Find Academic Supervisors

• Computer Vision
• Pattern Recognition
• Facial Analysis
• +5 more

Jorge Manuel M. C. Pereira Batista is an Associate Professor at the Department of Electrical and Computer Engineering , University of Coimbra, Portugal. He serves as a senior researcher at the Institute for Systems and Robotics (ISR-UC) and leads the Computer Vision Group. His career spans academic roles, research coordination, and industry collaboration. Academic Affiliation: University of Coimbra (Electrical & Computer Engineering Department) Research Institute: Institute for Systems and Robotics (ISR-UC) His research focuses on Computer Vision , Pattern Recognition , and applications of Differential Geometry in these fields. Key subdomains include facial analysis, visual surveillance, real-time vision systems, and machine learning integration. From 2010–2023, his recent publications highlight advancements in probabilistic models , transformer architectures , multi-branch learning , and biomimetic robotics . He has coordinated multiple funded projects such as: STORK : Avian protection systems NeuroCity : Intelligent street lighting 4D Facial Dynamics : Identity recognition iTRAFFIC : BRISA highway traffic monitoring His work bridges theoretical innovation (e.g., Riemannian manifold applications) with practical deployments in transportation, energy, and healthcare sectors.

• Database Systems
• Distributed Data Management
• Concurrency Control
• +5 more

Alan D. Fekete is a Professor at the University of Sydney's Department of Computer Science, specializing in database systems, distributed data management, and consistency models. His work spans transaction processing, cloud computing, and query optimization, with recent focus on enhancing database concurrency and serializable execution. Key Research Areas: Database Concurrency & Transaction Isolation Multicore Scalability & Distributed Systems Cloud Data Consistency & Replication Query Optimization & NoSQL Performance Recent publications (2023-2025) explore transactional frameworks for analytical interfaces, DB-OS co-design for data ingestion, and mixed isolation levels for serializable execution. Earlier works (2018-2014) address scalable lock managers, coordination avoidance in databases, and consistency properties in cloud storage. He has contributed to educational initiatives, including a data-centric computing curriculum (2021) and teaching threading concepts (2008). Collaborations include co-authors like Nancy Lynch, Uwe Röhm, and Joseph Hellerstein.

Pascal Mark GygaxView profile

Researcher

• Psycholinguistics
• Gender Studies
• Experimental Linguistics
• +4 more

Pascal Mark Gygax is a faculty member at the University of Fribourg , specifically within the Faculty of Philosophy under the Department of Psychology . His academic career spans psycholinguistics, cognitive psychology, and gender studies, focusing extensively on how language structures influence gender perceptions and cognitive biases. With a research profile marked by experimental methodologies, Gygax has published 64 works, including a 2021 book Does the Brain Think Masculine? that critically examines the psycholinguistic impacts of gender-fair language reforms. Role: Researcher at Department of Psychology, University of Fribourg Key Collaborations: Sandrine Zufferey, Ute Gabriel, Anton Öttl Research Focus: Gygax investigates the cognitive mechanisms behind gender representation in language, particularly how grammatical gender systems (e.g., French, German) perpetuate male-dominated mental models. His work explores: Experimental validation of gender-neutral pronouns Discourse connective processing across age groups Impact of language reform on occupational stereotypes Cross-linguistic comparisons of gender perception Implicit bias in performance evaluation (e.g., magic tricks) Recent Publications (2023-2025) demonstrate methodological rigor in studying: Neological intuition in Romance languages Temporal focus and spatial cognition Connective mastery in L2 contexts Participant variability in experimental linguistics Gender ratio norms across global languages Pragmatic constraints on causal connectives Scientific Contributions: While no explicit awards are listed, Gygax's work has significantly advanced: Development of experimental paradigms for gender perception studies Creation of multilingual datasets on role noun norms Validation of facial feedback mechanisms through collaborative research Understanding of discourse coherence in educational contexts Advising & Collaborations: Though specific students aren't named, Gygax collaborates with: Development of the Routledge Handbook of Experimental Linguistics Leadership in SNSF-funded projects Contributions to debates on inclusive language policies

• Macroeconomics
• Monetary and Banking Economics
• Fiscal Policy
• +5 more

Dr. Sedef ŞEN is an Associate Professor in the Department of Economics at Kastamonu University 's Faculty of Economics and Administrative Sciences. With a PhD in Economics from Yıldız Technical University (2017) and a Pre-Doctoral Research Fellowship at the University of Oklahoma (2015-2016), she specializes in Macroeconomics, focusing on Monetary-Banking , Business Cycle Fluctuations , and Fiscal Policy . Education: PhD (2017), Yıldız Technical University, Economics Pre-Doctoral Research Fellowship (2015-2016), University of Oklahoma, Political Science MA (2011), Istanbul University, Economic Policy BA (2009), Süleyman Demirel University, Economics Her research explores the interplay between financial development , economic growth , and political dynamics , including studies on credit composition, infrastructure impacts, and party ideology effects on fiscal policy. Her recent publications employ advanced econometric techniques like Bootstrap Panel Causality to analyze these relationships in Turkey and cross-country contexts. Scientific Contributions include international and national journal articles, book chapters, and conference presentations. She has supervised 7 master's theses on topics ranging from banking systems to corruption economics. Her current work at Kastamonu University continues to examine macroeconomic policy and growth determinants, with a recent postdoctoral focus on Energy and Climate Policy at Duke University's Nicholas Institute (2025).

Ashutosh BhaveView profile

Assistant Professor

• Quantitative Marketing
• Econometrics
• Machine Learning Applications in Marketing
• +4 more

Ashutosh Bhave is an Assistant Professor in the Department of Marketing at the University of Arkansas Walton College of Business . His research focuses on quantitative marketing, causal inference in policy analysis, and machine learning applications to consumer behavior. Education : PhD in Quantitative Marketing (UT Dallas), MS in Information Technology and Management (UT Dallas), BE in Information Technology (Pune University) Industry Experience : Worked at Digital Room, Inc. and Cognizant Technology Solutions Teaching : Undergraduate Marketing Research, Graduate Marketing Analytics His research combines econometric modeling with machine learning to analyze quasi-experimental datasets. Key areas include: Free shipping policy impacts in online retailing Social media brand conflicts and offline sales effects Substance use policy interactions (marijuana legalization vs cigarette sales) Psychedelics decriminalization effects Course modality impacts in business education Public policy evaluation through consumer data Publications demonstrate methodological expertise in: Quasi-experimental design Time-series analysis Causal inference techniques Machine learning integration Data-driven policy evaluation Consumer behavior modeling

Oliver FalckView profile

Research Professor

• Innovation
• Economic Growth
• Economic Development
• +2 more

Oliver Falck is a Research Professor at the Halle Institute for Economic Research (IWH) since March 2014 and holds the Chair of Economics, specifically Empirical Innovation Economics, at LMU Munich. He serves as Director of the ifo Center for Industrial Organisation and New Technologies and Programme Director of the CESifo Research Network. Current Positions: Research Professor (IWH), Professor of Economics (LMU Munich) Leadership Roles: Director (ifo Center), Programme Director (CESifo Research Network) Research Focus: His work centers on innovation, economic growth, entrepreneurship, and the intersection of technology with labor markets. Key themes include the impact of ICT skills on labor outcomes and the role of job training in mitigating automation risks. Scientific Impact: His recent publications analyze automation risk reduction through job training and the economic returns to ICT skills. These studies use cross-country data and instrumental-variable models to explore technology-induced labor market dynamics. Contributions: His research highlights mechanisms connecting digital skills, task composition, and wage outcomes, with findings on gender differences and age-related effects in training efficacy. He employs advanced methodologies like entropy balancing for causal inference in labor economics.

Chun-Biu LiView profile

Associate Professor

• Computational Mathematics
• Statistical and Computational Methods in Biophysical Systems
• Information Theory
• +4 more

Chun-Biu Li is an Associate Professor at the Department of Mathematics , Stockholm University , specializing in computational mathematics and statistical physics of biophysical systems. His research bridges information theory, machine learning, and nonequilibrium statistical mechanics to understand complex biological processes. Education: PhD in mathematical & statistical physics from the University of Texas at Austin (supervised by Ilya Prigogine), M.S. in mathematical physics from the University of Utah. Academic Experience: Associate Professor (2016–present) at Stockholm University, Associate Professor (2008–2016) at Hokkaido University, and JST/CREST Researcher (2005–2008) at Kobe University. Research Interests focus on data-driven statistical analyses, nonequilibrium biophysical systems, AI explainability, and fluctuation theorems. His work applies these methods to plant morphogenesis, molecular motor dynamics, and machine learning applications in life sciences. Teaching includes advanced courses on deep learning, reinforcement learning, and statistical methods for life science applications. His Supervision has guided over 30 students in topics ranging from protein mutation modeling to causal inference algorithms. Scientific Awards: Professional Development Award, University of Texas at Austin (2003) Summer Research Fellowship, University of Texas at Austin (2001) National Dean's List for Outstanding College Students (1997) Publications (110+) highlight his contributions to plant morphogenesis, single-molecule analysis, and statistical methods. Recent works examine DNA barcode clustering, rotary motor protein dynamics, and shape-aware data visualization techniques.

Yonggang LiuView profile

Associate Professor

• Ocean Circulation
• Coastal Ocean Observing
• Numerical Modeling
• +7 more

Dr. Yonggang Liu is an Associate Professor at the University of South Florida College of Marine Science , specializing in Physical Oceanography . He leads the Ocean Circulation Lab and focuses on coastal ocean dynamics, air-sea interactions, and environmental applications. Education: PhD in Physical Oceanography from University of South Florida, Postdoctoral work at University of Washington Email: yliu@usf.edu His research interests include: Coastal ocean circulation and Loop Current interactions Real-time monitoring systems (COMPS, TBON, HF Radar) Numerical modeling (WFCOM, TBCOM, EFCOM) Harmful algal bloom prediction (Karenia brevis) Storm surge and Sargassum tracking Pollutant/oil spill transport modeling Recent publication trends show expertise in: Coastal ocean model validation Eddy-resolving numerical simulations Machine learning applications (Self-Organizing Maps) Marine environmental hazard response Multi-decadal circulation analysis Hydrodynamic-biogeochemical coupling He contributes to scientific leadership as: Editor for Artificial Intelligence for the Earth Systems Guest Editor for Ocean Science Science Committee member at SECOORA

• Engineering Education
• Transition from Secondary to Higher Education
• Learning Analytics
• +4 more

Tinne De Laet is a Professor at the Faculty of Engineering Sciences, KU Leuven. She leads student guidance initiatives and contributes to educational policy through roles in disciplinary bodies and committees. Her research intersects engineering education, learning analytics, and artificial intelligence in pedagogy. Professor, Faculty of Engineering Sciences, KU Leuven Head of Student Guidance Engineering Sciences Member, KU Leuven Institute for Digital Society (DigiSoc) Member, KU Leuven Institute for Artificial Intelligence (Leuven.AI) Member, KU Leuven Institute for Educational Research (LIVO) Her research focuses on improving academic transitions, leveraging learning analytics for student support, and integrating AI into educational frameworks. Recent projects include: Co-promotor for causal pathology modeling in cerebral palsy (2025-2028) Promotor for concept mastery in differential equations (2025-2029) Promotor for LLM applications in education (2025-2029) Promotor for AI explainability in learning analytics (2024-2028) Co-promotor for AI explainability in learning analytics (2024-2028) Her publications highlight innovations in learning dashboards, ethical AI adoption, metacognitive scaffolding, and lifelong learning competencies. She actively shapes educational policy through curriculum committees and large-scale assessment frameworks.

Akanksha NegiView profile

Lecturer

• Econometrics
• Causal Inference
• Experimental Economics
• +3 more

Akanksha Negi is a Lecturer (Assistant Professor) in the Department of Econometrics and Business Statistics at Monash University, Australia. Her academic journey includes a PhD in Economics (2020) from Michigan State University, preceded by a BS and MS in Statistics from the University of Delhi, India. Education: PhD in Economics, Michigan State University (2020) BS and MS in Statistics, University of Delhi (India) Research Interests focus on Econometrics, particularly Causal Inference and Experimental Design. Her work addresses methodological challenges in treatment effect estimation, including misclassification, heterogeneity, and missing data, with applications to agricultural economics and network transaction costs. Trends in Publications highlight contributions to Difference-in-Differences, Doubly Robust Estimation, and M-Estimation frameworks. She also explores dynamics in agricultural markets, aligning with UN Sustainable Development Goals (SDGs) related to poverty reduction and economic prosperity.

Wolfgang SpohnView profile

Professor

• Epistemology
• Philosophy of Science
• Induction and Causation
• +11 more

Wolfgang Spohn, born in 1950, is a distinguished Professor of Philosophy at the University of Konstanz. He has served as editor-in-chief of Erkenntnis for over 13 years and is recognized as one of Germany's most prominent analytic philosophers and philosophers of science. His academic work spans multiple disciplines within philosophy, with particular emphasis on formal approaches to philosophical problems. Spohn's research interests encompass epistemology and philosophy of science, particularly induction and causation; ontology and metaphysics; philosophy of language and philosophy of mind; logic, philosophical logics, and philosophy of logic and mathematics; and action theory, decision theory, game theory, social choice theory, and the theory of practical rationality. His most significant contribution is the development of ranking theory, which provides a formal framework for understanding belief dynamics and has profound implications for numerous philosophical domains including causation, lawlikeness, dispositions, and the structure of scientific reasoning. His recent publications demonstrate a continued focus on ranking theory applications, epistemic justification, causation, and decision theory. Spohn's work consistently bridges formal methodology with deep philosophical insights, exploring how epistemic states relate to objective features of the world. Lakatos Award (2012) for his book 'The Laws of Belief' Frege Prize recipient for contributions to analytic philosophy Spohn has supervised an extensive number of doctoral and habilitation projects, mentoring scholars who have gone on to professorial positions at institutions worldwide. His supervision spans topics in epistemology, philosophy of science, logic, and decision theory. His research is supported through various projects including the Reinhard Koselleck Project, Logic in Philosophy, and collaborations on Relevance Theory of Meaning and Causality and Probability. His work continues to shape contemporary debates in formal epistemology and the philosophy of science.

Sam PowerView profile

Lecturer

• Computational Statistics
• Monte Carlo Methods
• Markov Chain Monte Carlo (MCMC)
• +4 more

Sam Power is a Lecturer in the School of Mathematics at the University of Bristol . He holds a PhD in Mathematics from the University of Cambridge (awarded January 2021) and an MMath. His research focuses on computational statistics, Monte Carlo methods, and probabilistic modeling. Education PhD, University of Cambridge (30 Aug 2016 – 30 Jan 2021) MMath, University of Cambridge Research Interests Dr Power’s work lies at the intersection of probability theory , statistics , and machine learning . He investigates advanced Monte Carlo techniques including Markov Chain Monte Carlo (MCMC), particle methods, and piecewise-deterministic Markov processes. His recent projects explore convergence guarantees via functional inequalities such as Poincaré and log-Sobolev inequalities, state-space models for online learning, and uncertainty quantification. Publication Trends Across 20+ publications (2019–2025), Power has consistently advanced theoretical understanding and practical performance of sampling algorithms. Key themes include error bounds for particle and gradient-based methods, weak Poincaré inequalities, and applications in machine-learning systems such as online skill rating and Bayesian active learning. Scientific Awards No awards explicitly listed in the provided material. Students & Grants No explicit information on supervised students or funded grants is present. Labs & Teams Dr Power is affiliated with the School of Mathematics at Bristol; no specific laboratory or research group name is provided.

• Econometrics
• Applied Microeconomics
• Quantitative Methods
• +3 more

Daniel Gutknecht, Ph.D., is a Professor in the Department of Economic Policy & Quantitative Methods (EQ) at the Faculty of Economics, Goethe University Frankfurt am Main. His academic work spans econometrics, applied microeconomics, and quantitative methods, with a focus on causal inference and time series analysis. Econometrics Methodology Quantile Regression Panel Data Analysis Nonlinear Models Recent research contributions include advanced econometric techniques such as staggered adoption DiD designs, sparsity tests for high-dimensional regressions, and intercept estimation in nonlinear selection models. His publications address critical challenges in quantile forecast optimality, nowcasting monotonicity, and heaped duration data modeling, reflecting interdisciplinary applications in public health and macroeconomic policy. Current teaching includes Advanced Econometrics 1 and Fundamentals of Econometrics for the Winter semester 2025/26. Contact details: Office RuW 3.211, Theodor-W.-Adorno-Platz 4, Frankfurt am Main; email: gutknecht@wiwi.uni-frankfurt.de .

• (Applied) microeconomics
• Experimental and Behavioral Economics
• Labor Economics
• +4 more

Wladislaw Mill is a non-tenured Assistant Professor of Behavioral Economics in the Department of Economics at the University of Mannheim, Germany. His research investigates the intersection of morality and economic systems, focusing on the "dark side" of human behavior including discrimination, corruption, power abuse, tax evasion, war experiences, and spiteful economic decisions. Mill's research program spans Applied Microeconomics, Experimental and Behavioral Economics, Labor Economics, Political Economy, Public Economics, Economic Theory, and Economics of Crime. He employs a methodological toolkit combining theoretical modeling with laboratory, online, and field experiments, supplemented by big-data approaches (web-scraping) and machine learning tools (computer vision) to establish causal relationships in complex social settings. His work addresses critical questions about how discrimination shapes job networks, what drives power abuse, how war experiences affect religiosity, and how spiteful preferences manifest in economic behavior. His recent publications (2021-2025) reveal a cohesive focus on experimental investigations of destructive social dynamics, norms, and behavioral anomalies. Key thematic clusters include spite in strategic interactions (auctions, litigation), discrimination in professional contexts, the socio-psychological impacts of conflict and war, and the economic consequences of polarization. This body of work consistently bridges theoretical innovation with empirical validation through diverse experimental methodologies. Scientific Awards: No awards were mentioned in the provided text. Advising and Grants: The available documentation does not specify doctoral advisees, research grants, or funding sources. Labs and Teams: Mill is affiliated with the Collaborative Research Center TR 224 (CRC TR 224) at the University of Bonn as indicated in their member directory, while maintaining his primary appointment at the University of Mannheim. His research leverages both institutional environments for experimental and field-based investigations.

Ladan ShamsView profile

Professor

• Multisensory Perception
• Bayesian Causal Inference
• Computational Neuroscience
• +7 more

Ladan Shams is a Professor in the Department of Psychology , Department of BioEngineering , and Neuroscience Program at the University of California, Los Angeles (UCLA), where she directs the Multisensory Perception Laboratory . Her research explores how the brain integrates sensory information into coherent perceptions, combining behavioral studies, mathematical modeling, and computational approaches. Academic Affiliation: Department of Psychology, BioEngineering, and Neuroscience Program at UCLA Lab: Multisensory Perception Laboratory Research Focus: Dr. Shams investigates multisensory integration , Bayesian causal inference , perceptual learning , memory , and neural mechanisms of sensory processing. Recent work examines how crossmodal interactions influence memory, body perception, and aesthetic evaluation. Publications: Her 15 most recent articles (2022–2025) address topics like Bayesian causal inference , BCI tools , sensory precision , and perceptual learning , reflecting her computational and experimental approach to multisensory research. Scientific Recognition: Dr. Shams received the UCLA Undergraduate Research Faculty Mentorship Award (2021) and serves as Associate Editor for Psychonomic Bulletin & Review , Multisensory Research , and Frontiers in Integrative Neuroscience . Students: Mentored graduate students like Charlotte Kelly (NDSEG Fellow), Haocheng (BCI workshop organizer), and Sashel Haygood (NSF GRFP Honorable Mention) Funding: Supported by NSF, NIH, and DARPA grants Media: Featured in Science Friday , NPR , and ESPN for the Jersey Study