Prof. Dr. Alexander Stroh-Steckelberg is Professor of Political Science with a focus on African Politics & Development Policy at the University of Bayreuth since 2022. He serves as Deputy Head of the Bayreuth International Graduate School of African Studies (BIGSAS) until 2025 and has held prior roles as Junior Professor and Senior Fellow at BIGSAS (2015–2021). His academic career includes research associate positions at the GIGA German Institute of Global and Area Studies (2006–2015) and teaching roles at the Universities of Abomey-Calavi, Heidelberg, and Lüneburg. Stroh-Steckelberg’s research spans comparative democracy studies , judicial politics , electoral systems , political party dynamics , and development policy in Africa, with regional expertise in Francophone West Africa and Rwanda . His work emphasizes institutional diffusion, informal networks in courts, and the interplay between formal and informal governance structures. Recent publications reveal a focus on judicial appointment policies , electoral manipulation , and local governance challenges across Africa. He contributes to methodological advancements in comparative area studies and network analysis , particularly in non-Western democracies. Stroh-Steckelberg is actively involved in academic communities including the American Political Science Association , German Political Science Association , and Association for African Studies in Germany .
Max Planck Institute for Plant Breeding ResearchGermany
Adam Runions is a researcher in the Department of Computer Science at the University of Calgary, leading the MPG Partner Group in computational analysis of leaf development through collaborative work with Miltos Tsiantis. His group is embedded in the Graphics Cluster, focusing on interdisciplinary problems at the intersection of computer science and developmental biology. University of Calgary - Department of Computer Science MPG Partner Group (2022) Graphics Cluster affiliation His research explores computational modeling and analysis of plant form and development across multiple scales, integrating geometric modeling, physically-based simulation, and computer-aided design. Key themes include plant morphogenesis, self-organization of natural forms, and cross-disciplinary applications in computer graphics and animation. Recent publications emphasize plant development (leaf shape, bark patterning), mathematical modeling (auxin-driven patterning), and geometric techniques (subdivision surfaces, PUPs). Collaborations span institutions like the Max Planck Institute for Plant Breeding Research. Scientific Awards Marie Sklodowska-Curie Fellowship Best Paper Award (International Conference on Cyberworlds 2015) Best Student Paper Award (Computer Graphics International 2011) The group actively recruits BSc, MSc, and PhD students with backgrounds in computer science and mathematics for projects on plant form simulation and digital content creation. Research integrates evolutionary biology, biomechanical modeling, and computational techniques.
Nancy Margaret Reid is a University Professor of Statistical Sciences at the University of Toronto, holding the Canada Research Chair in Statistical Theory and Applications. She has served as Scientific Director of the Canadian Statistical Sciences Institute (2015–2019) and led the Department of Statistical Sciences as Chair (1997–2002). Her research focuses on theoretical statistics, particularly likelihood inference and foundational aspects of statistical methodology. Reid earned her PhD from Stanford University (1979) under Rupert G. Miller, with Brad Efron and Vernon Johns on her committee. Reid's accolades include Fellowships from the Royal Society, Royal Society of Canada, and National Academy of Sciences, as well as the Guy Medal in Gold (2022) and David R. Cox Award (2023). She has authored influential books like *Theory of the Design of Experiments* and contributed to courses on mathematical statistics and likelihood inference. Active in academic service, she teaches graduate-level courses and has advised numerous students and postdocs in theoretical and applied statistical research.
Roger Boltshauser is a Full Professor and Deputy Head at the Department of Architecture, ETH Zurich. His practice and academic work emphasize tectonic building culture, proportion, and material experimentation, diverging from mainstream German-Swiss architectural trends. He combines teaching with active architectural practice, influencing younger generations at ETH and TU Wien. Key themes: Tectonic structures, grid-based order, social responsibility in architecture, critique of modernist canons Notable projects: Hochhaus H1 Zwhatt-Areal (2025), Masterplan Zoo Basel (2025), Centre for Dental Medicine Zurich (2025) His buildings prioritize mass and permanence , evident in projects like the Kopfholz School and Rauch House . Recent works at the EPFL Solar Biennale (2025) and Architecture of Memory exhibition (2025) explore sustainable design and cultural narratives. Boltshauser’s studio on Dubsstrasse exemplifies research into load-bearing structures and urban spatial relationships.
Swiss Federal Institute of Technology in LausanneSwitzerland
Ali H. Sayed is the Dean of the School of Engineering (Faculté des sciences et techniques de l'ingénieur - STI) at École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, where he also directs the Adaptive Systems Laboratory (Laboratoire de systèmes adaptatifs). Previously, he served as an emeritus professor and chair of the Electrical Engineering Department at UCLA. He is a highly cited researcher and a member of the US National Academy of Engineering and the World Academy of Sciences. Sayed served as president of the IEEE Signal Processing Society in 2018 and 2019. Professor Sayed's research focuses on adaptation and learning theories, data and network sciences, statistical inference, multi-agent systems, adaptive networks, and optimization. His work bridges theoretical foundations with practical applications in signal processing, machine learning, and network science. He has made significant contributions to distributed learning algorithms, social learning over networks, and adaptive signal processing techniques that have influenced both academic research and practical implementations. His recent publications demonstrate a strong focus on multi-agent systems, distributed learning, privacy-preserving techniques, and social learning over networks. The research trends show increasing emphasis on federated learning with privacy guarantees, graph-based learning approaches, and the intersection of social dynamics with information processing. His work consistently addresses fundamental theoretical questions while maintaining relevance to practical applications in communication networks, social media analysis, and distributed artificial intelligence systems. Professor Sayed has received numerous prestigious awards throughout his career, including: IEEE Fourier Award (2022) Norbert Wiener Society Award (2020) IEEE Signal Processing Society Education Award (2015) Papoulis Award from the European Association for Signal Processing (2014) Technical Achievement Award from IEEE Signal Processing Society (2012) Terman Award from the American Society for Engineering Education (2005) IEEE Donald G. Fink Prize (1996) Multiple Best Paper Awards from IEEE and EURASIP Sayed has authored or co-authored over 570 publications and six monographs. He has mentored numerous PhD students and researchers in the fields of signal processing and adaptive systems. His editorial leadership includes serving as Editor-in-Chief of IEEE Transactions on Signal Processing (2003-2005) and EURASIP Journal on Advances in Signal Processing (2006-2007), as well as Founding Editor-in-Chief of the Open Access Book Series on Information and Learning Sciences. At EPFL, Professor Sayed leads the Adaptive Systems Laboratory, which focuses on developing theoretical frameworks and practical algorithms for adaptive systems, networked learning, and distributed signal processing. The lab's research encompasses both fundamental theoretical investigations and applications to real-world problems in communications, social networks, and computational biology.
Emma Pierson is an Assistant Professor of Computer Science at the University of California, Berkeley, affiliated with the Berkeley Artificial Intelligence Research Lab (BAIR) , Computational Precision Health , and the Center for Human-Compatible AI . She focuses on developing data science and machine learning methods to address issues in healthcare equity and social inequality . Her work includes studies on race adjustments in clinical algorithms, migration patterns, and leveraging LLMs for health equity. Education: Ph.D. in Computer Science from Stanford University (2020), Master’s in Statistics from the University of Oxford. Prior roles include Assistant Professor at Cornell Tech, Senior Researcher at Microsoft Research, and data scientist at 23andMe and Coursera. Research Interests: Her research spans fair clinical prediction , sparse autoencoders , health disparities , and algorithmic fairness . Notable projects include the MIGRATE dataset for granular migration analysis and studies on policing disparities. Awards: NSF CAREER Award, Rhodes Scholarship, Hertz Fellowship, MIT Technology Review 35 Innovators Under 35, and Samsung AI Researcher of the Year. She writes a statistics blog ( Obsession with Regression ) and contributes to media outlets like The New York Times and FiveThirtyEight . Labs/Teams: Leads the MIGRATE project, a collaboration to analyze fine-grained migration data. Engages in interdisciplinary work across AI, healthcare, and social science.
Richard J. Cook is a University Professor and Mathematics Faculty Research Chair in the Department of Statistics and Actuarial Science at the University of Waterloo. He holds cross-appointments at the School of Public Health and Health Systems at the University of Waterloo and the Faculty of Health Sciences at McMaster University. Previously, he held a Tier I Canada Research Chair in Statistical Methods for Health Research from 2005 to 2019. His educational background includes: BSc in Statistics from McMaster University MMath in Mathematics from University of Waterloo PhD in Statistics from University of Waterloo Professor Cook's research focuses on developing and applying statistical methods for public health research. His primary areas of interest include the analysis of life history data, longitudinal data analysis, methods for incomplete data, clinical trial design, and multivariate analysis. His work provides critical methodological frameworks for understanding disease progression and evaluating interventions in complex health settings. He has made significant contributions to the development of multistate models for disease processes and methods for handling interval-censored data. His extensive publication record demonstrates consistent focus on methodological innovations addressing real-world health research challenges. Recent work emphasizes estimand specification in clinical trials, transportability of research findings, and causal inference methods. His research bridges theoretical statistics with practical applications in autoimmune diseases, transfusion medicine, and public health. Professor Cook has received significant professional recognition: Tier I Canada Research Chair in Statistical Methods for Health Research (2005-2019) Mathematics Faculty Research Chair at University of Waterloo His students have earned prestigious awards including multiple Pierre-Robillard Awards, ISCB Student Conference Awards, and ENAR Distinguished Student Paper Awards, with notable achievements like Dr. Shu (Joy) Jiang being named in the Forbes Top 30 Under 30 North America (2023) for Healthcare. Professor Cook has advised numerous graduate students throughout his career, with many going on to successful academic and industry positions. His research has been supported by various grants, and he collaborates extensively with researchers in rheumatology, transfusion medicine, and public health through affiliations with the Centre for Prognosis Studies in Rheumatic Diseases, the International Psoriasis and Arthritis Research Team, and the McMaster Centre for Transfusion Research. He leads a vibrant research team that includes research associates, post-doctoral fellows, and graduate students working on cutting-edge statistical methodology. His research group maintains strong connections with multiple institutions and research centers focused on health outcomes and disease progression.
Micah Hale is a Professor and Department Head of Civil Engineering at the University of Arkansas, Fayetteville, and holds the Twenty First Century Endowed Leadership Chair in Civil Engineering. His work focuses on concrete materials, structural performance, and sustainable construction practices. Education: Ph.D., M.S., and B.S. in Civil Engineering from the University of Oklahoma. Dr. Hale’s research explores High-Performance Concrete , Bond Behavior of Prestressing Strands , and Mitigation of Alkali-Silica Reaction (ASR) . He also investigates Thermal Energy Storage applications for solar power systems and sustainable ultra-high-performance concrete (UHPC) development. His publications highlight advancements in concrete durability, prestressed girder analysis, and environmentally conscious material design. Recent studies emphasize calcium oxychloride formation , prestress transfer modeling , and self-consolidating concrete optimization. His scholarly output spans structural mechanics, chemical durability, and material sustainability. Awards: Twenty First Century Endowed Leadership Chair in Civil Engineering As an educator, Dr. Hale teaches Reinforced Concrete Design , Prestressed Concrete Design , and Concrete Materials and Mixture Proportioning . His contributions to engineering ethics education and student engagement further underscore his academic leadership.
John Ford is an Associate Professor in the Department of Nuclear Engineering at Texas A&M University. His research focuses on radiobiology, radiation carcinogenesis, and medical applications of radiation. He holds academic appointments within the College of Engineering and contributes to the Health Physics, Radiation Biology & Medical Physics research group. Education includes a B.S. and M.S. in Nuclear Engineering from Mississippi State University (1982, 1986), a Ph.D. in Biomedical Sciences from the University of Tennessee (1992), and postdoctoral training at Oak Ridge National Laboratory (1992–1993). His work emphasizes understanding radiation effects on biological systems, with notable contributions to radiation dosimetry, bystander signaling mechanisms, and dietary modulation of radiation damage. Recent studies explore space radiation monitoring technologies and therapeutic applications of radiation. Awards include the BP Award for Teaching Excellence (2007) and ARRO Educator of the Year (2013–2014). Research spans interdisciplinary areas such as radiation-induced cancer mechanisms, nutritional interventions to mitigate radiation effects, and advanced radiation detection instrumentation. He has advised numerous projects in radiation safety curriculum development and collaborated on NASA-funded studies modeling radiation impacts on astronauts.
Juan Camilo Gómez is an Associate Professor with tenure at the University of Washington Bothell's School of Business, specializing in game theory, bargaining, and microeconomic theory. He earned his Ph.D. in Economics from the University of Minnesota and his B.Sc. in Mathematics from Universidad de los Andes in Colombia. Education: Ph.D. Economics (1998–2003), University of Minnesota, Minneapolis, MN B.Sc. Mathematics (1990–1996), Universidad de los Andes, Bogotá, Colombia Research Interests: His research focuses on foundational and applied aspects of game theory, including bargaining models, coalition formation, cooperative solution concepts, and general equilibrium. He explores how efficiency can be achieved in strategic interactions, especially when agents may behave manipulatively or when traditional balance conditions do not hold. His work contributes to understanding how coalitions form and how outcomes can be predicted or designed to ensure equitable and efficient allocations. He also investigates the implications of reference points in bargaining and the role of aspirations in shaping cooperative behavior. Publications Overview: Across his publications, a clear trajectory emerges from foundational theoretical work—such as axiomatizing core extensions in cooperative games—to applied models that predict coalition formation and bargaining outcomes. His research consistently bridges rigorous mathematical frameworks with practical economic questions, including market interpretations of cooperative solutions and strategic pricing models like 'Pay What You Want'. Awards and Honors: 2010 MBA Professor of the Year, University of Washington Bothell Teaching and Advising: Gómez has taught a wide range of courses from undergraduate calculus and mathematical economics to graduate-level game theory and quantitative methods for business. He has held teaching roles at institutions including Macalester College, University of Copenhagen, Universidad de los Andes, and University of Minnesota. He has also co-directed undergraduate theses, such as that of Santiago Saavedra, and served on numerous academic committees including MBA Admissions and faculty hiring. Labs and Teams: While no specific lab is mentioned, his collaborative working papers with researchers like Camelia Bejan and P.V. Balakrishnan suggest active participation in research networks focused on game theory and economic modeling.
Debdeep Pati is a Professor in the Department of Statistics at the University of Wisconsin-Madison, affiliated with the School of Computer, Data & Information Sciences. His research focuses on Bayesian methods, high-dimensional data analysis, machine learning, and computational statistics, with applications in health data and network analysis. He has contributed to approximate Bayesian computation, graphical models, and fair algorithms. Key research interests include Bayes theory in high dimensions, hierarchical modeling, efficient Bayesian computation, and real-time tracking algorithms. His work bridges theoretical advancements with practical applications in areas like electronic health records and nuclear physics constraints. Recent work emphasizes Wasserstein-guided nonparametric Bayes, fair clustering algorithms, and variational inference in singular models. He has developed software for covariate-dependent Gaussian graphical modeling, published in ACM Transactions on Mathematical Software . Grants: NSF proposal on Wasserstein-guided nonparametric Bayes, NIH R01/R21 grants on periodontal disease and diabetes comorbidity. Advising: No named advisees listed but actively supervising research in Bayesian computation and high-dimensional statistics. Awards: 2024 JASA reproducibility award for 'Covariate-Assisted Bayesian Graph Learning.' He is an Associate Editor for Journal of Computational and Graphical Statistics and has organized workshops at Banff International Research Station (BIRS) and the Institute for Mathematics and its Applications (IMSI).
Lars Nordström is a Professor at the Division of Electric Power and Energy Systems within KTH Royal Institute of Technology, Stockholm, Sweden. His work bridges control systems , communication networks , and power systems , with a focus on future architectures, functionality, and quality aspects of ICT for power grid operations. He has led initiatives such as the Swedish Centre of Electric Power Engineering and served as Thematic Leader for Smartgrids in KIC InnoEnergy. In 2014, he was a Visiting Professor at Washington State University. Education : Ph.D., MSc.EE Nordström's research explores the intersection of smart grids , machine learning , and cybersecurity for power systems. Key areas include: Wide-Area Monitoring and Control (WAMC) systems Decentralized control strategies for DC microgrids Impedance modeling using neural networks Data-driven methods for islanding detection ICT reliability and protocol design for grid operations His recent publications emphasize machine learning applications in power systems, including LSTM networks for EV charging management, graph attention networks for stability monitoring, and digital twin approaches for cyber-attack mitigation. These works span disciplines such as Smart Grids, Power Electronics, and Data Science. Scientific Recognitions : Senior Member, IEEE Senior Member, CIRED Senior Member, Cigre Past Chairman, Swedish IEC TC57 Mirror Committee Nordström actively teaches and examines graduate courses like Communication and Control in Electric Power Systems and Computer Applications and Machine Learning in Electric Power Systems . His work influences industry practices through collaborations on digital substations, energy market analysis, and resilience strategies.
Natalie Enright Jerger is a Professor in the Department of Electrical and Computer Engineering at the University of Toronto's Faculty of Applied Science and Engineering. She holds the Canada Research Chair in Computer Architecture and serves as Director of the Division of Engineering Science (2023-2028). Previously, she was the Percy Edward Hart Professor (2016-2019). She received her B.S. in Computer Engineering from Purdue University (2002), and M.S./Ph.D. in Electrical Engineering from University of Wisconsin-Madison (2004/2008). Her research focuses on: Multi/many-core architectures and on-chip networks Cache coherence protocols and memory hierarchy optimization Approximate computing and sustainable systems Intermittent computing for energy-harvesting devices Hardware acceleration for machine learning Her publications demonstrate strong emphasis on networks-on-chip (NoC) innovations, including routing algorithms, deadlock handling, power-efficient designs, and topology optimizations. Recent work expands into approximate computing, mobile architectures, and ML-driven hardware design. Major Awards: Fellow of Engineering Institute of Canada (2023) McLean Senior Fellow (2019) IEEE Micro Top Picks (2016) ACM/IEEE Microarchitecture Hall of Fame (2015) Sloan Research Fellowship (2015) Canada Research Chair (current) Distinguished Scientist, ACM Fellow, IEEE She leads the NEJ research group and collaborates with industry partners including Intel, AMD, Qualcomm, and IBM. Her work is funded by NSERC, CFI, and industrial grants. She co-chaired ASPLOS 2023 and HPCA 2014, and actively promotes diversity through WICARCH and ACM initiatives.
Robert Likamwa is an Associate Professor at Arizona State University, affiliated with the School of Arts, Media and Engineering and the School of Electrical, Computer and Energy Engineering. His research focuses on the intersection of mobile computing, augmented reality, and sensor design through Meteor Studio. Ph.D., Rice University M.S., Rice University B.S., Rice University His work spans three core research arcs: (i) advanced visual capture systems, (ii) hybrid virtual-physical immersion through sensory augmentation, and (iii) data-driven frameworks for AR/VR storytelling. He explores mobile operating systems, low-power architectures, computational imaging, and holographic computing. Recent publications analyze multi-resolution visual sensing, geospatial cross-virtuality collaboration, planetary data visualization, spatial audio optimization, and multi-sensory virtual environments. His 2013 paper on energy-proportional image sensors received the Best Paper Award at ACM MobiSys. Best Paper Award, ACM MobiSys 2013 LiKamWa advises graduate students through research and thesis courses and leads grants related to mobile vision systems, haptic interfaces, and energy-efficient sensor design. He directs Meteor Studio, a research group focused on immersive technology innovation.
Professor Raghavendra Rau is the Sir Evelyn de Rothschild Professor of Finance at Cambridge Judge Business School, University of Cambridge. He is the Founder and Academic Director of the Cambridge Centre for Alternative Finance (CCAF) and serves on editorial boards of journals like the Journal of Corporate Finance and Journal of Banking and Finance. He will be President of the Financial Management Association in 2025 and has held visiting roles at Gresham College, Universiti Malaya, and University of Jordan. Education: MBA (IIM Bangalore), MSc, PhD (INSEAD) Previous Roles: Principal at Barclays Global Investors, Ambank Chair, Gresham Professorship His research focuses on how investors and firms process information, with key areas including corporate governance, behavioral finance, fintech, digital finance, CEO decision-making, and ESG. He explores links between prenatal environmental exposure and executive risk-taking, gender diversity in finance, and regulatory impacts on crowdfunding and digital lending. Recent publications analyze serial acquirers' behavior, CSR impacts on firm value, superstitious fund managers, and digital financing regulations. His work bridges behavioral biases, environmental factors, and financial innovation. Awards include the 2015 Ig Nobel Prize in Management.
