Claus Munk is a Professor at Copenhagen Business School's Department of Finance, where he researches dynamic asset allocation, life-cycle financial planning, and housing economics. His work employs stochastic modeling to analyze consumption-investment decisions under uncertainty. Research interests focus on: Optimal portfolio strategies across life stages Housing market interactions with financial decisions Retirement savings mechanisms and decumulation Stochastic interest rate and income risk modeling Welfare implications of financial regulations Publication analysis reveals consistent focus on life-cycle finance since 1998, with recent emphasis on retirement systems (2019), mortgage structures (2018), and ETF-based portfolios (2024). Methodologically, his work combines theoretical frameworks with empirical validation using household data. Professor Munk maintains research collaborations with Goethe University Frankfurt economists and co-advises projects through Copenhagen Business School. His personal academic website is available at: http://sites.google.com/view/clausmunk/home
Professor Tim Straub serves as Professor for General Business Studies, particularly Management of Digital Technologies at Hochschule Reutlingen's ESB Business School since 2023. He also holds the position of Programme Director for the BSc International Management Double Degree (IMX) and Programme Leader for the German-Mexican Double Degree program. His academic journey includes previous roles as Interim Professor for Information Systems and Business Analytics (2021-2023), Department Lead at FZI Forschungszentrum Informatik (2019-2021), and research positions at Karlsruhe Institute for Technology. His educational background includes: Doctorate (Dr. rer. pol.) from Karlsruhe Institute for Technology (2017) Master of Science in Information Engineering and Management from Karlsruhe Institute for Technology (2010-2013) Bachelor of Science in Information Engineering and Management from Karlsruhe Institute for Technology (2006-2010) Professor Straub's research spans Management Information Systems, Platform Economics, and Business Analytics with a recent strong focus on industrial applications of artificial intelligence. His work bridges theoretical frameworks with practical manufacturing applications, particularly in explainable AI for root cause analysis, production optimization, and quality control in industrial settings. He has developed frameworks that combine machine learning with traditional quality management approaches like the Ishikawa model, making AI more accessible to shopfloor workers. Analyzing his 15 most recent publications (2022-2025), a clear trend emerges toward applied AI research in manufacturing contexts. Approximately 75% of his recent work focuses on AI applications in industrial production, particularly CNC tool manufacturing, gear production, and quality control systems. His research consistently emphasizes explainability, ensuring AI systems provide transparent reasoning that industrial workers can understand and trust. The interdisciplinary nature of his work combines information systems theory with mechanical engineering applications. Professor Straub maintains an active research agenda with consistent publication output across top conferences and journals in information systems and manufacturing. His collaborative approach is evident in his extensive co-authorship network, particularly with researchers like Daniel Kiefer, Günter Bitsch, and Clemens van Dinther. While specific funding sources aren't detailed in the provided information, his applied research focus suggests strong industry partnerships and potential involvement in German government-funded digitalization initiatives, as indicated by publications in the 'Projektatlas Künstliche Intelligenz in der Produktion' supported by the Federal Ministry of Education and Research. Students working with Professor Straub would engage with cutting-edge research at the intersection of business administration and digital technologies, with particular opportunities in AI applications for manufacturing industries. His role as program director for international double degree programs indicates a commitment to global educational experiences and cross-cultural business perspectives.
Professor Frank Truckenmüller is a faculty member at Reutlingen University's Faculty of Engineering in the Department of Energy Systems and Energy Efficiency. He serves as a key researcher at the REZ - Reutlinger Energiezentrum (Reutlingen Energy Center), focusing on practical implementation of energy system innovations. His research centers on virtual power plant technologies, particularly the 'Virtuelles Kraftwerk Neckar-Alb' demonstrator project. Key interests include: Power distribution automation and cable network optimization Electricity price forecasting for energy markets Integration of renewable energy sources into grid systems CO2 heat pump technologies and low-voltage grid management Regional energy cycle development Recent publications (2021-2024) demonstrate strong activity in grid automation, with multiple papers on cable distributor systems and virtual power plant implementation. His work bridges theoretical modeling with practical field applications, particularly in the Neckar-Alb region. Professor Truckenmüller teaches Energy Technology covering: Development trends in energy systems Conventional and renewable energy technologies Energy conversion fundamentals Energy systems team management His research is supported through the ZIM-Kooperationsnetzwerk 'Virtuelles Kraftwerk Neckar-Alb', which provides practical demonstration capabilities for virtual power plant concepts. The REZ facility enables collaboration on decentralized energy systems and grid integration challenges. Office hours are Wednesdays by appointment in Building 20, Room 214. Contact: frank.truckenmüeller@reutlingen-university.de | +49 7121 271 7100.
Gül Calikli is an Associate Professor (Senior Lecturer) in Software Engineering at the School of Computing Science, University of Glasgow, United Kingdom. She has held academic positions at several prestigious institutions including the University of Zurich as a senior researcher, Chalmers | University of Gothenburg as a lecturer, and postdoctoral fellowships at The Open University (UK) and Ryerson University (Canada). Dr. Calikli earned her Ph.D. in Computer Engineering from Boğaziçi University in Istanbul. Her academic journey reflects a strong commitment to advancing empirical software engineering with a focus on human aspects. Dr. Calikli's research centers on the intersection of software engineering and cognitive psychology, with a particular emphasis on understanding and mitigating cognitive biases in software development practices. Her work explores how human cognitive limitations impact program comprehension, code review, and vulnerability detection. She investigates how to present information effectively to software practitioners considering human cognitive constraints, and develops tools and techniques based on cognitive psychology to enhance decision-making in software development. Her research also incorporates machine learning systems with "human in the loop" approaches, creating joint cognitive systems that extend human intelligence. Analysis of Dr. Calikli's recent publications reveals a consistent focus on human aspects in software engineering, particularly examining cognitive biases like confirmation bias and their impact on software quality. Her work spans multiple domains including code review practices, vulnerability detection, program comprehension, and privacy-aware software development. A notable trend is her methodological approach combining controlled experiments, field studies, and quantitative analysis of system logs to investigate human factors in software engineering. Best Paper Award at ESEM2013 (Industry Track) Chalmers Area of Advance SEED Funding in 2018 ACM SIGSOFT Distinguished Artifact Award at ICSE 2020 ACM Distinguished Paper Award at ICSE 2021 ACM SIGSOFT Distinguished Paper Award at ESEC/FSE'22 Distinguished Reviewer Award at ICSME'23 Distinguished Reviewer Award at ICPC'22 Dr. Calikli actively supervises PhD students working on diverse topics including team dynamics in agile development, eye-tracking for human-AI pair programming, leveraging LLMs for software development/testing, and sustainability in software engineering teams. She has served on numerous program committees for major software engineering conferences including ASE, ICSE, FSE, and ESEC/FSE. Her research has been supported by various funding mechanisms, including the Chalmers Area of Advance SEED Funding. As an active member of the software engineering community, Dr. Calikli contributes to the advancement of the field through her service on editorial boards (including ACM Transactions on Software Engineering and Methodology), participation in the EPSRC Peer Review College, and organization of conference tracks such as the ICPC 2024 ERA Track which she co-chaired.
Jingyue Li is a Professor in the Department of Computer Science at the Norwegian University of Science and Technology (NTNU), within the Faculty of Information Technology and Electrical Engineering. She earned her Ph.D. in Software Engineering from NTNU in 2006 and has extensive industrial experience including positions at IBM and DNV Research and Innovation. Her educational background includes: Ph.D. in Software Engineering from NTNU (2006) Professor Li's research spans several key areas in software engineering with a focus on both theoretical and practical applications. Her work bridges traditional software engineering practices with emerging technologies, particularly in the domain of security and blockchain systems. She has conducted extensive empirical research and applied design science methodologies to develop innovative tools and approaches. Her recent publications demonstrate a strong trend toward blockchain technologies, software security, and the intersection of AI with software engineering. The research shows increasing focus on practical applications of blockchain in decentralized autonomous organizations, consensus protocols, and security vulnerabilities in smart contracts. There's also significant work on integrating security practices into DevOps (DevSecOps) and applying machine learning techniques to software engineering problems. Professor Li has received recognition through her leadership roles in major conferences: General Chair for FSE 2025 (The ACM International Conference on Foundations of Software Engineering) Member of the EASE (International Conference on Evaluation and Assessment in Software Engineering) steering committee In terms of research leadership, Professor Li has served as Principal Investigator (PI) or Key Scientist on numerous research projects including TRACE4EU (2023-2025), PaaSforChain (2020-2023), CyberSmart (2017-2020), and several others focused on blockchain, security, and software engineering. She has also conducted research visits to institutions including University College London, University of Washington, Hiroshima University, and Peking University. Her research group appears to be actively engaged in both theoretical and applied research, with strong industry connections through projects like CyberSmart and SecureCyber that address real-world challenges in cybersecurity and smart city infrastructure.
Prof. Dr. Markus Reichstein serves as Director of the Department of Biogeochemical Integration at the Max Planck Institute for Biogeochemistry and Professor of Global Geoecology at Friedrich Schiller University Jena. He is Founding Director of both the Michael Stifel Center Jena for Data-Driven and Simulation Sciences and the ELLIS Unit Jena, positioning him at the forefront of integrating artificial intelligence with Earth system science. His research focuses on understanding ecosystem responses to climate variability from an Earth system perspective, with particular emphasis on climate extremes and ecosystem resilience. Prof. Reichstein combines artificial intelligence with systems modeling approaches to analyze experimental data, ground-based observations, and satellite Earth observations across multiple spatial scales. His recent publication record shows a strong emphasis on applying machine learning to biogeochemical processes, with numerous 2025 publications addressing carbon cycle modeling, soil moisture prediction, drought impacts, and AI applications for climate risk assessment. These works demonstrate his interdisciplinary approach that bridges ecology, climate science, and computational methods. Piers J. Sellers Mid-Career Award from the American Geophysical Union (2018) ERC Synergy Grant (2019) Gottfried Wilhelm Leibniz Prize (2020) AGU Fellow (2025) As department director and through his various leadership roles, Prof. Reichstein oversees substantial research funding and mentorship opportunities. His department regularly welcomes new researchers and students, fostering an environment of international collaboration. The integration of the Michael Stifel Center and ELLIS Unit with his department creates unique opportunities for students interested in the intersection of AI and environmental science. The Department of Biogeochemical Integration, under Prof. Reichstein's leadership, serves as a hub for innovative research on Earth system processes, combining traditional ecological approaches with cutting-edge computational methods to address pressing climate challenges.
Ralf Fendel is a Professor at WHU – Otto Beisheim School of Management, where he is a member of the Economics Group. His research focuses on macroeconomic policy with particular emphasis on the European Central Bank, monetary theory, and international finance. Contactable at ralf.fendel@whu.edu, he investigates critical contemporary issues including financial crises, climate change impacts on monetary policy, and Eurozone economic stability. Professor Fendel's expertise spans Macroeconomics (including Open Economy Macroeconomics), Monetary Theory and Policy, International Finance, European Integration, Growth and Development, and Financial Crises. His work consistently addresses the European Central Bank's policy mechanisms, inflation dynamics, and the interplay between monetary policy and global economic challenges. Recent research explores how climate change affects financial stability and how geopolitical events like Trump's trade war influence market behavior. Analysis of his 14 publications from 2020-2023 reveals a concentrated research trajectory on ECB communications, monetary policy transmission in the Eurozone, and pandemic-era economic responses. Key methodological approaches involve econometric analysis of bond yields, inflation forecasting, and recession probability modeling. His work demonstrates how central bank forward guidance affects market expectations and how country-specific factors mediate policy impacts across Eurozone core and periphery nations. As part of WHU's Economics Group, Professor Fendel contributes to a research ecosystem focused on European economic policy development. The group examines macroeconomic theory, monetary economics, and international finance through both theoretical frameworks and empirical analysis of real-world policy challenges, with particular attention to ECB operations and Eurozone integration dynamics.
Dr. Andrea Silber is a Professor of Medicine (Medical Oncology) at Yale School of Medicine and serves as the Assistant Clinical Director for Diversity and Health Equity at Yale Cancer Center. She is also the Associate CEHE Director for Clinical Research and the Medical Director of the Connecticut Cancer Screening Program (CCSP). With over 40 years of experience in oncology, Dr. Silber specializes in breast cancer treatment with a focus on underserved populations, particularly African American women, and has directed a cancer clinic for the uninsured and underinsured for two decades. Dr. Silber's educational background includes: MD from Yale University School of Medicine (1982) BA from New York University (1981) Undergraduate studies at Oberlin College (1977) Residency and fellowship training at Yale-New Haven Hospital Dr. Silber's research focuses on breast cancer disparities, community outreach, and improving access to cancer care for underserved populations. She has designed culturally competent programs like the Comprehensive Breast Cancer Outreach and Support Program for Underserved Women and received national recognition for her expertise in breast cancer among African American women. Her recent work examines cardiovascular risk in cancer survivors, health disparities in breast cancer outcomes, and the experiences of women of color after mastectomy through the 'Living Flat' study, demonstrating her commitment to addressing systemic barriers to care through community partnerships. Dr. Silber's publication record shows a consistent focus on breast cancer research with emphasis on health equity. Her recent work spans clinical trials, epidemiological studies, and community-based research examining outcomes for underserved populations. She frequently collaborates with researchers across Yale Cancer Center on studies related to treatment response, survivorship, and health disparities in cancer care, often bridging clinical oncology with community outreach to address systemic barriers to care. Dr. Silber has received numerous prestigious awards for her contributions to cancer care and health equity: Connecticut Cancer Partnership Cancer Champion Award (2019) Yale Cancer Center Award for Excellence in Clinical Care (2019) Women in Strength Award, Get in Touch Foundation (2010) Physician of the Year, Business New Haven (2009) Lane Adams Quality of Life Award (2007) National Komen award for the Sister to Sister Program (1996) As a principal investigator, Dr. Silber leads several significant research initiatives focused on improving care for underserved cancer patients. She directs the Avon-Pfizer Metastatic Breast Cancer Grants Program: Identify-Amplify-Unify, which helps organizations support patients navigating medical and emotional challenges. She also leads the 'Breast Cancer S.W.A.T. Team' program funded by CT Health and Educational Facilities Authority. Through her role with the Connecticut Health Foundation leadership fellowship, she works to increase clinical trial participation among ethnic minorities. Her research often involves medical-legal partnerships to help economically disadvantaged breast cancer patients adhere to treatment. While Dr. Silber does not appear to lead a specific research laboratory, she is deeply involved with multiple research teams and initiatives at Yale Cancer Center. She collaborates extensively with the Center for Breast Cancer and participates in clinical research teams focused on breast oncology. Her work emphasizes community partnerships and culturally competent care delivery, with a focus on building sustainable relationships that improve cancer screening and treatment access for diverse populations in the Greater New Haven area.
Prof. Dr. Thomas Kopinski is a Professor at the Faculty of Engineering and Economics, South Westphalia University of Applied Sciences in Meschede, Germany. He leads the AI Safety and Collective Intelligence Lab, focusing on cutting-edge research in machine learning applications for industrial and automotive systems. His work bridges academic research and industry collaborations, notably with BMW AG. Research Focus: His team explores: Deep learning architectures for real-time gesture recognition and automotive HMI AI safety protocols and collective intelligence frameworks Industrial applications including predictive maintenance and anomaly detection 3D programming and sensor fusion techniques Team & Students: Current advisees include PhD candidates working on: Bayesian deep learning for predictive maintenance (Felix Neubürger) Generative models for image synthesis (Yasser Saeid) Object recognition in crash test videos (Daniel Gierse) Key Projects: Actively directs WiTraPres and Core Transformer initiatives, with upcoming R&D in AI Safety launching in 2025. Industrial collaborations focus on automotive safety systems and manufacturing optimization.
Michael Hochberg is a Research Director at the French National Centre for Scientific Research (CNRS) and External Professor at the Santa Fe Institute. He is affiliated with the Institute of Evolutionary Sciences of Montpellier (ISEM) at the University of Montpellier, where he leads the Experimental Community Evolution Team. His research bridges evolutionary biology, disease ecology, and applied therapeutics. Hochberg's work explores how environmental and spatial dynamics mediate ecological and evolutionary processes, with emphasis on: Phage-bacteria coevolution and antibiotic resistance management Cancer evolution, intratumor heterogeneity, and adaptive therapies Social evolution in pathogens and transitions from parasitism to mutualism Ecosystem-level approaches to disease treatment His recent publications (2017–2021) demonstrate strong foci on evolutionary medicine, including phage steering to combat antibiotic resistance, COVID-19 mitigation modeling, tumor clonal dynamics, and ecological frameworks for disease management. These works integrate experimental data with computational models to predict therapeutic outcomes. Hochberg mentors a robust cohort of students and postdocs, with alumni now in academic roles worldwide. His lab investigates community evolution through microbial systems, cancer cell interactions, and environmental feedback on social behaviors.
Manfred Stoll is a Full Professor and Head of the Department of General and Organic Viticulture at Hochschule Geisenheim University. His research focuses on sustainable viticulture, climate change adaptation, and grapevine physiology. He holds a PhD from the University of Adelaide and a Diploma in Biology from Julius Maximilians University of Würzburg. Research interests include: Vineyard responses to elevated CO₂ and drought stress Agrivoltaic system economics in viticulture Organic/biodynamic viticulture life-cycle assessments Precision viticulture technologies for stress monitoring His recent publications analyze climate adaptation strategies, berry ripening under environmental stressors, and sustainable vineyard management. Trends include agrivoltaics integration, CO₂ impact studies, and terroir-specific climate resilience. Stoll leads field experiments like the VineyardFACE project, investigating carbon enrichment effects on grape composition. He collaborates internationally on climate adaptation research and develops low-input viticulture systems for steep-slope terrains.
Alexander Mitsos is a Professor at Forschungszentrum Jülich in Germany, where he leads research at the intersection of process systems engineering, chemical engineering, and computational methods. His work spans optimization theory, machine learning applications, and energy systems, with a focus on developing novel methodologies for complex engineering problems across multiple domains. Dr. Mitsos's research interests center on the application of advanced optimization techniques to chemical engineering problems. His primary areas of focus include: Process systems engineering and optimization Machine learning applications in chemical engineering Energy systems and hydrogen technologies Bioprocess engineering and control systems Ammonia energy storage and carbon capture His recent publications reveal a strong trend toward integrating machine learning with traditional chemical engineering approaches. He has pioneered work on graph neural networks for molecular property prediction, reinforcement learning for control systems, and bilevel optimization for energy systems. His research demonstrates a consistent focus on developing computationally efficient methods that bridge theoretical advances with practical engineering applications, particularly in sustainability-focused domains like hydrogen technologies and carbon emission reduction. The analysis of his 15 most recent publications shows a balanced portfolio between theoretical method development (e.g., optimization algorithms) and practical applications (e.g., cement production, hydrogen compression). Dr. Mitsos has mentored numerous graduate students and postdoctoral researchers, as evidenced by his extensive publication record with junior authors. His research has been supported by various grants focused on energy transition, process optimization, and sustainable chemical engineering solutions, with significant collaborations across European institutions. The funding landscape for his work appears to emphasize sustainability transitions and industrial decarbonization, particularly in energy-intensive sectors. His work appears to be conducted within a research group focused on process systems engineering, with strong connections to both computational mathematics and practical chemical engineering applications. The group maintains laboratories for experimental validation of computational models, particularly in bioprocess engineering and hydrogen technologies, while maintaining strong theoretical foundations in optimization and control theory.
