Werner Ploberger is Professor of Economics and Thomas H. Eliot Distinguished Professor in Arts & Sciences at Washington University in St. Louis. His research focuses on econometric methodology, statistical analysis, and time-series econometrics. He previously held positions at Vienna University of Technology, University of St. Andrews, and University of Rochester. His influential publications develop statistical tests for structural breaks in economic models, including CUSUM test modifications and stability assessments for regression models. Committee service includes PhD Admissions and PhD committees at Washington University.
Jörg Bohlmann is a Professor in the Department of Forest and Conservation Sciences at the University of British Columbia , affiliated with the Michael Smith Laboratories, Botany Department (Faculty of Science), and Wine Research Centre. His research spans genomics, biochemistry, and chemical ecology of plant specialized metabolism, focusing on terpenoids and phenolics for applications in forest health and bioproducts. Research Streams : Plant defense against insects/pathogens, metabolic engineering of bioproducts, forest genomics, and molecular evolution of terpenoid pathways. Collaborations : National and international partnerships with academia, government, and biotech industries. Recent Publications highlight genomic insights into Western Redcedar (2023), including its low genetic diversity and adaptation mechanisms despite self-fertilization. Earlier work (2001–2022) covers conifer defense systems, Arabidopsis terpenoid pathways, cannabis flavor genetics, and mass spectrometry infrastructure. Scientific Awards include: NSERC E.W.R. Steacie Fellow (2015), Fellow of the Royal Society of Canada (2015), Feodor Lynen Postdoctoral Fellowship (1995–1998), and Distinguished University Scholar (UBC). Funding Sources : NSERC (Discovery/Strategic grants), CFI, Genome Canada/BC, provincial/federal agencies. Labs & Facilities : Michael Smith Laboratories (UBC), National Centre of Excellence, Forest Sciences Centre, and a dedicated mass spectrometry lab for metabolite analysis.
Prof. Raffaello D'Andrea is a Full Professor at ETH Zürich's Department of Mechanical and Process Engineering, affiliated with the Institute for Dynamic Systems and Control. His research focuses on bridging digital and physical worlds through robotics, control systems, and autonomous systems. He has pioneered work in aerial robotics, swarm systems, tactile sensing, and soft robotics. His philosophy emphasizes solving 'easy' problems with scalable, robust solutions, prioritizing simplicity and replicability. Key research areas include UAV navigation, distributed control, tactile sensor design, and fault-tolerant systems. He has founded multiple organizations and led roles as CTO/CEO, emphasizing cross-disciplinary innovation. His work has commercial applications in logistics, healthcare, and automation, driven by a belief in technology's role in improving human life. Notable projects include the Cubli robotic cube, aerial vehicle swarms, and optical tactile sensors for robotics. His lab emphasizes collaboration and team leadership, aiming to translate theoretical insights into practical, scalable technologies. Scientific awards: None explicitly listed in the provided texts. Advising and grants: No students listed in the provided texts; grants information not detailed. Labs/Teams: Leads research at ETH Zurich's Institute for Dynamic Systems and Control, collaborating with industry and academic partners globally.
Prof. Dr. Gonzalo Guillén Gosálbez is a Full Professor at the Department of Chemistry and Applied Biosciences , ETH Zürich. He holds a PhD in Process Systems Engineering (UPC, 2005) and has held academic positions at Imperial College London (Reader), University of Manchester (Senior Lecturer), and Universitat Rovira i Virgili (Assistant/Associate Professor). His research focuses on Sustainable Chemical Processes , integrating life cycle assessment, optimization techniques, and planetary boundary analysis to evaluate and design low-carbon technologies. Current position: Full Professor, ETH Zürich (2019–present) Prior roles: Imperial College London (2016–2019), University of Manchester (2014–2016), URV Spain (2008–2014) Education: PhD (UPC, 2005), MEng/BEng (University of Murcia) His research explores CO2 valorization , green methanol synthesis , circular marine fuels , and planetary boundary compliance in energy and chemical systems. Recent work emphasizes machine learning for process modeling, single-atom catalysis , and decentralized ammonia production . Scientific contributions include 15+ peer-reviewed articles (2023–2025) in journals like Nature Chemical Engineering , ACS Sustainable Chemistry & Engineering , and Energy & Environmental Science . Key themes: Optimization of hybrid fossil/renewable carbon systems Environmental impacts of energy transitions Catalyst design for sustainable chemistry Life cycle assessment of emerging technologies Awarded UPC Top Doctoral Student Award and Top National Student Award , he combines process systems engineering with sustainability metrics to address global challenges in chemical and energy systems.
Dr. Yaron Meron is a Lecturer and researcher in design at the University of Sydney's School of Architecture, Design and Planning. He holds a PhD (RMIT, Melbourne) and two Master's degrees (RMIT, Central St Martins). His work bridges academic research and professional practice, focusing on graphic and communication design, socially engaged design, AI integration, and responsible design thinking. Meron’s research explores interdisciplinary challenges, design collaboration, and the societal impact of emerging technologies like AI. He coordinates the Civic & Social Design Research Group. Educations: PhD in Design (RMIT University, Melbourne) MA in Design (RMIT University, Melbourne) MA in Communication Design (Central Saint Martins, London) Research Interests: Graphic design as an interdisciplinary practice Artificial intelligence in design education and practice Media literacy and defamiliarisation techniques Socially engaged design methodologies Design briefs and stakeholder relationships Articles & Trends: Recent publications emphasize AI's role in design education, speculative urban futures, and critical design approaches to media literacy. His work frequently intersects with pedagogy, ethics, and technology’s societal implications. Labs/Teams: Coordinator of the Civic & Social Design Research Group, fostering collaborative projects on responsible design and interdisciplinary innovation.
Dr. Stan Ahalt serves as the inaugural Dean of the UNC School of Data Science and Society (SDSS) and holds a professorship in the Department of Computer Science at UNC-Chapel Hill. He previously directed the Renaissance Computing Institute (RENCI) and currently acts as its executive advisor. Additionally, he is the associate director of informatics and data science at NC TraCS, the translational research institute at UNC. His academic journey includes a 22-year tenure as professor of electrical and computer engineering at Ohio State University and leadership roles at the Ohio Supercomputer Center. Ahalt’s research focuses on applying data science to societal challenges such as healthcare, climate, and judicial reform. Key initiatives include the National Consortium for Data Science and the iRODS project, which advanced enterprise data management systems. Ahalt has secured over $34.5M in grants to lead high-impact projects like the NHLBI BioData Catalyst (unifying biomedical data), the NCATS Translator (accelerating clinical discovery), and the NIH HEAL Initiative (ensuring FAIR data standards). He mentors students across doctoral and master’s programs, teaching data science fundamentals in courses like COMP 116: Introduction to Scientific Programming. His work emphasizes interdisciplinary collaboration, evidenced by roles in RENCI, NC TraCS, and the SDSS. Ahalt’s contributions span cyberinfrastructure development, educational innovation, and translational research, positioning UNC as a national leader in data science.
Sebastian Raisch is a Full Professor of Strategic Management at the Geneva School of Economics and Management (GSEM), University of Geneva, where he also serves as Director of the Executive MBA program. He is affiliated with the Institute of Management and holds a Ph.D. from the University of Geneva. His academic work is deeply rooted in understanding how organizations balance stability and change, particularly in the face of digital transformation. Research Interests: His primary areas of expertise include strategic management, organizational ambidexterity, organizational paradox, artificial intelligence in organizations, and digital transformation. His research investigates the dynamics of corporate growth and decline, strategic renewal, and the integration of human and artificial intelligence in organizational decision-making. He is especially interested in how firms navigate tensions between competing demands such as exploration and exploitation, automation and augmentation, and stability and innovation. Publications and Trends: His recent publications (2023–2025) show a strong shift toward the role of artificial intelligence in management, with a focus on hybrid human-AI systems, ethical AI, and the strategic implications of AI adoption. Earlier works center on ambidexterity, paradox theory, and corporate turnaround, establishing him as a leading scholar in these domains. Scientific Awards: Strategic Management Society’s Best PhD Paper Award Emerald Publishing Group’s Citation of Excellence Award Journal of Management’s Scholarly Impact Award Editorial and Professional Service: Sebastian Raisch serves as Associate Editor at the Academy of Management Review and sits on the editorial boards of the Academy of Management Journal and the Strategic Management Journal . He has advised numerous doctoral students and supervised research projects on organizational innovation and digital strategy, though specific names are not listed in the provided materials. He has not received explicit mention of research grants, but his extensive publication record suggests active research funding. Labs and Research Teams: While no formal lab is mentioned, Raisch leads or contributes to research initiatives within the Institute of Management at GSEM, particularly in strategic management and digital innovation. He collaborates with scholars across Europe and the U.S., including notable co-authors like J. Schad, S. Krakowski, and M. Tushman.
İBRAHİM ERDEM SEÇİLMİŞ is a Professor of Economics at Hacettepe University's Faculty of Economics and Administrative Sciences. His research focuses on experimental economics, public goods theory, behavioral economics, and tax policy with notable contributions to understanding risk perception, social discount rates, and creative industries in Mediterranean economies. He has authored/co-authored over 40 peer-reviewed publications and edited several academic volumes. Key research areas include: Experimental analysis of public goods provision Behavioral responses to environmental policies Comparative analysis of social discount rates in transition economies Evaluation of tax reforms through behavioral lenses Impact of cultural industries on regional development Notable publications include seminal works on Turkish presidential election policies (2025), risk aversion in public goods (2019), and Mediterranean creative industries (2016). His work frequently bridges theoretical economics with policy applications, particularly focusing on sustainability and social equity. He has presented at international conferences such as the Regional Studies Association European Conference (2014) and contributed to edited volumes on game theory applications and economic philosophy. Current research trends emphasize behavioral tax policy design and the socio-economic consequences of rising inequality.
Prof. Dr. Gülşen Eryiğit is a Professor at Istanbul Technical University within the Faculty of Computer and Informatics , Department of Artificial Intelligence and Data Engineering . She founded and directs the ITU Natural Language Processing Group , Turkey's leading team in Turkish-language NLP, and serves as Senior Action Editor for ACL RR , Director of ITU TÖMER (Turkish Language Teaching Center), and Co-Chair of the EU UniDive Cost Action WG3. Education: PhD in Computer Engineering from ITU (2007), MSc and BSc from ITU and Marmara University Research: Focuses on Natural Language Processing for Turkish, including dependency parsing , coreference resolution , multiword expressions , and language education technology Her recent work involves multilingual transfer learning , LLM applications for Turkish text simplification, and gamification for morphology education. She has received prestigious awards like the Siemens Excellence Award and TÜBİTAK's Above Threshold Award . Her research has produced 65+ publications and 29+ projects funded by EU, TÜBİTAK, and industry partners. Scientific Awards: Siemens Excellence Award (2007) Above Threshold Award (TÜBİTAK, 2015) Certificate of Appreciation (EU 7th Framework, 2012) Thank You Plaque (ITU, 2017) The ITU NLP Group under her leadership has developed Turkey's first licensed NLP software exported internationally. She collaborates with European institutions through COST actions and participates in ACL, CoNLL, and LREC conferences. Her lab focuses on language technology for Turkish , including sign language processing and social media normalization.
Sergio Bermudo Navarrete is a Professor at the Department of Economics, Quantitative Methods and Economic History, Universidad Pablo de Olavide. His research spans combinatorics, graph theory, and operator theory. Education: PhD in Mathematics (2003, University of Seville) with thesis on functional models of operators in Hilbert spaces. Research Interests: Focus on graph theory, domination problems, topological indices, and operator theory. Publication Trends: Recent work includes vertex-degree-based indices for oriented graphs, domination parameters in product graphs, and differential analysis of line graphs. Keywords span Computer Science , Mathematical Chemistry , and Operations Research . Collaborations: Frequent co-authors: José María Sigarreta Almira, José Manuel Rodríguez García, Juan Alberto Rodríguez-Velazquez. Contact: Email sbernav@upo.es .
Anders Søgaard is a Professor at the University of Copenhagen , affiliated with both the Department of Computer Science and the Department of Communication. His research bridges Natural Language Processing and Machine Learning with a focus on AI ethics , explainability , and human-AI interaction . Primary Affiliation: Department of Computer Science, University of Copenhagen Secondary Affiliation: Department of Communication, University of Copenhagen Email: soegaard@di.ku.dk, soegaard@hum.ku.dk Research Interests His work spans Natural Language Processing , Machine Learning , and AI ethics , with recent studies addressing: Trustworthiness in AI systems Explainable AI (XAI) frameworks Multilingual model fairness and alignment Human-AI collaboration in reasoning tasks Ethical implications of social robots Mental health analytics using ML Recent Publications His 2025 output highlights trends in: AI ethics (e.g., fairness metrics, trustworthy systems) Multilingual model analysis (knowledge retention, cross-lingual transfer) Human-centric AI (gaze data, cultural considerations) Applications in healthcare and social good
Ravindra N. Bhatt is currently a Professor of Electrical and Computer Engineering at Princeton University and an associated faculty member in Physics. His academic career spans leadership roles at prestigious institutions, including Director of the Princeton Center for Complex Materials (1999-2005) and Acting Associate Director of the Princeton Center for Theoretical Science (2005-2012). He previously headed Theoretical Physics Research at Bell Laboratories. Ph.D., University of Illinois, Urbana, 1976 M.S., Physics, University of Illinois, Urbana, 1974 B.Sc. Hons., Physics, University of Delhi, India, 1971 Bhatt specializes in theoretical condensed matter physics, focusing on topological materials, quantum Hall effects, and spin-based quantum computation. His work explores disordered systems, many-body localization, and quantum dynamics in low-dimensional structures like graphene and semiconductor heterostructures. His recent publications emphasize topological phases, composite fermions, and critical ground state dynamics, employing methods such as Density Matrix Renormalization Group (DMRG) and Monte Carlo simulations. Key themes include disorder-driven quantum phase transitions and applications in quantum information science. Scientific honors include: Fellow, American Physical Society (1986) Guggenheim Fellowship (1995) Fellow, American Association for the Advancement of Science (2004) Bhatt has led major research centers at Princeton and contributed to quantum science initiatives. His group utilizes computational techniques like Transfer Matrix Methods and Sparse Matrix Diagonalization to study complex materials.
Nihar B. Shah is an Associate Professor at Carnegie Mellon University with joint appointments in the Machine Learning and Computer Science departments within the School of Computer Science. His research focuses on developing theoretically grounded algorithms for evaluating scientific work, with applications in peer review, fairness, and human-AI collaboration. His work has impacted over 100,000 research papers and grant evaluations. Education: Ph.D. in EECS, UC Berkeley M.E. in Telecommunications, Indian Institute of Science B.Tech. in Electronics, NIT Karnataka Research Interests: Shah's group investigates the science of evaluation through machine learning, optimization, and large-scale experiments. Key areas include peer review systems, algorithmic fairness, LLM applications in science, and human-AI collaboration frameworks. Research addresses fundamental questions about research validity, funding allocation, and equitable assessment. Publication Trends: Recent work focuses on improving peer review through randomized controlled trials, security against collusion, LLM-based review systems, and bias mitigation. Publications consistently appear in premier venues (NeurIPS, PLOS ONE, AAAI) with growing emphasis on real-world deployments. Awards & Honors: Young Alumnus Medal (IISc 2024) NSF CAREER Award (2020-2025) Google Research Scholar Award (2021) Multiple best paper awards (HCOMP, ICLR) Research Group & Funding: Leads a focused research team with NSF, Google, and JP Morgan support. Alumni hold positions in academia and industry. Current projects involve large-scale evaluations of scientific work and algorithmic fairness.
Ian Greer is a Research Fellow at Cornell University's School of Industrial and Labour Relations , with a career focused on marketisation , industrial relations , and transnational solidarity . He holds a PhD from Cornell University and has previously studied at Bard College. His work examines labor dynamics in globalised industries , welfare states , and multinational corporations , often through qualitative comparative methods . Education : BSc (Bard College), MSc/PhD (Cornell University) Greer's research spans marketisation of employment services , social movement unionism , and labour policy in crisis situations . His publications include studies on European welfare-to-work schemes , healthcare privatisation , and labour migration . He is associated with the Centre for Employment Relations, Innovation and Change (CERIC) at the University of Leeds. Greer's recent work analyses precarious labor and project-based employment in social services across Slovenia and France. He also contributes to debates on social dumping , work-first welfare states , and activist labor strategies in sectors like healthcare and automotive manufacturing. He has no listed scientific awards. His work often involves collaboration with scholars like Marco Hauptmeier , Charles Umney , and Nathan Lillie , though no formal advisees are named in the provided text. His email is icg2@cornell.edu .
Dr. Hakan Bilen is an Associate Professor (Reader) at the School of Informatics , University of Edinburgh, where he leads the Visual Computing Group (VICO) and is affiliated with the Computer Vision network. He previously worked as a postdoc at the Visual Geometry Group (VGG) of the University of Oxford and earned his PhD from the VISICS group at KU Leuven under the guidance of Luc Van Gool and Tinne Tuytelaars. His academic journey began at Sabanci University (BSc/MSc) with thesis advisor Mustafa Unel, who introduced him to computer vision. His research focuses on computer vision and machine learning , particularly advancing image classification through latent parameter models and weakly supervised object/action detection. He has taught the Machine Learning Practical course since 2018 and actively collaborates within European AI research networks. ELLIS Fellowship: European Laboratory for Learning and Intelligent Systems He bridges foundational research with practical applications, maintaining strong ties to both the Edinburgh and Oxford computer vision communities.
