Dr. Adegboyega Ojo is a Professor at the School of Public Policy and Administration (SPPA), Carleton University , holding the prestigious Canada Research Chair (Tier 1) in Governance and Artificial Intelligence since 2014. His work bridges digital government , AI governance , and smart city development , with a focus on public sector innovation and policy analytics . Research Interests Smart Cities and Urban Digital Infrastructure Open Government Data and Transparency Blockchain Applications in Public Administration AI Ethics and Algorithmic Governance Electronic Participation and Citizen Engagement Publication Trends : His research emphasizes interdisciplinary approaches to digital governance, often involving data-driven policy analysis , smart city frameworks , and open data platform design . Collaborations span institutions in Ireland, Poland, and the U.S., with citations exceeding 5,200. Scientific Awards : Canada Research Chair in Governance and AI (Tier 1) Labs & Teams : Collaborates with the Insight Centre for Data Analytics (Ireland), Delft University of Technology , and United Nations University on projects like OpenGovIntelligence and BOLD (Big and Open Linked Data).
Mohsen Lesani is an Associate Professor in the Computer Science and Engineering Department at the University of California, Santa Cruz's Baskin School of Engineering. His research focuses on reliability and security of software systems, particularly concurrent and distributed systems, with recent emphasis on secure replicated systems and distributed machine learning. Dr. Lesani received his PhD from UCLA, MS in artificial intelligence from Sharif University of Technology, and BS in software engineering from University of Tehran. He was previously a postdoc at MIT. His educational background provides a strong foundation for his interdisciplinary research spanning programming languages, distributed systems, and security. His research interests center on creating reliable and secure distributed systems. Current projects include resilient and secure distributed systems, heterogeneous and reconfigurable secure distributed systems, automatic analysis and synthesis of replicated objects, verification of distributed systems, data analytics, secure exchange across blockchains, machine learning for performance models, domain-specific languages and type systems, and automatic fence insertion for concurrent systems. His work bridges theoretical foundations with practical implementations to address real-world challenges in distributed computing. Lesani's research has been recognized with several prestigious awards including the NSF CAREER award in 2020 and DARPA YFA award in 2022. His work has also received the SIGPLAN Research Highlight in 2019, a distinguished paper award at OOPSLA 2018, and a best paper award at ISSRE 2015. These accolades reflect the impact and quality of his contributions to the field. He actively mentors PhD students in the Safe and Secure Software (S3) lab, including Xiao Li, Eric Chan, Javad Saber-Latibari, and Tejas Mane. His research has been supported by multiple NSF grants, demonstrating sustained funding for his innovative work. Lesani serves on program committees for major conferences including POPL, PLDI, OOPSLA, and DISC, contributing to the academic community. Lesani leads the Safe and Secure Software (S3) lab at UC Santa Cruz, where his team works on cutting-edge research in distributed systems, programming languages, and security. The lab fosters a collaborative environment where theoretical insights are translated into practical systems that address real-world challenges in reliability and security of distributed applications.
Yiming Yang is a Professor at the Language Technologies Institute and Machine Learning Department within the School of Computer Science at Carnegie Mellon University , where he has held faculty positions since 2003. His research spans foundational and applied aspects of machine learning , artificial intelligence , and scientific computing . Professor, Carnegie Mellon University (2003–Present) Associate Professor, Carnegie Mellon University (1996–2003) Yang's research focuses on LLM-based problem-solving agents , combinatorial optimization , and scalable oversight frameworks . His work explores diffusion models, Langevin dynamics, and Fourier neural operators for NP-hard problems, while advancing reinforcement learning techniques for self-play supervision and principle-driven fine-tuning of large language models. Recent publications highlight his contributions to code synthesis , PDE solving , and multi-agent reinforcement learning . Key methodologies include demonstration-guided control, retrieval-augmented reasoning, and test-time scaling laws. His team has developed frameworks like FEEDER for efficient in-context learning and μTransfer-FNO for zero-shot hyperparameter transfer in PDE solvers. Notable scientific achievements include: Best Student Paper Runner Up (2013) Best Theoretical Paper Award (1994) Best Theoretical Paper Award (1993) Yang has mentored over 20 PhD students and postdocs, including Shengyu Feng , Zhiqing Sun , and Aman Madaan , across domains like graph learning , extreme multi-label classification , and language model alignment .
Albert Atserias is a Professor in the Department of Computer Science at the Universitat Politècnica de Catalunya (UPC), affiliated with the Faculty of Informatics of Barcelona (FIB) and the ALBCOM research group (Algorithms, Bioinformatics, Complexity, and Formal Methods). He is also associated with the Institut de Matemàtiques de la UPC-BarcelonaTech. His research is central to theoretical computer science, with a strong emphasis on logic and complexity. Atserias's research interests span Computational Complexity, Logic in Computer Science, Finite Model Theory, Proof Complexity, and Constraint Satisfaction Problems . His work explores the fundamental limits of computation, the expressive power of logical languages over finite structures, and the complexity of proving mathematical statements. He investigates the algebraic and combinatorial properties of proof systems, the limits of efficient algorithms for constraint solving, and the theoretical foundations of databases. His research often bridges logic, algebra, and combinatorics to provide deep insights into computational phenomena. The trends in his recent publications show a sustained focus on the logical and algebraic underpinnings of computational problems. Key themes include the consistency and complexity of database queries , the power and limitations of proof systems (like resolution and sum-of-squares), and the expressive power of homomorphism counts in graph theory. His work on the hardness of automating resolution and the development of circular proof systems are particularly significant contributions to proof complexity. The 2024 PODS Best Paper Award for work on relational consistency underscores the impact and timeliness of his research. Among his notable scientific awards are the prestigious ICREA Acadèmia , the PODS 2024 Best Paper Award , the Premi Extraordinari de Doctorat (Extraordinary Doctoral Prize), and the Kleene Award for Best Student Paper . These accolades reflect both the excellence of his early work and his continued leadership in the field. Atserias has been a principal investigator on numerous competitive research projects, including funding from the European Research Council (ERC) and the Spanish Ministry of Science. He has advised doctoral students, such as Toni Hakoniemi, whose thesis on proof complexity he supervised. His extensive collaborative network includes leading researchers like Phokion Kolaitis, Anuj Dawar, and Victor Dalmau. He has also served on the scientific committees of major conferences, contributing to the academic community. He is a core member of the ALBCOM research group , a leading team at UPC focused on theoretical aspects of computer science, which provides a vibrant environment for research in algorithms, complexity, and formal methods. His work is also connected to the broader Institut de Matemàtiques de la UPC, fostering interdisciplinary collaboration between computer science and mathematics.
Dr. Preston Foerder is Assistant Professor of Psychology specializing in comparative cognition research. His work examines problem-solving abilities across species including elephants, otters, dolphins, and therapy dogs. Key findings include documenting the first evidence of insightful tool use in elephants and analyzing socialization effects on feline cognition. Current research investigates therapy dog impacts on human anxiety and zoo animal enrichment strategies. Foerder's doctoral research established novel paradigms for studying insight in non-human species. His zoo-based approach combines behavioral observation with controlled cognitive testing. Prior to academia, Foerder worked professionally as a puppeteer, bringing unique perspectives to animal behavior interpretation.
Forest Agostinelli is an Assistant Professor in the Department of Computer Science and Engineering at the Molinaroli College of Engineering and Computing, University of South Carolina, where he is also affiliated with the AI Institute. His research focuses on designing AI algorithms for pathfinding problems, integrating deep learning, reinforcement learning, heuristic search, and formal logic. He holds a Ph.D. in Computer Science from the University of California, Irvine, an M.S. from the University of Michigan, and a B.S. in Electrical and Computer Engineering from The Ohio State University. Research Overview : Agostinelli’s work emphasizes solving pathfinding problems in domains like robotics, theorem proving, and molecular optimization. His group develops explainable AI methods to enable collaboration between humans and machines. Key projects include DeepCubeA (solving the Rubik’s Cube via deep reinforcement learning) and neural activation function research. Funding & Awards : He has secured grants from NSF, NASA EPSCoR, and South Carolina’s ASPIRE and MADE programs. Notable awards include the NSF Graduate Research Fellowship and the Graduate Education for Minority Students Fellowship. Teaching : He teaches courses in Artificial Intelligence (CSCE 580) and Deep Reinforcement Learning and Search (CSCE 790), mentoring over 15 students at undergraduate and graduate levels. Labs & Collaborations : Active in AI-driven education and interdisciplinary projects, his lab contributes to tools like ALLURE for children’s learning and Bioinformatics platforms like CircadiOmics.
Dr. Arno Berger is a Professor in the Department of Mathematical and Statistical Sciences at the University of Alberta. He holds a Dipl.Ing. (ME) and Dipl.Ing. (MSc) in Mechanical Engineering and Applied Mathematics from TU Wien (Vienna University of Technology), followed by a Dr. techn (PhD) and Habilitation in Applied Mathematics from the same institution. His research focuses on dynamical systems, ergodic theory, Benford's Law, nonautonomous dynamics, bifurcation theory, applied probability, and dimensional analysis. He has held visiting positions at prestigious institutions including Georgia Tech, University of Warwick, Goethe University Frankfurt, and University of Canterbury. His recent work includes studies on Saint-Venant-Polya inequalities, planar curves with position-dependent curvature, and distributions of logarithmic functions. He co-authored the seminal book An Introduction to Benford's Law (2015), and maintains the Benford Online Bibliography. His teaching spans courses like Differential Equations and Real Variables. Dr. Berger’s research has explored Benford’s Law in diverse contexts, from stochastic processes to finite-time dynamics. His articles often bridge theoretical insights with practical applications, emphasizing the ubiquity of Benford’s Law in mathematical systems.
Pankaj Kumar Maskara is a Professor of Finance at the H. Wayne Huizenga College of Business & Entrepreneurship , Nova Southeastern University. He holds a Ph.D. in Business Administration from the University of Kentucky and has academic credentials from Boston College, Middle Tennessee State University, and Tribhuvan University. His expertise spans corporate governance, information asymmetry, financial institutions, and fintech. Education : Ph.D. (University of Kentucky), M.S. in Finance (Boston College), M.B.A. (Middle Tennessee State University), B.B.A. (Tribhuvan University) Maskara's research focuses on corporate governance, financial inclusion through P2P lending, and AI applications in business. He has published in journals like Journal of Financial Economics and Journal of Banking and Finance . His work often bridges academic rigor with practical insights from his corporate and entrepreneurial experience. He received the 2019 International Teaching Award from the Financial Management Association for innovation in finance education. As CEO of Educators Park , he supports startup acceleration and cross-border business expansion in India/China. Maskara also authored books like Entrepreneur's Handbook and Making Sense of Accounting and Finance . Scientific Awards : 2019 International Teaching Award (FMA) He actively advises on entrepreneurship, has spoken at global forums like the Baidu World AI Conference, and contributes to community initiatives as president of a non-profit organization.
Robert G. Bland is a Professor at Cornell University's School of Operations Research and Information Engineering (ORIE). He joined Cornell in 1978 after roles at SUNY Binghamton and research fellowships in Belgium. He is affiliated with the Center for Applied Mathematics and specializes in linear programming, combinatorial optimization, and network flow theory. His research emphasizes algorithmic efficiency, duality theory, and applications in scheduling and resource allocation. Education: B.S. (1969), Cornell University M.S. (1972), Cornell University Ph.D. (1974), Cornell University Research Interests: Focuses on linear programming duality, combinatorial abstractions, computational methods for optimization, and applications in logistics, scheduling, and scientific computing. Notable work includes the development of new pivoting rules for the simplex method and empirical studies of network flow algorithms. Publications Insight: His work spans foundational LP theory, combinatorial optimization, and algorithmic analysis. Key themes include duality frameworks, Camion bases, and large-scale TSP applications in crystallography. Recent publications address abstract dualities and historical perspectives on pioneers like D. Ray Fulkerson. Awards: Recipient of Cornell's prestigious Merrill Outstanding Educator Award (3 times) and twice recognized as ORIE's best teacher. Member of the Mathematical Optimization Society and American Society for Engineering Education. Grants & Projects: Conducted service projects on vehicle routing and examination scheduling. Collaborated on computational studies of min cost flow algorithms and network flow performance. Labs/Teams: Active in ORIE's research groups, particularly those focused on optimization theory and computational methods.
Peter G. Troyan is an Associate Professor of Economics and Director of Graduate Studies at the University of Virginia, where he has served on the faculty since 2014. His research bridges theoretical and experimental economics with practical applications in market design, focusing on strategic behavior in matching systems and auction mechanisms. Education: Ph.D. in Economics, Stanford University (2014) B.S. in Mathematics (with High Honors) and Physics, University of Michigan (2008) Troyan's research centers on microeconomic theory with emphasis on game-theoretic foundations of market design. His work develops novel frameworks for matching under constraints, analyzes strategic manipulation in allocation mechanisms, and pioneers experimental validations of theoretical predictions. Key contributions include formalizing 'obvious strategyproofness' as a solution concept and designing ranking methods that improve welfare in competitive matching processes. His interdisciplinary approach integrates experimental economics to test theoretical models in real-world settings like school choice and labor markets. His publication record reveals a consistent trajectory toward foundational contributions in mechanism design, with increasing focus on simplicity principles and behavioral realism. Recent work in Econometrica establishes theoretical limits of mechanism simplicity, while experimental studies in Games and Economic Behavior validate preference structures in matching markets. The recurring themes across his publications demonstrate how theoretical insights can be operationalized to solve allocation problems with distributional constraints. Scientific Awards: Best Paper Award and Exemplary Theory Paper Award at ACM Conference on Economics and Computation (EC19) UVA Quantitative Collaborative (2022) and Arts & Sciences Research Grant (2022) Roger Sherman Fellowship (2019-2020) and multiple university research grants Stanford and University of Michigan fellowships during graduate training Troyan directs the Economics Department's graduate program while securing continuous research funding, including five consecutive Bankard Fund grants (2017-2024) supporting his theoretical and experimental work. His service includes editorial roles at the American Economic Journal: Microeconomics and extensive peer review for top economics journals. As an active conference participant, he regularly presents at the ACM Conference on Economics and Computation and Econometric Society meetings, contributing to the market design research community through the University of Virginia Bankard Workshop in Economic Theory. His leadership extends to mentoring graduate students in economic theory research and collaborating with international scholars like Marek Pycia and Thayer Morrill. Current projects explore desirable ranking methodologies and the boundaries of strategyproof allocation mechanisms, positioning his work at the forefront of market design theory.
Scott Durbin is an Assistant Professor and Program Coordinator for Music Business at the University of Louisiana at Lafayette , affiliated with the School of Music & Performing Arts . With a career spanning academia and the entertainment industry, he is best known as a co-founder of the Grammy-winning children's band Imagination Movers , which produced a Disney Channel series and earned an Emmy Award for Outstanding Original Song (2008–2009). His academic work focuses on bridging real-world music industry practices with education. Bachelor of Arts (B.A.) , Centenary College of Louisiana (1992) Master of Education (MEd) in Curriculum and Instruction , University of Louisiana at Lafayette (2019) Teacher's Certificate (1994), University of New Orleans Scott's expertise lies in Music Business , Digital Service Providers (DSPs) , Musical Copyright and Rights Management , and Musical Monetization . His research emphasizes Metadata integration for rights tracking and revenue generation, reflecting his industry experience with Disney, Concord Music, and mechanical licensing frameworks. His publications include children's music albums and educational songbooks, showcasing cross-disciplinary impact in Entertainment Industry , Artist Management , and Streaming Revenue Models . These works highlight his role in evolving music industry practices through Digital Distribution and Licensing Agreements . Drs. Chuck and Sue Lein/BORSF Endowed Professorship in Music Management/Business (2015) Rising Star Award , College of Arts (2015) Eminent Faculty Award for Service Leadership (2015) ASCAP Plus Award (2015, 2016, 2019) Daytime Entertainment Emmy® (2008–2009) As a Mechanical Licensing Collective (MLC) Educator Ambassador , Scott shares industry insights on Musical Copyright and Digital Licensing . He teaches courses like MUS 455: Artist Management, Booking, and Touring , leveraging his experience negotiating contracts with Disney and managing large-scale tours.
Professor Fabian Waleffe is an Applied Mathematician at the University of Wisconsin, Madison, holding a joint appointment between the Department of Mathematics and the Department of Engineering Physics. His academic career spans multiple decades with extensive teaching experience at both UW Madison and MIT. Professor Waleffe's primary research focuses on the fundamental problem of turbulence in fluid flows and its relation to Exact Coherent States. He developed the Self-Sustaining Process theory for shear flows, which provides an ab initio method to discover families of 3D traveling wave solutions of the Navier-Stokes equations in all canonical shear flows. His research also encompasses geophysical flows and computational methods for solving partial differential equations, including spectral integration methods and numerical techniques for incompressible flows. His publication record demonstrates consistent focus on hydrodynamic instabilities, turbulence, and coherent structures. Recent work examines optimal heat transport in Rayleigh-Bénard convection, streak instability, and near-wall turbulence, integrating theoretical analysis, numerical computation, and physical insight to address fundamental questions in fluid dynamics. His research has evolved from early work on triad interactions in homogeneous turbulence to the current focus on exact coherent structures that form the 'backbone' of turbulent shear flows. Professor Waleffe has taught extensively across the mathematics and engineering curriculum. He has taught Math 321 (Vector and complex calculus for the physical sciences) for 29 semesters at UW Madison, along with numerous other undergraduate and graduate courses. His teaching spans from introductory calculus to advanced graduate topics in hydrodynamic instabilities and turbulence, reflecting his deep commitment to mathematical education in the physical sciences.
Tomer Moshe Schlank is a Professor of Mathematics at the University of Chicago, conducting cutting-edge research at the intersection of Algebraic Topology and Arithmetic Geometry with significant contributions to Chromatic Homotopy Theory and Algebraic K-Theory. His research program centers on deep structural connections between homotopy theory and number theory, particularly exploring redshift phenomena, ambidexterity in K(n)-local homotopy theory, and ∞-categorical frameworks. Schlank's work bridges abstract homotopy-theoretic constructions with concrete arithmetic applications, advancing our understanding of stable homotopy categories and their algebraic representations. Analysis of his recent publications reveals a dominant trend toward chromatic redshift phenomena in algebraic K-theory, cyclotomic extensions, and ambidextrous structures in homotopy theory. His work consistently demonstrates how higher categorical methods solve foundational problems in stable homotopy theory while generating new insights for arithmetic geometry. Tomer Schlank mentors numerous graduate students including PhD candidates Arye Deutsch, Shai Keidar, Jonatan Kogan, Asaf Yekutieli, Shauly Ragimov, Jacob Lerma, and Yuqin Kew ang, along with MSc student Iyar Mazor. His extensive network of former students and collaborators encompasses Edo Arad, Netanel Stein, Yizhak Zanghi, Asaf Horev, Lior Yanovski, Shachar Carmeli, Shay Ben-Moshe, Segev Cohen, Noam Zimhoni, Ariel Davis, and Shaul Barkan. Scientific Awards: None listed in the provided information.
E. Lea Johnston is the Clarence J. TeSelle Professor and Professor of Law at the University of Florida Levin College of Law. She is a leading expert in mental health law, criminal law, and criminal procedure, with her work appearing in top law reviews and peer-reviewed interdisciplinary journals. Her scholarship has been widely cited by legal scholars, appears in leading treatises, and has received attention from courts and social scientists. Her theory of sentencing forms part of the theoretical framework for the standard textbook for forensic psychiatry fellowship programs. Professor Johnston earned her A.B. from Princeton University and her J.D. (cum laude) from Harvard Law School. Before entering academia, she worked as a litigation associate at Arnold & Porter LLP in Washington, D.C., served as director of the Maryland Public Interest Research Group, and clerked for Judge Richard Tallman of the U.S. Court of Appeals for the Ninth Circuit. Johnston's research primarily focuses on the intersection of mental health and criminal justice. Her work examines how mental illness impacts criminal responsibility, competence to stand trial, sentencing, and diversion programs. She has made significant contributions to understanding diminished responsibility doctrines, insanity defenses, mental health courts, and assisted outpatient treatment. Her scholarship often employs interdisciplinary approaches, integrating legal analysis with insights from psychology, psychiatry, and behavioral sciences to develop more humane and just approaches to mentally ill offenders within the criminal justice system. Her publications demonstrate consistent scholarly output with significant impact across multiple disciplines. The trajectory of her work shows an evolution from foundational analyses of legal standards for mentally ill defendants toward more comprehensive reform proposals addressing systemic issues in how the criminal justice system handles mental illness. Elected to American Law Institute (2020) Former Chair of Criminal Justice Section, American Association of Law Schools Former Chair of Law and Mental Disability Section, American Association of Law Schools Member of Legal Scholars Committee, American Psychology-Law Society Professor Johnston has significantly influenced both legal scholarship and practice through her theoretical contributions and practical recommendations. Her work on sentencing theory for mentally ill offenders has been incorporated into forensic psychiatry training materials, demonstrating real-world impact beyond academia. While specific grant information isn't detailed in the provided text, her extensive publication record and leadership roles suggest substantial research support throughout her career. Her scholarship serves as a critical bridge between legal doctrine and clinical mental health practice, offering frameworks that balance therapeutic needs with justice considerations.
Lorenzo Melito is a Professor in the Faculty of Engineering at Università Politecnica delle Marche (UNIVPM) in Ancona, Italy. His research focuses on coastal engineering, fluid dynamics, and environmental modeling with particular emphasis on wave dynamics, tsunami inundation, and coastal adaptation to climate change in Mediterranean environments. Dr. Melito's research interests span several critical areas in coastal engineering and environmental fluid mechanics. His work on wave-current interactions, steady streaming, and infragravity dynamics provides fundamental insights into coastal processes. He has developed semi-empirical approaches for tsunami inundation mapping that have been applied to Italian coastlines. His research on munitions mobility in estuaries addresses important environmental contamination issues, while his work on coastal inundation modeling contributes to climate change adaptation strategies for the Marche Region and beyond. His publications demonstrate expertise in both theoretical modeling and experimental approaches to understanding complex coastal phenomena. Analysis of Dr. Melito's recent publications reveals a strong focus on coastal processes in the Adriatic Sea region, particularly in microtidal environments. His work combines theoretical modeling, numerical simulation, and experimental approaches to understand complex wave-bottom interactions, sediment transport, and coastal flooding mechanisms. A recurring theme is the application of fundamental fluid dynamics principles to solve practical coastal engineering problems, with emphasis on Italian coastal regions including the Marche Region and the Tyrrhenian and Adriatic coasts. His research bridges theoretical fluid dynamics with practical coastal management applications, particularly for hazard assessment and climate change adaptation.
