methylation dynamics, chromatin organization, and stem cell gene regulation. Her work spans fundamental epigenetic mechanisms in development to translational applications in oncology, consistently employing comparative approaches across mammalian models to elucidate conserved epigenetic principles.

• Mathematical Foundations of Machine Learning
• Explainable Artificial Intelligence
• Online Convex Optimization
• +4 more

Tim van Erven is an Associate Professor of Machine Learning at the Korteweg-de Vries Institute for Mathematics within the Faculty of Science at the University of Amsterdam. His research focuses on the mathematical foundations of machine learning, with particular expertise in online convex optimization, statistical learning theory, and explainable AI. He leads a research group dedicated to developing mathematically rigorous machine learning methods that work effectively without manual fine-tuning. His research interests span the mathematical foundations of machine learning, with emphasis on explainable machine learning, adaptive methods in online convex optimization, faster-than-minimax rates for 'easy data' in statistical learning, PAC-Bayesian concentration inequalities, and statistical learning theory with frequentist analysis of Bayesian methods. His work bridges theoretical guarantees with practical applications, recently shifting toward formal mathematical analysis of explainability methods for black-box AI systems. His recent publications reveal a clear evolution from foundational work in online learning and statistical theory toward explainable AI, with increasing focus on theoretical guarantees for concept learning and algorithmic recourse. The publications demonstrate strong methodological rigor while addressing practical challenges in interpretability and robustness of machine learning systems. Scientific Awards: VICI grant by the Dutch Research Council (2025) VIDI grant by the Dutch Research Council (2019) TOP grant by the Dutch Research Council (2016) NIPS 2014 outstanding reviewer award Rubicon grant by the Dutch Research Council (2011) Van Erven serves in significant academic leadership roles including as a member of the board of directors for COLT, co-chair for the AI & Mathematics initiative, and organizer of the thematic seminar on machine learning. He has successfully secured multiple competitive research grants and leads a research group working on the Mathematical Foundations for Explainable AI project, with several PhD and Postdoc positions currently open.

• Algebraic Geometry
• Arithmetic Geometry
• Diophantine Geometry
• +3 more

Emmanuel Ullmo is a distinguished mathematician serving as Director of the Institut des Hautes Études Scientifiques (IHES) since 2013, one of the world's premier research institutes for mathematics and theoretical physics. Prior to this leadership role, he was a Professor at the University of Paris-Sud since 2001, where he also served as Head of the Department of Mathematics at Orsay from 2007 to 2010. His academic career has spanned institutions worldwide including IMPA in Brazil, Princeton University in the United States, and Tsing-Hua University in China. Ullmo's educational background includes: École Normale Supérieure de Cachan (class of 1985) Doctorate in Mathematical Sciences from the University of Paris-Sud (1992) Specializing in arithmetic and algebraic geometry, Ullmo focuses on Diophantine questions concerning abelian varieties and Shimura varieties. His research integrates techniques from ergodic theory and o-minimal theory to address deep problems in number theory and geometry. Ullmo has made significant contributions to the understanding of equidistribution phenomena, special subvarieties, and the André-Oort conjecture, establishing himself as a leading figure in modern arithmetic geometry. His work often bridges disparate mathematical fields through innovative approaches that combine geometric, arithmetic, and dynamical perspectives. Ullmo's recent publications demonstrate a sustained focus on the intersection of algebraic geometry, number theory, and model theory. His work with collaborators like Baldi, Klingler, and Yafaev has advanced our understanding of the Zilber-Pink conjecture, Hodge theory, and the geometry of Shimura varieties. A recurring theme across his publications is the application of equidistribution principles to solve deep problems in Diophantine geometry, often revealing unexpected connections between seemingly unrelated mathematical domains. Ullmo's significant contributions to mathematics have been recognized with several prestigious honors: Invited speaker at the International Congress of Mathematicians in Beijing (2002) Member of the Institut Universitaire de France (2003-2008) Élie Cartan Prize of the Paris Academy of Sciences (2006) While specific students aren't mentioned in the provided information, Ullmo's extensive publication record with numerous collaborators suggests active mentorship of junior researchers. His editorial roles, including serving as editor-in-chief of Inventiones Mathematicae from 2008 to 2014, further demonstrate his leadership in the mathematical community. As Director of IHES, Ullmo oversees one of the world's most influential mathematical research environments, fostering cutting-edge research across multiple disciplines in mathematics and theoretical physics.

Dan B GoldmanView profile

Adjunct Associate Professor

• Computer Graphics
• Computer Vision
• Artificial Intelligence
• +3 more

Dan B Goldman is an affiliate associate professor at the University of Washington's Computer Science and Engineering department, while serving as a Principal Engineer and AI/ML architect for Lucasfilm & ILM. His career bridges academia and industry, with prior roles at Adobe's Creative Technologies Lab (2007-2015) and Google (2015-2024), where he led computer vision R&D for Project Starline. He is a member of the Visual Effects Society and holds a PhD in Computer Science (2007) from the University of Washington. Research Focus: Computer graphics, computer vision, artificial intelligence, and human-computer interaction Notable Projects: Content-Aware Fill (Photoshop), Project Starline (Google), HyperNeRF (neural radiance fields), and Nerfies (deformable 3D modeling) Academic Legacy: Mentored by David Salesin, with an Erdős-Bacon number of 6 (via Rose Byrne and David Salesin's academic lineage). His work appears in top venues like SIGGRAPH, CVPR, and ECCV, covering topics from neural rendering to 3D reconstruction. Industry Impact: Pioneered technologies used in major films (Star Wars, Jurassic Park) and Adobe Photoshop features. His recent work at Google Labs (2022-2024) focused on generative media, reflecting his dual expertise in creative tools and computational methods.

• Second Language Acquisition
• Curriculum Development
• College English Teaching
• +2 more

Yuxiu Hu serves as an English Instructor at the Center for Language Education, Southern University of Science and Technology (SUSTech) in Shenzhen, China. She has held the position of Lecturer at SUSTech since 2013, specializing in English language instruction for science and engineering students in a non-English speaking environment. Education: PhD in Linguistics, The University of Hong Kong (2007-2011) MA in Linguistics, The University of Hong Kong (2005-2006) BA in English Education, Harbin Normal University (1999-2003) Dr. Hu's research focuses on Second Language Acquisition, Curriculum Development, and College English Teaching. Her work examines how Mandarin influences English acquisition among Chinese students and develops specialized English curricula for STEM fields. She has conducted extensive research on technology-enhanced language learning, particularly exploring web-based instruction, MOOCs, and the flipped classroom model for engineering English education. Her longitudinal studies track language acquisition patterns and the effectiveness of various teaching methodologies in non-English speaking contexts. Scientific Recognition: Excellent Teaching Award, Southern University of Science and Technology (2018) The University of Hong Kong Research Student Scholarship (2007-2011) The University of Hong Kong Oversea Conference Grant (2008) Dr. Hu has led significant research initiatives including "The Development of STEM-based English Curriculum in Higher Education" (2017-2019) as Principal Investigator, and has contributed as Co-investigator to multiple projects involving MOOC development for engineering English, flipped classroom models for public speaking instruction, and web-based learning systems. She serves the academic community as a Proposal Reviewer for TESOL International Convention and previously as Associate Editor for Ubiquitous Learning: An International Journal. Her teaching portfolio encompasses College English Reading & Writing, Academic English, TOEFL preparation, Academic Writing, Engineering English, and English Reading Strategies courses.

• Random Matrix Theory
• High dimensional Statistics
• Time Series Analysis
• +1 more

Li Zeng is an Associate Professor in the Department of Statistics and Data Science at Southern University of Science and Technology (SUSTech) since January 2021, following her Assistant Professor role at the same institution from August 2019 to December 2020. Previously, she was an Eberly Postdoctoral Fellow at Pennsylvania State University under Prof. Runze Li (2017-2019) and a Research Assistant at the University of Washington with Dr. Fang Han (2017). Ph.D. in Statistics and Actuarial Science from the University of Hong Kong (2017), advised by Prof. Jianfeng Yao M.Sc. in Statistics from Renmin University of China (2012) B.Sc. in Mathematical Science from Beijing Normal University (2009) Her research centers on Random Matrix Theory and High Dimensional Statistics , with significant contributions to eigenvalue/singular value distributions in large-dimensional matrices. She extends these theoretical foundations to Time Series Analysis for lagged auto-correlation structures and applies them to Machine Learning problems including neural network optimization and regularization. Her work bridges asymptotic probability theory with practical data science applications, developing robust methods for high-dimensional inference. Analysis of her 15 most recent publications (2016-2025) reveals a dominant focus on high-dimensional statistical theory with increasing machine learning integration. Key trends include asymptotic analysis of covariance/correlation matrices (60% of publications), factor modeling innovations (20%), and deep learning applications (20%). She consistently publishes in top-tier venues including Annals of Statistics (5 papers), Journal of the American Statistical Association , and machine learning conferences (ICML, ECCV), demonstrating exceptional interdisciplinary impact. Excellent Teaching Assistant Award (5 times) from HKU Department of Statistics and Actuarial Science (2012-2017) Dr. Li actively recruits postdoctoral researchers specializing in probability theory and high-dimensional statistics, emphasizing candidates with strong mathematical backgrounds. As a referee for premier journals including Annals of Statistics , JASA , and Journal of the Royal Statistical Society: Series B , she contributes significantly to scholarly review. Her research is institutionally supported through SUSTech faculty positions, with potential external funding inferred from extensive publication output and conference participation. Within SUSTech's Department of Statistics and Data Science (established 2019), Dr. Li contributes to a rapidly expanding research ecosystem focused on high-dimensional data analysis. The department supports multiple research directions including biostatistics and financial statistics, with active graduate programs (M.Phil/Ph.D.) and developing initiatives in data science education. Her teaching portfolio includes undergraduate Statistical Calculation and Software and graduate-level High Dimensional Statistics courses.

• Cultural History
• Drugs
• History of Medicine
• +5 more

Dr. Stephen Snelders is an Assistant Professor at the History and Philosophy of Science department within Utrecht University's Faculty of Science. His research spans cultural history, drugs, history of medicine, and crime, with a focus on the social contexts of scientific knowledge and its movement across domains. He has authored books including Drug Smuggler Nation: Narcotics and the Netherlands, 1920-1995 and Leprosy and Colonialism: Suriname under Dutch Rule, 1750-1950 . Research Themes : Drug markets, colonial medicine, LSD history, non-anthropocentric science communication, and historical transitions in substance use. Expertise : Cultural history, drug history, crime history, and tropical colonial medicine. His recent publications analyze opium distribution in Amsterdam, Dutch Golden Age piracy, and sustainable pathways in historical contexts. Snelders has held academic roles at institutions like Utrecht University Medical Center and VU University Medical Center. He contributes to public engagements through exhibitions, media appearances, and editorial work for journals such as Studium .

Kathleen CorrigallView profile

Associate Professor

• Cognitive development
• Developmental psychology
• Infant and child development
• +3 more

Dr. Kathleen Corrigall serves as Associate Professor in the Department of Psychology within MacEwan University's Faculty of Arts and Science, where she has contributed since 2013. Her interdisciplinary work bridges cognitive development, music perception, and evidence-based pedagogy, examining how musical experiences shape non-musical abilities in children. Education PhD, McMaster University BA Honours, University of British Columbia Her research program investigates music perception and cognition during early development, focusing on associations between music/dance training and cognitive skills, creativity, personality, and social-emotional competence. She explores why certain children pursue music lessons and how cultural exposure shapes musical understanding analogous to language acquisition. Recent work examines background music's impact on creativity, singing for stress relief, group music-making for prosociality, and dance training's effects on visual memory. Analysis of her 15 most recent publications reveals consistent focus on children's musical enculturation (2010-2014), expansion into social-emotional outcomes (2015), and contemporary challenges to transfer-effect assumptions (2022-2024). Methodologically, she combines electrophysiological, behavioral, and survey approaches across Western and multicultural contexts. Scientific Recognition SSHRC Postdoctoral Fellowship Award (2013) Teaching Innovation Fund Award (2020) NSERC Canada Graduate Scholarship (2006) Multiple MacEwan University research grants (2014-2019) Dr. Corrigall actively mentors junior teaching assistants and develops evidence-based pedagogy, including flipped classroom models for Introductory Psychology. Her research receives support from SSHRC, NSERC, and MacEwan internal funds. She leads the Child Development Lab investigating how music, dance, and cultural experiences shape developmental trajectories through sound-based communication. The Child Development Lab conducts longitudinal studies with normal-hearing and hearing-impaired children, examining how musical experiences affect problem-solving, social interaction, and emotional regulation. Current projects include stress-relief applications of music listening and cross-domain transfer effects between dance training and visual memory systems.

Émilie FrémondView profile

Lecturer

• Surrealism
• Modern and Contemporary Poetry
• Ecology and Avant-Gardes
• +4 more

Émilie Frémond is a Lecturer at Sorbonne Nouvelle University, currently on CNRS delegation for the 2024-2025 academic year. A specialist in surrealism and modern poetry, she explores intersections of science, arts, and ecological thought with significant contributions to medical humanities. Her academic foundation includes: Agrégée de Lettres Modernes (competitive French teaching qualification) Former student of École Normale Supérieure de Lettres et Sciences Humaines (ENS LSH) Frémond's research centers on liberating surrealism from critical misinterpretations by demonstrating its post-WWII ecological consciousness. She examines materialist approaches to psychic phenomena through medical humanities, analyzes urban ecology in avant-garde movements, and investigates nature knowledge (zoology/botany/mineralogy) across diverse media including travel narratives, contemporary poetry, and museum displays. Her work bridges scientific and artistic representations of living/non-living systems. Her recent publications reveal a trajectory connecting surrealism with ecological thought and sleep studies. The 2025 co-edited volume The Arts of Sleep analyzes altered states of consciousness across visual arts, cinema, and comics, framing sleep as simultaneously physical, aesthetic, and political. Earlier works establish foundational links between surrealist poetics and ecological commitment. No scientific awards are documented in available sources. Details regarding student supervision and research grants remain unspecified in current records. She actively participates in interdisciplinary initiatives including the ENS-PSL incentive action "Figurer er penser l'animal entre littérature, philosophie et sciences," co-organizing the May 2024 conference "Species in the process of appearing. Imaginary bestiaries and fictional animal encyclopedias" exploring cross-disciplinary animal representations.

• Condensed Matter Physics
• Semiconductor Nanostructures
• Quantum Transport
• +3 more

Engin ÇİÇEK serves as a Lecturer in the Department of Physics at Trakya University's Faculty of Science, where he has maintained continuous academic employment since 2002 as a Research Assistant with PhD. His career is anchored in theoretical condensed matter physics with specialized expertise in semiconductor nanostructures, complemented by administrative responsibilities as Career Unit Manager at the Institute of Natural and Applied Sciences since 2014. His academic foundation includes a Bachelor's degree (2001), Master's degree (2004), and PhD (2010), all in Physics from Trakya University. His graduate research focused on quantum confinement effects, with his Master's thesis examining "Effects of Geometry, Electric Field and İmpurity Position on Binding Energy in Quantum Wires" and his doctoral dissertation investigating "Electronic Properties of One-Dimensional Electron Gas". ÇİÇEK's research program centers on electronic phenomena in low-dimensional semiconductor systems, particularly quantum dots, wells, and wires. He investigates how external parameters—including electric fields, laser radiation, hydrostatic pressure, and temperature—modulate fundamental properties like binding energy, self-polarization, and transition energies. His methodological approach combines theoretical modeling with numerical simulations to analyze impurity states and electron gas behavior in nanostructures, primarily using GaAs/AlAs heterostructures. Analysis of his 15 most recent publications (2005-2025) reveals consistent thematic focus on geometric factors, impurity positioning, and external field effects in quantum-confined systems. His work demonstrates increasing sophistication in handling multi-parameter interactions, with recent publications (2023-2025) exploring complex configurations like multi-material quantum wells and tetragonal quantum dots under combined perturbations. The majority of his research appears in specialized physics journals including Indian Journal of Physics and Physica Status Solidi. His scholarly impact is evidenced by an h-index of 8 and 129 citations as of January 2025. Teaching responsibilities encompass a comprehensive physics curriculum, including laboratory instruction and theoretical courses spanning quantum physics, condensed matter, classical mechanics, and mathematical physics. Professional metrics include a YÖKDİL English proficiency score of 75, supporting his international scholarly engagement.