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Anthony W. LynchView profile

Professor

• Finance
• Asset Pricing
• Portfolio Choice
• +4 more

Anthony W. Lynch is a Professor of Finance at the Leonard N. Stern School of Business, New York University, where he has been a faculty member since 1994. He is also a Research Associate at the National Bureau of Economic Research since 2002 and has held visiting positions at Columbia University and the Wharton School of the University of Pennsylvania. Education: PhD in Finance and Economics, University of Chicago, 1994 Bachelor of Commerce (Honours), University of Queensland, 1989 Bachelor of Laws (Honours), University of Queensland, 1989 Master of Financial Management, University of Queensland, 1988 Bachelor of Commerce, University of Queensland, 1986 Professor Lynch's research centers on asset pricing , portfolio choice , and mutual funds , with a strong emphasis on modeling investor behavior under uncertainty, transaction costs, and habit formation. His work integrates macroeconomic factors with financial decision-making, particularly in life-cycle investing and retirement planning. He has made significant contributions to understanding how frictions such as taxes, liquidity, and borrowing constraints impact optimal investment strategies. His recent publications demonstrate a consistent focus on dynamic portfolio optimization, stochastic volatility, and the implications of behavioral and structural frictions in financial markets. Themes across his work include time-consistency in decision-making, risk premia estimation, and the interaction between human capital and financial wealth. Scientific Awards and Honors: Glucksman Prize (twice) for best finance research paper by an NYU professor Research Associate, National Bureau of Economic Research (since 2002) Associate Editor, Review of Finance Session Chair, American Finance Association (AFA) and Western Finance Association (WFA) Meetings Professor Lynch advises doctoral students and contributes to academic leadership through editorial and conference roles. He has not received mention of external research grants in the provided text, but his NBER affiliation suggests involvement in collaborative, funded research initiatives. He teaches foundational courses including Foundations of Finance (MBA), Finance Theory I , and Seminar in Asset Pricing Theory (PhD level), shaping the next generation of finance scholars and practitioners. He is affiliated with the Department of Finance at NYU Stern and conducts research that bridges theoretical models with empirical validation, often using advanced econometric and computational methods. His academic network includes leading institutions such as Chicago, Columbia, and Wharton, reflecting his prominence in the finance community.

Dan WarrenView profile

Academic

• Population Biology
• Ecology
• Evolution
• +9 more

Dan Warren is a Senior Research Fellow at the Gulbali Research Institute, Charles Sturt University, where he conducts interdisciplinary research in population biology, ecology, evolution, and conservation. His work centers on developing and refining species distribution models and environmental niche models to understand biodiversity and support conservation under global change. PhD in Population Biology, University of California, Davis Dan Warren's research interests lie in the development and application of quantitative tools for ecology and evolution. He focuses on species distribution models (SDMs), environmental niche models (ENMs), and their use in understanding biodiversity patterns, evolutionary processes, and conservation planning. His methodological innovations, such as those in the ENMTools R package, are widely adopted. His work spans animal behavior, climate change impacts, and conservation management, with strong relevance to UN Sustainable Development Goals on climate action and life on land. His recent publications reflect a consistent focus on improving the accuracy, interpretation, and application of species distribution models. Trends include addressing bias in model outputs, enhancing methodological standards, and developing robust tools for conservation under climate uncertainty. He frequently publishes in top ecological journals such as Ecography and Methods in Ecology and Evolution , and his work integrates software development with theoretical ecology. Dan Warren has served in key scientific roles, including as Associate Editor for Ecography and Systematic Biology , and as a reviewer for the IPBES global assessment. These contributions highlight his leadership in advancing scientific rigor and policy relevance in biodiversity science. He is actively involved in mentoring and collaborative research, contributing to datasets and methodological frameworks used by the broader ecological community. His work supports both academic inquiry and practical conservation, emphasizing robust, data-driven decision-making.

• Financial Econometrics
• Time Series Analysis
• Econometrics
• +5 more

Mustafa Hakan Eratalay is a Lecturer in Econometrics at the University of Tartu's School of Economics and Business Administration (50% position). Previously, he served as Associate Professor of Financial Econometrics (2015–2017) and Lecturer (2012–2015) at the European University at St. Petersburg. He holds a PhD in Economics from the University of Alicante (2012), specializing in Multivariate Volatility Modeling and Estimation under Dr. M. Angeles Carnero. His research focuses on Financial Econometrics, Time Series Analysis, Systemic Risk, ESG Ratings, and Social Networks. Key projects include analyzing cultural impacts on consumer confidence, cryptocurrency price prediction using machine learning, and evaluating ESG ratings' effects on systemic risk. He has contributed to studies on Baltic stock markets, ECB communications during crises, and Moscow Stock Exchange dynamics. Eratalay has published in journals like Journal of Risk and Financial Management , Computational Economics , and Economics of Transition . He collaborates with institutions like the Estonian Research Council and the European Commission on projects addressing economic resilience, cultural metrics, and modular nuclear power plant feasibility.

Ferdinand HeimerlView profile

Academic

• Roman Provincial Archaeology
• Late Roman Military Fortifications
• Ceramic Analysis
• +5 more

Jun.-Prof. Dr. Ferdinand Heimerl is a Junior Professor for Roman Provincial Archaeology at the University of Trier's Faculty III. His research focuses on Roman military fortifications, ceramic analysis, and archaeological heritage communication. He has held roles including Deputy Director of FoRuM and ERASMUS Coordinator for Archaeology. He has conducted excavations in Augsburg, Bitburg, and Trier, and served at institutions like the Rheinisches Landesmuseum Trier. Education: MA (2014, LMU Munich), PhD (2019, LMU Munich). Affiliations: Member of Rei Cretariae Romanae Fautores, Computer-Anwendungen und Quantitative Methoden in der Archäologie, and Association ATEG. His research interests span Late Roman military structures, geoarchaeology, and economic history. Key publications include studies on Bitburg's fortifications and North African ceramics from Augsburg. He has received awards like the Eduard-Anthes-Preis (2021) and the Dr.-Heinz-Cüppers-Preis (2024). Teaching includes courses on Roman provincial archaeology, digital archaeology, and underwater archaeology in collaboration with peers like Dr. Max Fiederling. He advises PhD students on topics like Dark Earth in Bitburg and Roman logistics in Luxembourg. He leads projects such as TRANSMARE and directs the Archäologiepark Belginum's scientific board. Active in heritage communication, he developed archaeological trails and smartphone apps for public engagement.

Rong ChenView profile

Professor

• Nonlinear Time Series Analysis
• Multivariate Time Series
• Monte Carlo Methods
• +5 more

Rong Chen is a Distinguished Professor and Chair of the Department of Statistics at Rutgers University, within the School of Arts and Sciences. With a Ph.D. from Carnegie Mellon University, Professor Chen has established himself as a leading researcher in statistical time series analysis, Monte Carlo methods, and their applications across various fields. Professor Chen's research focuses on: Nonlinear and Multivariate Time Series Analysis Monte Carlo Methods, Statistical Computing and Bayesian Analysis Statistical Applications in Science, Engineering and Business His research trajectory has evolved significantly over the years, beginning with foundational work on nonlinear time series and moving toward more complex high-dimensional tensor time series analysis. Recent publications show a strong emphasis on matrix and tensor factor models for high-dimensional time series, reflecting the growing importance of analyzing complex structured data in modern applications. His work bridges theoretical statistical innovation with practical problem-solving across finance, engineering, and computational biology. Professor Chen has been recognized for his contributions to the field with prestigious fellowships: ASA Fellow (American Statistical Association) IMS Fellow (Institute of Mathematical Statistics) As Chair of the Department of Statistics, Professor Chen oversees academic programs including the Master in Financial Statistics and Risk Management (FSRM) and the Master in Data Science (Statistics Track) programs. His leadership extends to guiding research directions in the department and fostering collaborations across disciplines. Professor Chen has secured numerous research grants supporting work in time series analysis, statistical computing, and applications in finance, engineering, and bioinformatics. Professor Chen's research group maintains active collaborations with researchers in finance, engineering, and computational biology, applying statistical innovations to real-world problems including financial time series analysis, protein folding studies, HIV infection dynamics modeling, wind power forecasting, and nuclear material detection systems.

Felix JonasView profile

Assistant Professor

• Biochemistry
• Gene Regulation
• Transcription Factors
• +4 more

Prof. Dr. Felix Jonas is an Assistant Professor of Biochemistry at the School of Science, Constructor University Bremen, Germany. He leads research on the biochemistry of gene regulation , focusing on molecular mechanisms governing transcription factor function and chromatin dynamics in Saccharomyces cerevisiae . His work integrates CRISPR-Cas9, Next-Generation Sequencing, and computational data analysis. Education: B.Sc. in Molecular Life Sciences (University of Luebeck), M.Sc. in Biology: Cell Biology (ETH Zurich), Ph.D. in Bioengineering (Imperial College London) Work Experience: Postdoc/Senior Postdoc at Weizmann Institute of Science (2017-22), Visiting Student at Weizmann Institute (2015-16), International Program Associate at RIKEN (2011) Teaching: General Biochemistry (CH-100-B), Introduction to Bioinformatics (JTMS-10), Current Topics in Life Sciences (CA-BCCB-801), Advanced Biochemistry II - Molecular Genetics (CO-403-A) His research explores transcription factor target search , histone dynamics , and chromatin structure-function relationships . Recent publications highlight discoveries in nucleosome replacement, protein disorder grammar, and histone acetylation impacts on replication. Articles emphasize interdisciplinary approaches to eukaryotic gene regulation and systems biology. Visit his lab’s PhD recruitment page or watch his Fragile Nucleosome Talk for deeper insights into his work.

Suzanne R. BlackView profile

Research Fellow

• Digital Humanities
• Literary Studies
• Fan Studies
• +5 more

Dr. Suzanne R. Black is a Postdoctoral Research Associate at the University of Edinburgh, working within the CoSTAR Foresight Lab. Her research sits at the intersection of humanities inquiry and computational methods, focusing on digital literary culture, fanfiction, and creative industries data analysis. She holds a PhD from the University of Edinburgh where her doctoral work examined 21st-century digital literary networks. PhD in English Literature, University of Edinburgh Her research interests center on digital literary culture , fanfiction archives , and queer/feminist theories applied to contemporary reading practices. She pioneers computational approaches like topic modeling to analyze large-scale datasets from platforms such as Goodreads, investigating how readers construct literary value and negotiate canonicity in digital spaces. Her work reveals how fan communities dynamically define 'classics' through emotional engagement and collective discourse. Recent publications demonstrate a cohesive trajectory in cultural analytics and digital literary studies , blending computational techniques with critical theory to examine pandemic impacts on festivals, NFT ownership models, and DEI initiatives in creative sectors. A recurring theme is the tension between algorithmic systems and human-centered cultural production. Fellowship at the Institute for Advanced Studies in the Humanities Dr. Black has secured research funding through institutional fellowships supporting her Goodreads fanfiction analysis. While not formally advising graduate students, she actively shapes academic discourse through invited lectures at Newcastle University, the University of Edinburgh, and Porty Pride events. Her grant-funded projects often involve cross-disciplinary collaboration with data scientists and social researchers. As a core member of the CoSTAR Foresight Lab, she contributes to the Edinburgh Futures Institute's mission of data-driven creative industry innovation. Her work integrates digital humanities methodologies with cultural analytics to address structural biases in digital heritage preservation and fanfiction archiving.

Crystal FausettView profile

Assistant Professor

• Human-Centered Cybersecurity
• Human-Computer Interaction
• Research Methods
• +6 more

Dr. Crystal Fausett is an Assistant Professor in the School of Information at San José State University. Her academic work bridges human factors, cybersecurity, and human-computer interaction, with a strong focus on how individuals and teams interact with technology in high-stakes environments such as healthcare, emergency services, and cyber operations. She teaches courses including ISDA 121 – Human Centered Cybersecurity and ISDA 130 – User Centered Interface Architecture and Prototyping, reflecting her interdisciplinary expertise. Ph.D. in Human Factors, Embry-Riddle Aeronautical University (2024) M.S. in Human Factors, Embry-Riddle Aeronautical University (2022) B.A. in Psychology, San José State University (2020) A.A. in Social and Behavioral Sciences, Santa Barbara City College (2018) Her research interests include human-centered cybersecurity, human-computer interaction, usability and UX design, teamwork and transactive memory systems, training methodologies (particularly simulation-based), and information behavior across diverse user groups such as healthcare providers, cyber defenders, and naval personnel. She applies both qualitative and quantitative methods, including expert interviews, board game simulations, and meta-analytic techniques. The recent publications highlight a strong trend in applying human factors principles to cybersecurity team performance, adaptive training, and healthcare safety. Her work increasingly explores innovative methods such as gamified simulations to study team dynamics and cognitive load in complex operational environments. There is a consistent emphasis on improving system efficiency, safety, and collaboration through human-centered design. Dr. Fausett has no listed scientific awards in the provided text. She has served as an Instructor of Record in Human Factors and Behavioral Neurobiology at Embry-Riddle Aeronautical University (2023–2024) prior to her current role. There is no mention of current grant funding or student advising in the provided materials. Her research often involves collaboration with experts in human factors and healthcare, particularly Dr. Joseph R. Keebler and Dr. E. Salas, suggesting active participation in research teams focused on team performance and safety-critical systems. She is involved in research labs or teams centered on human factors in cybersecurity and healthcare, particularly through collaborative projects involving simulation-based training and team cognition studies. Her use of board games like [d0x3d!] as experimental testbeds indicates innovative lab-based methodologies for studying real-world team interactions in controlled environments.

Lev MichaelView profile

Professor

• Anthropological Linguistics
• Linguistic Typology
• Language Documentation
• +10 more

Lev Michael is a Professor of Linguistics at the University of California, Berkeley, in the Department of Linguistics within the College of Letters and Science. His research focuses on anthropological linguistics, typology, and the documentation and description of Amazonian languages, particularly in Peru. He is actively engaged in fieldwork, language revitalization, and the study of South American historical and contact linguistics. Research Interests: Lev Michael's work spans a wide range of topics in linguistic anthropology and descriptive linguistics. He specializes in the documentation of endangered Amazonian languages such as Iquito and Nanti, examining grammatical phenomena like evidentiality, negation, and subject-verb agreement. His research integrates fieldwork with computational methods, particularly in phylogenetic classification of language families like Tupí-Guaraní and Arawakan. He is deeply committed to language revitalization and community-based lexicography, contributing to school dictionaries and literacy materials. Recent Research Trends: His recent publications (2017–2022) reflect a strong emphasis on lexicography, computational phylogenetics, and the sociocultural dimensions of language use. Articles span from dictionary compilation to Bayesian modeling of language evolution, demonstrating a unique blend of traditional fieldwork and cutting-edge quantitative analysis. There is a consistent focus on Arawakan and Tukanoan languages, evidentiality, poetic structure in oral traditions, and the historical relationships among South American language families. Scientific Contributions: Co-developer of lexicographic resources for Iquito and other endangered languages Pioneer in applying computational phylogenetics to South American language classification Contributor to the understanding of evidentiality and reported speech in Amazonian languages Advocate for language revalorization and community-led documentation Advising and Grants: While specific students and funded grants are not listed in the provided text, Lev Michael frequently collaborates with students and community members on documentation projects. His extensive co-authorship with scholars like Christine Beier and Jaime Pacaya Inuma suggests a collaborative, team-based research model involving students, local speakers, and interdisciplinary partners. His work likely involves external funding given the scale of fieldwork and publication output, though specific grants are not mentioned. Labs and Research Teams: Lev Michael is associated with the Fieldwork and Language Documentation group and the Language and Social Context faculty at UC Berkeley. His collaborative projects involve multidisciplinary teams including linguists, anthropologists, and native speaker consultants, particularly from Peruvian Amazonian communities. He contributes to digital language archiving and lexicography using tools like FLEx (FieldWorks Language Explorer), indicating involvement in computational language documentation initiatives.

• Bank Soundness
• Artificial Intelligence
• Student Learning
• +1 more

Dr. Charmele Ayadurai is a researcher affiliated with the Department of Finance at Durham University . Her work spans interdisciplinary themes including bank soundness , artificial intelligence , and student learning and wellbeing . Education: Not explicitly detailed in available texts. Her research focuses on: Financial stability mechanisms in banking Ethical AI applications for economic decision-making Socioeconomic determinants of child welfare and educational equity Policy interventions for poverty reduction Recent publications analyze childcare affordability , post-pandemic equity strategies , and machine learning in banking . She collaborates with multidisciplinary teams across health, education, and finance domains. Notable affiliations include: Centre for Banking Institutions and Development School of Education (associated with pedagogy reports) N8 Research Partnership Health Equity North Her work has been cited in policy frameworks addressing regional disparities in the UK and Malaysia.

Wang ChunView profile

Associate Professor

• Operations Management
• Stochastic Control
• Decision-Making under Uncertainty
• +9 more

Wang Chun is a tenured Associate Professor in the Department of Management Science and Engineering at the School of Economics and Management, Tsinghua University. He currently serves as Deputy Director of the department and has held academic positions at Tsinghua since 2017. His work bridges stochastic control, reinforcement learning, and machine learning applications in operations management and financial technology. Education: Bachelor's Degree from Tsinghua University (2005) Master's Degree from the University of Wisconsin-Madison (2008) Doctorate in Operations Research from Columbia University (2014) Research Interests: His research focuses on stochastic control and decision-making under uncertainty, particularly in inventory management, revenue management, financial engineering, and sports analysis. He also investigates reinforcement learning algorithms for dynamic optimization and applies machine learning to business data analytics and financial technology. Published Work Trends: Wang’s publications span operations research, financial mathematics, and computational management science. Recent studies address seasonal optimization patterns, robust inventory models, and game-theoretic approaches to sports analytics. His work integrates theoretical advancements in dynamic programming with practical applications in financial engineering and market microstructure. Career History: 2023–Present: Associate Professor, Tsinghua University 2020–2023: Associate Professor, Tsinghua University 2017–2020: Assistant Professor, Tsinghua University Researcher at KCG (New York), leading studies on quantitative investment and asset optimization

• Business Information Systems
• Information Systems Architecture
• Data Distribution in Enterprises
• +2 more

Prof. Dr. Sven Pohland is a faculty member at the Berlin School of Economics and Law, affiliated with the School of Economics and Law and the Department of Quantitative Methods and Business Information Systems. His research focuses on business information systems, enterprise application integration, and information distribution frameworks. His work examines cross-organizational collaboration through system architecture and business networking technologies. Publications highlight advancements in enterprise modeling, data governance, and networked business models, with a particular emphasis on practical implementations in global enterprises. Contact: spohland@hwr-berlin.de

• Distributed Systems
• Cloud Computing
• Edge Computing
• +7 more

David Bermbach is a Full Professor at Technische Universität Berlin , leading the Scalable Software Systems group since 2023. His research focuses on distributed systems, serverless computing, and benchmarking, with significant work on edge and fog computing architectures. He is affiliated with the Einstein Center Digital Future and co-chairs interdisciplinary projects like SimRa for bicycle traffic safety. Full Professor, Scalable Software Systems (2023–present) ECDF-Professor, Mobile Cloud Computing (2017–2023) Postdoctoral Researcher (2014–2017) Education : Diploma in Business Engineering (2010) – Karlsruhe Institute of Technology (KIT) PhD in Computer Science (2014, summa cum laude) – KIT Research Interests span distributed systems with emphasis on cloud, edge, and fog computing, serverless architectures, IoT platforms, and benchmarking frameworks. His work addresses consistency-performance trade-offs, resource placement, and interdisciplinary applications in urban mobility and satellite edge computing. Article Trends show a focus on serverless computing (12/15), edge-cloud integration (9/15), and benchmarking methodologies (7/15). Key themes include optimizing function placement, federated learning architectures, and low-earth orbit computing systems. Scientific Awards Best Paper Award – ShutPub (2024) Best Workshop Paper – A Research Perspective on Fog Computing (2017) Best Paper Runner Up – Benchmarking Eventual Consistency (2014) Summa Cum Laude PhD Thesis (2014) Advising & Grants include mentoring students like Tobias Pfandzelter and Trever Schirmer, leading funded projects through the Einstein Center Digital Future, and contributing to 6G network research. His team works on cloud federation, serverless optimization, and real-world IoT applications.

Ørjan Grøttem MartinsenView profile

Professor

• Bioimpedance
• Biomedical Physics
• Electronics and Instrumentation
• +3 more

Ørjan Grøttem Martinsen is a Professor of Electronics at the Department of Physics, Faculty of Mathematics and Natural Sciences, University of Oslo. He also holds a temporary research position at the Medical Technology Business Area of Oslo University Hospital. With over three decades of experience, he has established himself as a leading expert in bioimpedance research and applications. Education: High-voltage engineer degree (1983) Cand. scient. in electronics/measurement technology (1990) Dr. scient. with thesis on skin's electrical properties (1995) Professor Martinsen's research centers on bioimpedance—the passive electrical properties of biological tissues that vary with anatomy and physiology. His work spans diverse applications including medical diagnostics (skin cancer detection), food quality assessment (fresh vs. thawed fish), skin condition monitoring (moisture levels), and stress level evaluation. His research bridges physics, engineering, and medical applications, creating practical diagnostic tools from fundamental electrical principles. He has pioneered methods to characterize tissue properties through impedance measurements, with particular focus on electrodermal activity and skin impedance. His recent publications (2022-2025) demonstrate a strong interdisciplinary approach combining bioimpedance with machine learning, robotics, and advanced signal processing. The work spans from fundamental biophysics (GABA detection, tissue characterization) to practical applications (dental anxiety assessment, ADHD treatment evaluation). Key trends include integration of AI with bioimpedance measurements, development of novel sensor systems, and expansion into new application areas like optogenetics and micro-robotics. Awards and Recognition: IEEE Senior Member (2006) CLABIO Award (2012) Fellow at Institute of Physics (FInstP) (2015) Dr. Honoris Causa, Tallinn University of Technology (2018) UiO Innovation Award (2019) Member of Norwegian Academy of Technical Sciences (2021) Professor Martinsen has served as Editor-in-Chief of the Journal of Electrical Bioimpedance since 2010 and was President of the International Society for Electrical Bioimpedance (2010-2016). His research has attracted significant funding, enabling collaborations across engineering, medical, and biological disciplines. He has supervised numerous students and researchers in the Bioimpedance Group at UiO, fostering a strong research environment that bridges theoretical and applied work. His work is conducted primarily through the Oslo Bioimpedance Group and Sensorama SmartSense research teams, which focus on developing innovative measurement techniques and applications of bioimpedance technology. These groups maintain strong collaborations with medical institutions and industry partners to translate research findings into practical healthcare solutions.

Susan MurrayView profile

Professor

• Nonparametric Survival Analysis
• Missing Data Issues
• Quality-of-Life Research
• +6 more

Susan Murray , ScD, is a Professor in the Department of Biostatistics at the University of Michigan School of Public Health. She has made significant contributions to survival analysis methodology, particularly in lung allocation systems and quality-of-life-adjusted survival models. Education: ScD in Biostatistics (Harvard, 1994), MS in Biostatistics (Harvard, 1992), BA in Statistics and English (Rice, 1990) Roles: Biostatistical Editor for American Journal of Respiratory and Critical Care Medicine , member of Cystic Fibrosis Foundation's Data and Safety Monitoring Board Her research focuses on nonparametric survival analysis with informative censoring, group sequential methods for censored data, and quality-of-life-adjusted survival models. She pioneered Lung Allocation Score development and dependent censoring methodology. Recent collaborative work with pulmonary researchers has advanced CT parametric response mapping for COPD progression, machine learning applications in proteomics, and spatially localized lung disease analysis. Her publications show strong emphasis on survival modeling , censored data handling, and transplantation outcomes . Scientific Awards: University of Michigan School of Public Health Excellence in Teaching Award (2003) On Job/On Campus Master's Program Teacher of the Year (2001) Professor Murray maintains active collaborations with University of Michigan Medical School pulmonary researchers and national institutions. She has served on editorial boards for Biometrics and Lifetime Data Analysis , and currently contributes to the American Journal of Respiratory and Critical Care Medicine as Biostatistical Editor.