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Andrew CaplinView profile

Professor

• Cognitive Economics
• Behavioral Macroeconomics
• Human-AI Collaboration
• +3 more

Andrew Caplin is a Silver Professor of Economics at New York University's Department of Economics. He leads the Sloan Foundation Program on Cognitive Economics at Work and has made groundbreaking contributions to cognitive economics, behavioral macroeconomics, and human-AI collaboration. NYU Department of Economics Sloan Foundation Program on Cognitive Economics at Work Copenhagen Life Panel (CLP) research His research spans cognitive economics, focusing on decision-making mistakes, AI integration in economic systems, and housing finance reforms through equity-sharing mortgages. He developed novel frameworks for measuring subjective earnings risk, economic decision-making skills, and collaborative human-AI protocols in medical and financial contexts. Scientific Awards Sloan Foundation Program leadership Caplin's work examines belief calibration, rational inattention, and career trajectory dynamics. His Copenhagen Life Panel leverages Danish administrative data to study labor market transitions and economic well-being across life cycles, while his equity-sharing mortgage research addresses housing affordability through market design innovations.

• Tax Law
• Tax Policy
• Behavioral Economics
• +4 more

Kathleen DeLaney Thomas is the Aubrey L. Brooks Distinguished Professor of Law at the University of North Carolina School of Law , where she focuses on tax law, behavioral economics, and policy reform. Her work addresses modern challenges in taxation, including gig economy compliance, wealth tax equity, and AI-driven valuation frameworks. Key Research Areas : Tax policy, behavioral law and economics, equity in tax systems, and digital economy regulation. Collaborations : Frequently works with Jay A. Soled and Erin Adele Scharff on interdisciplinary tax studies. Policy Impact : Submits amicus briefs to influence Supreme Court cases like South Dakota v. Wayfair and Loudoun County v. Dulles Duty Free . Scientific Awards : Aubrey L. Brooks Distinguished Professor of Law Recent Article Trends explore AI integration in tax administration, quarterly reporting for gig workers, and behavioral nudges to enhance compliance. Her work bridges legal scholarship with technological and socioeconomic shifts.

• Signal Processing
• Electrical Engineering
• Machine Learning
• +3 more

Dario Sciacca is a researcher at the École Polytechnique Fédérale de Lausanne (EPFL) , affiliated with the School of Engineering . He works within the Signal Processing Laboratory 5 (LTS5) , contributing to research in signal processing and related disciplines. His primary research interests include Signal Processing Electrical Engineering Machine Learning Digital Signal Processing

• Computer Science
• Artificial Intelligence
• Pattern Recognition
• +3 more

Vlad Atanasiu is a Senior Researcher at the Department of Computer Science, University of Fribourg, affiliated through the Interfaculty unit. His work is situated within the broader domain of computer science, with a focus on intelligent systems and data analysis. The research interests of Vlad Atanasiu, inferred from his departmental affiliation and standard trajectories in computer science research, include artificial intelligence, machine learning, pattern recognition, document analysis, natural language processing, and computational linguistics. These areas align with modern challenges in understanding and processing complex data, particularly textual and structured information. No recent publications were listed in the provided text, so no trend analysis of articles can be performed. No scientific awards were mentioned in the provided information. No information was provided regarding student advisement, research grants, or funding activities. No details about labs, research teams, or collaborative groups were included in the source text.

• Operations Research
• Scheduling Optimization
• Metaheuristics
• +11 more

Marino Widmer is a Full Professor and Head of the Department of Computer Science at the University of Fribourg, within the Faculty of Mathematics, Natural Sciences and Medicine. He is actively engaged in research and academic leadership, with a strong publication record in operations research, scheduling, optimization, and intelligent systems. His research interests span Operations Research, Scheduling Optimization, Metaheuristics, Artificial Intelligence, Machine Learning, Decision Support Systems, Supply Chain Management, Automated Driving, Human-Computer Interaction, Workforce Planning, and Industrial Engineering . His recent work focuses on human factors in automated driving, including physiological monitoring, takeover quality prediction, and multimodal interfaces for driver support. The analysis of his recent publications reveals a strong trend toward interdisciplinary research combining AI, human factors, and industrial applications, particularly in transportation and public sector management. His work integrates machine learning with physiological data to improve safety in automated vehicles and applies decision analysis to real-world organizational challenges. Awarded no explicitly mentioned scientific awards. He has advised researchers such as Agneta Ramosaj and Francesca Venteicher and has been involved in projects related to fire department mergers, sales forecasting, and AI companions for drivers. While no specific grants are mentioned, his extensive publication output suggests sustained research funding. He leads the Department of Computer Science and is involved in interdisciplinary collaborations across engineering, psychology, and public administration. Marino Widmer is affiliated with the Institute for Automation and Operations Research at the University of Fribourg and has collaborated with institutions in Canada, France, and across Europe. His research has practical applications in manufacturing, transportation, and public service optimization.

Barbara BeckView profile

Lecturer

• Archaeometry
• Geochemical Traceability
• Metal Provenance
• +5 more

Dr. Barbara Beck is a Lecturer at the University of Geneva, where she conducts interdisciplinary research at the intersection of Earth sciences and archaeology. Based at B 701, 66 Bvd Carl Vogt, she specializes in archaeometry with a strong focus on the geochemical traceability of metals, particularly gold. Her work combines scientific analysis with historical inquiry to solve archaeological problems. Her research interests center on archaeometry and ancient metallurgy , employing geochemical methods and machine learning to determine the provenance of metals. This approach enables precise sourcing of archaeological metal artifacts, contributing to a deeper understanding of ancient trade, technology, and cultural exchange. Dr. Beck teaches Introduction to Ancient Metallurgy , sharing her expertise in historical metal production techniques and scientific analysis methods. Her research bridges geosciences and cultural heritage, promoting innovative applications of data science in archaeology. While no publications or awards are listed in the current profile, her work reflects a growing trend in digital and scientific archaeology. Her integration of machine learning into geochemical analysis highlights a forward-looking, interdisciplinary methodology. Dr. Beck is the founder of geoforensic Sàrl , a company likely focused on forensic geochemistry and material traceability, extending her academic work into applied and commercial domains. This initiative underscores her commitment to translating scientific research into practical solutions. She advises no students listed in the current record and has not disclosed any grant funding. However, her independent research and entrepreneurial activity suggest active engagement in both academic and professional spheres.

• Soft Robotics
• Robotic Manipulation
• Biomimetic Design
• +5 more

Kai Junge is a robotics researcher at École polytechnique fédérale de Lausanne (EPFL), affiliated with CREATE-LAB in the School of Engineering. His work focuses on developing advanced robotic systems with emphasis on compliant interactions, biomimetic design, and applications in agriculture and food systems. Dr. Junge's research interests span several cutting-edge domains in robotics: Soft robotics and compliant manipulation systems Biomimetic design of anthropomorphic robotic hands Variable stiffness actuation for improved dexterity Agricultural robotics with focus on delicate fruit harvesting Tactile sensing and multi-modal perception for contact-rich tasks Human-robot interaction and imitation learning His recent publications demonstrate a strong trend toward developing robotic systems that leverage compliance and biomimetic principles to achieve human-like or even superior manipulation capabilities. The work spans from fundamental research on compliance in robotic hands to practical applications in agriculture and food safety. A notable pattern is the development of the ADAPT Hand, which incorporates spatially distributed compliance to enhance robustness in manipulation tasks, achieving 93% success rate across 24 objects with varying geometries. His research also extends to agricultural applications where soft robotic grippers have demonstrated 95.4% picking success rate for blackberries while improving shelf life by 30-150%. Dr. Junge has been involved in several research projects funded by various organizations including the European Union's Horizon 2020 program, the Japan Science and Technology Agency, and Berry Gardens Ltd. His collaborative work with Josie Hughes and other researchers has resulted in numerous publications in top robotics conferences and journals. He is actively involved with CREATE-LAB at EPFL, where his team develops innovative robotic systems for manipulation, agricultural applications, and food safety testing. The lab's work on the ADAPT Hand, closed-structure soft grippers for agriculture, and robotic swallowing simulators demonstrates a commitment to translating robotics research into practical applications that address real-world challenges.

Angelo CiaramellaView profile

Lecturer

• People Attraction
• Talent Acquisition
• Human Resource Management
• +5 more

Angelo Ciaramella serves as a lecturer and Competence Center Manager for the CAS FH in Strategic Talent Acquisition, while operating as Managing Director of ciaramella & partner GmbH and founder of the People Attraction Institute. His professional affiliations include board membership at the HR Association ZGP and advisory roles for HR Today, positioning him at the intersection of academic instruction and industry transformation in talent management. Ciaramella's research focuses on the strategic evolution of People Attraction beyond traditional HR frameworks, emphasizing data-driven competence centers, sales-oriented service divisions, and value-added consulting units. His work examines how changing market demands necessitate repositioning talent functions as strategic sparring partners and change agents, with particular attention to AI integration and organizational development in recruitment processes. This research bridges academic theory with practical implementation across insurance, banking, media, manufacturing, real estate, transportation, and IT sectors. His recent publications demonstrate a clear trajectory toward redefining talent acquisition as a revenue-generating strategic function rather than a transactional HR activity. The articles reveal consistent themes of operational transformation, technological integration (particularly AI), and the critical need for change agent skills among executives leading talent functions. Ciaramella consistently advocates for holistic people attraction models that function as value-adding strategic units rather than support services. Through ciaramella & partner GmbH, he operationalizes these concepts by running Switzerland's first CAS FH in Strategic Talent Acquisition, developing client recruitment processes to achieve state-of-the-art Holistic People Attraction Excellence. The consultancy's approach emphasizes agile solutions that transform people attraction into a strategic sparring partner, data-driven competence center, sales-oriented service division, value-added consulting unit, and change agent for executives – embodying the theoretical frameworks explored in his publications.

Andrew SontaView profile

Assistant Professor

• Environmental Economics
• Real Estate Economics
• Public Policy
• +3 more

Andrew Sonta serves as an Assistant Professor at the Swiss Federal Institute of Technology Lausanne (EPFL), specializing in interdisciplinary research at the nexus of environmental policy, real estate economics, and behavioral science. His scholarly work investigates how green building regulations influence residential markets and societal outcomes, with a geographic focus on Switzerland. Key research themes include the economic valuation of sustainability certifications, mental health correlations with housing environments, and machine learning applications for policy impact forecasting. Current projects examine institutional frameworks shaping eco-friendly construction norms and resident well-being metrics. Recent publications analyze Switzerland's green residential policy landscape, demonstrating methodological integration of behavioral economics and computational techniques to quantify regulatory effectiveness across economic and social dimensions.

Negar KiyavashView profile

Associate Professor

• Business Analytics
• Data Science
• Machine Learning

Negar Kiyavash is an Associate Professor and Chair of Business Analytics at École Polytechnique Fédérale de Lausanne (EPFL). Her work focuses on data science and machine learning applications within business contexts. Email: negar.kiyavash@epfl.ch LinkedIn: Negar Kiyavash Profile

Sofia ForssView profile

Researcher

• Animal Behaviour
• Comparative Cognition
• Behavioral Ecology
• +5 more

Sofia Forss is an Ambizione Group Leader at the University of Zurich 's Department of Evolutionary Biology and Environmental Studies since 2022. Previously held positions include Junior Fellow at Collegium Helveticum (2021–2022) and Postdoctoral Researcher roles at the University of Zurich (2020–2021), University of Lausanne (2019–2020), and Eberhard Karls University of Tübingen (2017–2019). Education: Ph.D. in Evolutionary Anthropology (2010–2016), University of Zurich M.Sc. in Evolutionary Anthropology (2007–2009), University of Zurich B.Sc. in Biology (2003–2006), University of Zurich Her research focuses on Animal Curiosity , Comparative Cognition , and Urbanization Effects on primate behavior. Key themes include social learning mechanisms , captivity-induced cognitive changes , and developmental influences on problem-solving. Recent work examines transdisciplinary curiosity frameworks connecting animal behavior, infant psychology, and AI development. Selected publications reveal patterns in primate innovation (2025), urban vervet monkey cognition (2024), and ape curiosity dynamics (2022-2024). Research spans species from orangutans to mongooses, exploring sociality-cognition links , nutritional-social trade-offs , and methodological biases in cognitive studies. Scientific Awards: Swiss National Science Foundation funding (2022–present) Wenner Gren Foundation grant (2019–2020) Forschungskredit funding (2020–2021)

• Species Distribution Modeling
• Biodiversity Conservation
• Climate Change Ecology
• +3 more

Antoine Guisan is a Professor in the Department of Ecology and Evolution at the University of Lausanne, leading the Guisan Group within the Institute of Earth Surface Dynamics. His work focuses on species distribution modeling (SDMs), climate change ecology, and biodiversity conservation, particularly in alpine and tropical ecosystems. He collaborates extensively on mechanistic niche models, invasive species dynamics, and nature's contributions to people (NCPs). Affiliation: Department of Ecology and Evolution, Faculty of Geosciences and Environment, University of Lausanne Research Themes: Species distribution modeling, niche truncation, climate change impacts, microbial biogeography, conservation prioritization His recent publications emphasize spatially nested SDMs, glacier retreat effects on functional diversity, and invasive species modeling. Awards and part-time status are not mentioned. Students include Bart Steen, Mathieu Knight, and Antoine Adde.

Mario Daniele AmoreView profile

Professor

• Family Business
• Corporate Governance
• Strategy
• +3 more

Mario Daniele Amore is Full Professor at Bocconi University, Research Affiliate at CEPR, Research Member at the European Corporate Governance Institute (ECGI), and Board Member of the International Corporate Governance Society (ICGS). He is Associate Editor of Management Science and Journal of Corporate Finance and serves on the Editorial Review Board of the Strategic Management Journal . Research Interests: Family business dynamics and governance Corporate governance structures and mechanisms Strategic management and entrepreneurship Decision-making processes of entrepreneurs and corporate managers Venture capital and entrepreneurial finance Role of culture and organizational identity in firm performance His scholarly output (2022-2025) emphasizes how family ownership, governance choices, and leadership transitions shape innovation, patenting, and venture-capital activities. Recent themes include the impact of CEO succession on patenting in family firms, the use of AI to detect family influence, and the consequences of hiring “lucky” CEOs. Collectively, the articles span strategic management, finance, innovation, and behavioral economics. Editorial & Professional Service: Associate Editor, Management Science Associate Editor, Journal of Corporate Finance Editorial Review Board Member, Strategic Management Journal Research Affiliations: Center for Economic Policy Research (CEPR) – Research Affiliate European Corporate Governance Institute (ECGI) – Research Member International Corporate Governance Society (ICGS) – Board Member

• Cellular Automata
• Artificial Life
• Discrete Dynamical Systems
• +3 more

Barbora Hudcová is a Lecturer at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Basic Sciences and the Department of Mathematics . She works under the Chair of Statistical Field Theory and is involved in teaching courses like "Cellular Automata and Models of Artificial Life" through the SMA-ENS program. Her research focuses on computational and dynamical aspects of discrete systems. Research Interests Cellular Automata Artificial Life Discrete Dynamical Systems Computational Complexity Reservoir Computing Statistical Field Theory Publications Her work explores computational hierarchies, complexity transitions, and mathematical structures in cellular automata, with recent contributions to encoding-decoding relations and dynamical cavity methods. Key topics include artificial life modeling, computational universality, and transient behavior analysis in discrete systems.

Lénaïc ChizatView profile

Assistant Professor

• Optimal Transport
• Machine Learning
• Deep Learning
• +3 more

Lénaïc Chizat is a Tenure Track Assistant Professor at the Swiss Federal Institute of Technology in Lausanne (EPFL) within the School of Basic Sciences and Institute of Mathematics. He chairs the Dynamics of Learning Algorithms (DOLA) laboratory and teaches advanced courses in machine learning and computational optimal transport, focusing on mathematical analysis of neural networks and measure transportation theory. His research centers on optimal transport theory and its applications to deep learning, with emphasis on Wasserstein geometry, entropic regularization, and gradient flow dynamics. He investigates implicit regularization in neural networks, convergence properties of learning algorithms, and the infinite-width limits of deep architectures. His work bridges theoretical mathematics with practical machine learning challenges, particularly in computational aspects of modern supervised learning. Analysis of his 15 most recent publications (2023-2025) reveals a strong thematic focus on entropic optimal transport, where he has made fundamental contributions to Sinkhorn algorithm convergence in continuous settings and Wasserstein barycenter computation. His research consistently explores the mathematical foundations of deep learning, especially training dynamics, min-max optimization, and the role of initialization in neural network scaling. Chizat currently advises PhD student Wang Guillaume Yitian and leads the DOLA laboratory, which develops theoretical frameworks for understanding learning algorithm dynamics through the lens of optimal transport and measure-valued optimization.