Find Academic Supervisors

David PoeppelView profile

Professor

• Auditory Cognition
• Speech Perception
• Neuroscience
• +3 more

David Poeppel is a Professor of Psychology and Neural Science at New York University (NYU), affiliated with the College of Arts and Science. He holds a PhD and BS from MIT, with postdoctoral training at UCSF. His research focuses on auditory cognition, speech perception, and the neural basis of language, employing techniques like MEG, EEG, and fMRI. Key interests include the temporal dynamics of speech processing, neurophysiological mechanisms of lexical access, and multisensory integration in language. Education: PhD (1995) and BS (1990) in Psychology/Cognitive Science from MIT. Positions include Professorships at NYU (2009–present) and University of Maryland (1998–2009). Awards include a 2004 American Academy Fellowship and a 2003–2004 Berlin Wissenschaftskolleg Fellowship. Research trends emphasize neural entrainment to speech structures, auditory-motor coupling, and the interplay between perception and production. Recent work explores how temporal rhythms shape auditory processing and how brain rhythms predict speech tracking variability. The Poeppel Lab also investigates musical perception and the neural underpinnings of vocal emotion. Publications span over 200 peer-reviewed articles, with recent contributions on spectrotemporal modulation, neural chunking in language, and the role of amplitude modulation in distinguishing speech from music. His work bridges cognitive science, neuroscience, and clinical applications, such as stuttering mechanisms and speech rehabilitation.

• Political Institutions
• Political Economy
• Media and Politics
• +3 more

Kevin DeLuca is an Assistant Professor of Political Science at Yale University and a Resident Fellow at the Institution for Social and Policy Studies (ISPS). He is also a Faculty Affiliate at the Center for the Study of American Politics (CSAP). His research focuses on political institutions, the political economy of media, and election laws, particularly examining the role of local newspapers in shaping political outcomes. DeLuca holds a Ph.D. in Political Economy and Government from Harvard University (2023), an M.A. in Economics from the University of Texas at Austin (2015), and a B.A./B.S. in Economics and Psychology from the same university (2014). He teaches courses such as 'Data Analytics for Redistricting and Voting Rights' and 'Regulating Elections: Voting Rights and Election Law.' His work intersects with computational methods in redistricting analysis and the influence of media on electoral processes. Previously, he collaborated with institutions like the MIT Election Data and Science Lab (MEDSL) and the Stanford-MIT Healthy Elections Project. His research emphasizes methodologies like Bayesian geocoding for redistricting validation and explores partisan dynamics in gerrymandering solutions. He has contributed to groundbreaking studies on candidate quality measurement via media endorsements and the impact of top-tier elections on down-ballot races.

Andrew KernerView profile

Associate Professor

• International Relations
• Political Economy of Finance
• Foreign Investment
• +5 more

Andrew Kerner is an Associate Professor in the Department of Political Science at Michigan State University (MSU), specializing in the politics of international business, finance, and trade. He holds a PhD in Political Science from Emory University, focusing on corporate governance and securities law reform. His research examines foreign investment, multinational production, investor-state dispute settlement, financialization, and pension reform's political consequences. Kerner has taught at MSU since joining from the University of Michigan, where he was previously an assistant professor. His work spans journals like International Organization and British Journal of Political Science , with recent focus on gender dynamics in central banking and the political economy of economic data. He is also involved in methodological contributions to political science education. Kerner’s research emphasizes globalization’s societal impacts, including how traditional gender roles influence opposition to economic integration and how offshore production shapes public trade policy attitudes. Key themes include the interplay between financial institutions and political systems, regulatory frameworks for international investment, and the societal implications of economic policy shifts. His interdisciplinary approach bridges comparative politics and international relations, addressing both theoretical and applied questions in global political economy.

Renato PajarolaView profile

Professor

• Computer Graphics
• Scientific Visualization
• 3D Modeling
• +5 more

Prof. Dr. Renato Pajarola is the Head of the Visualization and MultiMedia Lab at the Department of Informatics, University of Zurich. His research focuses on computer graphics, scientific visualization, and geometric processing, with applications in 3D scanning, point cloud analysis, and real-time rendering. He leads a team developing advanced visualization techniques for high-dimensional data, parallel rendering frameworks, and interactive systems for complex datasets. Key research areas include: 3D reconstruction of indoor environments Tensor approximation for volume visualization Interactive ray tracing and point cloud processing Parallel rendering frameworks (e.g., Equalizer) Scientific computing and sensitivity analysis His recent publications emphasize: High-dimensional data exploration using tensor methods Efficient rendering techniques for large-scale point clouds Integration of citizen-reported weather data for environmental analysis Prof. Pajarola’s lab collaborates on projects like VIAN (visual annotation tool for film analysis) and Terrender (web-based terrain visualization). His Erdős number is 3, reflecting interdisciplinary research connections in mathematics and computer science.

Nikita KarpenkoView profile

Professor

• Algebraic Geometry
• Algebra
• Quadratic Forms
• +3 more

Nikita Karpenko is a Professor at the Department of Mathematical and Statistical Sciences, University of Alberta. His research focuses on algebraic geometry, quadratic forms, algebraic groups, and motivic cohomology. He has advised six Ph.D. students, including Jean-Paul BONNET and Eoin MACKALL. His work spans topics like Chow groups, motives, and cohomological invariants of algebraic varieties. His recent publications explore advanced algebraic structures such as upper motives of reductive groups, twisted Poincaré duality, and quadratic forms in fundamental ideals. He has presented at numerous conferences, including the Fields Institute Workshop on Exceptional Algebras and Groups (2012), the Brauer Group Conference (2015), and the International Conference on the Algebraic and Arithmetic Theory of Quadratic Forms (2013). His research bridges algebraic geometry with number theory and topology, contributing to foundational questions in quadratic form theory and algebraic cycles.

Barbara FischerView profile

Lecturer

• Evolutionary Medicine
• Obstetric Selection
• Pelvic Evolution
• +4 more

Barbara Fischer is an Elise Richter Fellow and Lecturer at the University of Vienna, Department of Evolutionary Biology. Her research investigates the evolutionary biomechanics of human childbirth, combining geometric morphometrics, comparative anatomy, and evolutionary modeling to resolve the 'obstetric dilemma'. Key contributions include the cliff-edge model of obstetric selection explaining rising Caesarean rates, analyses of sexual dimorphism in hominin pelves, and methods for skeletal age estimation using pubic symphysis morphology. Comparative work extends to Darwin's finches' self-medication behaviors and stickleback adaptation plasticity. She develops statistical approaches for morphological integration studies and teaches biostatistics, mathematical biology, and evolutionary medicine. Recognized with an Elise Richter Fellowship and science communication awards.

Rajiv McCoyView profile

Assistant Professor

• Computational Genomics
• Human Evolution
• Reproductive Genetics
• +3 more

Rajiv McCoy is an Assistant Professor in the Department of Biology at Johns Hopkins University (JHU). He holds a PhD in Biology from Stanford University and completed postdoctoral training at Princeton University and the University of Washington. His research integrates computational and statistical approaches to study human evolution, genetics, and reproduction, with a focus on genomic mechanisms underlying aneuploidy, embryo development, and somatic evolution. The McCoy Lab is affiliated with JHU’s Cell, Molecular, Developmental Biology, and Biophysics (CMDB) doctoral program. Key research interests include understanding how germline and somatic evolution shape genome function and reproductive outcomes. The lab employs advanced genomic methods to analyze chromosomal instability, recombination patterns, and the genetic basis of aneuploidy in human embryos. Recent work has explored maternal meiotic recombination, genomic mosaicism, and the evolutionary implications of Neanderthal introgression. Lab members have presented at conferences such as Cold Spring Harbor’s Biology of Genomes and the Broad Institute’s Mutations in Time and Space. Notable collaborations include studies with the Preimplantation Genetic Diagnosis International Society (PGDIS) and the Origins of Aneuploidy Research Consortium (OARC). The lab actively engages in genomic benchmarking, pangenome research, and the development of improved reference genome tools.

• Genomics
• Bioinformatics
• Statistical Genetics
• +5 more

Dr. John Shaffer is an Assistant Professor at the University of Pittsburgh School of Dental Medicine, specializing in genetic research. His work focuses on applying statistical and bioinformatics methods to understand genetic contributors to complex diseases like orofacial clefts, dental caries, and craniofacial phenotypes. He explores epigenetic mechanisms, gene-environment interactions, and 3D morphological analysis. Education: PhD in Human Genetics, University of Pittsburgh (2008). Research interests include: Heritability and linkage analysis Genetic architecture of craniofacial traits Epigenomic studies in cancer and neurotrauma recovery Public health disparities in oral care Genetic epidemiology of dental diseases Publications highlight advancements in: Cranial vault morphology genetics Orofacial cleft risk loci identification Genetic basis of dental caries Environmental influences on oral health Collaborations include the GLIDE2 oral health genomics consortium and multi-ethnic GWAS initiatives.

Alan MurrayView profile

Professor

• Geographic Information Science
• Spatial Optimization
• Emergency Response Planning
• +5 more

Alan Murray is a **Professor and Vice Chair for Academic Personnel** in the Department of Geography at the University of California, Santa Barbara (UCSB), where he also holds the Yardi Chair in Geography. He previously held professorial roles at Ohio State University, Arizona State University, and Drexel University before returning to UCSB in 2015. Murray earned his BS in Mathematics, Master’s in Statistics and Applied Probability, and PhD in Geography, all from UCSB. His research focuses on **geographic information science (GIScience)**, **spatial optimization**, **emergency response**, **health informatics**, **urban development**, and **infrastructure systems**. He has pioneered methodologies for integrating multi-objective spatial optimization with GIS to address urban planning challenges, such as smart mobility and wildfire risk mitigation. His work emphasizes practical applications in disaster response, public health, and sustainable land use planning. Murray has advised numerous graduate students and contributed to cross-disciplinary initiatives in GIScience education and technology integration. His research has been disseminated through high-impact publications in journals like *Geographical Analysis* and *International Journal of Geographical Information Science*. He has also directed centers such as the Center for Urban and Regional Analysis. Key areas of current research include: GIScience education reform Spatial optimization for emergency response systems Wildfire risk assessment and community resilience Equitable urban planning frameworks His work bridges theoretical advancements with real-world applications, addressing pressing issues like climate adaptation, infrastructure resilience, and smart city design.

Subham KailthyaView profile

Teaching Professor

• Political Economics
• Development Economics
• Firm Productivity
• +5 more

Subham Kailthya is a Teaching Professor in Economics at the University of Warwick, UK. He holds a PhD from the University of Reading, an MSc from the Madras School of Economics, and a BA from the University of Pune. His research focuses on political economics, development economics, and applied microeconometrics, particularly examining how transportation infrastructure impacts firm productivity, political competition influences public service provision, and workfare programs mitigate climate vulnerabilities in India. He has published in journals like World Development and Journal of Comparative Economics , and his work addresses topics such as healthcare prioritization, urban slum public services, and climate resilience. At Warwick, Kailthya leads the EC122: Statistical Techniques A module and lectures in EC902: Econometrics A and EC976: Econometrics. He supervises MSc dissertations and undergraduate projects, and previously taught development economics and microfinance at the University of Reading. His research highlights include analyzing road infrastructure’s role in Indian manufacturing productivity and the electoral incentives shaping healthcare investments. He actively explores the political economy of public provision, spatial interactions in governance, and the socio-economic impacts of weather shocks. Kailthya’s work bridges theoretical models with empirical data, offering insights into governance mechanisms and development challenges in India.

Katherine StorrsView profile

Senior Lecturer

• Visual perception
• Deep learning
• Psychophysics
• +7 more

Katherine Storrs is a Senior Lecturer in the School of Psychology at the University of Auckland, New Zealand. She leads the Computational Perception Lab, where she combines computational modeling and psychophysical experiments to study visual perception. Her research is supported by a Marsden Fast Start grant, and she is actively involved in teaching and academic service. She earned her PhD in Psychological Science from the University of Queensland in 2015 and has held postdoctoral positions at Justus-Liebig University (Germany) and the MRC Cognition and Brain Sciences Unit (Cambridge, UK). She also worked as a Data Scientist at Twitter in London. Dr. Storrs' research focuses on how the visual system interprets material properties such as gloss, shape, and reflectance. She uses unsupervised deep learning models to simulate and predict human perception, particularly in ambiguous or complex visual environments. Her work bridges cognitive science, neuroscience, and artificial intelligence. Her most recent publications explore topics such as gloss perception, mental rotation, face similarity, and the role of statistical learning in shape encoding. These works frequently appear in high-impact journals like Nature Human Behaviour , PNAS , and Current Biology , demonstrating a strong trend toward using computational models to explain perceptual phenomena. Marsden Fast Start Grant (2021) Humboldt Research Fellowship (2019) UK National Finalist, FameLab (2017) Editorial Board Member, Nature Communications Psychology (2023–) Editorial Board Member, OpenMind (2022–) Social Media Editor, Perception and i-Perception (2020–) She supervises graduate students and teaches courses including PSYCH 306 (Research Methods), PSYCH 775 (Visual Perception in Brains and Machines), and PSYCH 109. She also mentors students in honours, master's, and PhD programs. Her lab is actively involved in interdisciplinary collaborations, particularly with researchers in machine learning and computational neuroscience. The lab is funded by the Marsden Fund and supported by access to high-performance computing resources for training deep neural networks.

Chenjuan MaView profile

Assistant Professor

• Health Services Research
• Home Care
• Nursing Workforce
• +12 more

Chenjuan Ma is an Assistant Professor at NYU Rory Meyers College of Nursing, where she conducts health services research focused on optimizing nursing care, patient safety, and outcomes, particularly in home healthcare and among vulnerable populations such as persons with dementia and racial/ethnic minorities. She holds a PhD from the University of Pennsylvania and degrees in nursing from Xi'an Jiaotong University, China. Education: PhD, University of Pennsylvania (2012) MSN, Xi'an Jiaotong University, China (2008) BSN, Xi'an Jiaotong University, China (2005) Her research integrates theories and methodologies from nursing, sociology, medicine, statistics, and data science, with expertise in large datasets and quantitative analysis. She is currently leading a National Institute on Aging-funded project on racial and ethnic disparities in home health care for individuals with Alzheimer’s Disease and Related Dementias. Her work spans health policy, nursing workforce dynamics, care quality, and health equity. Her recent publications (2020–2025) reflect a strong trend in home health care quality, disparities in access and outcomes, geriatric care, mental health, and innovative models like internet-based nursing services. She frequently employs advanced statistical methods and large national datasets to address critical gaps in healthcare delivery and equity. Scientific Awards: Vivian G. Prins Global Scholar, NYU (2021) New Investigator Award, AcademyHealth (2020) Vivian G. Prins Global Scholar, NYU (2020) Columbia University Scholarship (2019) NYU CTSI Fellowship (2018) President Gutmann Leadership Award (2011) ThinkSwiss Award (2011) Rising Star, STTI (2011) She is actively mentoring PhD students and has contributed to policy-relevant research on nurse work environment, staffing, and patient outcomes. Her collaborations span multiple institutions and disciplines, reflecting her interdisciplinary approach. She is a member of AcademyHealth, American Nurses Association, Eastern Nursing Research Society, and Sigma Theta Tau. Her research has significant implications for improving care delivery models, reducing disparities, and shaping health policy, particularly in long-term and home-based care settings.

Michael O'HearView profile

Professor

• Criminal Law
• Sentencing
• Criminal Procedure
• +5 more

Michael O'Hear is a Professor of Law at Marquette Law School, Marquette University, where he has been a faculty member since 2000. He teaches Criminal Law and Criminal Process and is a nationally recognized expert in criminal punishment and sentencing. Education: Yale College – Undergraduate Degree Yale Law School – Juris Doctor (JD), Editor-in-Chief, Yale Journal of Law & the Humanities, Editor, Yale Law Journal Professor O'Hear's research focuses on criminal law, sentencing policy, judicial behavior, and criminal justice reform. His work critically examines the impact of sentencing guidelines, mandatory minimums, plea bargaining, and racial disparities in punishment. He has published extensively on how political, institutional, and procedural factors shape sentencing outcomes and mass incarceration. His scholarly output includes over eighty articles, books, and book chapters. Key themes across his recent publications include judicial discretion, federalism in sentencing, rehabilitation, and the erosion of trial rights due to plea bargaining dominance. His work combines doctrinal legal analysis with empirical and policy-oriented approaches. Scientific Awards and Honors: Robert W. Warren Public Service Award – Eastern District of Wisconsin Bar Association Elected Member – American Law Institute Professor O'Hear has held significant academic leadership roles, including serving as the Law School's first Associate Dean for Research from 2008 to 2015. He has also contributed to public service as a member of the Milwaukee Fire and Police Commission (2010–2016). He is actively involved in professional legal communities, admitted to the Illinois and Wisconsin Bars, and a member of the American Law Institute. He advises graduate and law students in criminal law and sentencing, though specific advisees are not listed. His research has been supported by institutional and scholarly grants, enabling extensive publication and policy engagement. He is affiliated with legal research centers and contributes to national discourse on criminal justice reform through his writings, public service, and academic leadership.

Savannah L. KellyView profile

Associate Professor

• Data Science Education
• Statistical Literacy
• Research Methods
• +7 more

Savannah L. Kelly is Associate Head and Associate Professor in the Scholar Support and Data Services (SSDS) Department at the University Libraries of the University of Mississippi. She plays a key role in advancing data and statistical literacy among students, faculty, and librarians through research, instruction, and collaboration. Her educational background includes a PhD in Higher Education with an Interdisciplinary Minor in Applied Statistics, a Master of Library and Information Science, and a Bachelor of Science in Psychology with a minor in Philosophy. Dr. Kelly's research focuses on promoting data science and statistical competencies in higher education, interdisciplinary research collaborations, and understanding students’ perceptions of STEM majors and careers. She is passionate about improving quantitative research skills and supporting learners through innovative pedagogical approaches. Her recent publications and presentations highlight a strong trend in statistical education, research data services, information literacy, and academic librarianship. She emphasizes accessible data science training, the use of tools like R and Zotero, and the importance of aligning library services with student needs. IRDL Scholar (2016) IRDL Mentor (2018–2020) ACRL Immersion Program (Teacher Track, 2010; Assessment Track, 2012) Excellence in Assessment Award, Westmont College (2012) People’s Choice Award, EBLIP 2017 Dr. Kelly actively mentors students and collaborates across disciplines. She has led workshops and developed programming such as an R workshop series for graduate students. Her work is supported by professional development grants and institutional programs like IRDL. She is a Certified Instructor for The Carpentries, reflecting her commitment to open, reproducible research practices. She contributes to library-led research through projects on student research challenges, faculty-librarian collaboration, and service loads in academic librarianship. Her work helps shape library instruction, research support services, and data science initiatives at the institutional and national levels.

• Statistical Signal Processing
• Array Signal Processing
• Machine Learning
• +12 more

Vicente Zarzoso is a full Professor at Université Côte d'Azur and a Chairholder at the 3IA (Interdisciplinary Institute of Artificial Intelligence), where he conducts research at the intersection of artificial intelligence, signal processing, and biomedical engineering. His work is primarily affiliated with the I3S laboratory, a joint CNRS and Université Côte d'Azur research unit. His research focuses on fundamental aspects of statistical and array signal processing, machine learning, tensor decompositions, L1-norm criteria, blind and semi-blind estimation, source separation, and independent component analysis. These methodologies are applied to critical challenges in biomedical signal processing , including atrial fibrillation analysis, physiological signal modeling, and fetal electrocardiogram extraction, as well as in communications , such as channel identification and equalization. The IAblation project, led by Prof. Zarzoso, aims to develop AI-driven solutions for patient-centered catheter ablation in atrial fibrillation, positioning his work at the forefront of computational medicine. This initiative reflects a strong translational focus, bridging advanced signal processing with clinical cardiology to improve treatment efficacy. While no specific publications or awards are listed in the provided text, his research profile demonstrates a consistent trajectory in developing robust, mathematically grounded AI and signal processing techniques for real-world healthcare applications. His leadership in the 3IA highlights his role in shaping interdisciplinary AI research in France. Scientific Awards: No awards mentioned. Prof. Zarzoso advises students and leads a research team within the 3IA and I3S, though specific advisees are not listed. He is involved in significant research grants supporting AI for integrative computational medicine, particularly through his 3IA Chair. His lab contributes to the Doctoral & Postdoctoral Seminar program, indicating active mentorship and academic leadership. The research is conducted within the I3S laboratory, a key hub for digital sciences at Université Côte d'Azur, and is part of the broader 3IA ecosystem focused on ethical and human-centered AI. His team collaborates across disciplines, integrating expertise from engineering, computer science, and clinical medicine.