جستجوی استاد راهنمای دانشگاهی

Govind P. Agrawalمشاهده پروفایل

استاد

• Nonlinear Optics
• Quantum Electronics
• Laser Physics
• +۷ مورد دیگر

Govind P. Agrawal is a Professor of Optics and Physics at the University of Rochester. He holds concurrent positions as a Fellow of the IEEE and the Optical Society of America (OSA). His research focuses on theoretical optics, nonlinear optics, laser physics, and semiconductor lasers, with notable contributions to fiber optics and optical communications. Education: Agrawal earned his MS (1971) and PhD (1974) from the Indian Institute of Technology, New Delhi. He has held prior positions at École Polytechnique (Paris), City University of New York, and AT&T Bell Laboratories before joining the University of Rochester in 1989. Research Interests: Agrawal's work explores quantum electronics, soliton dynamics, Raman scattering, and temporal reflection phenomena. He has authored seminal books such as Nonlinear Fiber Optics and Semiconductor Lasers , and published over 300 journal articles. His recent studies emphasize spatiotemporal dispersion, multimode fiber optics, and integrated photonics systems. Editorial Roles: He served as Topical Editor for Journal of the Optical Society of America B (1993–1998) and currently contributes to editorial boards for optics journals and book series. Awards: Honored as a Fellow of the IEEE and OSA for his transformative contributions to optics and photonics. Key Contributions: Pioneered theories on graded-index fiber amplifiers, temporal reflection in nonlinear media, and soliton-based technologies. His research bridges fundamental optics with practical applications in telecommunications and photonics systems.

Yasmin Kafaiمشاهده پروفایل

استاد

• Computational Thinking
• Artificial Intelligence Education
• STEM Equity
• +۳ مورد دیگر

Yasmin Kafai is a Professor at the University of Pennsylvania's Graduate School of Education (GSE), Department of Learning Sciences. Her research focuses on computational thinking, AI education, and equitable K-12 computing pedagogy. She has pioneered work on integrating electronic textiles (e-textiles) and participatory design into STEM education to engage youth in critical perspectives of technology. Kafai's recent work emphasizes algorithmic literacy, youth-led auditing of machine learning systems, and bridging technical and societal dimensions of computing. Key research areas include: computational empowerment, AI ethics in education, youth agency in technology design, and culturally responsive computing curricula. Her projects often involve hands-on making activities, such as constructing generative AI models or debugging e-textile systems, to foster both technical and critical understandings. Publications from 2024-2025 highlight trends in youth engagement with generative AI, algorithm auditing frameworks, and the intersection of physical computing with growth mindset practices. She has also explored the role of storytelling methodologies in reimagining computing narratives for marginalized groups. Kafai collaborates extensively with teachers to develop scalable professional development programs addressing equity in CS education. Her work frequently appears in learning sciences and computing education journals, with a focus on practical classroom implementations and systemic educational reforms. Ongoing efforts include designing 'Hour of Code' activities that integrate critical AI literacy and fostering youth as co-designers of ethical technology solutions.

• Wireless Communications
• MIMO Systems
• Signal Processing
• +۳ مورد دیگر

Oussama Damen is a Professor at the University of Waterloo's Department of Electrical and Computer Engineering. His research focuses on advanced wireless communication systems, particularly in MIMO (Multiple-Input Multiple-Output) systems, signal processing, and machine learning applications in telecommunications. He is actively involved in developing innovative solutions for beamforming, hybrid precoding, and distributed decoding in massive MIMO and millimeter-wave networks. Damen's work also extends to optical fiber communication, federated learning in wireless systems, and optimization of resource allocation in next-generation networks like 5G/6G. His research interests include wireless communication theory, antenna system design, channel modeling, and algorithm development for improving spectral and energy efficiency. He has contributed extensively to the theoretical foundations of MIMO detection, lattice reduction techniques, and statistical signal processing methods. Notable trends in his publications emphasize bridging theoretical performance limits with practical implementations, particularly in scenarios involving channel impairments, limited backhaul capacity, and multi-core fiber transmission. His work often addresses fairness and optimization in distributed systems, including federated learning frameworks and hybrid beamforming architectures. No scientific awards or grants are explicitly mentioned in the provided information. Damen has advised no listed students, and no specific lab affiliations are noted.

• Non-Communicable Diseases
• Global Health
• Health Services Research
• +۳ مورد دیگر

Dr. Jeremy I. Schwartz is an Associate Professor at Yale School of Medicine (Department of Medicine) and Yale School of Public Health (Department of Chronic Disease Epidemiology). He specializes in non-communicable diseases (NCDs), global health, and digital health interventions. As Firm Chief of Yale Primary Care Residency Program and Director of the Faculty Network Program at the Yale Institute for Global Health, he leads initiatives to improve healthcare delivery in low-resource settings. He co-founded the Uganda Initiative for Integrated Management of Non-Communicable Diseases (UINCD), collaborating with Ugandan institutions to address fragmented NCD care. His research focuses on hypertension, diabetes, and heart failure management in Uganda, leveraging mobile health (mHealth) tools. He also directs the 'Topics in Global Medicine' course at Yale, training future healthcare leaders in global health challenges. Education: MD from University of Rochester School of Medicine & Dentistry (2006), BS from Cornell University (2000). Honors include the Doran J. Stevens Prize (2006), Gold Humanism Honor Society (2006), and Alpha Omega Alpha (2005). Key roles: Medical Director of the Eastern Caribbean Health Outcomes Research Network (ECHORN), Co-Director of UINCD, and affiliated faculty at the Yale Institute for Global Health and Center for Interdisciplinary Research on AIDS. His work emphasizes interdisciplinary collaboration, with a focus on Africa and the Caribbean. Research emphasizes integrated care models, digital health innovations, and policy advocacy for NCDs. Recent projects include adapting mobile health applications for heart failure patients and evaluating cost barriers to essential medicines in Uganda.

Mohammadreza Karamadمشاهده پروفایل

استادیار

• Electrochemistry
• Heterogeneous Catalysis
• Material Science
• +۳ مورد دیگر

Mohammadreza Karamad is an Assistant Professor in the School of Sustainable Energy Engineering at Simon Fraser University (SFU), with a joint appointment in the Sustainable Energy Engineering department. His research focuses on computational materials discovery, leveraging quantum-mechanical methods (e.g., DFT) and machine learning (ML) to design advanced energy materials for clean technologies like hydrogen storage and catalysis. He holds a Ph.D. from the Technical University of Denmark (DTU) and completed postdoctoral research at Stanford University. His academic background includes leadership roles in the CMD Lab (Computational Materials Discovery), where he explores novel materials for electrochemical energy conversion processes. Key research areas include electrochemistry, heterogeneous catalysis, and material science, with a particular emphasis on CO2 reduction, ammonia synthesis, and sustainable energy storage solutions. Dr. Karamad collaborates with industry and academic partners to advance materials discovery through high-throughput computational screening and AI-driven approaches. He actively seeks motivated students (undergraduate and graduate) to join his research program, focusing on developing next-generation energy materials. His lab is located in room B8220, and he can be reached at mkaramad@sfu.ca. Notable technical contributions include pioneering work on transition metal nitrides for CO2 reduction, single-atom catalysts for ammonia synthesis, and machine learning frameworks for predicting material properties. His research bridges fundamental theory with practical applications, addressing global challenges in sustainable energy and environmental technology.

Jesse D. Jenkinsمشاهده پروفایل

دانشیار

• Energy Systems Modeling
• Deep Decarbonization
• Low-Carbon Energy Technologies
• +۳ مورد دیگر

Jesse D. Jenkins is an Associate Professor of Mechanical and Aerospace Engineering and the Andlinger Center for Energy and the Environment at Princeton University. His joint appointment bridges the School of Engineering and Applied Science and the Andlinger Center, focusing on macro-scale energy systems engineering. He holds a Ph.D. in Engineering Systems from MIT (2018) and completed a postdoctoral fellowship at Harvard Kennedy School. Research Interests: Energy systems modeling, deep decarbonization pathways, low-carbon technologies, and energy policy. He leads the Princeton ZERO Lab, which develops optimization-based models to evaluate clean energy transitions and inform policy. Key Awards: Howard B. Wentz Jr. Junior Faculty Award, Princeton Engineering Teaching Excellence Award, TIME100 Next (2024), and recognition in ENR's 2022 Top 25 Newsmakers for leadership in climate policy analysis. Professional Contributions: Serves on advisory boards for Eavor Technologies, Rondo Energy, and Dig Energy. Co-hosts the podcast Shift Key on energy transition strategies. Labs/Teams: Directs the ZERO Lab and co-leads the REPEAT Project, analyzing U.S. decarbonization pathways and federal policy impacts.

• Radiotherapy
• Medical Imaging
• Clinical Imaging
• +۳ مورد دیگر

Dr. Mark Gardner is a Research Fellow in Clinical Imaging at the ACRF Image X Institute, part of the University of Sydney's Sydney School of Health Sciences and Faculty of Medicine and Health. His work focuses on advancing radiation therapy and medical imaging technologies, with particular emphasis on improving treatment accuracy and patient comfort. Gardner holds a PhD from Flinders University, completed in collaboration with the Medical Device Research Institute, and has held research roles at the Cystic Fibrosis Airway Research Group (CFARG). His current projects include the Nano-X radiation therapy device and the Remove the Mask initiative , which aims to eliminate immobilization masks in head and neck cancer treatments. Gardner is affiliated with organizations like the IEEE Engineering in Medicine and Biology Society and the American Association of Physicists in Medicine. Research interests span radiation oncology, translational research in medical imaging, and device innovation. His work integrates advanced imaging techniques (e.g., synchrotron X-rays, cone-beam CT) with machine learning and wearable sensors to address challenges in respiratory therapy and tumor targeting. Notable contributions include developing real-time motion tracking for radiation therapy and improving mucociliary transport measurements. Awards: FameLab 2020 State Finalist, 2018 Medtech e-Challenge Winner, 2017 3MT Runner-Up Grants/Projects: Nano-X radiation therapy development, Remove-the-Mask surface-guided system Collaborations: Industry partnerships, multi-institutional research networks Gardner advises Chen Cheng on real-time head/neck motion monitoring during radiation therapy. His lab contributes to open-source tools and preclinical imaging advancements, bridging engineering and clinical oncology.

Katrina Morgan-Innesمشاهده پروفایل

مدرس

• Energy Harvesters
• Flexible and Wearable Technologies
• 2D Materials
• +۳ مورد دیگر

Katrina Morgan-Innes is a Lecturer (Assistant Professor) at the School of Electronics and Computer Science, University of Southampton. Her research focuses on advanced flexible materials for energy harvesting and storage, leveraging semiconductor industry fabrication techniques to develop wearable thermoelectric devices and next-generation batteries. She leads the Morgan Materials and Devices for Energy (MADE) research group and a £220k EPSRC New Horizons grant (Smart Cloth). Her work emphasizes commercial scalability and integration of 2D materials with flexible substrates. Education: MPhys in Physics (University of Sussex, 2011), CASE Award PhD in Electronics and Computer Science (University of Southampton, 2016–2022). Previous roles include Photonics Development Engineer at the AIM Photonics Programme (SUNY) and Visiting Fellow at the Optoelectronics Research Centre. Research interests include energy harvesters, flexible wearables, 2D materials, and nanofabrication. She has pioneered scalable manufacturing methods for photonic and energy devices and contributed to chalcogenide material applications. Her research group aims to create fully flexible systems enabling integrated sensing, power, and communication on lightweight platforms. Key grants include EPSRC funding for wearable thermoelectric generators and collaborations like the ChAMP/WAFT-funded projects on flexible ion sensors and 3D nanophotonics. She has published in high-impact journals (e.g., ACS Applied Materials and Interfaces , npj 2D Materials and Applications ) and conferences, focusing on thermoelectric materials, photonic heterostructures, and scalable manufacturing. Awards: UNSW Women in Engineering Visiting Fund (2019), Top 100 Physics Paper (2020), Outreach Engagement Award (2016) Labs/Teams: Morgan MADE Group, Collaboration with Optoelectronics Research Centre and Zepler Institute Advocacy: Chair of WiSET+ (University-wide STEM+ Equality Committee), founder of Early Career Researcher Forum

• AgriFood Supply Chain Logistics
• Supply Chain Management
• Logistics Network Design
• +۴ مورد دیگر

Prof. Jack van der Vorst is the Personal Professor of AgriFood Supply Chain Logistics at Wageningen University's Operations Research and Logistics Group. Previously serving as a member of the Board of Directors of Wageningen University & Research (until 2024) and General Director of the Social Sciences Group, he leads over 1000 personnel across three institutes. His advisory roles include the Topteam AgriFood (Science Captain), Top consortium for Knowledge and Innovation (TKI), The Sustainability Consortium (TSC), and Florensis BV's Supervisory Board. With 20+ PhD supervisions and 200+ publications, his research focuses on innovative logistics concepts in AgriFood systems, including supply chain resilience, sustainability, and system innovation. His work integrates modeling frameworks with practical industry applications, emphasizing perishable products, horizontal collaboration, and environmental efficiency. Research interests span AgriFood System Design, Supply Chain Strategy, and Performance Management. His recent studies address challenges like postharvest loss reduction in developing countries, CO2 emission minimization in cold chains, and circular economy implementation in mushroom supply chains. Methodologically, he employs multi-criteria decision models, optimization techniques, and simulation to address complex logistics problems. Publications highlight themes such as horizontal collaboration success factors, vulnerability assessment frameworks, and green supply chain design. His work bridges academic rigor with industry needs, often collaborating with policymakers and international organizations to promote sustainable agri-food systems.

Christiana Mavroyiakoumouمشاهده پروفایل

استادیار

• Fluid Dynamics
• Fluid-Structure Interactions
• Vortex Dynamics
• +۶ مورد دیگر

Christiana Mavroyiakoumou is a Courant Instructor/Assistant Professor at the Courant Institute of Mathematical Sciences, New York University. She specializes in fluid dynamics and fluid-structure interactions, with a focus on vortex dynamics, membrane flutter, and bio-inspired systems. Her research integrates modeling, numerical simulations, and experimental insights to study phenomena such as bird flock formations and fish swimming hydrodynamics. Mavroyiakoumou holds a Ph.D. from the University of Michigan (2022), an M.Sc. from the University of Oxford (2017), and a B.Sc. from Imperial College London (2016). Education: PhD in Applied & Interdisciplinary Mathematics, University of Michigan (2017–2022) MSc in Mathematical Modeling and Scientific Computing, University of Oxford (2016–2017) BSc in Mathematics, Imperial College London (2013–2016) Her research interests span fluid-structure interactions, vortex dynamics, and collective locomotion. She investigates how fluid flows mediate interactions between bodies, such as the aerodynamics of bird formations and the hydrodynamics of flapping foils. Her work bridges theoretical models with experimental observations, contributing to both fundamental science and bio-inspired engineering. Mavroyiakoumou has received prestigious awards including the Joseph B. Keller Fellowship (NYU), Peter Smereka Award (U-M), and ProQuest Distinguished Dissertation (U-M). She actively engages in academic service, organizing conferences and mentoring students. Her teaching experience includes courses on mathematical modeling, differential equations, and algebra at NYU and the University of Michigan. Key Research Themes: Flow-mediated collective behavior and instability mechanisms Vortex wake interactions and their role in locomotion Membrane dynamics in inviscid and viscous flows She collaborates with experimentalists like Leif Ristroph and Jun Zhang at NYU's Applied Math Lab, focusing on experimental validation of theoretical models. Her recent work explores self-amplifying waves in bird formations and the aerodynamic origins of flight coordination.

Marcel Dettlingمشاهده پروفایل

مدرس

• Predictive Analytics
• Applied Statistics
• Data Mining
• +۶ مورد دیگر

Dr. Marcel Dettling is a Group Lead in Data Analysis and Statistics at the ZHAW School of Engineering , focusing on predictive analytics, applied statistics, and complex data analysis. He also serves as a Lecturer at ETH Zurich , teaching advanced statistical methods. Education : PhD in Mathematics (2000-2004), ETH Zurich Postdoc in Applied Statistics (2004-2006), Johns Hopkins University His research spans predictive analytics (regression, classification, time series), data mining, and applications in health economics, transportation safety, social sciences , and business analytics . Recent work includes pharmaceutical cost group analysis for Swiss healthcare and predictive maintenance for marine vessels. Selected publications highlight his expertise in flight trajectory modeling , deep learning error mitigation , and statistical frameworks for rehabilitation finance . His projects address diverse fields like crowdworking in nursing, energy optimization for shipping, and customer behavior prediction.

Swati Aggarwalمشاهده پروفایل

استاد

• Artificial Intelligence
• AI in Health and Medicine
• AI in Society
• +۶ مورد دیگر

Swati Aggarwal is a Professor in Artificial Intelligence at the Faculty of Logistics, Molde University College (HiMolde). Her research focuses on AI applications in healthcare, ethics, cognitive development, and neural networks. She holds a PhD in Neutrosophic Neural Networks, a Master's in Information Technology, and a Bachelor's in Computer Science and Engineering. Previously, she was a Marie Curie Postdoc Fellow at NTNU, working on AI models for cognitive assessment in infants (AIM_COACH project). Research Interests - AI in Health/Medicine - Ethics in AI and Societal Impact - EEG/BCI for Cognitive Assessment - Machine Learning and Deep Learning Publications Her recent work spans AI ethics, BCI applications, adversarial attacks, and healthcare diagnostics. Notable contributions include EEG-based infant perceptual monitoring (2025) and malaria detection via EfficientNet (2023). She also explores cross-lingual adversarial robustness and blockchain in hospitality systems. Labs/Teams - ABC-AI: Applied, Basic, and Conscientious AI Group - Virtual Technologies and Learning Research Group

Ruth Greenwoodمشاهده پروفایل

استادیار بالینی

• Election Law
• Voting Rights
• Civil Rights
• +۳ مورد دیگر

Ruth Greenwood is a Clinical Assistant Professor of Law and Director of the Election Law Clinic at Harvard Law School, Harvard University. She specializes in election law litigation, voting rights advocacy, and training future election lawyers. Her work focuses on challenges to partisan gerrymandering, minority vote dilution, and legal strategies to reform redistricting processes. Education: LL.M., Columbia Law School (2009) LL.B./B.Sc., University of Sydney (2005/2003) Research Interests: Election law federalism, voting rights enforcement, redistricting commission design, and combating racial gerrymandering through litigation and legislative advocacy. Her work emphasizes state-level voting rights acts as critical tools for addressing federal law shortcomings. Professional Affiliations: Board Member and Secretary of PlanScore (2019–present), former roles at the Campaign Legal Center, Chicago Lawyers’ Committee for Civil Rights, and the DNC’s Voting Rights Institute. Admitted to multiple federal courts including the Supreme Court of the United States. Courses Taught: Election Law Clinic and Seminar series, Writing Group on Voting Rights (2024–2025).

• Computational Linguistics
• Computer Science
• Machine Learning
• +۱ مورد دیگر

Noah A. Smith is an Adjunct Professor of Computer Science and Engineering at the University of Washington. His work focuses on computational linguistics, machine learning, and natural language processing. He holds a Ph.D. in Computer Science from Johns Hopkins University (2006). His research explores ethical AI applications, multimodal systems, and foundational aspects of language models. Key research areas include: Ethical considerations in NLP, such as detecting rights abuses through text analysis Efficient decoding and alignment strategies for large language models Large-scale evaluation frameworks for multitask and multimodal generation Understanding pretraining dynamics and data composition effects Recent work emphasizes transparency in language models (e.g., tracing outputs to training data) and improving alignment through human feedback. He has contributed to open-source projects like OLMo and Dolma, advancing reproducibility in NLP research. No awards explicitly listed in provided texts. No specific advising or grant details available, though extensive publication output indicates active research involvement.

Syed Bahauddin Alamمشاهده پروفایل

استادیار

• Artificial Intelligence
• Digital Twins
• Nuclear Engineering
• +۵ مورد دیگر

Syed Bahauddin Alam is an Assistant Professor at the University of Illinois Urbana-Champaign (UIUC) in the Nuclear, Plasma & Radiological Engineering department. He holds appointments in the Grainger College of Engineering and the National Center for Supercomputing Applications (NCSA). His research focuses on AI-driven digital twins, uncertainty quantification, and cybersecurity for nuclear systems. Education: B.Sc. in Electrical and Electronics Engineering, Bangladesh University of Engineering and Technology (BUET), 2011 MPhil in Nuclear Energy, University of Cambridge, 2013 PhD in Nuclear Engineering, University of Cambridge, 2018 Research Interests: AI and Digital Twins for Nuclear Energy Multiscale Modeling with Uncertainty Quantification Cybersecurity for Nuclear Systems Sensors and Instrumentation for Reactor Monitoring His work emphasizes explainable AI (XAI), physics-informed machine learning, and robust design optimization. Key contributions include AI-powered digital twins for nuclear systems, which received global media coverage and top 5% Altmetric scores. Awards & Honors: 2025 Dean’s Award for Excellence in Research (UIUC) 2024 Illinois Innovation Award Finalist 2022-2021 Outstanding Teaching Award (Missouri S&T) 2017 Cambridge Philosophical Society Research Studentship Award Grants & Funding: $700,000 U.S. Nuclear Regulatory Commission (NRC) Distinguished Faculty Development Award (2024) $2 million DOE grant for nuclear fuel storage solutions (2023) $500,000 NRC R&D Grant (2024) Labs & Teams: Leads the MARTIANS Lab (Machine Learning and ARTificial Intelligence for Advancing Nuclear Systems), focusing on hybrid data-physics-driven AI and explainable machine learning for nuclear engineering challenges.