Find Academic Supervisors

Anders Olof LarssonView profile

Professor

• Political Communication
• Digital Political Communication
• Social Media
• +7 more

Anders Olof Larsson is a Professor at the School of Communication, Leadership and Marketing at Kristiania University College in Oslo, Norway. Originally from Sweden, he specializes in digital political communication, with particular expertise in social media platforms' role in political processes, journalism, and election campaigns. His research takes a strongly comparative approach across countries, platforms, and time periods. Professor Larsson's research interests focus on political communication in digital environments, with particular attention to how political actors use social media platforms for campaigning and public engagement. His work examines cross-national differences in digital political communication, platform-specific affordances, and longitudinal changes in how political actors utilize emerging technologies. He has conducted extensive research on Facebook, Twitter, Instagram, and newer platforms like TikTok, with special attention to comparative Scandinavian contexts. His recent publications reveal a strong focus on comparative digital political communication across multiple dimensions - comparing different countries' approaches, analyzing various social media platforms' unique characteristics, and examining longitudinal changes in digital campaigning. His work spans theoretical, methodological, and empirical contributions to understanding how digital technologies reshape political communication globally. Professor Larsson actively supervises research and has sought both master's level research assistants and PhD candidates for projects including the 'Scandinavian Political Communication During the Pandemic' initiative. He has organized academic events including the 'Comparative Digital Political Communication' preconference for the International Communication Association. His research is conducted through several collaborative projects including the DigiWorld project and CamforS (Campaigning for Strasbourg), which conducts cross-national comparisons of campaign mobilization in social media. These projects adopt comparative approaches to studying political communication across different contexts and platforms.

Zihao FuView profile

Academic

• Large Language Models
• Natural Language Processing
• Machine Learning
• +7 more

Zihao Fu is a Research Assistant Professor at The Chinese University of Hong Kong (CUHK), specializing in Large Language Models (LLMs) and Natural Language Processing (NLP) . His work bridges computational methods with social sciences, focusing on model instability, repetition, hallucination, and algorithmic fairness. He has held research positions at the Oxford Internet Institute and the Language Technology Lab at the University of Cambridge. Education Ph.D. in Systems Engineering and Engineering Management (2017–2021), CUHK M.Eng. in Aeronautics and Astronautics (2012–2015), Beihang University B.Eng. in Automation Science (2008–2012), Beihang University His research explores the theoretical foundations of LLMs, addressing challenges like repetition , instability , and hallucination . He integrates linguistics , cognitive science , and fairness frameworks to enhance both foundational understanding and real-world applications of language technologies. Recent work includes biomedical NLP applications ( BAND dataset ), parameter-efficient model adaptation, and fairness toolkits ( OxonFair ). Zihao leads projects like BioCaster (disease outbreak monitoring) and CAM-Tool (cloud task distribution). He is actively mentoring postdoctoral researchers at CUHK and CUHK (Shenzhen), with expertise in machine learning , knowledge base integration , and parallel computing systems . His industry experience includes developing distributed algorithms at Alibaba Cloud’s PAI platform.

• Cybersecurity
• Computer Science
• Social Media Analysis
• +5 more

Dr. S. Zannettou is a Researcher specializing in Technology, Policy and Management with a focus on Organisation & Governance. He is an active contributor to the Cybersecurity (TPM) research project, investigating internet security, data governance, and information policy within socio-technical systems. His research spans interdisciplinary domains including: Cybersecurity infrastructure and threat analysis Social media algorithm behavior and user engagement Data donation methodologies for platform studies Toxicity dynamics in online communities Personalization systems in content recommendation Information dissemination patterns Recent publications analyze social media ecosystems through empirical data, examining TikTok's recommendation mechanics, news consumption patterns, and personalization tradeoffs. His work consistently employs computational methods to study platform governance, algorithmic bias, and user behavior across digital environments. He collaborates with international researchers on the Cybersecurity (TPM) project, which investigates: Cyber threat intelligence frameworks Internet infrastructure vulnerabilities Business risk modeling Information control mechanisms

Leigh VanHandelView profile

Associate Professor

• music theory pedagogy
• music cognition
• relationship between music and language
• +3 more

Leigh VanHandel serves as Chair of the Music Theory Division and Associate Professor of Music Theory at the University of British Columbia's School of Music within the Faculty of Arts. Her academic journey includes a B.M. from Ohio State University, an M.M. from SUNY Stony Brook, and a Ph.D. from Stanford University. Dr. VanHandel's primary research focuses on music theory pedagogy, music cognition, the relationship between music and language, and computer-assisted research. Her scholarship seeks to understand how music works and how humans process music, with particular emphasis on applying cognitive research to music theory teaching methods. She investigates how best practices in STEM pedagogy can be adapted to music theory instruction, bridging scientific understanding with practical teaching applications. Her recent publications include The Routledge Companion to Music Theory Pedagogy (2021), which she edited and contributed to, and Oxford University Press's Music Theory Skill Builder , an online drill and practice program. These works reflect her commitment to developing innovative approaches to music education that incorporate cognitive science principles. Dr. VanHandel directs the UBC VanLab, an interdisciplinary research group investigating music cognition, with current projects including the Tempo Project that examines how listeners perceive and process tempo in music. She also founded and hosts the Workshops in Music Theory Pedagogy at UBC, which brings together scholars to discuss current research and practices in the field. Her service extends to editorial boards for Music Theory Spectrum , Music Perception , Empirical Musicology Review , and the Journal for Music Theory Pedagogy , as well as leadership roles in the Society for Music Theory and the Society for Music Perception and Cognition.

Dag SjøbergView profile

Professor

• Software Engineering
• System Development
• IT Systems
• +12 more

Dag Sjøberg is a Professor at the Department of Informatics (Ifi), University of Oslo . He also holds a part-time position at SINTEF Digital . His research focuses on empirical software engineering with emphasis on development processes , agile methodologies , technical debt , and programming skill assessment . Research Interests: Empirical methods (controlled experiments, case studies) Construct validity frameworks Agile and Lean practices Microservices architecture Software quality and maintainability Scientific Achievements: Led Simula Research Laboratory's Software Engineering department ranked #1 globally (2004-2008) Developed Guidelines for Construct Validity in software engineering research Extensive publication record in top venues like IEEE Transactions and Journal of Systems and Software Academic Background: Cand.scient. in Informatics (University of Oslo, 1987) PhD in Software Engineering (University of Glasgow, 1993) Professional Involvement: Co-founder and board member of three IT companies Former research director at Simula Research Laboratory (2001-2008) Current head of the Programming and Software Engineering research section at Ifi

Benedikt SchmitzView profile

Researcher

• Superconductivity
• Laser-Plasma Physics
• Particle Acceleration
• +4 more

Benedikt Schmitz is a PostDoc researcher at the Technical University of Darmstadt, working at the Institute of Nuclear Physics (IKP) and the Theory of Electromagnetic Fields (TEMF). His research spans multiple domains of physics including superconductivity, laser-plasma interactions, and AI-supported modeling of complex physical phenomena. PhD in Physics from Technical University of Darmstadt (2023) Master's research at Helmholtz-Zentrum Berlin (2016-2018) Dr. Schmitz's research focuses on superconductivity, particularly magnetic field interactions with superconductors, and laser-plasma physics for particle acceleration. His work on radiochromic film dosimetry led to pyRES, an open-source evaluation tool. He pioneered AI applications in physics research, developing surrogate models using deep learning for neutron yield prediction and liquid target experiments. His research bridges traditional physics with modern computational approaches, demonstrating how machine learning can transition from research subject to research tool. His publication record shows a clear evolution from superconductivity research toward laser-plasma physics and AI modeling. Early works focused on SRF cavity diagnostics, while recent publications center on laser-driven neutron sources and deep learning applications. This progression reflects his doctoral work and growing expertise in computational physics. His articles demonstrate interdisciplinary approaches combining plasma physics, nuclear engineering, and machine learning to solve complex problems in particle acceleration and detection. First prize at Medtech:Hack with BIOSCAN at CERN (April 2018) Dr. Schmitz has led multiple research projects including SRF Magnetometry during his Master's work, Neutron Prediction and TNSA Liquid Leaf for his PhD, and ongoing development of pyRES. His BIOSCAN detector project resulted in a patent and demonstrates his ability to translate physics concepts into medical applications. He has developed software tools like LabTab for electronic lab journals and maintains active GitHub repositories for his research code. His projects consistently combine experimental work with computational modeling and increasingly incorporate machine learning approaches. His research is conducted within collaborative teams including the TEMF group at TU Darmstadt under Prof. Boine-Frankenheim for his doctoral work, and previously with Prof. Jens Knobloch's group at Helmholtz-Zentrum Berlin. His work spans multiple laboratories and computational environments, utilizing particle-in-cell simulations, Monte Carlo methods, and deep learning frameworks to advance understanding in his fields of interest.

Daniel BarretoView profile

Professor

• Discrete Element Method (DEM)
• Soil Mechanics
• Geotechnical Engineering
• +5 more

Daniel Barreto is a Professor at Edinburgh Napier University , specializing in Discrete Element Method (DEM) simulations and soil mechanics . His research emphasizes particle shape and size distribution effects on granular material behavior, with applications in permeability estimation, liquefaction mitigation, and nature-inspired ground engineering. Education : PhD in Soil Mechanics (Imperial College London, 2010), MSc in Soil Mechanics and Engineering Seismology (Imperial, 2005), Civil Engineering (Universidad de los Andes, 2003). Research : Focuses on DEM, grading entropy theory, and particle-scale interactions in sand-rubber mixtures, with implications for seismic isolation and sustainable soil stabilization. Awards : Royal Academy of Engineering Leverhulme Trust Fellowship COST Action Chair for Open Network on DEM Simulations (ON-DEM) Emeritus Member of Royal Society of Edinburgh Young Academy of Scotland Publications : Pioneering studies on DEM-based critical state behavior, particle breakage quantification, and permeability models for granular soils, with a 2023 Transportation Geotechnics paper on hydraulic radius applications. Collaborations : Leads ON-DEM, a global network advancing open-source DEM tools, and contributes to interdisciplinary projects involving synthetic root mimics and microbial soil interactions.

• Econometrics
• Nonparametric Estimation
• Causal Inference
• +4 more

Christoph Breunig is a Professor in the Department of Economics at the University of Bonn. His work bridges theoretical econometrics with empirical applications, focusing on nonparametric methods, instrumental variable modeling, and causal inference. His research addresses challenges in high-dimensional data, missingness mechanisms, and treatment effect estimation. University: University of Bonn Department: Economics Academic Rank: Professor Email: cbreunig@uni-bonn.de Research Trends: Nonparametric and semiparametric estimation techniques Applications of instrumental variables in causal inference Handling missing data and measurement error High-dimensional statistical models with economic applications Specification testing in complex regression frameworks Connections between microeconomic theory and empirical methods

Kai ReimersView profile

Professor

• Business Information Systems
• Organization Theory
• Industry-wide Information Infrastructures
• +4 more

Kai Reimers is a Professor of Business Information Systems at RWTH Aachen University's School of Business and Economics. He has held this position since September 2003 and previously served as a guest professor at Tsinghua University's School of Economics and Management in Beijing from 1998 to 2003 with support from the German Academic Exchange Service (DAAD). Professor Reimers received his education in business sciences in Germany, earned his doctorate in economics and business administration from the University of Wuppertal, and completed his habilitation at the University of Bremen. His academic career spans over two decades with a focus on the intersection of business information systems and organization theory. His research primarily focuses on: Development of industry-wide information infrastructures Development of IT standards Development of enterprise-wide information systems Professor Reimers' work examines how economic activities organization affects Electronic Business and vice versa, with the ultimate goal of better designing and managing inter-organizational information systems (IOIS). His research spans from foundational work on electronic markets in the 1990s to contemporary studies on digital transformation, data governance, and healthcare information systems. His recent publications (2024-2025) address cutting-edge topics including applying boundary object theory to medical prescriptions in digital healthcare contexts and proposing ownership-based approaches for data market compatibility aligned with EU privacy and antitrust objectives. Professor Reimers leads the Research Group Electronic Business, which is part of the School of Business and Economics at RWTH Aachen University and closely associated with the Computer, Learning and Teaching Space (CLeVer) of the Faculty. The group focuses on diverse aspects of Electronic Business, particularly the electronic support of inter-organizational business processes through information technology.

Lorenzo GarlappiView profile

Professor

• Asset Pricing
• Credit Risk
• Real Options
• +4 more

Lorenzo Garlappi is the TSX Venture Exchange Professor of Finance at the Sauder School of Business, University of British Columbia. He holds a PhD from UBC, a Doctorate from the University of Trieste, and a BS in Economics from Bocconi University, Italy. His research focuses on asset pricing, credit risk, real options, and portfolio choice, with applications to corporate finance and investment strategies. Education: PhD in Finance, University of British Columbia (UBC) Doctorate in Economics, University of Trieste, Italy BS in Economics, Bocconi University, Milan, Italy Research Interests: Garlappi explores theoretical and empirical aspects of financial markets, including: Credit risk dynamics and debt issuance strategies Monetary policy impacts on investment behavior Climate change effects on real estate pricing Optimal portfolio diversification under uncertainty Real options in corporate decision-making Awards & Recognition: Dimensional Fund Advisors Distinguished Paper Award (2021) Best Paper Award at ASU Sonoram Winter Conference (2019) Summer Haven Investment Management Prize (2019) Crowell Memorial Prize (2010) Teaching & Contributions: Teaches Risk Management and Financial Engineering at Sauder. His work bridges academic rigor and practical finance, offering frameworks for addressing market inefficiencies and uncertainty. He collaborates with industry practitioners to refine asset allocation strategies and corporate finance policies. Labs & Teams: Leads research initiatives at Sauder’s Finance Division, focusing on computational finance, corporate governance, and sustainable investing. Engages in interdisciplinary projects with economics and environmental science departments.

Serkan GugercinView profile

Professor

• Model Reduction
• Dynamical Systems
• Numerical Analysis
• +6 more

Serkan Gugercin is the Class of 1950 Professor of Mathematics and Deputy Director of the Division of Computational Modeling and Data Analytics (CMDA) at Virginia Tech's College of Science. He is also affiliated with the Department of Mechanical Engineering. His research focuses on model reduction, dynamical systems, numerical analysis, and scientific computing, with applications in engineering and data-driven methods. Gugercin has held prestigious titles such as the A.V. Morris Professorship (2016–2019) and received awards like the NSF Early CAREER Award (2007) and Alexander von Humboldt Fellowship (2016). He earned his Ph.D. in Electrical Engineering from Rice University (2003) and has secured over $5.5M in research funding. His work bridges numerical methods, control theory, and optimization, emphasizing high-fidelity reduced models for complex systems. Education: B.S., Middle East Technical University (1997); M.S. and Ph.D., Rice University (1999, 2003). Key contributions include co-authoring the textbook *Interpolatory Methods for Model Reduction* (SIAM) and advancing structure-preserving interpolation techniques for nonlinear systems. Research areas include data-driven modeling, parametric systems, and energy-based approximation methods. Labs/Teams: CMDA Program, part of Virginia Tech’s Academy of Integrated Science. Collaborates on interdisciplinary projects involving power networks, fluid dynamics, and mechanical systems. Active in editorial roles for SIAM Journal on Scientific Computing and Systems & Control Letters.

• Socio-Technical Software Engineering
• Developer Attitudes
• Automation in Software Engineering
• +3 more

Dr. Emily Winter is a Lecturer in Computing and Communications at Lancaster University, part of the School of Computing and Communications (SCC) since 2018. Her research focuses on socio-technical aspects of software engineering, including developer attitudes toward automation, human values in SE, and diversity in computing education. She holds a PhD in Sociology from Lancaster University, an MA in Sociological Research, and a BA in History. Emily has contributed to projects like the Fixie Project (investigating developer attitudes to automated tools) and the Values in Computing initiative. She is a Fellow of AdvanceHE and has received an ESRC 1+3 award for her postgraduate studies. Her external roles include serving as a Reviewer for Information and Software Technology , Workshop Chair for the International Workshop on Genetic Improvement (2022), and Program Committee member for several conferences. Emily teaches the SCC 130 module and actively engages in research addressing gender dynamics in CS education and ethical software design. Key research interests include qualitative methods in SE, developer-centric tool design, and fostering inclusive educational environments. Her work bridges social sciences and computing, emphasizing empirical studies of human-computer interaction in software development. Emily has published widely on topics like automatic program repair, SAST tool usage, and gender representation in CS. Her awards reflect her commitment to pedagogical innovation and social science contributions to computing. She is affiliated with the Security Lancaster research group and is based at InfoLab21.

Peter HedströmView profile

Professor

• Analytical Sociology
• Social Networks
• Segregation Processes
• +4 more

Professor Peter Hedström is a leading academic at Linköping University (LiU), serving as the founder of the Institute for Analytical Sociology (IAS) and holding a senior research fellowship at Nuffield College, Oxford. He earned his PhD in Sociology from Harvard University and has held professorships at prestigious institutions including the University of Chicago, Stockholm University, and NYU Abu Dhabi. His research focuses on social networks, segregation processes, and the methodology of social sciences, with grants from the European Research Council and Swedish Research Council. Hedström is a fellow of the Royal Swedish Academy of Sciences, Royal Swedish Academy of Letters, and Norwegian Academy of Science and Letters. Research Interests: Hedström’s work explores how social networks influence societal phenomena, particularly segregation. His recent studies challenge traditional views on gender segregation, proposing the 'Trojan-horse mechanism' where networks can reduce segregation. He also investigates urban scaling and regional divides, using computational social science methods. His methodologies combine causal inference, machine learning, and large-scale data analysis. Awards: He received the Robert K. Merton Award for his groundbreaking article on gender segregation and is frequently cited in global rankings. His contributions to analytical sociology have positioned IAS as a hub for computational social science. Grants & Collaborations: Supported by major grants, Hedström leads SweCSS, a computational social science center. He advises students and collaborates with global researchers through visiting programs. The IAS, founded in 2014, drives interdisciplinary research on societal challenges like segregation and urban dynamics. Labs & Teams: As IAS director, Hedström fosters collaboration between social and computational sciences. The institute’s work spans migration, cultural dynamics, and policy analysis, with projects like the SweCSS Visiting Fellows Program enhancing international partnerships.

Or BrookView profile

Associate Professor

• Competition Law and Policy
• Antitrust
• Regulation
• +3 more

Dr. Or Brook is an Associate Professor of Competition Law and Policy at the School of Law, University of Leeds, and Deputy Director of the Centre for Business Law and Practice. They hold interdisciplinary qualifications, including a PhD from the Amsterdam Centre for European Law and Governance, an LLM in European Competition Law from the University of Amsterdam, and degrees in Law and Economics from the Hebrew University of Jerusalem. Research focuses on international EU competition law, antitrust, and empirical legal methods. Notable projects include the Priority Setting Project (funded by ESRC) and a comprehensive study of judicial review in EU competition law. They co-edit the Research Handbook on Abuse of Dominance and lead the UK branch of ASCOLA, contributing to policy discussions through international collaborations. Education: PhD in Law, University of Amsterdam LLM in European Competition Law, University of Amsterdam LLB and BSc in Economics, Hebrew University of Jerusalem Research interests emphasize empirical analyses of legal texts, institutional enforcement practices, and competition law’s intersections with other regulatory frameworks. Recent monograph Non-Competition Interests in EU Antitrust Law (Cambridge UP, 2022) presents novel empirical data on public policy influences in EU competition enforcement. Key awards include the Michael Beverley Innovation Fellowship (associated member), supporting entrepreneurial academic initiatives. Their work bridges law and economics through interdisciplinary methods, advocating for empirical rigor in European legal scholarship.

Rafal KulikView profile

Professor

• Extreme Value Theory
• Time Series Analysis
• Long Memory and Heavy-Tailed Processes
• +4 more

Rafal Kulik is a Full Professor in the Department of Mathematics and Statistics at the University of Ottawa (Faculty of Science). He holds a MSc from Ulm University (Germany) and a PhD from Wrocław University (Poland). Research Interests: Dr. Kulik specializes in Extreme Value Theory, Time Series Analysis (particularly long-range dependence and heavy-tailed processes), Data Privacy (including Differential Privacy), and Statistical Inference. His work bridges theory with applications in econometrics, financial mathematics, risk management, and privacy-preserving data analysis. Recent Contributions: Recent research focuses on clustering of extremes in stochastic processes, statistical foundations of differential privacy, and high-dimensional data analysis. Key methods include bootstrap techniques for tail processes, asymptotic expansions for block estimators, and analysis of regularly varying time series. Advising & Grants: Supervised over a dozen PhD/MSc students and postdocs. Current projects include NSERC grants on Extreme Value Theory and MITACS collaborations on privacy frameworks. Active in benchmarking large language models' privacy risks. Administration: Associate Editor for Extremes , Electronic Journal of Statistics , and others. Member of the University of Ottawa Board of Governors.