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Carla Boutin-FosterView profile

Adjunct Associate Professor

• Health Equity
• Racial Disparities in Healthcare
• Cardiovascular Disease
• +7 more

Dr. Carla Boutin-Foster is an Adjunct Associate Professor in both Population Health Sciences and Medicine at Weill Cornell Medical College. She has established herself as a leading researcher in health equity and racial disparities in healthcare through her extensive scholarly contributions and community-engaged research approach. Her educational background includes an M.D. from State University of New York Health Science Center at Brooklyn (1994), an M.S. from Weill Cornell Graduate School of Medical Sciences (1999), and a B.A. from New York University (1990). M.D., State University of New York Health Science Center at Brooklyn (1994) M.S., Weill Cornell Graduate School of Medical Sciences (1999) B.A., New York University (1990) Dr. Boutin-Foster's research spans multiple critical areas in health disparities research, with particular emphasis on cardiovascular disease, hypertension management, and the impact of social determinants on health outcomes among racial and ethnic minority populations. Her recent work has pioneered frameworks for promoting anti-racism in clinical practice and medical education, examining the implications of removing race coefficients from clinical algorithms, and developing community-based interventions to address healthcare disparities. She frequently employs qualitative methodologies to capture patient and community perspectives, contributing to culturally tailored interventions like the HeartSmarts faith-based cardiovascular health education program and the MISTER B Trial for colorectal cancer screening among older Black men. Her publication record demonstrates consistent scholarly productivity from 2001 through 2024, with recent work increasingly focused on anti-racism frameworks in medicine, community perspectives on health equity, and syndemic approaches to understanding health disparities during the COVID-19 pandemic. Her research bridges clinical practice, medical education, and community engagement to address systemic inequities in healthcare delivery. Dr. Boutin-Foster has collaborated extensively with researchers at Weill Cornell and other institutions, with Mary E. Charlson as her most frequent collaborator (18 publications together). Her work demonstrates a commitment to translating research findings into practical interventions and educational frameworks that can be implemented in clinical settings. She has been actively involved in medical education through initiatives like the "Community Perspectives in Medicine" elective for first-year medical students, emphasizing the importance of understanding community contexts in clinical practice. Her research has significant implications for clinical practice, medical education reform, and health policy aimed at eliminating racial disparities in healthcare.

Olusegun Michael OtunugaView profile

Assistant Professor

• Stochastic Modeling
• Mathematical Epidemiology
• Biostatistics
• +7 more

Olusegun Michael Otunuga is an Assistant Professor in the Department of Mathematics at the College of Science and Mathematics and the Department of Population Health Science: Division of Biostatistics and Data Science at Augusta University. He holds a Ph.D. in Pure & Applied Mathematics from the University of South Florida and has been actively contributing to interdisciplinary research in stochastic modeling, epidemiology, biostatistics, and financial mathematics. Ph.D., Pure & Applied Mathematics, University of South Florida, 2014 M.S., Mathematics, Marshall University, 2009 B.Sc., Mathematics, Federal University of Agriculture, Nigeria, 2006 Dr. Otunuga's research focuses on the development and analysis of stochastic models to understand complex systems in biology, medicine, and economics. His work spans tumor growth dynamics under environmental stress, multi-strain epidemic modeling (including HIV, TB, measles, and COVID-19), vaccine breakthrough infections, and financial time series forecasting. He employs advanced techniques such as stochastic differential equations, parameter estimation, and first-passage-time analysis. The recent publications highlight a strong trend in applying mathematical rigor to public health challenges, particularly in modeling infectious disease spread with stochastic realism. His work bridges theoretical mathematics with practical applications in biostatistics and data science, often involving real-world data from U.S. states and global health contexts. The integration of time-varying parameters and random perturbations enhances model accuracy and predictive power. Scientific Awards: Excellence in Research Award, College of Science and Mathematics, Augusta University, 2024 Dr. Otunuga actively mentors students and serves as a faculty advisor for Pi Mu Epsilon and Goldwater Scholarship candidates. He has not received mention of specific grants in the provided text, but his sustained publication record and patent suggest active research funding. He contributes extensively to academic service through multiple committees at the department, college, and university levels, and has served as a reviewer for scholarly journals. He is involved in research teams and workshops such as the POPUPS Workshop at Augusta University, where he leads training on biostatistics and data analysis using R. His collaborative work includes joint research with the Ladde research group, culminating in a patented method for dynamic process modeling.

Jay I. FrankelView profile

Professor

• Heat Transfer in Hypersonics
• Inverse Heat Transfer Problems
• Thermal Measurements
• +7 more

Jay I. Frankel is a Professor and Department Head at the Department of Mechanical & Aerospace Engineering at New Mexico State University (NMSU). He earned his Ph.D. (1986), M.S.M.E. (1982) from Virginia Tech and a B.S.M.E. (1980, Magna Cum Laude) from the University of Maryland. Ph.D., Virginia Tech (1986) M.S.M.E., Virginia Tech (1982) B.S.M.E., University of Maryland (1980) His research focuses on thermal sciences in aerospace contexts, including: Inverse heat conduction problems Calibration methods for thermal sensors Uncertainty and sensitivity analysis High-temperature measurements for hypersonic vehicles His work often employs integral equations and advanced mathematical techniques to solve real-world thermal challenges in propulsion and aerospace systems. Recent publications explore: Calibration methods for heat flux estimation Experimental validation of thermal models Time-spectral approaches for dynamical systems Nonlinear diffusion modeling Key honors include: 2018 AIAA Special Award for CIEM development 2010 General H.H. Arnold Award for thermal analysis in propulsion 2005 AIAA Associate Fellow 2000 Fellow of Computational Mechanics at Wessex Institute He has secured significant funding from the National Science Foundation, Air Force Research Laboratory, NASA, and Department of Energy for projects related to: Hypersonic thermal protection systems Advanced sensor development Calibration methodologies under extreme conditions His laboratory team collaborates on emerging thermal diagnostics and inverse problem solutions.

Laura BakkensenView profile

Professor

• Environmental Economics
• Natural Resource Economics
• Climate Change Policy
• +3 more

Laura Bakkensen is the Mikesell Professor in Environmental and Natural Resource Economics at the University of Oregon's Department of Economics. Her research focuses on the economic impacts of natural disasters, particularly tropical cyclones and floods, using applied microeconometric techniques to analyze global risk patterns and inform policy on insurance regulation, post-disaster aid, and adaptation projects. Ph.D., Environmental and Natural Resource Economics, Yale University M.Sc., Environment and Development, London School of Economics B.A., Economics, Whitman College Her scholarly work explores: Economic consequences of climate change and disaster risk Flood cost assessment methodologies across North America Insurance market dynamics under climate uncertainty Behavioral economics of disaster preparedness Policy effectiveness in coastal and floodplain management International collaboration in climate impact research Scientific awards include: National Academies Gulf Research Program Early-Career Fellowship (2017-2019) JEEM Best Paper Award (2020) She has advised international initiatives through the National Science Foundation and Fulbright Teaching Grant to South Korea, with current research spanning three continents and involving interdisciplinary collaborations with climate scientists, hydrologists, and policy makers. Her methodological innovations in flood economic impact assessment have been adopted across Canada, Mexico, and the United States.

Howard SchwartzView profile

Professor

• Machine Learning
• Adaptive Control
• Multi-Agent Machine Learning
• +3 more

Professor Howard Schwartz is a distinguished academic in Electrical and Computer Engineering at Carleton University , with a career spanning academia, industry, and robotics research. He earned his BEng in Civil Engineering from McGill University (1982), followed by MSc (1984) and PhD (1986) in Aerospace and Mechanical Engineering from MIT. His academic leadership includes serving as Department Chairman (2009-2013) and authoring the seminal text Multi-Agent Machine Learning: A Reinforcement Approach (Wiley, 2014). As an Associate Editor for IEEE Transactions on Cybernetics , he shapes discourse in cybernetic systems and machine learning. Research Focus Professor Schwartz's research bridges theoretical and applied domains: Machine learning for robotics and autonomous systems Adaptive control theory and multi-agent systems Reinforcement learning algorithms with fuzzy logic integration Real-time video analytics and GPS receiver development Nonlinear control systems for UAVs and wind energy optimization Industry Experience His career includes impactful industry engagements: Early development of high-performance GPS receivers at Canadian Marconi Co. (1982-1984) Sabbatical at March Networks (2001-2002) for video analytics Software quality control at CMC Electronics (2008) Software development for TV set-top boxes at Espial Inc. (2014-2015)

• Wood Science
• Structural Engineering
• Timber Mechanics
• +5 more

Marie Johansson is a Professor in Timber Engineering at the Department of Building Technology, Faculty of Technology, Linnaeus University. Her career spans teaching structural engineering in bachelor’s and master’s programs and leading research projects on wood quality, strength grading, and timber mechanics. Acting supervisor in two PhD projects Expert Team Leader for "Construction & Design" in BioInnovation SIO-programme Research Interests : Wood material properties (shape stability, stiffness, strength) Connection technology in timber structures Climate change adaptation in agriculture (Öland, Sweden) Modular multi-storey timber buildings Fiber orientation modeling for strength prediction Publication Trends : Recent work focuses on wind-induced vibrations in tall timber structures, 3D fiber orientation models, genetic selection for timber traits, and non-destructive evaluation of wood properties. Collaborations with international conferences (WCTE, ICEM) and institutions highlight her contributions to wood science and sustainable construction. Research Groups : Leads the Wood Building Technology group, emphasizing applied mechanics and industrialized timber construction.

Matthew RosenzweigView profile

Assistant Professor

• Mathematical Physics
• Nonlinear Partial Differential Equations
• Probability
• +4 more

Matthew Rosenzweig is an Assistant Professor in the Department of Mathematical Sciences at Carnegie Mellon University's Mellon College of Science, specializing in mathematical physics, nonlinear partial differential equations, and probability with applications to many-body systems and wave turbulence. His educational background includes: Ph.D. in Mathematics, University of Texas at Austin Postdoctoral Appointment, Massachusetts Institute of Technology Undergraduate Degree, Harvard University Rosenzweig's research focuses on effective dynamics of large-scale systems such as Coulomb/Riesz gases, where he derives nonlinear dispersive, fluid, and kinetic equations from microscopic particle interactions. His work bridges physics and mathematics, increasingly incorporating statistical and machine learning perspectives. Key contributions address mean-field convergence , propagation of chaos , and scaling limits for singular interactions. Analysis of his 15 most recent publications (2022-2024) reveals a dominant trend in uniform-in-time mean-field theory for singular potentials, with strong emphasis on logarithmic Sobolev inequalities, wave turbulence connections (e.g., stochastic KdV equations), and fluid dynamics applications like the Lake equation. The research spans mathematical physics, probability theory, and nonlinear PDE analysis, often featuring collaborations with Sylvia Serfaty and Gigliola Staffilani. Rosenzweig's research is funded by National Science Foundation grants DMS-2441170 and DMS-2345533. As a former CLE Moore Instructor at MIT and Simons Collaboration postdoc, he maintains active involvement in the Center for Nonlinear Analysis at CMU, though no formal lab structure is specified in available materials.

David P. FieldView profile

Professor

• Physical Metallurgy
• Materials Characterization
• Solid Mechanics
• +4 more

David P. Field is a Professor at Washington State University's Voiland College of Engineering and Architecture , where he serves as Director of the Institute of Materials Research and Associate Dean for Research and Graduate Education. His expertise spans physical metallurgy , materials characterization , and microstructure engineering . Ph.D. in Mechanical Engineering, Yale University, 1991 M.S. in Mechanical Engineering, Brigham Young University, 1988 B.S. in Mechanical Engineering, University of Wyoming, 1987 Research focuses on metal deformation , recrystallization mechanisms , and advanced microscopy techniques , particularly addressing texture evolution and grain boundary engineering . Key article trends include computational modeling of microstructural heterogeneity, additive manufacturing of titanium, and thermomechanical processing of uranium-molybdenum alloys. Scientific recognitions include: 2024 Plenary Lecture at ICOTOM 20 2023 Fellow of ASM International 2015 MLK Distinguished Service Award 2011 Best Paper in Physical Sciences, Microscopy and Microanalysis Field has advised 15+ graduate researchers and led international collaborations at institutions like Universite de Lorraine and IISC Bangalore. His work integrates experimental and computational approaches to solve materials challenges in energy and manufacturing sectors.

Matthias BeckerView profile

Professor

• Human-Computer Interaction
• Simulation and Modeling
• Distributed Systems
• +6 more

Matthias Becker is a Professor at the Institute for Practical Computer Science within the Faculty of Electrical Engineering and Computer Science at Leibniz University Hannover, where he has been a core member of the Human-Computer Interaction group since 2019. He serves as Internship Coordinator for Computer Science and Computer Engineering and holds key roles in the Computer Science Examination Board and Selection Committee, actively shaping academic governance and student development. His academic journey began with PhD studies at the University of Bremen (1996-2000) supported by a DFG grant, followed by a postdoctoral permanent position at Leibniz University Hannover (2000-2019), an Associated Assistant Professor role at École des Mines de Nantes (2000), and a Habilitation in Computer Science in 2013. This foundation enabled his transition to a full professorship in 2019. Becker's research spans Human-Computer Interaction, Simulation and Modeling, and Bio-inspired Computing, with applications in agriculture, renewable energy, and manufacturing. His work integrates distributed systems, optimization algorithms, and wireless sensor networks to solve complex real-world problems, such as greenhouse monitoring, wind farm logistics, and tire noise reduction. Recent publications reveal a strategic focus on practical validation of simulation models and cross-domain applications of nature-inspired algorithms. His 15 most recent publications (2018-2024) demonstrate consistent innovation in applying simulation techniques to offshore wind farm installation, agricultural pest management, and sports science. These works emphasize real-world validation, collaborative problem-solving, and the development of domain-specific optimization frameworks that bridge theoretical algorithms and industrial implementation. As Internship Coordinator, Becker facilitates critical industry-academia connections for students, while his examination board responsibilities ensure rigorous academic standards. His leadership in the Human-Computer Interaction group drives research on interactive systems for agriculture, energy, and health, with particular emphasis on user-centered design in complex operational environments like wind farm logistics and greenhouse automation.

Yi Ting ChuaView profile

Research Fellow

• Cybercrime
• Online Criminal Behavior
• Social Network Analysis
• +5 more

Dr. Yi Ting Chua is a Research Fellow at the University of Cambridge's Department of Computer Science and Technology, affiliated with the Cambridge Cybercrime Centre. She holds a PhD in Criminal Justice from Michigan State University (2019), with prior collaborative work under Dr. T. Holt and Dr. O. Smirnova. Current research bridges computer science, criminology, and gender studies in cybercrime contexts Key methodological approach: Social network analysis of online communities Her article trends ( 2013-2020 ) show interdisciplinary focus on: Cybercrime market economics (price analysis, revenue estimation) Radicalization dynamics in far-right forums Gender roles in online criminal subcultures Framework development for unintended cybersecurity consequences Notable scientific contributions include: 2020 Best Paper (STAST) for cybersecurity framework research 2019 Best Paper (APWG eCrime) for unintended harms analysis Active in stakeholder engagement projects related to: Intimate partner abuse victim support Far-right forum monitoring Cybercrime dataset standardization

Tanushree RoyView profile

Assistant Professor

• Cybersecurity
• Fault diagnostics
• Socio-technical systems
• +4 more

Dr. Tanushree Roy serves as an Assistant Professor in the Department of Mechanical Engineering at Texas Tech University's Whitacre College of Engineering and is an Affiliate Faculty member at the National Wind Institute. Her research pioneers resilient human-centric smart city infrastructures through the integration of control theory, mathematical modeling, and machine learning to address critical challenges in safety, security, and resource optimization for urban systems. Her academic foundation includes: Ph.D. in Mechanical Engineering from The Pennsylvania State University (2022) M.S. in Mathematics from University of Central Florida (2015) M.E. in Electrical Engineering from Indian Institutes of Engineering Science and Technology, India (2011) B.Tech in Applied Electronics and Instrumentation from Maulana Abul Kalam Azad University of Technology, India (2009) Dr. Roy's research centers on cybersecurity , fault diagnostics , and socio-technical systems with specialized applications in smart transportation networks and battery energy storage systems. She develops innovative frameworks that merge human-centric sensing with technical measurements to combat cyberattacks and physical faults in cyber-physical-social systems, emphasizing safety-critical resilience for urban citizens. Her methodology uniquely combines model-based control with data-driven machine learning to address challenges like social data integrity, human behavior modeling, and multi-scale anomaly characterization. Analysis of her 15 most recent publications (2021-2025) reveals dominant trends in cyberattack detection for connected vehicles, thermal fault tolerance in battery systems, and socio-technical traffic modeling. Key technical approaches include Koopman operator theory for secure estimation, control barrier functions for safety certification, and redundancy-based data fusion techniques. These works consistently bridge theoretical control systems with practical smart city implementation, demonstrating strong interdisciplinary connections between transportation engineering, energy systems, and cybersecurity. No scientific awards are documented in the provided information. Dr. Roy actively mentors three PhD students—Sanchita Ghosh (since 2022), Faysal Ahamed, and Soumyoraj Mallick (both since 2024)—alongside undergraduate researcher Mercedes Hernandez. Her research is executed through the Smart Human-centric Automation Resilience (SHARE) Lab, which has secured projects including the secure autonomous mobility testbed and participates in workforce development via Texas Tech's Engineering Research Internship Experience (ERIE) program for high school students. The SHARE Lab operates at the intersection of transportation and energy systems, maintaining two primary research thrusts: resilient human-centric transportation networks and safeguarding battery energy storage infrastructure. Current projects include SUMO-based cyberattack validation for connected vehicle platoons, self-learning voltage estimation under sensor attacks, and thermal fault-tolerant battery management. The lab maintains active collaborations with national conferences (ACC, CCTA) and industry partners to advance real-world implementation of resilient smart city technologies.

• Mathematical Biology
• Disease Modeling
• Physiological Modeling
• +2 more

Erica Rutter is a faculty member in the Department of Applied Mathematics at the University of California, Merced, where she joined in July 2019. Prior to this position, she was a postdoctoral scholar at North Carolina State University. Dr. Rutter received her B.Sc. from the University of Michigan in 2009 in Applied Mathematics and Japanese. After her undergraduate studies, she worked for several years as a Research Technician at the Center for Radiative Shock Hydrodynamics in the Atmospheric Oceanic and Space Sciences Department at the University of Michigan. She then pursued her doctoral studies, obtaining a PhD in Applied Mathematics from Arizona State University in 2016. Her research interests span mathematical biology with a focus on disease modeling, physiological modeling, and ecotoxicology. She employs techniques from various mathematical disciplines, including machine learning, to address complex biological problems. Her work often involves developing mathematical models to understand biological processes and applying computational methods to analyze biological data. Dr. Rutter's publication record demonstrates an interdisciplinary approach across mathematical oncology, ecotoxicology, and biomedical image analysis. Her research shows a progression toward increasingly sophisticated methods for modeling biological systems, with emphasis on tumor heterogeneity, glioblastoma growth, and equation learning from limited biological data. She maintains an active research program at UC Merced, contributing to the academic community through her teaching and research mentorship in the Department of Applied Mathematics.

• Organizational Behavior
• Healthcare Management
• Technology Adoption
• +3 more

Leila Ahmadpour is a Postdoctoral Fellow at Luiss University and the University of Bologna, holding a PhD in Management from the University of Bologna. She serves as an Adjunct Professor in master's programs at Luiss University's Department of Business and Management, teaching courses on healthcare innovation and circular economy. Education: Postdoctoral Fellow (2023-present) at University of Bologna and Luiss University, Rome Visiting Scholar (2022-2023) at San Jose State University, California, USA PhD in Management (2017-2022) from University of Bologna, Italy M.Sc in Industrial Engineering, Supply Chain Management (2011-2013) from Islamic Azad University, Qazvin, Iran Her research spans two critical domains: surgical team dynamics with focus on technology integration (particularly 3D printing in orthopaedic workflows), and circular business model implementation in startups. She examines knowledge sharing, boundary blurring, and performance in temporary medical teams while investigating sustainable investor support for circular economy practices in entrepreneurial ventures. Her work bridges organizational theory with practical healthcare and sustainability challenges. Publication analysis reveals a methodological shift from early supply chain risk modeling (2015-2017) toward contemporary studies on surgical teams and circular business models (2022-2025). Recent work demonstrates strong emphasis on 3D printing technology adoption in healthcare settings and circular economy applications, utilizing case studies across surgical environments, construction industries, and Iranian manufacturing sectors. Dr. Ahmadpour has no documented scientific awards. Her academic contributions include teaching master's level courses and participating in research projects at Luiss University and the University of Bologna, though specific grant funding or student advising roles remain unreported. Her operational base is Luiss University's Department of Business and Management, where she applies interdisciplinary approaches to organizational innovation.

• Machine Learning
• Deep Learning
• Predictive Maintenance
• +3 more

Peyman Mashhadi is a Senior Lecturer at the School of Information Technology , Halmstad University. His research focuses on machine learning applications in predictive maintenance, automotive systems, and computational optimization. Position: Senior Lecturer University: Halmstad University Email: peyman.mashhadi@hh.se His work spans machine learning , deep learning , and predictive maintenance , with a particular emphasis on feature selection , optimization algorithms , and automotive diagnostics . He has contributed to multitask learning, domain adaptation, and industrial applications of neural networks. Recent publications highlight trends in automotive engineering (battery health estimation, turbocharger diagnostics), computational methods (genetic algorithms, metaheuristics), and machine learning (stochastic optimization, transfer learning). Key themes include robustness in predictive models and cross-domain adaptability. Contact details: peyman.mashhadi@hh.se

• Networked Epidemic Modeling
• Control Theory
• Machine Learning
• +4 more

Philip E. Paré is the Rita Lane and Norma Fries Assistant Professor of Electrical and Computer Engineering at Purdue University's College of Engineering. His research focuses on networked epidemic modeling, control theory, and data-driven systems analysis, with applications to public health and product demand dynamics. Research Areas: Networked Epidemic Modeling, Control Theory, Machine Learning, Privacy in Cyber-Physical Systems Recent work explores multi-virus spread, differential privacy in epidemic models, and optimal curing strategies. A 2023 NSF CAREER Award recipient, he develops frameworks for counterfactual analysis and feedback control in societal-scale challenges. Scientific Awards: NSF CAREER Award (2023)