Marilyn J Smith is the David S. Lewis Professor and Director of the Vertical Lift Research Center of Excellence (VLRCOE) at the Georgia Institute of Technology's Daniel Guggenheim School of Aerospace Engineering. She leads a seven-university consortium conducting vertical lift research for the U.S. Army, Navy, and NASA, and has secured over $200 million in collaborative research funding. Computational Nonlinear Computational Aeroelasticity Lab Director NASA FUN3D development team contributor Aerospace Systems Design Lab (ASDL) affiliate Her research spans unsteady aerodynamics, computational aeroelasticity, and sustainable energy applications across rotary-wing, fixed-wing, and launch vehicles. She serves on the Vertical Lift Consortium (VLC) Board of Directors and Vertical Flight Society (VFS) Board, while acting as VFS Deputy Technical Director for Aeromechanics and leading international NATO AVT panels on UAV aerodynamics. Recent publications focus on galaxy cluster cosmology, ship-helicopter dynamic interface modeling, and Type Ia supernova analysis. She has won prestigious awards including the AIAA Aerodynamics Award and multiple American Helicopter Society honors for research, mentoring, and service. 2022 AIAA Aerodynamics Award 2015 Best Paper Awards at AHS Forum 2014 & 2012 AHS Agusta-Westland International Fellowships Her laboratory work integrates high-performance computing with aerospace design and develops advanced turbulence models through partnerships with Georgia Tech Research Institute (GTRI). She contributes to public science communication with appearances on National Geographic, PBS, NPR, and local media.
جستجوی استاد راهنمای دانشگاهی
برای مسیر پژوهشیتان، استاد راهنما، استاد دانشگاه و پژوهشگر مناسب را پیدا کنید و با آنها ارتباط بگیرید.
نمایش ۱-۱۵ از ۳۵۲ استاد راهنما
اطلاعات پروفایلها از صفحات عمومی دانشگاهها گرفته شده و ممکن است بهروز نباشد.
Jay Hendersonمشاهده پروفایل
استادیار
Jay Henderson is an Assistant Professor in the Department of Computer Science at Memorial University of Newfoundland, leading the Human-Computer Interaction (HCI) Lab. His research focuses on quantitative HCI, measuring human performance with emerging technologies such as mixed reality and generative AI. He holds a PhD from the University of Waterloo and has held roles including Postdoctoral Fellow at Carleton University and Senior Research Scientist at Huawei Technologies Canada. Education: PhD in Computer Science, University of Waterloo (2021) BSc Hons in Computer Science (minors in Mathematics and Psychology), Mount Allison University (2016) Research Interests: Henderson’s work bridges computer science with psychology and mathematics, emphasizing objective measurement of user interactions. Key areas include mixed reality productivity, generative AI interfaces, gesture-based input, and multimodal feedback systems. His quantitative approach ensures practical insights for technology design. Key Grants & Awards: NSERC Discovery Grant ($155,000 over 5 years) NSERC Discovery Launch Supplement ($12,500) David R. Cheriton Graduate Scholarship ($20,000 over 2 years) Teaching & Supervision: Teaches courses like COMP 4303 (AI for Games) and supervises multiple graduate and undergraduate researchers. Notable supervisees include Daniel Jo (MSc) and Arunav Saha (BSc Honours). Service Contributions: Served on ACM committees including Graphics Interface and CHI Late Breaking Work. Acted as Virtual Chair for ACM ASSETS 2024 and contributed to ACM’s name change policy as a transgender advocate.
Mohammad Mohammadi Amiri serves as an Assistant Professor in the Department of Computer Science at Rensselaer Polytechnic Institute (RPI), appointed in Fall 2023. His research focuses on advancing artificial intelligence through strategic data utilization, with emphasis on large language models, data valuation, federated learning, and deep learning. Previously, he held postdoctoral appointments at Princeton University and MIT Media Lab, building on his strong educational foundation from Imperial College London, University of Tehran, and Iran University of Science and Technology. Education: Ph.D. in Electrical and Electronic Engineering, Imperial College London (2019) - Best Ph.D. Thesis Award recipient M.Sc. in Electrical and Computer Engineering, University of Tehran (2014) - Ranked 1st among all M.Sc. students B.Sc. in Electrical Engineering, Iran University of Science and Technology (2011) - Ranked 1st among all B.Sc. students Dr. Amiri's research centers on optimizing artificial intelligence systems through innovative data strategies. His work addresses critical challenges in large language models including efficiency, memory usage, alignment, and reasoning capabilities. In data valuation, he develops principled methods to quantify data worth for fair trading platforms. His federated learning research tackles privacy concerns, heterogeneous data distribution, and communication overhead in decentralized environments. The deep learning component explores theoretical foundations to improve model interpretability and robustness. Analysis of his recent publications reveals a strong focus on making AI systems more efficient and accessible, with particular emphasis on large language model optimization, federated learning advancements, and data valuation frameworks. His work bridges theoretical foundations with practical applications in wireless communications and distributed computing environments. Scientific Awards: IEEE Communications Society Young Author Best Paper Award (2022) Best PhD Thesis Award from IEEE Information Theory Chapter of UK and Ireland (2019) Eryl Cadwallader Davies Prize for Outstanding PhD Thesis (2019) EEE Departmental Scholarship at Imperial College London (2015-2019) Ranked 1st among M.Sc. students at University of Tehran (2014) Ranked 1st among B.Sc. students at Iran University of Science and Technology (2011) Dr. Amiri actively mentors graduate students, currently supervising five Ph.D. candidates and one M.Sc. student working on efficient LLM fine-tuning, inference, and storage. His research has attracted significant attention, evidenced by numerous keynote invitations at prestigious institutions including Bell Labs, MIT, King's College London, and various IEEE conferences. He serves on program committees for major conferences including IEEE Globecom and ICC, demonstrating his growing influence in the academic community. His research group operates at the intersection of machine learning and wireless communications, developing innovative solutions for resource-constrained environments while addressing fundamental theoretical challenges in AI systems. Current projects focus on making advanced AI more scalable and accessible through efficiency improvements in model training and inference.
Daniel Varonمشاهده پروفایل
استادیار
Daniel Varon is the Boeing Assistant Professor in Aeronautics and Astronautics at MIT, joining in July 2025. He is also affiliated with the MIT Institute for Data, Systems, and Society (IDSS). His research focuses on atmospheric composition, satellite remote sensing of greenhouse gases, and air pollution. Varon holds a PhD in Atmospheric Chemistry from Harvard University (2020), an MSc in Applied Mathematics, and dual undergraduate degrees in English Literature and Physics from McGill University. He has held postdoctoral roles at Harvard and Princeton University. His work uses satellite data to quantify methane and nitrogen oxide emissions, with applications in climate policy and environmental monitoring. Notable contributions include developing methods for detecting methane super-emitters via hyperspectral satellites and quantifying emissions from oil/gas fields. Varon has received over 3,000 citations and an h-index of 24 as of 2025, with extensive media coverage for his Nord Stream pipeline leak analysis. Varon has secured grants totaling $785K, including NOAA funding for geostationary satellite methane monitoring. He mentors postdocs and graduate students in satellite data analysis and machine learning applications. His teaching includes Harvard’s Atmospheric Chemistry course, where he received the Harvard Certificate of Distinction in Teaching. Varon serves as an Associate Editor for Atmospheric Measurement Techniques and contributes to initiatives like the Methane Emissions Detection Using Satellites Assessment (MEDUSA) Advisory Board. His lab focuses on integrating machine learning with satellite data to advance climate science.
Lily Hsuehمشاهده پروفایل
دانشیار
Lily Hsueh is an Associate Professor of Economics and Public Policy (with tenure) at the School of Public Affairs, Arizona State University (ASU), and a Visiting Scholar at the Woods Institute for the Environment, Stanford University. She is affiliated with multiple research centers, including the Julie Ann Wrigley Global Futures Laboratory, the Center for Environmental Economics and Sustainability Policy, the Center for Organization Research and Design, and the Political Economy Working Group at ASU. She earned her Ph.D. in Public Policy and Management from the University of Washington, an M.S. in Economics from University College London, and a B.A. in Economics from the University of California, Berkeley. Prior to her academic career, she worked as a Senior Analyst at the Federal Reserve Bank of San Francisco. Dr. Hsueh’s research focuses on the intersection of economics, politics, and governance in environmental policy. She investigates how alternative governance systems—such as voluntary programs and market-based mechanisms—affect policy outcomes in areas like climate change, toxic chemicals, and marine resources. Her work emphasizes the role of firms, institutions, and governments in shaping environmental governance and social equity. Her recent publications explore trends in corporate climate disclosure, sustainable public procurement, participatory budgeting, and the health impacts of environmental disasters. These studies employ rigorous econometric methods and contribute to both academic and policy debates on sustainability and governance. Recipient of the 2020–21 AAUW American Fellowship Two-time winner of the Distinguished Teaching Award at ASU (2016–17, 2021–22) Recipient of the 2023 Professor of Impact award (student-initiated) Elected to the APPAM Policy Council (2024–2028) Editorial board member of PLOS Climate Dr. Hsueh has secured research funding from NOAA, the V. Kann Rasmussen Foundation, and ASU. She actively mentors students and junior scholars and is currently completing a book with MIT Press titled Corporations at Climate Crossroads . She also leads curriculum development in economics and public policy at ASU and teaches across undergraduate, master’s, and Ph.D. levels. She is involved in several research teams and initiatives, including the Political Economy Working Group and the Sustainable Procurement Research Group at ASU, and collaborates with interdisciplinary teams at Stanford on climate governance research.
Gregory C. Gray, MD, MPH, FIDSA is a Professor in Infectious Disease Epidemiology at the University of Texas Medical Branch (UTMB) in Galveston, Texas, with appointments across multiple departments including Internal Medicine (Infectious Diseases), Microbiology & Immunology, and Global Health & Emerging Diseases. Dr. Gray has conducted epidemiological studies of infectious diseases for over 25 years across five continents, with a particular focus on occupational disease transmission, especially respiratory viruses. His research has examined farmers, veterinarians, turkey workers, swine workers, poultry workers, horse workers, cattle workers, hunters, and military personnel. He pioneered the Millennium Cohort Study, a prospective cohort study of approximately 300,000 people projected to continue through 2068, and has led numerous large-scale vaccine trials. As a strong advocate for the One Health approach, Dr. Gray has established One Health centers in the USA, Romania, and China, and developed four graduate programs in One Health (PhD, MHS, and certificates). His recent research focuses on zoonotic spillover events, universal influenza vaccines, and coronavirus detection in agricultural settings, with numerous publications in 2024-2025 addressing H5N1 avian influenza, respiratory virus transmission, and environmental health impacts. Selected honors include: Department of Defense Legion of Merit Medal Secretary of Defense Medal for Outstanding Public Service Medal of Honor from Mongolia's Minister of Health The Peace Medal awarded by the President of Mongolia University of Texas Medical Branch Robert E. Shope, MD Professorship Dr. Gray has authored over 350 peer-reviewed manuscripts cited more than 21,000 times (H-index 76). His current research portfolio includes multiple active grants from the USDA, Fogarty International Center, and private industry focusing on zoonotic disease surveillance, influenza vaccines, and coronavirus detection in agricultural settings. He has mentored numerous students and established international collaborations across six continents.
Professor Jia Chen is a Professor of Environmental Sensing and Modeling at the Technical University of Munich (TUM), holding positions in both the TUM School of Computation, Information and Technology (CIT) and the Department of Electrical and Computer Engineering, as well as the Department of Civil, Geo and Environmental Engineering. She also maintains an affiliation as an Associate at Harvard University. Her pioneering work focuses on developing novel optical sensors and atmospheric models to monitor and quantify greenhouse gas emissions in urban environments. Professor Chen's most significant contribution is the development of the differential column measurement method and the establishment of MUCCnet, the world's first permanent urban column sensor network. This groundbreaking work enables continuous, city-wide monitoring of greenhouse gases. Her research team has made notable discoveries, including quantifying methane emissions from events like the Munich Oktoberfest and identifying previously underestimated urban emission sources. Her research spans atmospheric science, environmental engineering, and climate change mitigation, with particular emphasis on: Urban greenhouse gas monitoring systems Advanced atmospheric modeling techniques Sensor network development for environmental monitoring Integration of machine learning with emission quantification Urban air quality assessment methodologies Professor Chen has received numerous prestigious awards including: Timothy Oke Award (2024) for original research in urban climatology ERC Consolidator Grant (2022) Arnold Sommerfeld-Award (2021) Germany's "Top 40 under 40" recognition by Capital Magazine (2020) Membership in the Global Young Academy (2021) She leads an extensive research group with numerous PhD students and postdoctoral researchers, and her work is supported by major funding from ERC, EU Horizon 2020, United Nations Environment Programme, NASA, ESA, German Federal Ministry of Education and Research, and German Research Foundation. Professor Chen has authored over 180 publications and 12 patents, with an h-index of 35.
Ugur Turhanمشاهده پروفایل
مدرس ارشد
Dr. Ugur Turhan is a Senior Lecturer in aviation at UNSW Canberra with over two decades of experience in academic and professional settings. His expertise spans Air Traffic Management, Airport Operations, Aviation Safety, and Human Factors in Aviation. Previously, he served as Assistant Professor at Eskisehir Technical University and Anadolu University, and held a visiting professorship at Embry Riddle Aviation Academy. Dr. Turhan earned his Ph.D. in Civil Aviation Management from Anadolu University. His academic journey includes significant contributions to aviation education and research across multiple institutions in Turkey and internationally. Dr. Turhan's research focuses on critical aspects of aviation safety and efficiency. His work explores human factors in air traffic control, aircraft maintenance procedures, and emergency management in aviation contexts. He has developed innovative approaches to training air traffic controllers using 3D simulation technology and has investigated the relationship between safety culture and operational performance in aviation organizations. His research bridges theoretical frameworks with practical applications to enhance aviation safety standards globally. Analysis of Dr. Turhan's recent publications reveals a strong emphasis on human factors across aviation domains. His work consistently addresses safety management systems, cognitive workload assessment, and maintenance procedures. A notable trend is the integration of neurophysiological measurements with operational data to assess air traffic controller performance. His research also demonstrates growing interest in the application of advanced technologies for improving maintenance documentation and technician performance. Dr. Turhan has secured significant research funding through multiple international projects. His leadership roles include: Researcher and Eskisehir Technical University Coordinator for the FACT project under European Commission HORIZON2020 SESAR call (2020-present) Researcher and Eskisehir Technical University Coordinator for the Skill-UP project under Erasmus+ (2020-present) Researcher and Anadolu University Coordinator for the STRESS Project under HORIZON 2020-SESAR-2015-1 (2016-2018) Researcher and Anadolu University Coordinator for the IMPACT Project under HORIZON 2020-DRS-2014 (2015-2018) Researcher and Anadolu University Coordinator for SECONOMICS project under European Commission FP7 (2012-2015) Researcher for Boeing-sponsored International Project on Aviation Educational Software (2014-2016) Dr. Turhan has supervised multiple doctoral and master's students in aviation-related fields. His doctoral students include Birsen Acikel (2016) who researched flight training airspace complexity and Tarık Güneş (2021) who assessed aircraft maintenance technician competency. His master's students have investigated topics ranging from Turkish airspace flexibility to aircraft maintenance documentation. Dr. Turhan also serves as a valuable resource for prospective PhD students interested in human factors and safety in aviation and air traffic management.
Marianna Ivashina is a Professor and Head of the Antenna Systems Research Group at Chalmers University of Technology's Department of Electrical Engineering . Her work focuses on array antennas , antenna integration with electronics , optimal beamforming , and over-the-air measurement methods . The group has achieved international recognition for innovations in ultra-wideband (UWB) feeds , Gap waveguide antennas , and Doherty-power-amplifier-integrated antennas for 5G/6G and radio telescope applications. Key projects include the SSF Sweden-Taiwan collaboration , EU Horizon 2020 MyWave , and VINNOVA ENERGETIC initiatives. Her recent publications emphasize millimeter-wave (mmWave) communication and reconfigurable intelligent surfaces (RIS) , with applications in 5G/6G networks , satellite communication (SatCom) , and advanced antenna testing chambers . She explores beamforming optimization , self-interference mitigation , and hybrid OTA environments to enhance wireless system performance. The group's work bridges theoretical advancements with practical implementations, including RFSoC testbeds and high-efficiency antenna arrays . Marianna leads major research programs funded by Ericsson , VINNOVA , and EUREKA EURIPIDES2 , addressing challenges in beamforming , antenna-IC integration , and automated design for 5G/6G . These projects highlight her role in advancing millimeter-wave communication and sensor integration technologies.
Helen Suh is a Professor at Tufts University, jointly appointed in the departments of Civil and Environmental Engineering and Community Health . As an internationally-recognized expert in air pollution health effects, she combines environmental epidemiology , exposure science , and data analytics to investigate how pollutants impact human health. Sc.D. , Harvard University (1993) M.S. , Harvard University (1990) S.B. , Massachusetts Institute of Technology (1985) Her research focuses on three areas: air pollutant impacts on cognitive performance and child development , multi-pollutant health effects , and GIS-based spatio-temporal modeling for epidemiological studies. Recent publications highlight her work on PM2.5 measurement error correction , hormonal disruptions in pregnancy , and machine learning applications in environmental health analysis. Current trends include: Advanced statistical methods for exposure assessment Multi-omics approaches to cardiometabolic health International comparative studies (e.g., Tehran, Puerto Rico) Long-term mortality analysis in Medicare populations Pollution-immune system interactions in vulnerable groups Policy-relevant modeling for air quality standards Helen Suh has served as an Associate Editor for the Journal of Exposure Science and Environmental Epidemiology and advised major U.S. and international health organizations. Her work spans over 150 publications and integrates multidisciplinary team leadership in environmental health science. Her laboratory develops large-scale data analytics tools and spatio-temporal exposure models to support population-level health research. Current projects include air pollution and aging cohorts , urban environmental noise measurement , and epigenetic responses to pollutants .
Wing Ng serves as Alumni Distinguished Professor and Chris C. Kraft Endowed Professor in Virginia Tech's Department of Mechanical Engineering within the College of Engineering. His career spans over four decades with continuous contributions to aerospace thermal systems and fluid dynamics research since joining Virginia Tech in 1984. Dr. Ng's academic foundation includes: Ph.D. in Mechanical Engineering from Massachusetts Institute of Technology (1984) M.S. in Mechanical Engineering from Massachusetts Institute of Technology (1980) B.S. in Mechanical Engineering from Northeastern University (1979) His pioneering research focuses on aeroacoustics of drones and jet engines, where he develops advanced diagnostics for turbine flow measurements and investigates transonic turbine blade aerodynamics. Current work explores aerothermal particle interactions in gas turbines and clean energy applications for wind turbines. His experimental approach bridges fundamental fluid dynamics with practical aerospace engineering solutions, particularly in cooling systems for high-temperature components. Analysis of recent publications (2024-2025) reveals three dominant research thrusts: turbine cooling optimization (film/phantom cooling configurations), particle dynamics in gas paths (impact/rebound mechanics), and novel measurement techniques (strain sensors, multiphase flow diagnostics). These studies consistently target performance enhancement and durability improvement in turbomachinery through experimental validation. Dr. Ng's exceptional contributions are recognized through: Virginia Tech Faculty Entrepreneur Hall of Fame (2017) William E. Wine Award for teaching excellence (2014) Multiple Certificates of Teaching Excellence (1985,1988,2011,2014) Dean's Award for Research Excellence (2013) Consecutive Best Paper Awards from ASME/AIAA (2001-2013) Fellow of ASME (1996) and Associate Fellow of AIAA (1992) As director of the Ng Lab, he maintains active collaborations with industry partners through Techsburg, Inc. (where he serves as Chairman) to translate research into commercial applications. His work on drone aeroacoustics and turbine diagnostics directly informs next-generation propulsion systems while addressing critical challenges in particle ingestion and thermal management.
- Aeroacoustics
- Turbomachinery
- Heat Transfer
- +۶ مورد دیگر
Markku Karjalainen is a Professor in the Department of Architecture at Tampere University's Faculty of Built Environment. With over 80 research publications spanning from 2016 to 2025, he has established himself as a leading expert in timber construction and wooden building systems in Finland. Professor Karjalainen's research primarily focuses on timber construction , particularly multi-story wooden buildings, dovetail wood construction techniques, and sustainable building practices. His work spans architectural design, structural engineering, fire safety, and environmental impact assessment of wooden structures. He has conducted extensive statistical analyses of Finnish timber residential buildings, examining construction practices from 1995 to the present. His research demonstrates a strong commitment to advancing wooden construction technologies while addressing practical challenges in fire safety, structural performance, and building physics. Analysis of his recent publications (2023-2025) reveals a consistent focus on dovetail construction techniques for mass timber elements, with numerous studies examining structural performance, fire properties, and air permeance. His work bridges theoretical research with practical applications in the construction industry, particularly in Finland where wooden multi-story construction has seen significant growth. Karjalainen's research often involves international collaboration, with studies comparing practices across different countries and examining global perspectives on timber construction. His scholarly output demonstrates a methodical progression from basic statistical analysis of building practices to increasingly sophisticated investigations of specific construction techniques and their performance characteristics. This evolution reflects both his growing expertise and the maturation of timber construction as a field of academic inquiry.
Ken Ferensمشاهده پروفایل
استادیار
Dr. Ken Ferens is an Assistant Professor in the Department of Electrical and Computer Engineering at the Price Faculty of Engineering, University of Manitoba. He serves as the Computer Engineering Champion in the Centre for Engineering Professional Practice and Engineering Education and directs the Applied Cognitive Intelligence (ACI) Research Group. Dr. Ferens is a senior member of the Institute of Electrical & Electronics Engineers (IEEE), Chair of the EduManCom Chapter of the IEEE, Vice-Chair of the Computer and Computational Intelligence Chapter of the IEEE, and Chair of the Industry, Teaching Assistants, and Student Forums for Engineering Curriculum Review and Improvement. Ph.D. (Computer Engineering), University of Manitoba, 1996 M.Sc. (Computer Engineering), University of Manitoba, 1991 B.Sc. (Electrical Engineering), University of Manitoba, 1989 Dr. Ferens has over 33 years of research experience in computational intelligence, focusing on cognitive machine learning, artificial intelligence, cognitive computational intelligence, chaos theory applications, agent-based models, and various optimization algorithms including simulated annealing, genetic algorithms, artificial neural networks, and particle swarm optimization. His research applies these techniques to develop software and hardware intrusion detection systems for cybersecurity applications. He teaches graduate-level courses on Computer Network Security and Applied Computational Intelligence, providing students with theoretical background and hands-on experience in state-of-the-art security methods. Analysis of Dr. Ferens' recent publications reveals a strong focus on applying cognitive and chaotic computational techniques to cybersecurity challenges, particularly malware detection and network intrusion detection. His work increasingly integrates complexity theory, fractal analysis, and hybrid optimization approaches to enhance security systems' effectiveness. There's a clear progression toward more sophisticated machine learning architectures applied to increasingly complex security scenarios, with growing emphasis on real-world IoT and network security applications. Best Paper Award at IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC 2022) Best Paper Award at IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC 2015) Best Journal Paper Award for 2013 (Journal of ICT Research and Applications) Best Poster Award at 12th International Conference on e-Health Networking, Application & Services (2010) Best Paper Award at IASTED International Conference on Computer, Electronics, Control, and Communication (1991) Dr. Ferens collaborates with national and international industry partners including the Department of Advanced Information Management, Content Technology Canadian Tire Corporation (CTC), and Magellan Aerospace. His research group has received funding supporting the Cyber-security Research Program, developing practical applications of computational intelligence for security systems. He has supervised numerous graduate students in the Electrical and Computer Engineering department, focusing on research at the intersection of machine learning and cybersecurity. Dr. Ferens leads the Applied Cognitive Intelligence (ACI) Research Group within the Department of Electrical and Computer Engineering, which focuses on applying cognitive, chaotic, and computationally intelligent algorithms to build intrusion detection systems. The group collaborates with industry partners to develop practical security solutions while providing students with hands-on research experience in cutting-edge security technologies. Their work spans both theoretical algorithm development and practical hardware implementation for real-world security applications.
Nicholas A Smithمشاهده پروفایل
استادیار
Dr. Nicholas A Smith is an Assistant Professor of Psychology at The University of Texas at Arlington, specializing in Industrial-Organizational Psychology and Workplace Diversity. He holds a PhD in Applied Psychology from Portland State University (2019), an MS in I/O Psychology from the University of Central Florida (2014), and a BS in Psychology from the same institution (2012). His research focuses on workplace diversity, mental health equity, and labor rights, with recent projects examining the impact of overtime legislation on Latinx agricultural workers and stigma reduction in service industries. He has secured grants totaling over $1.2 million, including a 2024 EPA grant for air quality advocacy in underserved communities and a Robert Wood Johnson Foundation-funded study on labor rights. Dr. Smith serves on editorial boards for Applied Psychology: An International Review and reviews for the Society for Industrial and Organizational Psychology. His teaching includes courses on Business Psychology and Research Methods. He actively engages in international collaborations, presenting at conferences in France, Spain, and Lithuania, and advocates for inclusive workplace policies through community-engaged research. His scholarly contributions span over 20 peer-reviewed articles, addressing topics from allyship strategies to stereotype content intersections. Despite no explicitly listed awards, his impactful grant-funded work reflects recognition of his research contributions.
Kamal Al Haddad is a Lecturer in the Department of Electrical Engineering at École de technologie supérieure (ÉTS). He holds a Doctorate from INTP, Toulouse, and advanced degrees from UQTR. His research focuses on power electronics, renewable energy integration, and smart grid technologies. He leads the GREPCI research group, specializing in Power Electronics and Industrial Control. Education: B.Eng., M.Sc.A. (UQTR), Doctorate (INTP, Toulouse). Research interests span energy conversion, industrial electronics, power quality, and electromagnetic interference. He emphasizes sustainable energy solutions, electric traction systems, and high-efficiency power sources. His work includes developing advanced power electronic converters and grid stability solutions. Recent articles highlight advancements in modular converters for STATCOM, AI-driven fault detection in hydrogenerators, and renewable energy policy frameworks. He has received notable awards, including the 2014 IEEE Eugene Mittelmann Prize and Fellowships from IEEE and other institutions. Supervised over 60 students, including doctoral theses on topics like hydrogenerator diagnostics, EV charging systems, and renewable energy integration. His research also involves real-time simulation of power systems and FPGA-based implementations. Labs/Teams: GREPCI – Power Electronics and Industrial Control Research Group, leading projects on smart grids and energy efficiency.