جستجوی استاد راهنمای دانشگاهی

Mizuki Mazzottaمشاهده پروفایل

استاد آموزشی

• Second Language Acquisition
• Applied Linguistics
• Language Pedagogy
• +۳ مورد دیگر

Mizuki Mazzotta is an Assistant Teaching Professor in the Department of Russian and East Asian Languages and Cultures at Emory University, where she also serves as Japanese Language Coordinator. Her academic journey includes a Ph.D. in Applied Linguistics from Georgia State University (2018) and M.A. degrees in Linguistics (McGill University) and Applied Linguistics (University of South Florida). Her research focuses on instructed second language acquisition, particularly the role of affect and sociocultural theory in L2 learning. She has extensive experience teaching Japanese language courses and mentoring students at Emory and previous institutions like Georgia State University. Education: Ph.D., Applied Linguistics, Georgia State University (2018) M.A., Linguistics, McGill University (2005) M.A., Applied Linguistics, University of South Florida (1997) B.A., English Literature, Soka University (1995) Research Interests: Instructed Second Language Acquisition Corrective Feedback in L2 Writing Sociocultural Theory in Language Education Learner Affect and Motivation Technology-Enhanced Language Learning Cultural Awareness in Language Instruction Awards & Grants: Recipient of multiple grants including the KAKENHI Grant (Japan), Mellon Humanities Pathways Grant, and Emory College Pedagogy Mini-Grant. Member of honor societies: Phi Beta Delta and Golden Key International. Service & Leadership: Executive Committee Member, Emory College Language Center Organizer of Japanese Program Guest Speaker Talks and Cultural Events Reviewer for Language Teaching Research and other academic journals Interviewer for the Japan Exchange Teaching Program Teaching & Mentorship: Instructor of Japanese language courses at Emory and Georgia State University Developer of study abroad programs in Japan and internship collaborations Mentor for Japanese interns and temporary faculty

• Wireless Communications
• Reconfigurable Intelligent Surfaces
• Physical Layer Security
• +۷ مورد دیگر

Dr. Sylvester Boadi Aboagye is an Assistant Professor in the School of Engineering at the University of Guelph, Canada. His research focuses on next-generation wireless communication and sensing systems, including reconfigurable intelligent surfaces (RIS), physical layer security, visible light communication (VLC), terahertz networks, and integrated sensing-communication frameworks. He received his Ph.D. and M.Eng. from Memorial University (Canada) and B.Sc. (Honors) from Kwame Nkrumah University of Science and Technology (Ghana). Prior to joining University of Guelph, he was a Postdoctoral Fellow at York University (2023). Dr. Aboagye's expertise includes machine learning for resource allocation, energy-efficient network design, and prototyping optical RIS systems. He currently serves as an Editor for IEEE Communications Letters and has received notable awards including the Governor General’s Gold Medal and recognition as an Exemplary Reviewer. His work addresses challenges in 6G systems, underwater communications, and sustainable network architectures.

Sujan Kumar Royمشاهده پروفایل

دانشگاهی

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۶ مورد دیگر

Sujan Kumar Roy is an Assistant Teaching Professor in the Department of Computer Science at Michigan Technological University. He holds a Ph.D. in Machine Learning with Computer Engineering and Signal Processing from Griffith University, Australia, and has earned multiple academic distinctions, including the 'Award of Excellence in the Research Thesis' and consideration for the 'Chancellor's Medal for Excellence in Ph.D. Thesis 2021.' Dr. Roy's teaching focuses on Computational Intelligence, Foundations of Data Science, Machine Learning, Data Mining, and Introduction to Data Science. His research explores applications of AI, ML, and Data Science in Cybersecurity, Medical Image Analysis, Healthcare Systems, and Speech Enhancement. He has contributed extensively to speech enhancement techniques, integrating Kalman filters with machine learning and deep learning approaches. Recent research trends in his publications emphasize the development of robust algorithms for speech enhancement in noisy environments, fusion datasets for hate speech detection, and adaptive filtering methods. His work bridges signal processing and AI, aiming to improve real-time system performance and noise robustness. Awards: Award of Excellence in the Research Thesis Consideration for Chancellor's Medal for Excellence in Ph.D. Thesis 2021 In teaching, Dr. Roy emphasizes foundational concepts and their practical applications. His grants and collaborations focus on advancing AI-driven solutions for healthcare and cybersecurity challenges. He is affiliated with the Department of Computer Science at Michigan Tech, contributing to both academic and research missions.

John J. Curtinمشاهده پروفایل

استاد

• Digital therapeutics
• Machine learning applications in mental health
• Addiction research
• +۵ مورد دیگر

John J. Curtin is a Professor in the Department of Psychology at the University of Wisconsin-Madison, where he directs the Addiction Research Center. His work bridges clinical psychology, computer science, and engineering to develop innovative digital solutions for mental health and addiction treatment. Dr. Curtin's research focuses on digital therapeutics and personal sensing technologies for substance use disorders and mental illness. His laboratory develops software applications that provide evidence-based interventions, treatment management tools, and enhanced communication with care providers. He specializes in algorithm development for moment-to-moment psychiatric risk prediction and just-in-time personalized interventions that adapt to both patient characteristics and their current context. His research program is highly interdisciplinary, collaborating with the Center for Health Enhancement Systems Studies, computer science, geography, and electrical and computer engineering departments. Dr. Curtin's work combines machine learning approaches with novel data streams from geolocation, cellular communications, social media activity, and wearable biosensors to create more effective and personalized treatment approaches. Dr. Curtin has secured continuous funding from the National Institutes of Health (NIAAA, NIDA, NCI and NIMH) since 1998. His current research examines machine learning-assisted precision medicine for smoking cessation, contextualized daily prediction of lapse risk in opioid use disorder, and dynamic real-time prediction of alcohol use lapse using mobile health technologies. His laboratory has produced numerous publications advancing the field of digital mental health interventions, with a particular focus on using technology to deliver precisely tailored treatments at the right moment for individuals struggling with substance use disorders.

Jordan Kidneyمشاهده پروفایل

مدرس

• Artificial Intelligence
• Machine Learning
• Multi-Agent Systems
• +۳ مورد دیگر

Jordan Kidney is a Lecturer in the Department of Mathematics & Computing at Mount Royal University (MRU), where he has taught since 2011. His academic background includes a B.Sc. and M.Sc. in Computer Science from the University of Calgary (2003 and 2006, respectively). Kidney’s teaching focuses on introductory and advanced programming, systems architecture, operating systems, and web development. His research interests span Artificial Intelligence, particularly machine learning and multi-agent systems. He is recognized for contributions to educational methodologies in computer science and the development of tools like the ARES Simulator for multi-agent systems research. Education: M.Sc. Computer Science, University of Calgary (2006) B.Sc. Computer Science, University of Calgary (2003) Research Interests: Kidney’s work emphasizes AI applications, including machine learning algorithms and multi-agent systems. He explores emergent behavior testing, cooperative behavior learning, and educational frameworks for complex topics like MAS. His research often intersects with practical tools, such as the ARES Simulator, which he has refined to enhance teaching and testing methodologies. Articles Trends: His publications highlight two key areas: computer science education for non-majors and multi-agent systems research. Recent work (2018) addresses course design challenges for interdisciplinary students, while earlier contributions (2002–2006) focus on ARES-based testing and cooperative behavior analysis in MAS. His earlier studies (2003) also explored genetic algorithms and diversity-driven optimization. Grants & Advising: No advising roles or grants are explicitly listed in the provided information.

Juan Alonsoمشاهده پروفایل

استاد

• Aerospace System Design
• Computational Fluid Dynamics
• Multi-Disciplinary Optimization
• +۷ مورد دیگر

Prof. Juan Alonso is the Vance D. and Arlene C. Coffman Professor and James & Anna Marie Spilker Chair in the Department of Aeronautics & Astronautics at Stanford University. He directs the Aerospace Design Laboratory (ADL), focusing on high-fidelity computational methods for aerospace system design. His expertise spans transonic/supersonic/hypersonic aircraft, rotorcraft, and launch vehicles. Alumni include record-holding teams for human-powered watercraft and lightweight unmanned aerial vehicles. Education: PhD (1997) from Princeton University in Mechanical & Aerospace Engineering; M.A. (1993) Princeton; B.S. (1991) MIT Aeronautics/Astronautics. Research emphasizes multi-disciplinary optimization, numerical methods, and parallel computing applied to advanced aircraft design, sustainable aviation, and UAS systems. Notable contributions include computational design frameworks like SU2 and SUAVE, and initiatives in curriculum development for engineering education. Recent work focuses on: GPU-accelerated CFD solvers, multi-fidelity surrogate models (e.g., VortexNet), contrail simulation frameworks, and battery degradation modeling for electric aircraft. Active in urban air mobility and high-fidelity trajectory optimization for hypersonic systems. Labs/Teams: Aerospace Design Laboratory (ADL) leading open-source computational tools development. Involved in NASA-funded projects and industry partnerships for advanced propulsion systems.

Anastasios P. Vassilopoulosمشاهده پروفایل

استاد مدعو

• Composite Materials
• Offshore Renewables
• Wind Turbine Technology
• +۵ مورد دیگر

Anastasios P. Vassilopoulos is an Adjunct Professor and Head of the Composite Mechanics Group (GR-MEC) at the École Polytechnique Fédérale de Lausanne (EPFL) within the School of Architecture, Civil and Environmental Engineering (ENAC). He holds additional roles as Director of the Doctoral Program in Civil and Environmental Engineering (EDCE) and is affiliated with multiple research groups and committees at EPFL. His expertise spans composite materials, structural adhesives, and offshore renewable energy systems. Education: PhD in Mechanical Engineering, University of Patras, Greece (2001) Dipl. Mechanical Engineer, University of Patras, Greece (1995) Erasmus Exchange, University of Bristol, UK (1994–1995) Research Interests: Offshore renewables, particularly wind turbine blade materials and joints Fatigue analysis of composite materials and adhesive joints Experimental and analytical methods for composite structures Design of composite constructions and structural integrity His work emphasizes practical applications in engineering, including wind energy systems and fiber-reinforced polymer (FRP) composites. Teaching & Labs: Teaches courses on structural mechanics, advanced composites, and floating offshore renewables Leads the GR-MEC lab, focusing on composite mechanics and joint behavior Supervised over 15 PhD students at EPFL Grants & Projects: Swiss National Science Foundation-funded projects on bonded composite structures and wind turbine blade materials Research on fire-resistant composite bridge decks and lightning effects on composite structures

• Medical Imaging
• Artificial Intelligence
• Machine Learning
• +۷ مورد دیگر

Dr. Neal Bangerter is a Visiting Professor in the Department of Bioengineering at Imperial College London's Faculty of Engineering. He specializes in medical imaging (MRI), artificial intelligence, machine learning, and signal processing. Dr. Bangerter holds adjunct appointments at INSEAD, the University of Utah, and Brigham Young University. His research focuses on ultra-high field MRI, AI applications in healthcare, and data-driven bioscience technologies. He leads the London Collaborative Ultra-High Field Scanner (LOCUS) project and advises companies on AI and innovation strategies. Education: B.S. in Physics (UC Berkeley), M.S. and Ph.D. in Electrical Engineering (Stanford University). Career highlights include roles at McKinsey & Company, Microsoft, and Reactrix, as well as founding BYU's Medical Imaging Research Center. He has pioneered cross-faculty initiatives like the Crocker Innovation Fellowship Program. Research interests include novel MRI pulse sequences, AI in medical imaging, and large-scale health data analysis. His work spans collaborations with Stanford, Oxford, Cambridge, and Siemens Healthcare. He teaches executive education at INSEAD, focusing on bridging technical concepts with business strategies. Key awards include the David Evans Chair at Brigham Young University. His contributions to the UK Biobank Neuroimaging study and development of MRI techniques like RAFO-4 highlight his impact on advancing imaging technologies and AI applications in healthcare.

H. Jane Baeمشاهده پروفایل

استادیار

• Turbulence Modeling
• Computational Fluid Dynamics
• Fluid Mechanics
• +۳ مورد دیگر

H. Jane Bae is an Assistant Professor of Aerospace at the California Institute of Technology (Caltech), affiliated with the Division of Engineering and Applied Science. Her research focuses on turbulence modeling, particularly developing high-fidelity computational methods to simulate high-Reynolds-number flows for applications in aircraft design, wind farms, and atmospheric predictions. She integrates machine learning, information theory, and numerical techniques to enhance turbulence modeling efficiency. Education: B.S. in Aerospace Engineering from Caltech (2011), Ph.D. in Mechanical Engineering from Stanford University (2018). She joined Caltech in 2021. Research interests include near-wall turbulence dynamics, resolvent analysis, sparse identification of nonlinear dynamics, and reinforcement learning for wall models in LES. Her work addresses computational cost reduction and model accuracy in complex flow simulations. Awards: 2023 Outstanding Referee Award from Physical Review. Teaching includes courses on fluid mechanics (Ae/APh/CE/ME 101 abc) and turbulence (Ae 239 ab). Her lab combines turbulence theory, high-performance computing, and data-driven methods to study unsteady flows over complex surfaces. Notable contributions include machine learning-based wall models and resolvent analysis frameworks for non-stationary flows.

Henrik von Colerمشاهده پروفایل

استادیار

• Music Technology
• Spatial Audio Systems
• Live Electronics
• +۳ مورد دیگر

Henrik von Coler is an Assistant Professor at Georgia Institute of Technology's School of Music within the College of Design. His work bridges engineering, electronic music, and empirical research, focusing on spatial audio systems, live electronics, and human-computer interaction in musical contexts. He joined Georgia Tech in 2023 after serving as director of the TU Studio for Electronic Music at Technische Universität Berlin from 2015 to 2023, where he founded the Electronic Orchestra Charlottenburg (EOC) to explore live electronic ensembles in multichannel environments. His research emphasizes the integration of sound, space, and HCI to enhance compositional and performative expressiveness. Notable projects include immersive audio installations, virtual instrument design, and AI-assisted composition. Coler has performed globally on immersive audio systems and curated international concerts. His technical contributions span spatial sound synthesis algorithms, networked music systems, and real-time signal processing tools. Key areas of exploration include volumetric music performances in metaverse environments, hybrid spatial interaction via ARCube, and statistical models for spectral synthesis. He has developed open-source systems like Orchestra (for metaverse performances) and SPRAWL (for ensemble interaction). Coler’s work often combines empirical research with artistic practice, aiming to redefine the boundaries of live electronic music through technological innovation. His academic output spans over 30 peer-reviewed articles since 2011, with recent focus on metaverse applications, AI-human collaboration, and immersive audio design. While no formal awards are listed, his leadership roles and project outcomes highlight significant contributions to music technology and spatial audio engineering.

Stephen Mangمشاهده پروفایل

دانشیار

• Chemical Education
• Analytical Chemistry
• Atmospheric Chemistry
• +۳ مورد دیگر

Stephen Mang is an Associate Professor of Teaching and Department Vice Chair in the Department of Chemistry at the University of California, Irvine (UCI). His research focuses on chemical education, particularly innovative teaching methods such as virtual interactive prelabs for analytical chemistry and redesigning courses like 'Writing for Chemists' using specifications grading. He has also contributed to atmospheric chemistry studies, exploring aerosol aging mechanisms, limonene oxidation products, and photochemical processes in secondary organic aerosols. Mang's work bridges pedagogical advancements with environmental chemistry research, emphasizing both educational technology and fundamental chemical analysis. His research interests span chemical education innovations, analytical chemistry pedagogy, and environmental chemistry topics like aerosol dynamics and mass spectrometry applications. His publications from 2004–2024 reflect a dual focus: early-career contributions to understanding atmospheric aerosol behavior and recent emphasis on enhancing STEM education through interactive tools and assessment strategies. Mang’s articles highlight advancements in course design and technical communication while maintaining a legacy in environmental chemistry. He has not been noted for awards in the provided texts but remains active in both teaching and interdisciplinary research at UCI.

Helen Lewisمشاهده پروفایل

دانشیار

• Metacognition
• Animal-Assisted Interventions
• Educational Pedagogy
• +۴ مورد دیگر

Dr. Helen Lewis is an Associate Professor in Education and Childhood Studies at Swansea University's School of Social Sciences. She serves as the School Education Lead and Programme Director for the Primary Postgraduate Certificate in Education (PGCE). Her work bridges teacher education, metacognitive development in children, and innovative uses of animal-assisted interventions in schools. Her research focuses on two pillars: 1) fostering children's thinking skills and metacognition through pedagogical frameworks like Project Zero's VSRD methodology, and 2) exploring how school dogs enhance pupil well-being, learning, and resilience. Recent projects include an ESRC-funded initiative creating best practice guidelines for canine-assisted education. Professionally, she holds certifications in animal-assisted play therapy and canine intervention strategies. She actively contributes to academic governance as an External Examiner at institutions like University College London and serves on national committees such as the National School Dog Alliance and Let's Think Forum. Her career highlights include leadership roles in program development (BA Education Studies, MA Education), peer review for academic journals, and governance as a primary school inspector for Estyn. She balances rigorous scholarship with practical advocacy for evidence-based educational practices.

• Robotics
• Autonomous Systems
• Unmanned Aerial Vehicles (UAVs)
• +۹ مورد دیگر

Nabil Aouf is a Professor of Robotics and Autonomous Systems in the Department of Electrical and Electronic Engineering at City, University of London, a position he has held since January 2019. Previously, from 2006 to 2018, he was Professor of Autonomous Systems at Cranfield University’s Defence and Security campus, where he also served as Head of the System and Autonomy Group and Research Lead of the Centre of Electronic Warfare, Information and Cyber. He earned his PhD in Electrical Engineering from McGill University Faculty of Engineering between 1999 and 2002. His research focuses on Robotics, Autonomous Systems, UAV Navigation, Computer Vision, and Fault-Tolerant Control . Key areas include visual odometry, sensor fusion (vision/IMU, RGBD, thermal-visible), robust control for UAVs, fault diagnosis in inertial systems, 3D perception, and autonomous landing. His work integrates theoretical control methods with real-time implementation in aerospace and defense contexts. His recent publications reflect a strong emphasis on robust optimization, multispectral vision, and real-time autonomous navigation. Trends indicate a focus on enhancing autonomy under uncertainty—through illumination-invariant stereo matching, L∞ optimization, and robust feature matching—particularly for UAVs operating in challenging environments. Nabil Aouf has collaborated extensively with researchers such as M. Richardson, O. Araar, T. Mouats, and M. Boulekchour across numerous projects in UAV control, sensor fusion, and autonomy. While no scientific awards are listed in the provided text, his leadership roles and sustained publication record in high-impact journals and conferences underscore his academic contributions. He has supervised or collaborated with several advisees including S.H. Almutairi, L. Chermak, I. Vitanov, and D. Nam, contributing to both theoretical developments and practical implementations in autonomous systems. His work has applications in aerospace, defense, planetary exploration, and critical infrastructure inspection.

Radu Jianuمشاهده پروفایل

مدرس

• Data Visualisation
• Visual Analytics
• Human Computer Interaction
• +۷ مورد دیگر

Dr. Radu Jianu is a Lecturer in the Department of Computer Science at City, University of London , where he has been a faculty member since 2016. He is affiliated with the giCentre , a leading research group in information visualization. He earned his PhD and MSc in Computer Science from Brown University, USA, and a Diploma in Engineering from the Polytechnic University of Timisoara, Romania. His academic career includes a previous role as Assistant Professor at Florida International University (2012–2016). His research focuses on Data Visualisation, Visual Analytics, and Human-Computer Interaction . He conducts interdisciplinary collaborations with domains such as biology, food policy, and energy decarbonisation, aiming to develop interactive visual tools that enhance data understanding and decision-making. His methodological approach includes user studies, eye-tracking, and the design of novel visualization techniques. Dr. Jianu teaches Programming in Java and Cognition and Technologies , and he coordinates the Programming Bootcamp. He also holds administrative responsibilities as the Progression and Support Director in the Computer Science Department and is a member of its Executive Committee (ExCo). His recent publications reflect a growing interest in LLM-assisted visual analytics, gaze-aware systems, and collaborative human-AI analytical frameworks . He has published in top venues such as IEEE TVCG, CHI, EuroVis, and Nature Immunology, with several best paper awards. His work on the RAMPVIS project highlights his contributions to visualization in public health emergencies. Scientific Awards: Best Paper Award, Symposium on Graph Drawing (2018) Best Short Paper Award, EuroVis (2020) Advising and Grants: Dr. Jianu supervises multiple PhD and MSc students, including Dany Laksono (Energy Decarbonisation) and Maeve Hutchinson (NLP-mediated Visualization). His students have co-authored high-impact, award-winning papers. He has been involved in funded research initiatives such as RAMPVIS, which received support from UKRI/EPSRC for developing visual analytics infrastructure during the COVID-19 pandemic. Labs and Teams: He is an active member of the giCentre at City, University of London, a hub for visualization research. He also collaborates with interdisciplinary teams in epidemiology, immunology, and computer science, contributing to large-scale projects like the Immunological Genome Project and RAMPVIS.

Tongguang Liمشاهده پروفایل

پژوهشگر ارشد

• Learning Analytics
• Artificial Intelligence in Education
• Self-Regulated Learning
• +۳ مورد دیگر

Tongguang Li is a Research Fellow at the Department of Human Centred Computing, Monash University. His research focuses on learning analytics, self-regulated learning, and AI applications in education. He has contributed to the development of the FLoRA engine, an AI tool designed to enhance hybrid human-AI regulated learning. Li’s work explores adaptive scaffolding, large language model (LLM) feedback systems, and the integration of multimodal data for educational insights. His recent studies investigate how LLMs like ChatGPT can provide effective feedback to students, analyze rhetorical patterns in writing, and measure the impact of scaffolding on learning processes. Li has been recognized for his research with the Conference Best Full Student Paper Award from the Australiasian Society for Computers in Learning in Tertiary Education (2022). Key themes in his work include understanding self-regulated learning strategies through trace data, optimizing adaptive systems for learner engagement, and leveraging AI for educational innovation. His research bridges cognitive science, data analytics, and educational technology to improve learning outcomes and pedagogical practices.