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Steven W. EvansView profile

Professor

• School Mental Health
• Attention-Deficit/Hyperactivity Disorder (ADHD)
• Adolescent Psychopathology
• +7 more

Steven W. Evans is a Distinguished Professor in the Department of Psychology at Ohio University, College of Arts and Sciences. He serves as Co-Director of the Center for Intervention Research in Schools (CIRS) and is the Editor-in-Chief of the journal School Mental Health . His work focuses on developing and evaluating school-based interventions for adolescents with ADHD and related challenges. Education: B.S., Bowling Green State University, Education M.A., Ball State University, Psychology Ph.D., Case Western Reserve University, Clinical Psychology Internship & Post-Doc, Western Psychiatric Institute & Clinic Dr. Evans’s research centers on treatment development and evaluation for adolescents with ADHD, particularly through the Challenging Horizons Program (CHP). His work explores academic, organizational, and social functioning outcomes, compliance effects, cost-effectiveness, and the role of working alliance and family dynamics. He emphasizes school-based, evidence-driven strategies to improve long-term success for youth with ADHD. His recent publications span topics such as cost-effectiveness of after-school programs, digital interventions (e.g., ATHEMOS video game), peer-supported engagement, and compliance trajectories. These works reflect a strong trend toward implementation science, personalized intervention models, and real-world applicability in educational settings. Scientific Leadership and Recognition: Editor-in-Chief, School Mental Health Co-Director, Center for Intervention Research in Schools (CIRS) Principal Investigator on grants from the Institute of Education Sciences and National Institute of Mental Health Dr. Evans has advised numerous graduate students, many of whom have gone on to PhDs and academic or clinical careers. His research includes grant-funded projects evaluating the long-term impact and economic value of ADHD interventions, with a focus on sustainable, school-integrated models. He collaborates extensively with scholars such as George J. DuPaul, Joshua M. Langberg, Julie S. Owens, and Samantha M. Margherio. He leads and contributes to major scholarly works, including handbooks and book chapters on school mental health, and has developed practical guides for educators and clinicians. His lab, CIRS, is dedicated to advancing science and practice in youth mental health through rigorous research and dissemination.

Mian M. HamayunView profile

Associate Professor

• Computer Science
• Transaction Level Modeling (TLM)
• MPSoC Simulation
• +15 more

Mian M. Hamayun is an Associate Professor of Computer Science and Head of Subject Group at the University of Birmingham Dubai campus, part of the College of Engineering and Physical Sciences. He holds a PhD in System Modelling, Simulation & Virtualization from the University of Grenoble Alpes, France, and has academic qualifications from Joseph Fourier University and COMSATS Institute of Information Technology, Pakistan. PhD in System Modelling, Simulation & Virtualization, University of Grenoble Alpes, 2013 MS in Informatics (Parallel & Distributed Systems), Joseph Fourier University, 2009 MSE in Software Engineering (Gold Medalist), COMSATS, 2005 PGCHE, University of Birmingham, 2021 FHEA and SFHEA, University of Birmingham (2021, 2024) His research spans Transaction Level Modeling (TLM) , MPSoC simulation , cloud computing , virtualization , Internet of Things/Vehicles , edge AI , and TinyML . He focuses on performance estimation, binary translation, and system-level simulation for embedded and distributed systems. The recent publications reflect a strong trend in IoT and vehicular networks , secure telemedicine , cloud orchestration , and embedded system simulation . His work integrates virtualization with security, real-time constraints, and machine learning on edge devices. Senior Fellow of the Higher Education Academy (SFHEA), 2024 Fellow of the Higher Education Academy (FHEA), 2021 Dr. Hamayun has supervised multiple research students and contributed to projects involving fatigue detection, person re-identification, retinal image analysis, and secure surgery frameworks. He has taught core computer science courses including Operating Systems, Networks, Data Structures, Algorithms, and Functional Programming at both undergraduate and postgraduate levels. His prior roles include Assistant Professor at NUST SEECS, R&D Engineer in France, and Lecturer at IUT1. He leads research in virtual prototyping and edge intelligence at the Dubai campus, contributing to smart city and cognitive systems initiatives. His lab work involves hybrid simulation environments, secure automotive platforms, and distributed IoT systems.

Onur UlgenView profile

Professor

• Industrial Engineering
• Discrete-Event Simulation
• Manufacturing Systems
• +5 more

Onur Ulgen is a Professor in the Industrial and Manufacturing Systems Engineering department at the University of Michigan-Dearborn , where he has held positions since at least 2011. His work focuses on applying simulation techniques to solve complex problems in manufacturing and industrial systems. Education Ph.D., Industrial Engineering , Texas Technological University M.S., Industrial Engineering , Texas Technological University B.S., Mechanical Engineering , Robert College Research Interests Professor Ulgen specializes in Discrete-Event Simulation (DES) applications across multiple domains. His work addresses Automotive Manufacturing challenges like assembly line optimization, selectivity bank modeling, and deadlock prevention. He also investigates Steel and Metal Manufacturing systems, high-speed production lines, and Medical Logistics resource allocation. Key subfields include production scheduling, software selection for industrial simulation, and integrated systems modeling. Recent Article Trends His publications from 2015 to 2007 demonstrate a sustained focus on simulation for Automotive , Aerospace , and Healthcare industries. Topics include capacity planning, material handling optimization, and simulation-based design validation. Specific methodologies emphasize discrete-event simulation , throughput analysis , and deadlock prevention in complex systems. Grants and Projects Ford Motor Company (2011-2012): Modeling selectivity buffers for conflicting constraints in vehicle assembly SAP America, Inc. (2000): Nonlinear demand forecasting and inventory management uncertainty SME Education Foundation (1996-1997): Manufacturing engineering support

• Wireless Communications
• Information Theory
• Physical Layer Security
• +7 more

Eduard A. Jorswieck is a University Professor of Communication Systems at the Institute of Communications Engineering , Technical University of Braunschweig, since 2019. He has previously held a professorship at TU Dresden (2008–2019) and has been a lecturer at TU Berlin (2005–2008). Currently, he serves as the Geschäftsführender Leiter (Managing Director) of the Institute of Communications Engineering. Education: Dipl.-Ing. in Computer Engineering (2000), Doctorate (2004) from TU Berlin. Research Interests: His work bridges information theory and wireless communications, focusing on physical layer security , energy efficiency , reconfigurable intelligent surfaces (RIS) , NOMA , MIMO systems , and machine learning for network optimization . He explores stochastic orders, game theory, and fractional programming for resource allocation in 5G/6G networks. Publications & Trends: Recent articles emphasize RIS-aided URLLC , STAR-RIS , 6G security , and AI-driven resource management . His studies span multi-antenna systems , terahertz ISAC , and multi-agent reinforcement learning for UAV networks. Awards: IEEE Signal Processing Society Best Paper Award (2006) IEEE Fellow (2020) Fellow of Industry Academy (AIIA, 2024) Best Paper Award at IEEE ICC 2024 Students & Collaborations: He has mentored researchers like K.-L. Besser, P.-H. Lin, and M. Mross. His lab collaborates on projects involving quantum communication , industrial IoT , and multi-agent systems .

Peter MichaelisView profile

Professor

• Environmental Economics
• Resource Economics
• Climate Change Economics
• +4 more

Prof. Dr. Peter Michaelis is Chair of Environmental and Resource Economics at the Faculty of Business and Economics, University of Augsburg, Germany. He has held this position since April 1999, leading research and teaching in environmental economics, resource management, and climate change policy. His research focuses on the economic aspects of environmental problems, with particular emphasis on climate change economics. Key areas include: Design and effectiveness of economic instruments in environmental policy Emissions trading systems and carbon pricing mechanisms Climate policy and innovation dynamics Resource economics and sustainable development Environmental policy instruments and their economic impacts Prof. Michaelis's publication record demonstrates a consistent focus on environmental economics, with numerous articles in leading journals examining CO2 pricing, emissions trading, climate policy, and environmental regulation. His recent work has particularly emphasized climate change economics, analyzing the economic implications of greenhouse gas accumulation and developing models for optimal climate policies. His research often addresses the theoretical and empirical challenges of climate change due to uncertainties, long-term impacts, and global nature of the problem. Among his notable recognitions: Recipient of the Baden-Württemberg Metal Industry Promotion Prize (1990) for his doctoral work on waste management Member of the Advisory Council on Environmental Issues (August 2000-June 2008) Prof. Michaelis leads the Chair of Environmental and Resource Economics, which includes several research associates and doctoral candidates working on various environmental economics projects. His team has undertaken research projects on economic instruments in environmental policy, environmental policy and innovations, promoting renewable energies, and optimal climate policies. The Chair also publishes the 'Augsburg Writings in Environmental Economics,' a series offering a forum for academic works addressing current topics in environmental economics and environmental policy. The Chair maintains active research collaborations and offers various lectures and seminars on environmental economics topics, though most courses are taught in German. Prof. Michaelis has also contributed to several environmental policy assessments as a member of the Advisory Council on Environmental Issues, providing expert advice to German policymakers.

Dan SteinbergView profile

Academic

• Probabilistic Machine Learning
• Variational Inference
• Bayesian Deep Learning
• +7 more

Dan Steinberg is a senior research scientist and team leader of the Decisions & Statistical Learning team at CSIRO Data61 in Canberra, Australia. His expertise lies in probabilistic machine learning, variational inference, Bayesian deep learning, causal inference, and their application to domains spanning synthetic biology, geospatial analytics, and algorithmic fairness. Education PhD in Computer Vision / Machine Learning (2013) – University of Sydney, Australian Centre for Field Robotics Bachelor of Engineering (Mechatronics, First-Class Honours) – University of Sydney (2008) Bachelor of Commerce (Finance) – University of Sydney (2008) Research Interests Steinberg’s core research agenda revolves around building scalable probabilistic models that can learn efficiently from limited or noisy data and provide principled uncertainty estimates. Key themes include: Variational Inference & Bayesian Deep Learning: developing lightweight yet powerful algorithms for approximate posterior inference in complex models (e.g., Aboleth, Revrand). Active Learning & Experimental Design: creating methods that decide which experiments or measurements will maximise information gain, with recent focus on in-silico protein engineering via Variational Search Distributions (VSD). Causal Inference: leveraging machine-learning tools to perform robust observational causal studies for evidence-based policy, including work on youth well-being and academic outcomes. Algorithmic Fairness: translating normative notions of equity into quantifiable objectives for regression-based decision systems. Large-scale Spatial Analytics: Landshark—an open-source TensorFlow toolkit for supervised learning on massive geospatial raster datasets. Notable Software & Tools Aboleth: A minimal-overhead TensorFlow framework for Bayesian deep learning. Landshark: Command-line tools for large-scale spatial inference. Revrand: Scalable Bayesian generalised linear models with non-conjugate likelihoods. libcluster: Extensible C++ library for hierarchical Bayesian clustering. Scientific Awards Oral Presentation Award – ICML 2025 Workshop on Scaling up Intervention Models (SIMS) Oral Presentation Award – NeurIPS 2024 Workshop on Bayesian Decision-making and Uncertainty (BDU) Oral Presentation Award – NeurIPS 2023 Workshop on Adaptive Experimental Design and Active Learning Spotlight Paper Award – NeurIPS 2014 (Extended and Unscented Gaussian Processes) Research Team & Collaborations As Team Leader – Decisions & Statistical Learning at CSIRO Data61, Steinberg directs a multi-disciplinary group that partners with government agencies (e.g., Jobs and Skills Australia, Australian Institute of Health and Welfare) and industry to deploy machine-learning solutions at scale. He has previously held roles as Principal Researcher at Gradient Institute (2019-2023), Senior Research Engineer at CSIRO Data61 (2016-2019), Researcher at NICTA (2013-2016), and Research Associate at the University of Sydney (2012-2013).

Burhaneddin SandikciView profile

Associate Professor

• Decision-Making Under Uncertainty
• Medical Decision Making
• Healthcare Operations
• +3 more

Burhaneddin Sandikci is an Associate Professor of Operations Management at the Booth School of Business, University of Chicago . His research focuses on decision-making under uncertainty in medical decision-making and healthcare operations , using advanced methodologies such as Markov decision processes , stochastic programming , and simulation . His recent work includes: Equilibrium analysis of marginal organ transplantation to address shortages. Modeling breast cancer screening with supplemental tests for high-risk patients. Developing parallel bounding methods for multistage stochastic programs . His publications appear in top-tier journals like Operations Research , Management Science , and Hepatology . He has received prestigious awards including the IIE Pritsker Doctoral Dissertation Award and INFORMS Bonder Scholarship . His research bridges operations management with healthcare policy , impacting organ allocation, transplant outcomes, and hospital capacity optimization.

Gilles DurantonView profile

Professor

• Urban Economics
• Transportation Economics

Gilles Duranton is the Dean's Chair in Real Estate Professor at the Wharton School of the University of Pennsylvania, where he has been teaching since 2012. He previously held academic positions at the University of Toronto (2005-2012) and the London School of Economics (1996-2005). At Wharton, he served as Chair of the Real Estate Department from 2013 to 2019. Dr. Duranton earned his PhD from the London School of Economics in 1997 and his BSc from HEC in 1991. His academic career spans nearly three decades with significant contributions to urban economics and transportation economics. Duranton's research primarily focuses on urban economics and transportation economics, with particular interest in urban mobility, density, agglomeration economies, and transportation infrastructure. His work examines how cities function, grow, and impact economic development, with studies spanning both developed and developing countries. He has conducted extensive research on traffic congestion, urban planning, and the economic implications of transportation systems, with fieldwork in countries including India and Latin America. His scholarly achievements have been recognized with numerous prestigious awards including the Walter Isard Prize for Scholarly Achievement (2014), the Hewings Prize (2007), the August Lösch Prize (2006), and the Philip Leverhulme Prize (2003). He is a Fellow of The Regional Science Association and has served as President of both the Urban Economics Association and the North American Regional Science Council. Duranton has held significant editorial roles as Co-editor of the Journal of Urban Economics and as a member of several editorial boards. He is also a Research Associate at the National Bureau of Economic Research and a Research Fellow at the Centre for Economic Policy Research. His professional affiliations include the LSE International Growth Centre and the LSE Centre for Economic Performance.

Julie L. RoseView profile

Associate Professor

• Contemporary Political Philosophy
• Economic Justice
• Social Justice
• +2 more

Julie L. Rose is an Associate Professor in the Department of Government at Dartmouth College and serves as the Hans ’80 and Kate Morris Director of the Ethics Institute (2025-2029). She previously held postdoctoral positions at Brown University’s Political Theory Project, Stanford University’s Center for Ethics in Society, and was a Fellow-in-Residence at Harvard University’s Edmond J. Safra Center and Academic Visitor at Oxford University’s Nuffield College. Ph.D. in Political Philosophy from Princeton University M.A. in Political Philosophy from Princeton University B.S. from Cornell University Her research focuses on contemporary political philosophy, emphasizing economic justice, distributive equity, and the ethical dimensions of work, leisure, and time allocation. She explores intersections of environmental ethics, gender, and family justice, advocating for fair discretionary time distribution as a matter of citizenship rights. Her recent publications (2013-2025) span distributive justice, temporal ethics, and critiques of economic growth. Themes include rethinking work-leisure balance, Machiavellian political theory, and egalitarian policy frameworks. John C. Donovan Prize (2017) Co-editor of symposium on economic justice and privatization She serves as Associate Editor of the American Political Science Review (2024-2028) and teaches courses on Ethics and Public Policy, Justice and Work, and Environmental Ethics. Her work bridges philosophical theory with practical policy implications.

Anders Bredahl KockView profile

Professor

• Econometrics
• High-dimensional Statistics
• Time Series Analysis
• +4 more

Anders Bredahl Kock is a Professor of Economics at the University of Oxford, affiliated with St Hilda's College and the Aarhus Center for Econometrics (ACE). His research focuses on high-dimensional econometric methods, particularly in instrumental variable regression, panel data models, and statistical learning applications in economics. Professor Kock's research interests center on econometric theory with emphasis on high-dimensional statistics. His work develops innovative methods for handling large datasets in economic applications, including regularization techniques, hypothesis testing in high dimensions, and treatment effect estimation. He has made significant contributions to the understanding of moment inequalities, panel data models, and forecasting methodology. His recent publications demonstrate a strong focus on high-dimensional inference problems, with particular attention to instrumental variable methods, treatment allocation, and sequential decision making. His work bridges theoretical econometrics with practical applications in economics, showing how modern statistical techniques can address traditional economic questions with complex data structures. Award mentioned on August 22, 2022 Professor Kock collaborates extensively with leading researchers in econometrics, including David Preinerstorfer, Sophocles Mavroeidis, and Mehmet Caner. His research has been published in top-tier journals including Econometrica, Journal of Econometrics, and Journal of the American Statistical Association. His methodological contributions have practical implications for economic policy analysis and causal inference in observational studies.

Marlon F. R. AlvesView profile

Assistant Professor

• Strategy
• Organizational Adaptation
• Dynamic Capabilities
• +5 more

Marlon F. R. Alves is an Assistant Professor of Strategy at SKEMA Business School, specializing in organizational adaptation, dynamic capabilities, and cognitive processing in extreme situations. His research explores the interplay between intuition and reflection in managerial decision-making, particularly during discontinuous change. Current affiliation: SKEMA Business School Academic rank: Assistant Professor Key research areas include: Strategic adaptation in ambiguous environments Intuition vs reflection in crisis management Sustainable dynamic capabilities Internationalization strategies Knowledge management systems Green innovation performance His recent work focuses on organizational resilience, environmental strategy implementation, and the cognitive foundations of competitive advantage. Studies employ experimental methodologies (e.g., virtual games) and quantitative analyses across multiple industries including biotechnology, banking, and bioenergy.

Roy E. WelschView profile

Professor

• Statistics
• Data Science
• Statistical Learning
• +10 more

Dr. Roy E. Welsch is the Eastman Kodak Leaders for Global Operations Professor of Management and a Professor of Statistics and Data Science at the MIT Sloan School of Management and the MIT Center for Statistics and Data Science . He currently serves as Director of the MIT Center for Computational Research in Economics and Management Science . Education : AB in Mathematics from Princeton University (1969), MS and PhD in Mathematics from Stanford University Dr. Welsch's research spans advanced statistical methodologies and their interdisciplinary applications. His work focuses on: Robust statistical methods for regression and covariance modeling Applications in financial markets, biomedical imaging, and drug repurposing Machine learning algorithms for high-dimensional data analysis Statistical computing and computational finance Uncertainty quantification in experimental design His recent publications emphasize cross-domain applications of machine learning, particularly in financial forecasting, biomedical diagnostics, and network behavior modeling. Notable trends include: Development of robust statistical frameworks Integration of NLP techniques in financial analysis Biomedical image processing algorithms for disease quantification Time-series and high-content analysis Portfolio optimization under uncertainty Scientific Recognition : Fellow of the Institute of Mathematical Statistics Fellow of the American Statistical Association Fellow of the American Association for the Advancement of Science Eastman Kodak Leaders for Global Operations Professorship As a dedicated educator, Dr. Welsch teaches Data Analysis and Applied Statistics courses focusing on regression modeling, experimental design, and quality control with applications in finance and marketing.

• Trauma Surgery
• Orthopaedics
• Osteoporosis Research
• +7 more

Christian Heiß is a Professor and Director of the Clinic at the Clinic and Polyclinic for Trauma Surgery, University Hospital Giessen and Marburg GmbH, affiliated with Justus Liebig University Giessen. His clinical expertise spans Trauma Surgery, Orthopaedics, Special Trauma Surgery, Sports Medicine, Emergency Medicine, Physical Therapy, and Balneology. He serves as a Specialist in Surgery and Orthopaedics and Trauma Surgery, with additional specialization in Hand Surgery. Professor Heiß's research interests focus on Trauma Surgery, Orthopaedics, Osteoporosis Research, Bone Substitutes, Fracture Healing, Bone Adhesives, and Experimental Trauma Surgery. His work explores the complex relationship between bone metabolism, rheumatoid conditions, and trauma management. His research has significantly contributed to understanding bone healing processes, particularly in osteoporotic conditions, and the development of novel bone substitute materials. Analysis of his recent publications reveals a strong emphasis on clinical applications of bone biomaterials, management of trauma in patients with rheumatoid conditions, and biomechanical aspects of fracture healing. His work bridges fundamental bone biology with practical clinical applications, particularly in challenging cases involving osteoporosis and rheumatoid arthritis. May 2019: Conference President VSOU in Baden-Baden May 2018: Senior AOTrauma Surgeon March 2018: Honorary Member of SRATS (The Romanian Society of Arthroscopy and Sports Trauma) November 2016: Honorary doctorate from the University of Craiova, Romania March 2013: Osteology Research Group Award of the German Academy of Osteological and Rheumatological Sciences in Weimar Professor Heiß has been involved in numerous research collaborations and has served on multiple advisory boards including AO Trauma, Bone Adhesive (Stryker), Fracture Healing in Osteoporosis (Amgen), and Osteoarthritis (Novartis). His leadership extends to the SFB/TRR 79 research consortium, where he has been a member and board member since 2010. His laboratory work in the Laboratory for Experimental Trauma Surgery focuses on translational research connecting basic science discoveries with clinical applications in trauma surgery.

Xiaoyan HongView profile

Associate Professor

• Distributed Systems
• Internet of Things (IoT)
• Wireless Communications
• +4 more

Dr. Xiaoyan Hong is an Associate Professor in the Department of Computer Science at The University of Alabama's College of Engineering. Her research focuses on mobile/wireless networks, vehicular networks, and delay-tolerant systems. Ph.D., Computer Science, University of California-Los Angeles (2003) M.S., Computer Science, Zhejiang University (2000) Research spans Internet of Things (IoT) , Connected Vehicles , and Underwater Wireless Networks . Key projects include NSF-funded underwater robot communication infrastructure and smart traffic light systems. Recent work explores Named Data Networking (NDN) in vehicular environments, Task Synchronization for autonomous vehicles, and V2I Communication for traffic optimization. NSF Research Experience for Undergraduates (REU) grant recipient $1.5M NSF grant for underwater robotics networking Her research integrates with multiple engineering centers, including the Center for Advanced Vehicle Technologies and Center for Transportation Operations .

Xiaojun CaoView profile

Professor

• Optical Networks
• Wireless Networks
• Network Security
• +3 more

Dr. Xiaojun Cao is a faculty member at the Andrew Young School of Policy Studies, Georgia State University, specializing in optical and wireless network architectures, protocols, and security. His research addresses challenges in bandwidth scalability, network survivability, and future Internet design through innovations in multi-granular switching, traffic grooming, and cross-layer interactions. B.S., Engineering Physics, Tsinghua University, 1996 M.S., Electrical Engineering, Chinese Academy of Sciences, 1999 Ph.D., Computer Science and Engineering, State University of New York at Buffalo, 2004 His work spans three core areas: Optical Network Optimization : Developing waveband switching frameworks for backbone networks, focusing on multi-layer architectures and performance evaluation. Network Survivability : Designing proactive and reactive strategies for protection and restoration in optical and wireless systems. Edge Network Security : Advancing secure service function chain deployment in multi-vendor and zero-trust environments. Recent research trends highlight his leadership in Network Functions Virtualization (NFV) , Edge Computing , and AI-Driven Networking , with publications on blockchain-based federated learning, prompt chain deployment, and asymmetric protection mechanisms. His work bridges theoretical rigor with practical applications in 5G/6G, UAV networks, and smart infrastructure. Dr. Cao leads a research group exploring optical-wireless convergence and has contributed to foundational studies in network virtualization and traffic management.