Dr. Anil Ufuk Batmaz is an Assistant Professor in the Department of Computer Science and Software Engineering at Concordia University. His research focuses on Virtual Reality (VR), Augmented Reality (AR), and Human-Computer Interaction, with emphasis on interaction techniques, immersive analytics, and motor skill training systems. He holds a BSc in Electrical and Electronics Engineering (2007-2011), an MSc in the same field (2011-2013), and a PhD in Biomedical Engineering (2015-2018). His work bridges engineering and cognitive science, investigating how visual and haptic feedback impact user performance in immersive environments. Research interests include: 3D interaction techniques for mid-air tasks Effects of display technologies on motor coordination Hybrid UI design for mixed reality systems Training systems for precision tasks using VR Recent publications emphasize evaluation of AR/VR interfaces in healthcare, sports training, and collaborative environments. His work has appeared in venues like IEEE TVCG, ACM CHI, and ISMAR, addressing challenges in spatial navigation, error feedback, and system reliability.
Professor Christian Biener is a faculty member at the University of St. Gallen, affiliated with the School of Economics and Political Science and the Department of Economics. His research focuses on insurance economics, behavioral economics, and risk management, with particular emphasis on topics like cyber risk, microinsurance, health insurance design, and the societal impacts of emerging technologies such as chatbots and telematics. He holds a prominent role in academic and industry discourse through his extensive publication record and contributions to policy-relevant research. Biener’s work bridges theoretical economic analysis with practical applications, addressing challenges in global insurance markets, pandemic response strategies, and the interplay between technological innovation and human behavior. His research has explored how factors like microbiome composition influence economic decision-making, the ethical implications of contact-tracing apps, and the design of effective reinsurance strategies. He actively engages with industry trends, advising on future skills requirements in reinsurance and the balance between privacy and risk hedging in digital environments. His scholarly output spans over a decade, with recent trends emphasizing behavioral aspects of insurance decisions, the impact of global events on healthcare costs, and the transformational role of technology in insurance products. Biener’s articles consistently analyze both micro-level individual decision-making and macro-level market dynamics, offering insights that inform both academic theory and policy formation. While no formal awards are explicitly mentioned, his prolific publication record and institutional affiliation suggest significant recognition within the field. Biener’s work often incorporates experimental methodologies, such as randomized controlled trials, to empirically validate theoretical models. He collaborates across disciplines, integrating insights from psychology, computer science, and public health into his economic analyses. Biener’s current research agenda includes investigating the insurability of novel risks (e.g., cyber threats), optimizing microinsurance programs in emerging markets, and analyzing non-cognitive skills’ role in post-crisis economic recovery. He leads projects at the Institute for Economics (IVW) at HSG, contributing to both academic and applied research initiatives.
Benjamin Faber is an Associate Professor of Economics at the University of California, Berkeley, affiliated with the Department of Economics within the College of Letters and Science. His research focuses on international and development economics, exploring topics such as rural-urban migration, spatial inequality, e-commerce impacts, and responsible sourcing policies. He has held positions since 2013, including teaching graduate and undergraduate courses in development economics and international trade. Faber has organized numerous seminars including the Berkeley International Econ Seminar and Trade Work in Progress Seminar, fostering academic collaboration. His work appears in top journals like the Quarterly Journal of Economics and Review of Economic Studies, addressing welfare measurement, firm heterogeneity, and spatial economic dynamics. Notable contributions include analyzing China's highway system effects and Mexico's tourism impacts. His research often bridges theory with empirical evidence, emphasizing policy-relevant outcomes in developing economies. Education details are not explicitly listed in the provided materials, but his academic trajectory is evident through his prolific publication record and teaching roles since 2013. Faber's affiliations include the National Bureau of Economic Research (NBER) and Center for Economic Policy Research (CEPR), with his work frequently featured in policy platforms like VoxDev.org and the World Trade Report. His research questions address critical contemporary issues such as the distributional impacts of globalization and the role of digital technologies in reducing rural-urban divides. Advising and grants information is not specified, but his extensive collaborations with global institutions and co-authors from universities like MIT, Yale, and Peking University highlight his network-driven research approach. Faber's work is methodologically rigorous, combining large-scale data analysis with theoretical frameworks to inform policy decisions on migration, trade, and development interventions.
Francesca Marazzi is an Assistant Professor at the University of Rome Tor Vergata's Department of Economics and Finance. She holds affiliations with the CESifo Research Network (as an affiliate), the CESIEG research centre at LUISS Guido Carli University (Deputy Director), and the DEMA P research cluster at Middlesex University, London. Her research focuses on behavioral and experimental economics, particularly exploring dishonest behavior, responsibility avoidance, and health economics issues like women's health and obesity interventions. She teaches courses such as 'Coding for Economic Applications' and 'Research Methods for Social Sciences' at both bachelor's and master's levels. Her work bridges theoretical models with empirical experimentation, addressing topics like corruption, public goods provision, and policy design. Notable contributions include studies on transparency's impact on bribery, pandemic-related behavioral changes, and the effects of soft drink taxation on adolescent health. She actively participates in interdisciplinary projects, such as the CREA initiative integrating AI and mathematics for fairness assertions, and the LongITools exposome analysis in chronic disease research. Marazzi's academic output emphasizes experimental methodologies, with recent focus on pandemic-driven behavioral shifts, financial stability mechanisms, and innovative governance metrics leveraging earth observation data post-wildfires. Her research portfolio reflects a commitment to applied microeconomic analysis with direct societal relevance.
Professor Aris Syntetos is a Distinguished Research Professor and DSV Chair of Logistics and Manufacturing at Cardiff Business School, Cardiff University. He is the founder and Director of the PARC Institute of Manufacturing, Logistics and Inventory, which includes the RemakerSpace, and leads the university’s strategic partnership with DSV. Previously, he held faculty positions at the University of Salford and Copenhagen Business School. His research focuses on the integration of forecasting and inventory optimization, particularly in the context of intermittent demand, spare parts, closed-loop supply chains, and additive manufacturing. He is renowned for the Syntetos-Boylan Approximation and the Syntetos-Boylan-Croston classification method. His work is driven by sustainability and social impact, aiming to reduce inventory obsolescence and support circular economies. The 15 most recent publications highlight a strong trend toward integrating forecasting with inventory and maintenance decisions, with increasing emphasis on sustainability, social good, and advanced analytics. His work spans healthcare, automotive, retail, and humanitarian logistics, often employing machine learning and empirical validation. 2024 Goodeve Medal (Operational Research Society) 2016 Cardiff University Outstanding Doctoral Supervisor Award 2016 & 2019 Cardiff University Innovation and Impact Awards He has secured over £5 million in research funding as Principal Investigator from EPSRC, Innovate UK, and the Welsh Government, leading projects on remanufacturing, 3D printing, and sustainable supply chains. He advises major firms like Ocado, BT, and DSV, and his methods are used in commercial software. He supervises PhD students and actively promotes knowledge transfer. He is Editor-in-Chief of the IMA Journal of Management Mathematics and serves as Vice-President of the International Society for Inventory Research (ISIR). He has taught in the UK, China, Colombia, Denmark, France, Greece, Italy, and Latvia, primarily in Operations Management and Applied Statistics.
Bahman Rostami-Tabar is Professor of Analytics and Decision Sciences at Cardiff Business School, Cardiff University, UK. He is the founder and director of the Data Lab for Social Good and the founder and chair of the Forecasting for Social Good (F4SG) initiative sponsored by the International Institute of Forecasters. He also leads the 'Uncertainty & the Future' theme at the Digital Transformation Innovation Institute. His research spans probabilistic forecasting, operational research, and data science with applications in healthcare, humanitarian logistics, and sustainable development. Research Interests: His work emphasizes transforming data into insights for decision-making under uncertainty. His research is structured into three pillars: (1) Conceptual work on forecasting for social good and the UN Sustainable Development Goals; (2) Methodological innovations in temporal aggregation, hierarchical forecasting, and machine learning for time series; and (3) Applications in healthcare operations, global health, and humanitarian supply chains. He has collaborated with organizations such as the NHS, USAID, ICRC, and JSI. Publication Trends: His recent publications (2023–2025) focus on probabilistic forecasting in healthcare (e.g., emergency department arrivals, trauma networks), hybrid machine learning models for humanitarian demand, and the societal role of forecasting. There is a strong emphasis on real-world impact, with applications in public health, supply chain resilience, and data-driven policy. Scientific Awards: Goodeve Medal, Operational Research Society, UK (2024) Fellowship, Institute of Advanced Studies, Montpellier, France (2024) Public Value Fellow, Cardiff Business School (2021) Associate Fellow, NHS-R community (2021) MIM best paper award (IFAC, 2013) Best Track Paper Award, International Symposium on Industrial Engineering and Operations Management (2017) Supervision and Grants: He actively supervises PhD students in forecasting, healthcare systems, and supply chains. He leads the 'Democratising Forecasting' project, delivering free R-based forecasting training in developing countries. He also chairs the F4SG Research Grant program, awarding $5,000 to researchers in low- and lower-middle-income countries for socially impactful forecasting research. Labs and Teams: He founded and directs the Data Lab for Social Good at Cardiff Business School and leads the international Forecasting for Social Good network, which includes learning labs, hackathons, and a forecasting book club to foster global collaboration.
Giovanni Compiani is an Associate Professor at the University of Chicago Booth School of Business, specializing in Marketing. His research bridges industrial organization and quantitative marketing, focusing on advanced econometric methods. PhD, MPhil, MA in Economics from Yale University BSc, MSc in Economics from Bocconi University Previous Assistant Professor at Haas School of Business His work explores unstructured data integration in demand estimation, consumer search behavior on online platforms, risk preferences in cryptocurrency markets, and time perception in behavioral economics. He has published in top journals including Journal of Political Economy , Marketing Science , and Review of Economic Studies . Recent publications emphasize machine learning applications in econometrics, equilibrium modeling of lotteries, and crypto mining's economic impact. His research portfolio spans demand analysis, structural modeling, and behavioral insights. Editor's Choice Award, The Review of Asset Pricing Studies (2024) Developed nonparametric demand estimation frameworks Advances dynamic model identification with instrumental variables Compiani teaches Data Science for Marketing Decision Making at Booth and maintains active collaborations with researchers across econometrics, computer science, and behavioral disciplines.
Dr. Summer Han serves as Associate Professor of Medicine, Neurosurgery, and Epidemiology at Stanford University School of Medicine. She leads research through the Quantitative Sciences Unit (QSU) in the Biomedical Informatics Research Division of the Department of Medicine and maintains joint appointments in the Department of Neurosurgery. Her work bridges statistical methodology development with clinical applications in cancer screening and neuroscience. Her research program focuses on statistical genetics, molecular epidemiology, and risk prediction modeling for complex diseases. Key areas include developing novel methods for analyzing high-dimensional genomic data, creating dynamic risk prediction models under competing risks, and establishing evidence-based cancer screening strategies. Her team integrates genetic, environmental, and clinical factors to improve early detection of lung cancer and second primary malignancies, with particular attention to reducing racial disparities in screening outcomes. Dr. Han's scientific contributions have been recognized through prestigious awards including the NCI R37 MERIT Award for Early-Stage Investigators and the Department of Medicine Teaching Award in Biomedical Informatics Research. Her team has developed impactful tools such as the SPLC-RAT for second primary lung cancer risk assessment and RAMBO for brain metastasis prediction in lung cancer patients. She actively mentors PhD students and postdoctoral fellows, with several former trainees securing faculty positions at institutions including Cornell University and IIT Roorkee. Current research initiatives include the Oncoshare-Lung database integrating EHRs from Stanford Health Care and 23+ Sutter Health sites across Northern California, and the Cancer Data Science Shared Resources Core which she co-directs at the Stanford Cancer Institute. NCI R37 MERIT Award (Early-Stage Investigator) 2022 Department of Medicine Teaching Award in Biomedical Informatics 2024 SCI Equity Impact Research Grant 2024 Neurosurgery Research Seed Grant Award Multiple NCI R01 grants (CA226081, CA282793) Her laboratory collaborates extensively across Stanford Medicine, working with thoracic oncologists, neurosurgeons, and epidemiologists to translate statistical innovations into clinical practice. Current projects address socioeconomic factors in cancer risk stratification, real-time physical activity monitoring in spine surgery recovery, and machine learning approaches for genomic data analysis.
Julien Chanal is a researcher at the Faculty of Psychology and Educational Sciences, University of Geneva, specializing in Methodology and Data Analysis (MAD group). His work bridges educational psychology, motivation theory, and neuropsychology through empirical studies on self-determination, physical activity, and cognitive function. Primary affiliation: University of Geneva Research focus: Motivation and executive function assessment Key areas: Physical education, materialism effects, neuropsychological testing His research spans two decades, producing 38 publications with over 19,000 views. Recent projects examine motivation multidimensionality (2025), aerobic fitness-cognition links (2024), and neural correlates of materialism (2018). Despite extensive publication history, specific student names remain unspecified. Methodological innovations include epoch-length analysis in physical education (2015), self-concept modeling (2009), and neuropsychological norm establishment in Cameroon (2009). His work remains actively cited across disciplines, though no scientific awards are explicitly documented in available sources.
Dr. Anh Nguyen Nguyen Duc serves as Full Professor at the University of South-Eastern Norway and the Norwegian University of Science and Technology (NTNU), with visiting scholar positions across Norwegian, Finnish, Italian, and Vietnamese institutions. His academic work centers on software engineering with emphasis on human, process, and ecosystem dimensions of development. Education: MS: Technical University of Kaiserslautern and Blekinge Institute of Technology (double degree) PhD: Norwegian University of Science and Technology Research fingerprint analysis reveals dominant focus on software startups (27%), supplemented by software processes (6%) and engineering education (5%). His expertise spans cybersecurity, global software development, business-driven methodologies, and software analytics, consistently addressing human-organizational challenges in dynamic development environments. Recent publications (2024-2025) demonstrate accelerating integration of AI in software engineering, particularly through large language models for startup assistance, generative AI adoption frameworks, and autonomous agent systems. Concurrently, he investigates risk management in software ventures and fairness in educational ML applications, reflecting interdisciplinary work bridging software engineering with business, AI ethics, and educational technology.
Bogusława Whyatt is a Professor at the Faculty of English, Adam Mickiewicz University, Poznań. She holds a D.Litt. in linguistics (2014), Ph.D. in English (2000), and MA in English (1992) from Poznań institutions. Her academic profile spans psycholinguistics, translation studies, and cognitive approaches to translation processes. Key research themes include: Translation process dynamics and directionality effects Eye-tracking applications in translation reception studies Development of translation competence and pedagogy Psycholinguistic analysis of language processing Metacognitive skill transfer between translation and paraphrasing Recent publications focus on cognitive effort metrics, directionality impacts, and empirical methodologies combining eye-tracking and key-logging data. She leads major projects like Read Me (2021-2025) and EDiT (2016-2019), examining translated text reception and translation directionality respectively. Scientific honors include three consecutive Adam Mickiewicz University Rector's Awards for Organizational Excellence (2018, 2023, 2024). She supervises PhD research in translation cognition and has mentored four doctoral candidates to completion. Active in professional networks like the MC2 Lab and TREC consortium, she contributes to cognitive translation studies through methodological innovations and international conference organization. Her methodological expertise includes psychometrics, EEG research, and ATLAS.ti data analysis tools.
Michael Knaus is a Junior Professor (Assistant Professor) in the Department of Economics within the Faculty of Economics and Social Sciences at the University of Tübingen, Germany. His office is located at Mohlstraße 36, 4th floor, room 415. He teaches graduate-level courses on causal inference and causal machine learning. Dr. Knaus specializes in the intersection of causal inference and machine learning, with particular expertise in Double Machine Learning methods. His research focuses on developing advanced statistical techniques to estimate treatment effects across various economic contexts including labor markets, finance, education, and health economics. His work bridges theoretical econometrics with practical applications, emphasizing methodological rigor and real-world relevance. His recent publications demonstrate a clear progression toward increasingly sophisticated methods for handling heterogeneous treatment effects and complex causal structures. His research shows strong integration of machine learning algorithms with causal inference frameworks to address challenging policy questions across multiple domains. Double Machine Learning based Program Evaluation under Unconfoundedness (The Econometrics Journal, 2022) Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach (Journal of Human Resources, 2022) How Does Post-Earnings Announcement Sentiment Affect Firms' Dynamics? (Journal of Financial Econometrics, 2024) Effect or Treatment Heterogeneity? Policy Evaluation with Aggregated and Disaggregated Treatments (2021) Dr. Knaus has made significant methodological contributions through his development of the causalDML R package, which implements Double Machine Learning methods for binary and multiple treatment effect estimation. His work has been published in top econometrics and economics journals and has gained recognition in the research community, with his GitHub repository accumulating 36 stars. He frequently collaborates with Michael Lechner, a leading researcher in causal inference and program evaluation. His teaching includes E464 Causal Inference and E463 Causal Machine Learning, both graduate courses that combine theoretical foundations with practical implementation using R. These courses prepare students for advanced research and data science roles requiring sophisticated causal reasoning skills, emphasizing hands-on application of methods to real-world problems.
Pietro Rombola' is a PhD candidate (39th cycle, 2023-2026) and external lecturer at the Polytechnic University of Turin's Department of Management and Production Engineering (DIGEP). His academic appointment includes part-time teaching responsibilities alongside doctoral research under the supervision of Paolo Neirotti and Danilo Pesce. Teaching Activities: He serves as course collaborator for: Technology and Innovation Management module (Master's in Agritech Engineering, 2024/25) Challenge@PoliTo industry projects with EDISON NEXT SpA and NODES Spoke 1/IREN SpA (Engineering and Management, 2023/24) Future of Work curriculum (Bachelor's in Management Engineering, 2024/25) Research Focus: His work centers on Business Model Innovation with applications in sustainable energy transitions. Primary interests include: Managerial tensions in innovation implementation Sustainability-driven business model redesign Energy sector case methodologies Cross-industry convergence dynamics Publication Trends: His conference proceedings (2023-2025) demonstrate consistent focus on business model innovation frameworks within energy markets, employing empirical case studies to examine sustainability trade-offs, organizational adaptation, and performance impacts in transitional economies.
Tracy Hall is Professor in Software Engineering at Lancaster University's School of Computing and Communications, where she holds a Chair in Software Engineering Research and serves as Director of Post Graduate Teaching. Previously, she was Professor and Head of Computer Science at Brunel University London, and has held visiting positions at University College London and adjunct roles at the University of Oslo. With over 20 years of empirical software engineering research experience, she maintains extensive industrial collaborations. Her research focuses on: Software defect prediction and automatic repair Code analysis methodologies Software testing frameworks Human factors in software development Empirical studies of developer behavior Tool development for software engineers She leads research in automated defect repair techniques and vulnerability prediction, with recent work exploring AI-driven approaches to software quality improvement. Her publication portfolio (100+ papers) shows consistent focus on software quality enhancement, with recent emphasis on explainable AI for vulnerability prediction (2025), developer-centric testing tools (2024), and human factors in bug resolution (2022). Research frequently involves large-scale empirical studies and industry partnerships. Awards include multiple best paper awards for her contributions to software engineering research. As Principal Investigator, she secured significant funding including: EPSRC Fixie project: £400,000 for defect prediction/repair (2018-2020) EPSRC Fault Analysis grant: £128,578 (2016-2019) Current PhD supervisees include Gaz Bennett, Jesse Phillips, and Miles Walker working on software engineering challenges. She contributes to the Cyber Security Research Centre , Security Lancaster , and DSI-Foundations research groups. Teaches courses on IT Architecture and Software Studio.
Scott Shane is the A. Malachi Mixon III Professor of Entrepreneurial Studies and Professor of Economics at the Weatherhead School of Management, Case Western Reserve University, where he has been faculty since 2003. As the school's most highly cited researcher, his work bridges entrepreneurship, economics, and neuroscience with over 94 scholarly articles and 16 books including award-winning titles like Illusions of Entrepreneurship and Fool's Gold . Education: PhD, University of Pennsylvania (1992) Master of Science, University of Pennsylvania (1991) Master of Science, Georgetown University (1988) AB, Brown University (1986) Research Focus: Shane's work centers on five interconnected domains: (1) opportunity discovery and evaluation processes; (2) university spin-offs and technology commercialization; (3) business format franchising dynamics; (4) angel investment mechanisms; and (5) the genetic and neural underpinnings of entrepreneurial behavior. His research uniquely integrates biological perspectives with traditional entrepreneurship theory, challenging conventional wisdom through rigorous empirical analysis. Publication Trends: Recent work shows increasing interdisciplinary convergence, particularly in neuroscience applications to investor decision-making and founder behavior. His 2020-2025 publications demonstrate heightened focus on pitch dynamics, pandemic economic impacts, and genetic factors, while maintaining his signature critical analysis of entrepreneurship myths. The consistent appearance in top journals like Management Science and Academy of Management Journal underscores his field leadership. Scientific Recognition: Global Award for Entrepreneurship Research (2009) Weatherhead Enduring Impact Award (2015) Case Western Faculty Distinguished Research Award (2017) Multiple Best Business Book Awards for Illusions of Entrepreneurship and Fool's Gold Academy of Management Best Paper Award (2020, 2021) Professional Engagement: Beyond academia, Shane serves as Managing Director of the Comeback Capital Fund (investing in Heartland startups) and previously held board positions at JumpStart Inc. (2008-2009) and NorthCoast Angel Fund (2006-2018). He has consulted globally for organizations seeking innovation strategy guidance and taught executive education programs worldwide, while his classroom instruction focuses on entrepreneurial finance and technology strategy. Research Infrastructure: Shane's work is supported through the Greif Center for Entrepreneurship at Weatherhead, where he has directed major projects on technology commercialization and new venture finance. His current research leverages fMRI technology and genetic data to explore biological foundations of entrepreneurship, collaborating with interdisciplinary teams across economics, psychology, and neuroscience departments.
