Daniel Cooney is an Assistant Professor in the Department of Mathematics at the University of Illinois Urbana-Champaign. He holds additional affiliations as an Affiliate at the Carl R. Woese Institute for Genomic Biology. His research focuses on applying partial differential equations (PDEs), dynamical systems, and stochastic processes to study evolutionary dynamics, particularly in biological and social systems. Key themes include multilevel selection, evolutionary game theory, and the emergence of cooperative behavior. Cooney earned his PhD in Applied and Computational Mathematics from Princeton University, advised by Simon Levin, and completed a postdoc as a Simons Fellow in Mathematical Biology at the University of Pennsylvania. His work bridges theoretical mathematics with applications in ecology, epidemiology, and social sciences. Recent publications explore topics like altruistic punishment in cultural systems, classroom-turnover dynamics, and protocell evolution. He actively participates in academic outreach, co-organizing conferences such as the AMS Special Session on Mathematics of Infectious Disease and the SIAM Minisymposium on Social-Ecological Systems. His research has been published in high-impact journals including *Proceedings of the National Academy of Sciences* and *Bulletin of Mathematical Biology*.
Lourens Waldorp is an Associate Professor at the University of Amsterdam within the Faculty of Social and Behavioural Sciences , specifically the Department of Psychological Methods . His research focuses on network theory, causal inference, and statistical modeling in psychology and neuroscience. University of Amsterdam IAS Fellow (2024) His research interests include: Network psychometrics Causal inference in psychological models High-dimensional statistical methods Dynamical systems in psychopathology Graph theory applications Signal processing for biophysical data The trends in his recent publications center on causal modeling, network analysis of psychopathology, and statistical techniques for time-series data. He has developed methods for perturbation graphs, moderated network models, and dynamic intervention frameworks. Notable scientific awards : IAS Fellowship for 6 months (2024) He advises PhD students like Kyra Evers and collaborates with researchers across disciplines, including J. Haslbeck , D. Borsboom , and O. Ryan . His work intersects with network theory and clinical psychology .
Dr. Katerina Marcoulides is an Associate Professor in the Quantitative and Psychometric Methods Program at the University of Minnesota's Department of Psychology. She is affiliated with the Minnesota Population Center and serves as Co-Chair of the Structural Equation Modeling Special Interest Group (SEM SIG) for the American Educational Research Association. Her research focuses on advanced data mining and modeling techniques for complex longitudinal data, particularly applied to developmental processes in economically disadvantaged immigrant children. She holds a PhD in Quantitative Psychology from Arizona State University, an MA from UC Davis, and a BA from UC Santa Barbara. Education: PhD: Quantitative Psychology, Arizona State University MA: Quantitative Psychology, University of California, Davis BA: Psychology (minor in Education), University of California, Santa Barbara Research Interests: Dr. Marcoulides develops and applies statistical methods such as structural equation modeling (SEM), Bayesian synthesis, and data fusion to study developmental and educational processes. Her work emphasizes longitudinal data analysis, item response theory, and multilevel modeling. Recent projects include NIH-funded research on parenting, marginalization, and well-being during the pandemic. Awards: APS Rising Star Award (2021) NIH Grant Award Teaching & Collaboration: She teaches courses on SEM, multilevel modeling, and data analysis at the University of Minnesota. Previously at the University of Florida, she contributed to workshops on educational data mining and served as an APA Advanced Training Institute presenter. Her interdisciplinary collaborations span population studies, health inequities, and workforce research. Labs & Groups: She leads the Data Analytics and Visualization Lab and actively participates in the Minnesota Population Center, integrating computational and statistical innovations with real-world applications.
Prof. Dr. Christian Homburg holds the Chair of Business-to-Business Marketing, Sales & Pricing at the University of Mannheim's Faculty of Business Administration. Since 2007, he has been a Professorial Fellow at the University of Melbourne. His research spans marketing strategy, sales management, pricing, and customer relationship management, with a focus on business-to-business contexts. He collaborates with global firms such as Accenture, BOSCH, SAP, and BASF. Research Interests: Prof. Homburg explores topics like sales force automation, key account management, IoT in marketing, and augmented reality in sales. His work bridges academic theory and practical implementation, emphasizing organizational systems driving customer and competitor responsiveness. Scientific Awards: Hermann Billing Prize (1989) Multiple Best Paper Awards from the American Marketing Association (1997-2010) Louis W. Stern Award (2009) Best Paper Awards from Journal of the Academy of Marketing Science and Journal of Business to Business Marketing Publications: Author of 7+ editions of Marketing Management , co-editor of the Handbook of Customer Loyalty Management , and contributor to leading journals like Journal of Marketing and Strategic Management Journal .
Robert Pilawa-Podgurski is a Professor in the Electrical Engineering and Computer Sciences Department at UC Berkeley and founding director of the Berkeley Power and Energy Center (BPEC). He earned BS, MEng, and PhD degrees from MIT. His research focuses on power electronics, including renewable energy systems, electric vehicles, and high-efficiency power converters. He has received prestigious awards such as the IEEE Fellow (2024), Bakar Fellows Spark Award (2024), and the IEEE Richard M. Bass Outstanding Young Power Electronics Engineer Award (2014). His work emphasizes experimental validation through hardware prototypes. Education: BS in Physics and EECS (MIT, 2005), MEng (MIT, 2007), PhD in EECS (MIT, 2012). Research interests include power electronics for renewable energy, electric vehicles, energy harvesting, and advanced converter topologies. His lab has developed high-power density converters and innovative control techniques for flying capacitor multilevel converters. Recent publications focus on hybrid switched-capacitor architectures, voltage balancing, and ultra-high-current applications. Awards include over 17 IEEE prize papers and teaching accolades like the 2023 UC Berkeley EECS Outstanding Teaching Award. His group has advised numerous students, including postdocs and PhD candidates working on cutting-edge power electronics projects. Labs/Teams: Pilawa Research Group at UC Berkeley, collaborating on power electronics for clean energy and high-performance computing.
Susan J. Simkins is a Professor of Psychology at The Pennsylvania State University, where she serves as Lead of the CTSI-Team Science Core and is based in Moore Building at University Park. Her contact details include email sxm40@psu.edu and phone (814) 863-7387. Education Ph.D., Ohio State University, 1996 Research Interests Dr. Simkins' research centers on effective teamwork and performance through three interconnected streams: team composition/diversity (examining demographic, cognitive, and personality-based diversity within contingency frameworks), team cognition/mental models (focusing on shared understanding of tasks and teamwork dynamics), and temporal integration in teams (investigating time-based diversity, temporal leadership, and pacing styles). Her work emphasizes individual differences, cognitive processes, and temporal dynamics as critical determinants of team effectiveness in organizational contexts. Publication Trends Her 2013-2017 publications reveal a strong focus on temporal dimensions of teamwork, including polychronicity diversity, temporal conflict in specialized teams (e.g., culinary environments), and time-sensitive mental models. Key methodological approaches involve multilevel analysis and contingency frameworks, with applications spanning leadership theory, decision-making diversity, and climate interactions. Work appears consistently in top organizational psychology journals like Journal of Applied Psychology and Organizational Behavior and Human Decision Processes. Scientific Awards No scientific awards were documented in the provided text. Advising and Grants While the text confirms her faculty role and research leadership, specific details about graduate student advising, grant funding, or sponsored projects were not included in the source material. Labs and Teams Dr. Simkins leads the CTSI-Team Science Core, an initiative dedicated to advancing methodologies for studying team-based research structures and improving collaborative effectiveness in scientific and organizational settings.
Yiping Lu is an Assistant Professor in the Department of Industrial Engineering and Management Sciences at Northwestern University's McCormick School of Engineering. His research focuses on developing interdisciplinary approaches combining domain knowledge (differential equations, stochastic processes), machine learning, and experiments. Key interests include scientific machine learning (AI4Science), stochastic simulation, and robust machine learning. Education: Ph.D. in Applied and Computational Mathematics, Stanford University (2023) B.S. in Computational Mathematics, Peking University (2019) Research Highlights: Hybrid research integrating ML with scientific domains like PDEs and inverse problems Development of Physics-Informed Learning frameworks Contributions to deep learning theory (ResNets, neural collapse) Advances in kernel operator learning and adversarial robustness Awards: CPAL Rising Star Award (2024) University of Chicago Data Science Rising Star (2022) Stanford Interdisciplinary Graduate Fellowship (2021) Labs/Teams: SCALE Lab (Scientific Computation and Learning at Northwestern) Collaborations with NYU's Courant Institute and Stanford
Eli Ben-Michael is an Assistant Professor jointly appointed in the Heinz College of Information Systems and Public Policy and the Department of Statistics & Data Science at Carnegie Mellon University. He is affiliated with the CMU-NIST AI Measurement Science & Engineering Cooperative Research Center (AIMSEC), contributing to cutting-edge research at the intersection of statistics, policy analysis, and artificial intelligence. His educational background includes a PhD in Statistics from U.C. Berkeley and undergraduate studies at Columbia University where he earned a dual degree in Computer Science and Statistics. Prior to his current position, he completed a postdoctoral fellowship at Harvard University's Institute for Quantitative Social Science and Department of Statistics. Ben-Michael's research focuses on developing innovative statistical and computational methods for causal inference and policy evaluation, with particular emphasis on integrating machine learning techniques to address complex problems in public policy and social science. His work bridges theoretical statistics with practical applications in healthcare, criminal justice, education, and social policy. Current research directions include safe policy learning, sensitivity analysis for clustered data, and methodological innovations for the synthetic control method. His publication record shows a strong trajectory in top-tier journals including Journal of the American Statistical Association, Journal of the Royal Statistical Society, and Proceedings of ICML. Recent work demonstrates increasing focus on policy-relevant applications including abortion legislation impacts, pre-trial risk assessment, and healthcare disparities, while maintaining methodological rigor in causal inference frameworks. Ben-Michael has developed open-source software tools including augsynth and multical R packages, which implement his methodological contributions for synthetic controls and multilevel calibration weighting. These packages have been adopted by researchers in multiple disciplines for causal inference applications.
Frede Blaabjerg is a Professor at Aalborg University (AAU Energy) , affiliated with the Faculty of Engineering and Science . Since 1998, he has pioneered power electronics research in applications such as wind turbines , photovoltaic (PV) systems , reliability engineering , and Power-2-X technologies. Education : PhD in Electrical Engineering (1995, Aalborg University) Honorary Degrees : Honoris Causa at University Politehnica Timisoara (2017) and Tallinn Technical University (2018) His research focuses on power electronics control , system optimization , and reliability for renewable energy and electric mobility . Recent work includes grid-forming converters , virtual synchronous generators , and smart EV charging systems. Key publication trends span 15+ years , with over 3,733 peer-reviewed articles and 900+ journal papers in power electronics , renewables , and energy storage . Notable book series: Control of Power Electronic Converters and Systems (4 volumes, Elsevier). Scientific Awards : 46 IEEE Prize Paper Awards 2020 IEEE Edison Medal 2019 Global Energy Prize 2014 IEEE William E. Newell Power Electronics Award Leadership Roles : Editor-in-Chief, IEEE Transactions on Power Electronics (2006–2012) Chairman, Danish Council for Research and Innovation Policy (2020–) President, IEEE Power Electronics Society (2019–2020)
Professor Roberta Fida is the Head of the Leadership and Management Department at Aston Business School, part of Aston University in the UK. She holds a Professorship in Organisational Behaviour and Organisational Psychology, with prior roles including Professor of Work Psychology at the University of East Anglia and Chair of the Ethics Committee there. A Chartered Occupational Psychologist with the British Psychological Society, her research focuses on unethical workplace behaviors, moral disengagement, and workplace stress, particularly in healthcare contexts. She specializes in advanced data analytics like structural equation modeling and has led major grants including EDI initiatives and studies on workplace aggression policy mapping. Her work bridges academic research with practical applications to foster ethical and inclusive organizational cultures. Education: Laurea (5-year degree in Work and Organizational Psychology) from Sapienza University of Rome (2002) MA in Organizational Training (2004–2005) PhD in Psychology from Sapienza University (2006) Postgraduate Certificate in Higher Education Practice (UEA, 2017) Italian National Qualifications as Full Professor (2017) and Associate Professor (2013) Research Interests: Her core areas include moral disengagement, counterproductive workplace behaviors, stress resilience, healthcare leadership, and EDI. She has published over 60 articles and is listed in Stanford's Top 2% Scientists globally. Awards & Grants: NIHR Work & Health Development Award (2023–2024) for EDI Smart-Dash (£95,855) INAIL grants totaling over €1.1 million for psychosocial risk studies and work-related stress analyses ESRC funding for workplace wellbeing research (£659,540) Research Council of Canada grant for nurse leadership studies ($202,852) Teaching & Supervision: She has taught across undergraduate to postgraduate levels, including modules on organizational psychology, multivariate analysis, and conflict management. She supervises PhD students and has led course design for programs focusing on organizational wellbeing and research methods.
Ning Nan is an Associate Professor at the University of British Columbia's Sauder School of Business, specifically within the Department of Accounting and Information Systems. With a BA from Peking University, an MA from the University of Minnesota, and a PhD from the University of Michigan, Dr. Nan focuses on digital business strategy, evolvable IT infrastructure, and complex adaptive systems. His research explores blockchain applications, agent-based modeling, and the intersection of AI with societal challenges like sustainability. Education: PhD in Information Systems, University of Michigan MA in Information Systems, University of Minnesota BA in Computer Science, Peking University Research Interests: Dr. Nan investigates how technology shapes organizational and societal systems, with a focus on AI ethics, sustainability through personalized recommendations, and blockchain's role in decentralized supply chains. He employs agent-based modeling to simulate complex phenomena like innovation diffusion and online community dynamics. Recent work addresses explainable AI in smart cities and carbon-reduction gamification strategies. Teaching: In 2024-2025, he teaches Data Management for Business Analytics , emphasizing practical applications of data-driven decision-making. Key Research Themes: His articles highlight trends in AI sustainability (e.g., carbon footprint impacts of recommendation systems), digital business strategy (blockchain governance, app update strategies), and foundational IS theory (hyperturbulence and IS strategy).
Justin Jansen is a Professor of Corporate Entrepreneurship at Rotterdam School of Management (RSM) within Erasmus University Rotterdam. Affiliated since 2001, his academic career spans over two decades. He holds a PhD in Management (2005) from Erasmus University. His research focuses on organizational growth, strategic renewal, and leadership dynamics in fast-growing firms. He co-founded the Erasmus Centre for Entrepreneurship (ECE) and pioneered the European ScaleUp Institute, fostering scale-up ecosystems across Europe. His work bridges academia and practice, addressing how organizations navigate paradoxes between exploration and exploitation. He has advised companies and governments on innovation strategies and entrepreneurial ecosystems. Editorships include Journal of Management Studies , and he’s an editorial board member of leading journals like Academy of Management Journal . Notable awards include the ERIM Best Paper Award and being named one of the world’s top entrepreneurship scholars. Research highlights include frameworks for scale-up DNA, leadership roles in ambidextrous organizations, and the role of social networks in corporate-startup collaborations. He co-developed BuildtoGrow, a venture applying research-based game-based learning tools for scaling organizations. Key collaborations include work with the European ScaleUp Institute and advisory roles for governmental agencies on entrepreneurial climate improvement. His 50+ publications span topics like absorptive capacity, strategic agility, and middle management roles in strategy implementation.
Dr. Zara Ersozlu is a Senior Lecturer in Mathematics Education within the School of Education at the University of Newcastle, Australia. With a distinguished international career spanning multiple continents, she has held academic positions at prestigious institutions including North Carolina State University (USA), Gazi and Gaziosmanpasa Universities (Turkey), National Taiwan Normal University (Taiwan), The University of Western Australia, Murdoch University, and Deakin University. Her academic journey includes tenured positions as an Associate Professor and leadership roles as Department Head and Chair in teacher education disciplines. Currently, she teaches undergraduate and postgraduate courses in mathematics education, including Effective Pedagogies in Primary Mathematics, K-6 Mathematics, K-6 Numeracy, and Digitally Supported Learning. Dr. Ersozlu earned her Doctor of Philosophy from Firat University in Turkey and her Master of Art from Sakarya University. Her extensive academic preparation is complemented by five years of practical teaching experience in public schools prior to entering academia. This blend of theoretical knowledge and practical classroom experience informs her approach to teacher education and educational research. At the broadest level, Dr. Ersozlu's research investigates solutions to real-life problems impacting people's well-being, success, and capacity to achieve. Her scholarly work spans primary and secondary mathematics education, the psychology of mathematics (including metacognition, self-regulation, and anxiety), cross-cultural educational studies, teacher education, virtual simulated learning environments, and educational assessment. She has increasingly focused on the transformative potential of AI and machine learning in education, exploring how these technologies alter teaching, learning, and research processes. Her methodological expertise encompasses both quantitative and qualitative approaches, allowing her to effectively analyze both small and large educational datasets. Analysis of Dr. Ersozlu's recent publications reveals a strong emphasis on mathematics anxiety, teacher education, and the integration of technology in learning environments. Her work demonstrates a consistent focus on practical applications of educational research to address real-world challenges in mathematics education. The interdisciplinary nature of her research connects educational psychology, technology integration, and cross-cultural perspectives, with particular attention to how these elements intersect in teacher preparation and student learning outcomes. 2023 ATEA Research Recognition Award from the Australian Teacher Education Association 2021 Fellow of the Higher Education Academy (Advance HE, UK) 2010 Fellowship Program for Postdoctoral Researchers from the Council of Higher Education of Turkey Dr. Ersozlu is deeply committed to mentoring the next generation of scholars, currently supervising four PhD students and having successfully guided ten students to completion. Her grant portfolio includes significant funding for projects such as Best Practice Guidelines for RPL in Initial Teacher Education Programs ($60,000), Exploring the Reciprocal Relationship Between Mathematics Anxiety and Mathematical Resilience ($2,599), and multiple conference travel awards. She serves as an Associate Editor for several prominent journals including the International Electronic Journal of Mathematics Education and as Editor for Interdisciplinary STEM Education. Her editorial work reflects her standing as a respected voice in mathematics education research. Dr. Ersozlu's academic leadership extends to her role in developing innovative teaching approaches that integrate virtual simulation technology and learning analytics. Her work with TeachLivE™, a mixed-reality classroom simulation platform, demonstrates her commitment to creating authentic learning experiences for teacher education students. Through these initiatives, she bridges the gap between educational theory and classroom practice, preparing future educators to effectively implement evidence-based teaching strategies in diverse learning environments.
Dr. Daniel J. Bauer is a Professor and Director of the Quantitative Psychology Program and L.L. Thurstone Psychometric Laboratory at the University of North Carolina at Chapel Hill. His research focuses on advancing quantitative modeling techniques for studying negative social behaviors, health outcomes, and psychopathology, with expertise in generalized and nonlinear latent variable models, including multilevel models, structural equation models, and mixture models. His work emphasizes methodological innovations such as Bayesian regularization, measurement invariance evaluation, and the integration of deep learning with psychometrics. Bauer advises doctoral students in quantitative psychology and collaborates with developmental psychology programs. He leads the Thurstone Laboratory, one of the oldest quantitative psychology training programs in the U.S., emphasizing rigorous methodological training and applications in behavioral sciences. Bauer’s research trends span computational advancements in latent variable analysis, regularization for bias detection, and dynamic modeling of developmental processes. His advising includes over a dozen doctoral students now in academia and industry roles. He contributes to labs and initiatives like the Center for Developmental Science, advancing interdisciplinary research in psychological measurement and intervention evaluation.
Dr. Hanbo Shim is an Assistant Professor in the Department of Management at The University of Texas at Arlington, College of Business. He holds a PhD in Industrial Relations and Human Resources from Rutgers University and a BA in Mathematics and Economics from the University of Illinois at Urbana-Champaign. His research and teaching focus on Human Resource Management, Organizational Behavior, and HR Analytics. PhD, Industrial Relations and Human Resources, Rutgers University (2022) MS, Industrial Relations and Human Resources, Rutgers University (2019) MA, Human Resource Management, Rutgers University (2016) BA, Mathematics and Economics, University of Illinois (2012) Dr. Shim's research explores the temporal dynamics of employee performance, compensation systems, emotional intelligence, and social networks in organizations. He uses longitudinal analysis, multilevel modeling, meta-analysis, and computer simulation to examine how individual and interpersonal factors influence organizational outcomes. His work bridges HR analytics with behavioral science. His recent publications span topics such as green HRM, pay policy dynamics, emotional intelligence, and HR analytics education. These works reflect a strong interdisciplinary approach integrating psychology, sustainability, data science, and strategic management. His research has been presented at leading conferences including the Academy of Management and European Reward Management Conference. Award highlights include: Ralph Alexander Best Dissertation Award (2024) Innovative Teaching Award, Academy of Management HR Division (2022) Best Student Convention Paper Award (2020) Best Doctoral Conference Paper Award, Samsung Economic Research Institute (2020) Dr. Shim actively advises students through capstone and honors projects and serves on PhD and graduate studies committees. He has collaborated with SL Corporation on HR analytics and developed open-source educational materials. His service includes editorial board membership for Compensation & Benefits Review and ad hoc reviewing for top journals. He is also engaged in professional development workshops and public speaking, including for the Society for Human Resource Management at UTA. His lab and research activities emphasize simulation-based methods and real-world HR analytics applications.
