Find Academic Supervisors

Silvia LindtnerView profile

Associate Professor

• Science and Technology Studies (STS)
• Cultural Anthropology
• Feminist Studies
• +7 more

Silvia Lindtner is an Associate Professor at the University of Michigan's School of Information and Director of the Center for Ethics, Society, and Computing (ESC). She holds courtesy appointments in the Penny W. Stamps School of Art and Design and the Digital Studies Institute. Her work focuses on the social and cultural study of technology in China and globally, with a focus on data-driven governance, AI ethics, and the intersection of technology and labor. Lindtner has conducted nearly two decades of fieldwork in China, examining innovation ecosystems, digital economies, and the affective dimensions of state control. She is the author of the award-winning *Prototype Nation: China and the Contested Promise of Innovation* (2020) and co-author of *Technoprecarious* (2020). Education: PhD in Information and Computer Sciences from University of California, Irvine; BS/MS in Media Technology and Design from University of Hagenberg, Austria. Research Interests: Science and Technology Studies (STS), China Studies, HCI, Critical Computing, AI Ethics, Data Governance, Labor Studies, and Transnational Digital Economies. She explores how technological systems shape governance, labor practices, and everyday life, particularly in contexts of global inequality and state surveillance. Awards: Joseph Levenson Prize (2021), Francis L.K. Hsu Book Prize (2021), ACM Distinguished Member (2022), and fellowships from the National Committee on US-China Relations (2021-2023) and China-US Scholars Program (2021-2022). Grants: Supported by NSF, IMLS, Intel Labs, Google Anita Borg, and Chinese National Natural Science Foundation. Leads interdisciplinary initiatives including Tech.Culture.Matters research group and Michigan Interactive and Social Computing (MISC) research group. Labs/Teams: Directs the Center for Ethics, Society, and Computing (ESC) and collaborates with the Lieberthal-Rogel Center for Chinese Studies. Current projects include studies on affective control in AI governance and transnational data practices in healthcare and labor.

Suzanne S. LeeView profile

Associate Professor

• Financial Econometrics
• Empirical Finance
• Asset Pricing
• +6 more

Suzanne S. Lee is an Associate Professor of Finance at the Scheller College of Business, Georgia Institute of Technology, where she has been a faculty member since 2005. She also serves as the Ph.D. Coordinator, playing a key role in graduate education and research training. Her educational background is highly quantitative and interdisciplinary: Ph.D., University of Chicago MBA, University of Chicago M.S. in Statistics, University of Chicago Dr. Lee's research lies at the intersection of asset pricing and financial econometrics, with a strong focus on jump processes, market microstructure, and derivative markets. She investigates how sudden price movements (jumps) impact asset returns, risk, and information flow in financial markets. Her work extends to cryptocurrency, currency markets, and carry trade strategies, combining theoretical rigor with empirical validation using high-frequency data. The analysis of her recent publications (2008–2024) reveals a consistent and influential research program centered on detecting and modeling jumps in financial time series. Her work spans equity, currency, and cryptocurrency markets, often employing advanced nonparametric and econometric techniques. A recurring theme is the role of jumps in pricing anomalies, risk measurement, and market efficiency, with increasing attention to digital assets in recent years. Dr. Lee is actively engaged in the academic community through editorial service: Associate Editor, Journal of Banking and Finance Associate Editor, Asia-Pacific Journal of Financial Studies She has presented her research at premier conferences such as the American Finance Association, European Finance Association, Econometric Society, and Society for Financial Econometrics. Her publications appear in the most prestigious journals in finance and econometrics, including the Journal of Finance , Review of Financial Studies , Journal of Financial Economics , and Journal of Econometrics . While specific grant details are not listed, her sustained publication record in top journals indicates significant research funding and academic impact. She advises Ph.D. students through her role as Ph.D. Coordinator, though individual advisees are not named in the text. Dr. Lee's work contributes to both theoretical and applied finance, improving our understanding of market dynamics, risk modeling, and asset pricing under extreme events. Her research has practical implications for risk management, trading strategies, and financial regulation.

Ann B LeeView profile

Professor

• Scientific Machine Learning
• Trust-Worthy UQ
• Likelihood-Free Inference
• +1 more

Ann B. Lee is a Professor and Co-Director of the PhD Program in Statistics at Carnegie Mellon University , with a joint appointment in the Department of Statistics & Data Science and the Machine Learning Department. Prior to joining CMU, she held positions as a J.W. Gibbs Assistant Professor at Yale University and a visiting research associate at Brown University. PhD in Physics, Brown University MSc/BSc in Engineering Physics, Chalmers University of Technology, Sweden Her research focuses on statistical methodology for complex data in the physical sciences , emphasizing trustworthy inference, uncertainty quantification, and integration of classical statistics with machine learning. Recent work includes likelihood-free inference, calibrated forecasting, and diagnostics for generative models. The STAMPS research group , which she co-founded in 2018, hosts weekly meetings and public webinars. In Fall 2024, STAMPS will transition into a CMU Research Center. Recent publications span likelihood-free inference , climate modeling , and astronomy . Notable collaborations include applications to hurricane intensity guidance , galaxy redshift estimation , and cosmological parameter biases . She mentors PhD students and has advised multiple award-winning researchers, including ASA Best Student Paper Award winners. Her teaching includes advanced courses on probability, regression, and AI for climate sciences.

• Time Series Analysis
• Data Mining
• Machine Learning
• +3 more

Eamonn Keogh is a Professor in the Computer Science and Engineering Department at the University of California, Riverside. His pioneering work centers on the Matrix Profile, a transformative approach to time series data mining enabling efficient solutions for motif discovery, anomaly detection, and similarity search. His algorithms (STAMP, STOMP, SCRIMP, DAMP, SCAMP) offer exact, parameter-free, and scalable solutions across domains like seismology, bioinformatics, and industrial IoT. Research areas include: Development of ultra-fast algorithms for time series joins and motif discovery at unprecedented scales (breaking the 100 million barrier) GPU acceleration for time series mining Domain-agnostic methods for semantic segmentation and anomaly detection Novel primitives like Time Series Chains, Snippets, and Consensus Motifs His work is highly cited and recognized by industry and academia, with applications ranging from NASA's Cassini mission to detecting BGP anomalies in computer networks.

• Additive Manufacturing
• Micro Metal Forming
• Tribology
• +4 more

Dr Dongbin Wei is an Associate Professor at the School of Mechanical and Mechatronic Engineering , University of Technology Sydney (UTS), with a career spanning academia and industry. He holds a PhD in Materials Processing Engineering from the University of Science and Technology Beijing (2001) and academic appointments from 2005–2012 at the University of Wollongong (Research Fellow to Lecturer) and 2013–2017 at UTS (Senior Lecturer) before his promotion to Associate Professor in 2018. His research lies at the intersection of Mechanical Engineering , Manufacturing Engineering , and Materials Processing , focusing on: Ultrasonic Additive Manufacturing (UAM) Micro Metal Forming and Size Effects Tribology and Lubrication Numerical Simulations of Material Processing Composite Material Fabrication Key contributions include: Development of the Springback Path–Displacement Adjustment (SP-DA) method for stamping accuracy Advancements in femtosecond laser texturing for silicon wettability control Studies on nanolubrication in hot rolling Optimization of micro-deep drawing parameters He has secured competitive grants from the Australian Research Council (ARC) and industry partners like Weir Minerals Australia Ltd , including projects on: Revolutionizing mineral separation via additive manufacturing Super high-speed grinding technologies Mechanics of micro composite drill fabrication As a lead supervisor, he guided the 2022 thesis 'Creation and Validation of 3D Printable Mineral Separation Spiral' . His work bridges theoretical analysis, computational modeling (FEM/FEA), and practical validation in advanced manufacturing systems.

Sebastian BeilView profile

Research Fellow

• Electrosynthesis
• Photocatalysis
• Organic Catalysis
• +3 more

Dr. Sebastian Beil is a Research Fellow and Group Leader at the Max Planck Institute for Chemical Energy Conversion (MPI CEC) in Mülheim an der Ruhr, Germany, leading the 'Electrosynthesis and Photocatalysis' group since 2024. He holds a B.Sc. and M.Sc. from Christian Albrechts University of Kiel (2010–2015), a Ph.D. from Johannes Gutenberg University Mainz (2015–2019), and completed postdoctoral research at the University of Ulm (2019–2020) and Princeton University (2020–2021). He was an Assistant Professor at the University of Groningen (2021–2024) before joining MPI CEC. His research focuses on developing sustainable redox transformations using visible light or electrodes, combined with transition metal catalysis to synthesize complex molecules efficiently. The lab’s work bridges organic chemistry and electrochemistry, emphasizing green solvents and scalable methods. Recent research highlights include advancements in nickel-photocatalytic reactions, functionalization of carbon nanotubes, and mechanistic studies of energy transfer in photocatalytic systems. The team collaborates across disciplines, addressing challenges in catalyst design and reaction efficiency. Key team members include PhD students Annemijn van Koten (Unilever Prize awardee), Rani Kumari, Tim Stamp, Berjan Stouwie, Ning Wei, and Mahdi Samapour, along with postdoc Zeyu Feng. The lab is part of the broader Waldvogel Lab network, fostering interdisciplinary innovation in electrosynthesis.

Abdallah ChehadeView profile

Associate Professor

• Deep Learning
• Prognostics
• Reliability Analysis
• +8 more

Dr. Abdallah Chehade is an Associate Professor in the Department of Industrial and Manufacturing Systems Engineering at the University of Michigan-Dearborn , where he leads the Informatics, Reliability, and Data Analytics (IRDA) lab . He holds a Ph.D. in Industrial Engineering from the University of Wisconsin-Madison (2017), with minors in Computer Sciences and Statistics, alongside an M.S. in Mechanical Engineering and a B.E. in Mechanical Engineering from the American University of Beirut. Research Interests span safe and robust deep learning solutions , explainable AI , data fusion for degradation modeling , and Bayesian statistical modeling . His work integrates AI/ML with prognostics and Internet of Things (IoT) to address challenges in reliability analytics and industrial data science . Publications highlight advancements in deep autoencoders , LSTM networks , and hybrid models for warranty forecasting , with applications in battery cells , sheet metal stamping , and rail transportation . His grants from Ford, Honda, and the U.S. Army focus on smart manufacturing , AI for sensor modeling , and digital twins . Lab Members include Ph.D. students working on topics like physics-based AI , computer vision , and deep learning for prognosis . He serves on the INFORMS Quality, Statistics, and Reliability (QSR) Council and maintains affiliations with IEEE , INFORMS , and IISE .

Jürgen BernardView profile

Assistant Professor

• Visual Analytics
• Information Visualization
• Interactive Machine Learning
• +12 more

Jürgen Bernard is an Assistant Professor of Computer Science at the University of Zurich , leading the Interactive Visual Data Analysis (IVDA) Group . He is associated with the Digital Society Initiative (DSI) and holds a PhD in Computer Science from Technische Universität Darmstadt (2015) with a focus on time-oriented data analysis. His academic journey includes postdoctoral research at TU Darmstadt and the University of British Columbia. Education : Diploma in Computer Science (2009, TU Darmstadt) PhD in Computer Science (2015, TU Darmstadt) Research Interests : Dr. Bernard specializes in interactive visual data analysis , explainable machine learning , and human-centered AI . His work explores time series analysis , multivariate data exploration , and user-driven preference elicitation . He develops visual analytics systems for domains like healthcare , digital humanities , and industrial applications , with a particular focus on responsible AI and transparency in algorithmic systems . Research Trends : His publications emphasize interactive machine learning workflows , visual analytics for healthcare , and time-stamped event sequence analysis . Recent work includes LLM validation frameworks (Human-Data-Model Interaction Canvas) and personalized ranking systems funded by the Swiss National Science Foundation. He integrates temporal data with multivariate analysis across applications from medical manufacturing to chronic disease management . Scientific Recognition : EuroGraphics Young Researcher Award (2022) EuroVis Young Researcher Award (2021) Best Paper Awards at IEEE VIS (2021), EuroVA (2021, 2025) Dirk Bartz Prize (2017), Hugo-Geiger Preis (2016) Teaching & Grants : He teaches Interactive Visual Data Analysis (6 ECTS), Digital Health Seminars , and People-Oriented Computing . Currently leads a SNF Grant on Personalized Visual Analytics for multi-criteria decision support (2024-2028) with ETH Zurich's Prof. M. El-Assady.

Philipp NiewöhnerView profile

Visiting Professor

• Late Antique and Byzantine Archaeology
• History of Christianity
• Iconography and Art History
• +3 more

PD Dr. Philipp Niewöhner is a distinguished Visiting Professor at the University of Vienna and Privatdozent at Göttingen University. His work focuses on Late Antique and Byzantine archaeology , particularly in Constantinople, Anatolia, and the Mediterranean . He has held significant roles including Associate Member at the Sapienza Centre for Late Antiquity, Director of Excavations at Miletus (Turkey) for the German Archaeological Institute, and Fellow at Dumbarton Oaks and Forschungskolleg Humanwissenschaften. His research spans architectural history, iconography, and provincial cultural diversity in early Christianity. Education: Doctorate (2004) and Master’s (2001) from Mainz University University studies at Heidelberg, Mainz, and Thessaloniki (Erasmus, 1997–2001) Research Themes: Byzantine architectural ornamentation and aniconism Iconoclast controversy and imperial symbolism Provincial vs. metropolitan Christian traditions Byzantine-Ottoman continuity and cultural exchange Article Trends: Analysis of Hagia Sophia ’s minimalist design Reinterpretation of the Trier Ivory as historical documentation Study of regional diversity in church architecture Examination of marble provenance and spolia practices Scientific Awards: DFG Project Funding for iconoclasm studies Gerda Henkel Foundation Scholarship (2006) William Golding Fellowship (2012–2014) Grants and Collaborations: Co-authored works with Anthony Cutler on Byzantine ivory carving Leadership roles in excavations and academic institutions Contributions to journals like Travaux et Mémoires and Dumbarton Oaks Papers

Abdallah ElsayedView profile

Associate Professor

• Casting and Solidification of Light Alloys
• Materials Characterization
• Neutron Diffraction Analysis
• +7 more

Abdallah Elsayed, Ph.D., P.Eng., is an Associate Professor in the Department of Mechanical Engineering at the University of Guelph. His research focuses on casting and solidification of light alloys, materials characterization (including OM, SEM, TEM, XRD, DSC), and in-situ neutron diffraction for solidification/phase analysis. He also investigates molten metal treatment, defect/inclusion analysis, and nanoparticle applications in agriculture and environmental sustainability. His work bridges metallurgy with biomedical and environmental engineering, emphasizing sustainable materials innovation. Dr. Elsayed teaches undergraduate courses ENGG 2160 (Engineering Mechanics II) and ENGG 2120 (Materials Science). He leads the Gryphon Solidification and Materials Processing Laboratory (SaMPL), advancing research in alloy development and casting technologies. Recent work explores nanoparticle-based solutions for food preservation, water treatment, and nutrient recovery from industrial waste. His publications (2023-2025) emphasize interdisciplinary approaches, including novel alloys for biomedical implants, eco-friendly coatings, and sustainable agricultural practices. Key themes include optimizing electrical conductivity in aluminum alloys, mitigating alloy oxidation, and leveraging nanoparticles for environmental remediation. His research underscores both technical innovation and real-world applications in sustainability.

• Control Technology
• Distributed Optimization
• Machine Learning
• +4 more

Mikael Johansson is a Professor at Kungliga Tekniska Högskolan (KTH), specializing in Control Technology . He teaches and coordinates courses such as Distributed Optimization (FEL3311) and various advanced-level degree projects in computer science, electrical engineering, and systems engineering. His research spans Control Systems , Machine Learning , and Optimization , with a focus on asynchronous algorithms, federated learning, and applications in energy systems and construction. His work includes 15 recent publications on topics like neural networks, distributed optimization, and battery technology. Notable areas of contribution are in asynchronous learning, federated learning with privacy constraints, and quasi-Newton methods for optimization. His research bridges theoretical advancements with practical applications in urban design, healthcare, and autonomous systems.

Elisa RoßbergerView profile

Assistant Professor

• Near Eastern Archaeology
• Visual Archaeology
• Digital Humanities
• +5 more

Elisa Roßberger is an Assistant Professor with tenure track for Explorative Visual Archaeology of the Ancient Near East at the Free University of Berlin since October 2022. Previously, she held a similar position for Digital Humanities for Near Eastern Archaeology and Assyriology at Julius-Maximilians-Universität Würzburg (2021-2022). Her academic journey includes post-doctoral positions at LMU München's Graduate School Distant Worlds and Centre for Advanced Studies. Dr. Roßberger's educational background includes: PhD in Near Eastern Archaeology from Eberhard-Karls-Universität Tübingen (2010, summa cum laude), published as "Schmuck für Lebende und Tote" (2015) Graduate studies as a scholarship recipient of the DFG Graduate College "Forms of Prestige in Ancient Cultures" at LMU München (2006-2009) Studies in Near Eastern Archaeology, Political Science (International Relations), and Assyriology in Munich, Beirut, and Tübingen (2000-2006) Her research focuses on the archaeology of Iraq, Syria, and the Levant during the 3rd and 2nd millennia BCE, with particular emphasis on visual culture, multimodality, and digital approaches to ancient studies. She has conducted extensive fieldwork since 2000 at archaeological sites including Ba'ja (Jordan), Gerçin Höyük (Turkey), Tell Burak (Lebanon), Emar and Qatna (Syria), Tilla Bulak (Uzbekistan), and Ur (Iraq). Dr. Roßberger's scholarly output demonstrates consistent engagement with visual representation in ancient societies, particularly examining cylinder seals, terracotta figurines, and Babylonian imagery. Her work bridges traditional archaeological analysis with innovative digital methodologies, creating new approaches to understanding ancient material culture through multimodal analysis. Her major research projects include: Co-leading the interdisciplinary long-term project "KIŠIB. Digital Corpus of Ancient West Asian Seals and Sealings" since 2025 Leading the BMBF eHeritage project "Annotated Corpus of Ancient West Asian Imagery: Cylinder Seals" (ACAWAI-CS, 2020-2023) Leading the BMBF eHeritage project "Concept for Digitization of Ancient Near Eastern Cylinder and Stamp Seals" (DigANES, 2017-2018) Dr. Roßberger is actively involved in academic communities: Member of the DFG Network "Archaeological Image Research: Limitations and Transgressions of Images" since 2025 Co-Chair of the NFDI4Objects Community Clusters "Objects as Information Carriers" since 2024 Editorial board member for "Visual Culture of Ancient Western and Central Asia" (Palgrave Macmillan) Co-organizer of multiple international conferences on ancient Near Eastern temple inventories and digital perspectives on seals and sealings

Angela BatsonView profile

Research Fellow

• Road Safety Culture
• Occupational Health and Safety
• Aging Drivers
• +3 more

Angela Batson is a Research Fellow at the Monash University Accident Research Centre (MUARC), focusing on road safety, occupational health, and aging drivers. Her work contributes to UN Sustainable Development Goals (SDGs) related to safety and well-being. She has collaborated extensively on projects addressing road safety culture in Australian businesses, grey fleet management, and child passenger safety. Key contributions include evaluating the 'Safe Seats, Safe Kids' program and analyzing coroners’ recommendations for heavy vehicle driver safety. Her research spans barriers to aging driver health, workplace interventions, and gig economy transportation safety. Projects include national road safety partnerships with organizations like Transport Victoria and the Transport Accident Commission. She has served as a Chief Investigator (CI) or Associate Investigator (AI) in multiple funded initiatives since 2022, emphasizing collaborative, applied research. Batson’s publications emphasize practical solutions for improving driver safety through managerial strategies, policy evaluation, and systematic reviews. Her work bridges academic research with real-world applications in transportation safety and public health.

• Maritime safety management and leadership
• Maritime accident and casualty analysis
• Maritime Autonomous Surface Ships (MASS)
• +3 more

Tae Eun Kim is an Associate Professor in Maritime Safety Management at UiT The Arctic University of Norway, working within the Department of Technology and Security. Her research, teaching, and industrial collaboration focus on maritime safety and human factors, with particular expertise in maritime safety management, accident analysis, Maritime Autonomous Surface Ships (MASS), and human factors in maritime operations. Dr. Kim's research spans four interconnected domains: maritime safety management and leadership, maritime accident and casualty analysis, Maritime Autonomous Surface Ships (MASS), and human factors in maritime operations. She has developed assessment instruments like the Safety Leadership Self-Efficacy Scale (SLSES) and conducted STAMP-based causal analyses of maritime accidents. Her work on MASS addresses safety challenges in mixed navigational environments and examines leadership competencies for autonomous shipping operations. Her human factors research explores how technological advancements impact navigators' performance, crew dynamics, and safety outcomes, including gender parity issues in the maritime industry. Dr. Kim's publication record reveals a strong focus on the intersection of maritime safety, technology, and human performance. Her recent work increasingly addresses autonomous shipping technologies, with numerous publications on AI decision transparency, learning analytics in maritime simulator training, and multi-modal data analysis for nautical skill development. She has conducted systematic reviews on simulator training approaches and scenario design, contributing significantly to methodology development in maritime education and training. Her research demonstrates a clear trajectory toward integrating emerging technologies with traditional maritime safety practices as the industry transitions toward greater automation. Dr. Kim is actively involved in several significant research projects, including the i-MASTER EU Horizon Europe Research and Innovation Project, the REFRAME project, and the SPRICE project (Multidisciplinary approach for spray icing modelling). She is a member of both the Advanced Maritime Ship Operations research group and the Maritime Safety Science (MARSCI) Research Group, demonstrating her commitment to collaborative research in maritime safety science. Dr. Kim teaches several specialized courses at UiT, including SVF-3206 Safety Management and Accident Investigation, TEK-3014 Navigation Technology, MFA-2100 Maritime Digitalization, MFA-8010 Maritime HTO (Human-Technology-Organisation) and Innovation, and MFA-2018 Maritime Administration and Leadership. Her teaching portfolio reflects the interdisciplinary nature of her expertise, bridging engineering, safety science, and organizational behavior in maritime contexts.

Oliver HampeView profile

Research Professor

• Paleontology
• Vertebrate Paleontology
• Cetacean Evolution
• +3 more

Dr. Oliver Hampe serves as Scientific Director of the Vertebrate Paleontology and Geology Collections at the Museum für Naturkunde (Museum of Natural History), Leibniz Institute for Evolution and Biodiversity Research in Berlin, Germany. He also holds the position of Head of the Paleontological Preparation Laboratory. His expertise spans extinct aquatic vertebrates, paleopathology, and geoarchaeology, with significant contributions to cetacean evolution research. Hampe completed his studies in Chemistry and Geology-Paleontology from 1981-1987 at universities in Düsseldorf and Mainz, earning his Diploma in 1987. He received his PhD from Johannes Gutenberg University Mainz in 1991 and completed his habilitation for Palaeobiology and Zoology at Humboldt University Berlin in 2003, qualifying him as a Privatdozent. His research focuses on cetacean evolution, particularly Miocene whale fossils from German sites like Groß Pampau, with significant work on periotic bone anatomy. Hampe integrates traditional morphological analysis with advanced imaging techniques including CT scanning to study fossil specimens non-destructively. His paleopathological research examines diseases in fossils, such as osteomyelitis in Tyrannosaurus rex and bone tumors in whale specimens. He also maintains scholarly interest in the history of paleontology, particularly Werner Janensch's work and German expeditions to Tendaguru, Tanzania. Analysis of Hampe's recent publications reveals consistent focus on cetacean evolution, especially baleen whales from the Miocene epoch. His methodological approach frequently combines detailed morphological analysis with geological context to understand evolutionary patterns. He has made significant taxonomic contributions through studies of whale ear bone anatomy and has extended his research to pathological conditions in diverse fossil vertebrates. His interdisciplinary work bridges paleontology with medical imaging techniques and historical studies. As Head of the Paleontological Preparation Laboratory, Hampe oversees the curation and preparation of vertebrate fossil collections. His current research projects include cetacean studies from Groß Pampau, pathology research on dinosaurs and mammals, and investigations into aquatic adaptation in Cetartiodactyla supervised with PhD student Apolline Alfsen. His collaborative approach is evident in numerous publications with international researchers across Europe.