Dr. Jay Howell is an Associate Professor at the School of Education at the University of Southern Mississippi. He serves as Interim Associate Director and Program Coordinator for Secondary Alternate Route Licensure Programs . Based in Hattiesburg, he contributes to educator training and curriculum development. Bachelor's Degree - Auburn University (2001) Master's Degree - Auburn University (2007) PhD - Auburn University (2014) Dr. Howell's research focuses on problem-based inquiry , design-based research , and visual curriculum materials integration. His work advances teacher education through innovative methods like scaffolded lesson study and inquiry-based instruction in social studies. His recent publications demonstrate trends in geography education (2018-2022), historical inquiry (2017-2020), and teacher professional development (2017-2022). Key themes include authentic pedagogy , civic education , and visual resource design . Honor Society: Phi Kappa Phi As Program Coordinator for Secondary Alternate Route Licensure , he develops pathways for teacher certification while maintaining active research in curriculum & teaching through his personal website . Contact: James.B.Howell@usm.edu | 601.266.5810
Dr Tracey Booth is a Lecturer in Computer Science (HCI) and Co-Director of the MSc in Human-Computer Interaction Design at City, University of London's School of Science & Technology. She teaches modules including Interaction Design, Evaluating Interactive Systems, and User-Centred System Design. PhD in Human-Computer Interaction, City, University of London MSc (with Distinction), City University London Her research focuses on inclusive technology design, particularly for people with aphasia post-stroke. She developed EVA Park – a virtual world for communication therapy – through co-design with clinical populations. Her work addresses physical computing barriers for novices, including Arduino programming, and explores XR applications for healthcare. Selected trends from her publications: Hybrid virtual/physical environments for neurorehabilitation Visual programming for end-user developers Co-design methodologies with marginalized users Immersive systems for social skills training Accessibility in maker tools Scientific recognition: Award-winning EVA project With a decade of experience in voluntary sector technology projects before joining City, she has secured research funding for her EVA Park development and clinical trials. The Centre for HCI Design at City, University of London, serves as her primary research affiliation.
Lisa Torrey is an Associate Professor in the Department of Mathematics, Computer Science, and Statistics at St. Lawrence University. She teaches courses in programming, algorithms, artificial intelligence, machine learning, and computational theory. She earned her Ph.D. in Computer Science from the University of Wisconsin-Madison in 2009, where she researched relational transfer in reinforcement learning under Professor Jude Shavlik. Her research focuses on: Developing intelligent agents using reinforcement learning Human-inspired techniques for task transfer and multi-agent collaboration Educational applications of AI in computer science classrooms Machine learning approaches to crowd simulation and game AI She has recently shifted toward studying human learning dynamics in CS education. Her publications (2010-2020) predominantly explore reinforcement learning adaptations, educational AI frameworks, and knowledge-transfer mechanisms. A clear evolution is visible from theoretical machine learning toward applied educational research. She actively mentors students in AI/machine learning projects, with recent advisees including: Rodrick Mpofu (Explainable Image Classification) Lily Kendall (Sensitivity Analysis for Image Generation) Cooper Anderson (Audio Source Separation) Ellie Nichols (Avalanche Forecast Analysis) 15+ additional students across 2020-2025 No research labs or major grants are explicitly mentioned in available materials.
Jing-Rebecca Li is a Professor and Research Scientist at ENSTA Paris, affiliated with the Applied Mathematics Unit (UMA) and INRIA Saclay as part of the IDEFIX research team. Her work bridges advanced mathematical techniques with medical imaging applications, particularly in diffusion MRI. She maintains a dual affiliation between ENSTA Paris, a leading engineering school in France, and INRIA, the French national research institute for digital science and technology. HDR (Habilitation à Diriger des Recherches) in Mathematics, Université Paris-Sud, 2013 Ph.D. in Mathematics, Massachusetts Institute of Technology, 2000 B.Sc. in Mathematics, University of Michigan, 1995 Dr. Li's research focuses on developing sophisticated numerical methods to solve partial differential equations with applications in diffusion magnetic resonance imaging. Her work spans brain and cardiac imaging, numerical linear algebra, machine learning algorithms for inverse problems in PDEs, and natural language processing tools. She has pioneered approaches to simulate diffusion MRI signals in complex biological tissues, enabling more accurate interpretation of imaging data for neuroscience and cardiology applications. Her research has significant implications for understanding brain microstructure and cardiac tissue organization through non-invasive imaging techniques. Her recent publications demonstrate a clear trend toward increasingly sophisticated modeling of biological tissues, with growing emphasis on cardiac applications alongside her foundational work in brain imaging. She has developed robust computational frameworks that incorporate permeable interfaces, geometrical deformations, and realistic neuronal geometries to better simulate diffusion MRI signals. Her work increasingly integrates machine learning with traditional numerical methods, creating hybrid approaches that leverage the strengths of both paradigms for microstructure estimation. Householder Prize for the best dissertation in Numerical Algebra (2002) Dr. Li has supervised numerous doctoral students across multiple institutions, with a focus on computational methods for diffusion MRI. Her current research is supported by significant grants including the Engineering for Health (E4H) interdisciplinary center project investigating biomarkers for Multiple Sclerosis through diffusion MRI (2023-2025). Previously, she led the ANR-funded SIMUDMRI project (2010-2014) and participated in the US-French Collaboration project on Computational Imaging of the Aging Cerebral Microvasculature (2013-2016). Her work demonstrates strong interdisciplinary collaboration between mathematics, computer science, and medical imaging communities. As leader of the IDEFIX research team at INRIA Saclay, Dr. Li directs a group focused on inversion methods for differential equations applied to imaging and physics problems. Her team has developed the SpinDoctor software package, a widely used MATLAB toolbox for diffusion MRI simulation that has become a standard tool in the field. The team maintains strong collaborations with Neurospin (CEA) and international research groups working on advancing diffusion MRI methodology and applications.
Nathalie Sick is a Senior Lecturer in Contemporary Technology Management at the University of Technology Sydney (UTS), affiliated with the School of Mechanical and Mechatronic Engineering and the Centre for Advanced Manufacturing. She holds a PhD in innovation management from the University of Münster and has held roles including Deputy Head of School (Teaching and Learning) at UTS. Her research focuses on interdisciplinary collaboration, industry convergence, and technology forecasting, particularly in technology-driven sectors like energy storage and Industry 4.0. Education: PhD in Innovation Management (University of Münster), MSc in Business Administration and Industrial Engineering. Research interests include bridging boundaries between academia, industry, and government; leveraging digital technologies for sustainable production; and analyzing innovation ecosystems. She has contributed to frameworks for Industry 4.0 adoption, collaborative robotics safety, and value stream mapping. Her work spans over 100 publications, emphasizing actionable insights for socio-technical systems and open innovation strategies. Teaching and leadership: Developed courses in technology management, strategic leadership, and advanced manufacturing. Spearheaded programs like the Associate Degree of Advanced Manufacturing and the NETM micro-credential in industrial automation. Active in curriculum design and interdisciplinary education initiatives. Labs and teams: Core member of UTS's Centre for Advanced Manufacturing, leading projects on convergence in manufacturing and sustainable technologies. Collaborates with Siemens and industry partners on applied research.
Dr. Phillip Brooker is a Senior Lecturer in Sociology at the University of Liverpool, part of the School of Law and Social Justice and the Faculty of Humanities and Social Sciences. His research bridges sociology, philosophy, and digital methods, focusing on collaborative computing, science studies, and innovative methodologies. Key areas include ethnomethodology, conversation analysis, and the application of programming in social science research. Brooker’s work spans interdisciplinary projects such as analyzing NASA’s Apollo 13 mission through ethnomethodological lenses and developing the Chorus software for social media analytics. He is also the author of Programming with Python for Social Scientists (2019) and is completing a book on Skylab’s astronautics practices. Current projects include Skylab 2049 and Terra Pi , exploring maker technologies in social science. His teaching includes modules on programming for social science, sociological theory, and ethnomethodology. Professional roles include serving as Research Communications Coordinator at the University of Liverpool.
Dr. Joan Danielle Ongchoco is an Assistant Professor in Cognitive Science and Director of the UBC Perception & Cognition Lab at the University of British Columbia. She holds a PhD from Yale University (2022) and a BA (Honors) from Yale-NUS College (2017). Her research focuses on how perception interacts with broader mental processes, including decision-making, memory, and event segmentation. Before joining UBC, she conducted postdoctoral research at Humboldt Universität zu Berlin under Martin Rolfs. **Education**: PhD in Psychology, Yale University, 2022 BA (Honors) in Philosophy, Politics, and Economics, Yale-NUS College, 2017 **Research Interests**: Exploring the interplay between perception and cognition, with emphasis on memory distortions (e.g., facial aging biases), visual event boundaries and their impact on memory/attention, and the cognitive mechanisms underlying decision-making. Her work integrates experimental psychology, computational modeling, and neuroscientific perspectives. **Key Contributions**: Her lab investigates how perceptual processes shape higher-order cognitive functions. Notable studies include investigations into 'forward/backward aging' effects in facial memory, the role of event segmentation in temporal perception, and the cognitive costs associated with decision-making timelines. **Grants & Labs**: Directs the UBC Perception & Cognition Lab. Research supported by UBC infrastructure and collaborations with institutions like Humboldt Universität.
Dr. Matt Moores is a Lecturer in Statistical Science at the University of Wollongong (UOW), affiliated with the School of Mathematics and Applied Statistics within the Faculty of Engineering and Information Sciences. He joined UOW in 2018 and holds a Docent title in Computational Statistics from LUT University (2021) and is an Elected Member of the International Statistical Institute (2022). He leads research in Bayesian computation, uncertainty quantification, and spatial statistics, with applications in energy infrastructure, environmental modeling, and spectroscopy. His academic roles include Academic Program Director for the Bachelor of Data Science & Analytics and Subject Coordinator for courses such as DSAA301 and MATH205. He co-leads a 2023 Learning & Teaching Innovation Grant focusing on work-integrated learning (WIL) and serves as an Associate Editor for Statistics & Computing . Moores is a Chief Investigator in the ARC Research Hub for Transforming Energy Infrastructure (TIDE), contributing to digital engineering advancements. Research interests span Bayesian inverse problems in oceanography, combining neural networks with Bayesian methods, sequential Monte Carlo, and approximate Bayesian computation (ABC). His publications reflect expertise in Gaussian processes, spatial statistics, and computational algorithms for intractable likelihoods. Awards include the 2023 L&TIG and recognition for contributions to statistical methodology. Teaching and supervision focus on integrating practical industry experiences with theoretical foundations, supported by grants advancing pedagogical innovation. Collaborations span academia and industry, emphasizing interdisciplinary problem-solving in energy, environment, and data science.
Erica Smithwick is a Distinguished Professor of Geography at Pennsylvania State University, serving as Director of the Earth and Environmental Systems Institute (EESI) and Associate Director of the Institute of Energy and Environment (IEE). Her research focuses on landscape and ecosystem ecology, particularly disturbances such as wildfire and their impacts on socio-ecological resilience. She leads the LEAPS laboratory group, addressing climate change challenges through interdisciplinary collaborations. Key projects include the Visualizing Forest Futures (VIFF) initiative with the Menominee Tribal Nation and LandcapeU, advancing Food-Energy-Water nexus research. Dr. Smithwick has received major grants from NSF, NASA, and DOE, emphasizing transdisciplinary problem-solving. Affiliations: EESI Director, IEE Associate Director, Graduate Faculty in Ecology Program Education: Ph.D. in Ecosystem Ecology (implied through academic rank) Research interests span climate change impacts, wildfire management, and sustainable land-use strategies, with global projects in Africa, China, and the U.S. Her work bridges science and policy, addressing conservation challenges in protected areas and agro-pastoral systems. Awards include a Fulbright Scholarship and multiple federal grants. Recent publications highlight nature-based solutions for floods, rainfall variability, and mangrove monitoring tools. She actively engages in policy discussions on solar energy and relocation programs, emphasizing just transitions in environmental management.
Min Ding is the Bard Professor of Marketing at Penn State's Smeal College of Business with a joint appointment in Information Sciences. Holding dual Ph.D.s (Marketing from UPenn; Molecular Biology from Ohio State), his interdisciplinary research spans artificial empathy, logical creativity methods, digital intelligence, and cultural theory. Research Domains: Develops frameworks including Logical Creative Thinking (LCT), Bubble Theory (socioeconomic development), and Hualish Culture. His technical work focuses on audio-visual analytics applications in marketing, including privacy-preserving face recognition and brand voiceprints. Leadership: Editor-in-Chief of Customer Needs and Solutions. Former VP of INFORMS Society for Marketing Science. Authored books on creativity methods, Chinese culture, and socioeconomic development. Awards: Recognized with the Journal of Marketing's Maynard Award (2007) and Journal of Retailing's Davidson Award (2012).
Dr. Sam Cousley is an Instructional Associate Professor of Marketing at the University of Mississippi's School of Business Administration since 1999. He holds a DB.A. from Louisiana Tech University and degrees from Mississippi State University. His expertise bridges marketing, analytics, and machine learning applications in business. He teaches predictive modeling, marketing principles, and honors thesis courses. Education: B.S. Business, Mississippi State University (1967) M.B.A., Mississippi State University (1970) DB.A. Marketing, Louisiana Tech University (1974) Research interests focus on advanced statistical methods like nonlinear regression, cross-validation, and machine learning applications for solving business problems. His work spans legal and ethical issues in employment, multivariate analysis in marketing, and advertising effectiveness. Awards: Outstanding Professor of the Year (6-time recipient, Ole Miss School of Business) Prior experience includes roles as General Manager of radio stations and teaching at Arkansas State University. His publications address employment law, statistical methodologies, and marketing strategy innovations.
Dr. Cameron J. Turner serves as Associate Professor in Clemson University's College of Engineering, Computing and Applied Sciences since 2016, teaching engineering design methods, optimization, mechanical systems, and CAD/CAM. His research bridges computational capabilities with engineering design processes across multiple domains. His academic credentials include: Ph.D. in Mechanical Engineering from The University of Texas at Austin (2005) MSE from The University of Texas at Austin (2000) BSME from the University of Wyoming (1997) Turner's research centers on Computational Design Methods with emphasis on design analogy identification , early-stage problem modeling , surrogate modeling for complex systems , and additive manufacturing automation . His work integrates digital twin technology, tradespace exploration, and function-based design to solve engineering challenges in nonlinear and uncertain environments. Current investigations focus on immersive virtual environments for design reviews and intelligent robotic systems. Recent publications reveal accelerating research in digital twin applications for vehicle design, tradespace exploration methodologies, and data-driven decision support systems. These works span mechanical engineering, computer science, and systems engineering with strong emphasis on practical implementation in manufacturing and robotics. His professional recognition includes: CSM Design Program Director’s Award for service to capstone design program (2015) Turner actively shapes engineering education through leadership roles as Program Chair for ASME's CIE Division Executive Committee and member of ASME's International Design Simulation Competition Committee. His service extends to ASEE design communities and the Design Society, demonstrating commitment to advancing design pedagogy and practice. Current projects indicate expanding work in ground vehicle digital agents and Stewart platform calibration techniques. While specific laboratory details weren't provided, his research trajectory suggests active collaboration with computational design groups focusing on digital manufacturing and autonomous systems integration.
Mariana Levin is an Associate Professor of Mathematics at Western Michigan University, specializing in mathematics education research. Her work investigates mathematical cognition and learning processes across K-16 contexts. Education includes a PhD in Science and Mathematics Education from UC Berkeley, with postdoctoral work at Michigan State University and the University of Bologna. Research focuses on conceptual change, algebraic thinking, and disciplinary engagement. Publications examine knowledge construction processes, with recent work on algebraic reasoning (2022) and undergraduate proof comprehension (2018). Collaborative projects include NSF-funded research on STEM majors' agency development in mathematics. Teaching covers mathematics education, problem-solving, and teacher preparation. She mentors graduate students in mathematics education research.
Rahnuma Islam Nishat is an Assistant Professor in the Department of Computer Science at Brock University, located in St. Catharines, Ontario, Canada. She holds a BSc Engg from Bangladesh University of Engineering and Technology (BUET), and both MSc and PhD in Computer Science from the University of Victoria, BC, Canada. Her research focuses on theoretical and applied computer science, including graph theory, computational geometry, additive manufacturing (3D printing), data mining, and reconfiguration problems. She is supported by an NSERC Discovery Grant and has organized major conferences such as the 36th Canadian Conference on Computational Geometry (CCCG 2024) at Brock University. Her academic journey includes postdoctoral fellowships at the University of British Columbia Okanagan, Toronto Metropolitan University, and the University of Victoria. She has served on program committees for WALCOM 2023/2025, EuroCG 2025, and CCCG 2025. Her interdisciplinary work bridges mathematical puzzles and practical applications, particularly in additive manufacturing tool-paths and graph drawing visualization. Research highlights include contributions to Hamiltonian path reconfiguration in grid graphs, efficient spanning tree enumeration, and collision-free tool-paths for 3D printing. She actively engages with the computational geometry community through conference leadership and algorithmic problem-solving.
Robert Heckendorn, Ph.D., is an Associate Professor in the Department of Computer Science at the University of Idaho, part of the College of Engineering. His research interests span machine learning, evolutionary computation, robotics, optimization algorithms, computational biology, and transportation systems. He holds a Ph.D. and has contributed extensively to interdisciplinary areas such as autonomous systems, traffic simulation, and bio-inspired algorithms. His work often bridges theoretical foundations with practical applications, including developing high-fidelity traffic modeling tools, optimizing manufacturing processes, and advancing robotic control strategies. Notable contributions include neuroevolution techniques for crowd behavior prediction and fuzzy logic-based crowd management systems. He also explores evolutionary algorithms in biological fitness landscapes and disaster management scenarios. He has authored over 50 publications since 1997, focusing on algorithmic efficiency, population diversity in evolutionary systems, and multi-agent coordination. His research has implications for smart cities, healthcare, and autonomous vehicle technologies. Despite no listed awards here, his prolific output underscores his impactful contributions to computer science and engineering. As an educator, he contributes to curriculum development in computational thinking and web-based learning systems (e.g., vTutor platform). His lab likely focuses on real-world problem-solving through computational methods, though specific lab names aren’t mentioned. Collaborations with industry and interdisciplinary teams are implied through his research topics like connected-vehicle systems and cancer modeling via cellular automata.
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