جستجوی استاد راهنمای دانشگاهی

Sheldon M. Jeterمشاهده پروفایل

دانشیار

• Heat Transfer
• Combustion
• Energy Systems
• +۳ مورد دیگر

Sheldon M. Jeter is a retired Associate Professor at Georgia Institute of Technology, located in Love Building, Room 330. He holds a Ph.D. from Georgia Tech (1979), an M.S. from the University of Florida (1972), and a B.S. from Clemson University (1968). His research focuses on heat transfer, combustion, energy systems, and thermodynamics, with contributions to two-phase flow dynamics and fluid energy systems. Dr. Jeter has been a Registered Professional Engineer in Georgia and holds multiple patents, including innovations in heat and mass transfer enhancement and fluid systems. His work bridges theoretical and applied research, addressing challenges in thermal systems and energy efficiency. Education: Ph.D., Georgia Institute of Technology, 1979 M.S., University of Florida, 1972 B.S., Clemson University, 1968 Research Interests: Dr. Jeter’s research spans experimental and theoretical studies in heat transfer mechanisms, thermodynamics of mixtures, and innovative energy systems design. His applied work emphasizes improving fluid and thermal energy systems, while his basic research explores two-phase flow phenomena and boiling dynamics. He has pioneered methods to enhance nucleate boiling through electrohydrodynamic techniques and analyzed flow instability in complex geometries. Publishing Trends: His articles address critical areas like pressure drop in microchannels, two-phase flow in HVAC systems, and visualization of boiling dynamics. These studies underscore advancements in thermal management and energy system optimization. Awards & Recognition: Registered Professional Engineer in Georgia Patents & Contributions: Dr. Jeter holds four U.S. patents, including inventions related to electrode arrangements for heat transfer enhancement and novel fluid systems. His work reflects a commitment to translating theoretical insights into practical engineering solutions.

Jason Waithmanمشاهده پروفایل

دانشیار

• Cancer Immunology
• T Cell Immunity
• Dendritic Cell Biology
• +۳ مورد دیگر

Associate Professor Jason Waithman leads the Cancer Immunotherapy Program at the University of Western Australia's School of Biomedical Sciences. His expertise spans dendritic cell biology, T cell immunity, and cancer immunology. He holds dual affiliations with the School of Human Sciences and the Australian Centre for RNA Therapeutics in Cancer. Education: PhD in Immunology (University of Melbourne, 2008), specializing in CD8 T cell tolerance mechanisms. Research focuses on translational immunotherapy tools, genomic data science integration, and identifying novel therapeutic targets for cancer control. Key projects include CAR-T cell therapy optimization, immune response modulation in melanoma, and burn injury's impact on cancer immunity. Recent grants include leadership roles in skin cancer classification probes, high-content microscopy infrastructure, and natural killer cell enhancement therapies. He has authored 56 publications and 24 grants, with 4,513 citations and a h-index of 25. Labs/Teams: Cancer Immunotherapy Program, Australian Centre for RNA Therapeutics in Cancer. Collaborations span international institutions with a focus on immunology and oncology.

Nima Pouraliمشاهده پروفایل

استادیار

• Plasma Physics
• Plasma Engineering
• Electrochemical Reactors
• +۸ مورد دیگر

Dr. Nima Pourali is an Assistant Professor at the School of Engineering, University of Warwick (Coventry, England), since 2022. Previously, he held roles as a Research Fellow (2019–2022) and Postdoctoral Associate in the Electrical and Computer Engineering Department at Western University (London, Canada). His research focuses on experimental and computational plasma physics, plasma engineering, electrochemical reactors, and plasma-catalyst interactions. Key areas include sustainable plasma-catalytic nitrogen fixation, ammonia synthesis, methane conversion, and microfluidic plasma systems. His work integrates interdisciplinary approaches to address challenges in energy sustainability, such as optimizing plasma reactors for non-oxidative methane coupling and developing novel plasma-assisted synthesis processes. His publications emphasize plasma reactor design, energy efficiency, and cross-disciplinary reviews of emerging technologies. Pourali’s research has led to advancements in plasma photonic crystals, Faraday rotation tuning, and catalyst coating optimization. He collaborates on projects involving microkinetic modeling, plasma parameter analysis, and sustainable chemical processes. Office hours are Fridays 10 AM–12 PM during term time.

Marco Farinaمشاهده پروفایل

استاد

• Electromagnetic Fields
• Scanning Probe Microscopy
• Nanotechnology
• +۴ مورد دیگر

Marco Farina is a Full Professor in Electromagnetics at the Department of Information Engineering, College of Engineering, Polytechnic University of Marche, Italy. His research spans electromagnetic modeling, scanning microwave microscopy, and nanotechnology, with applications in 2D materials, biosensors, and advanced measurement systems. He is a Senior Member of IEEE and actively contributes to Technical Committees on RF Nanotechnology. Laurea and Ph.D. in Electronic Engineering from University of Ancona Research interests focus on quantitative scanning microwave microscopy, electromagnetic analysis of active/passive components, and nanoscale characterization techniques. His work bridges theoretical modeling with practical implementation, including the development of the EM3DS software suite and novel inverted SMM systems. Recent publications highlight interdisciplinary applications in biomedical analysis and semiconductor physics. Scientific recognition includes the 3M-Nano Best Conference Paper Award and grants from US Army Research Laboratory and US Air Force Office of Scientific Research. He holds an ESA-funded patent for VNA calibration and has co-authored a book on planar structure analysis. Collaborative projects emphasize RF device optimization and biological imaging.

Haydar Aygunمشاهده پروفایل

دانشیار

• Acoustic Materials
• Metamaterials
• Biomedical Acoustics
• +۷ مورد دیگر

Dr. Haydar Aygun serves as Associate Professor in Acoustics and Building Services at the Bioscience and Bioengineering Research Centre, Department of Civil and Building Services Engineering, University of Salford. He holds multiple leadership roles including Course Director for the MSc Environmental and Architectural Acoustics, Diploma in Acoustics and Noise Control, and The Acoustics Apprenticeship programs. With a PhD in Acoustics and Vibration from the University of Hull (2006), his academic foundation includes a MSc in Advanced Materials, Processes and Manufacturing (2002) and a BSc in Mechanical Engineering. Dr. Aygun's research spans multiple critical domains of acoustics: Development and characterization of novel acoustic materials and metamaterials for noise control Duct acoustics and sound propagation through complex media Biomedical applications including bone analysis and respiratory sound detection Vibration control of porous materials using advanced computational methods Environmental noise assessment and building acoustics solutions His publication record shows consistent scholarly output with 46 research items from 2006-2025, demonstrating particular productivity in recent years (7 publications in 2023). His work shows increasing integration of computational methods with experimental validation, expanding applications in medical diagnostics and sustainable building technologies. Dr. Aygun actively contributes to the academic community through multiple service roles: Editorial Board Member for Journal of Applied Acoustics EPSRC Grant Reviewer Reviewer for Journal of Applied Acoustics and Journal of the Acoustical Society of America Deputy leader of Biomedical Acoustics Special Interest Group within UK Acoustics Network As an educator, Dr. Aygun has supervised numerous PhD students and teaches across multiple levels from undergraduate Building Services Engineering to specialized postgraduate Acoustics programs. His consultancy work bridges academic expertise with practical industry applications in noise assessment, building acoustics, and event sound management.

Farouq Aliمشاهده پروفایل

استاد

• Enhanced Oil Recovery
• Reservoir Engineering
• Heavy Oil Recovery
• +۵ مورد دیگر

Farouq Ali is a Distinguished Professor in the Department of Petroleum Engineering at the University of Houston's Cullen College of Engineering. With over 40 years of experience spanning academia and industry, he is globally recognized as a leading expert in reservoir engineering and enhanced oil recovery techniques. Previously holding the Encana/Petroleum Society Chair at the University of Calgary, he has also served as a professor at Pennsylvania State University, University of Alberta, and University of Regina. His educational background includes: Ph.D. in Petroleum and Natural Gas Engineering, Pennsylvania State University M.S. in Petroleum and Natural Gas Engineering, Pennsylvania State University B.Sc. (Hons.) in Petroleum Production Engineering, Birmingham University, England B.Eng. in Electrical and Mechanical Engineering, Karachi University, Pakistan Professor Ali's research focuses on breakthrough methods for oil recovery from challenging reservoirs, particularly heavy oil systems. His pioneering work established micellar-polymer flooding as an industry standard and developed foundational steam injection techniques. Current investigations center on solvent-assisted thermal processes, pore-scale modeling of bitumen mobilization, and advanced reservoir simulation for optimizing steam-assisted gravity drainage (SAGD) and in-situ combustion. His 2015-2018 publications reveal a concentrated research trajectory toward integrating solvents with thermal recovery methods, developing non-equilibrium pore-scale simulators, and optimizing SAGD performance through analytical modeling. Key thematic clusters include solvent-steam synergies, temperature-dependent reservoir behavior, and field-scale implementation of advanced recovery techniques for oil sands and heavy oil deposits. His exceptional contributions are evidenced by prestigious accolades including: Election to the US National Academy of Engineering (2009) Anthony F. Lucas Gold Medal (SPE's highest technical honor, 2007) Kapitsa Gold Medal from Russian Academy of Sciences (1998) SPE Lester C. Uren Award (1996) Multiple SPE Distinguished Lecturer appointments Professor Ali maintains active industry engagement through over 250 reservoir studies and 30 major oilfield designs, advising governments and corporations on production strategies. His academic mentorship includes current Ph.D. candidate Seyed Mahdi Razavi, continuing his legacy of training petroleum engineering leaders. Research funding stems from extensive consulting contracts and collaborative industry projects focused on thermal recovery optimization. His laboratory investigations emphasize thermal recovery mechanisms and reservoir simulation, with current projects developing integrated solvent-steam models and advanced analytical tools for SAGD performance prediction. The research team maintains close industry partnerships for field validation of novel recovery techniques.

Kunlei Liuمشاهده پروفایل

استاد

• Advanced Combustion and Gasification
• Carbon Removal from Point Sources and Air
• Hydrogen Production
• +۱۲ مورد دیگر

Kunlei Liu is a Professor in the Department of Mechanical Engineering and Director of the Institute for Decarbonization and Energy Advancement (IDEA) at the University of Kentucky. He holds a Ph.D. in Thermoenergy Engineering from Southeast University (1993), an M.S. in Thermoenergy Engineering (1991), and a B.S. in Power Engineering (1988), all from Southeast University, Nanjing, PRC. His career includes roles as Associate Director for Research at the Center for Applied Energy Research (CAER) and academic positions at Western Kentucky University, including managing their Combustion Laboratory from 2002–2004. Prior to academia, he worked at The Babcock & Wilcox Company as an Advisory Engineer (2004–2005). Research Interests: Dr. Liu focuses on advanced combustion and gasification technologies, carbon removal from point sources and ambient air, hydrogen production, efficiency optimization, and material recovery from spent batteries and solar panels. His work integrates engineering, environmental science, and electrochemistry to address decarbonization challenges. He actively explores innovations in CO₂ capture solvents, electrochemical processes, and waste valorization strategies. Articles Trends: His recent publications concentrate on CO₂ capture via novel absorbents (e.g., diamine-based and potassium salts), electrochemical methods for CO₂ conversion, solvent degradation mechanisms, and material recovery from spent batteries and solar panels. He also investigates process intensification techniques using 3D-printed structured packing, microbubble technologies, and low-temperature methanation. Key areas include optimizing pilot plant performance, reducing nitrosamine contaminants, and enhancing system efficiency through computational modeling and experimental validation. Grants & Advising: While no advisees are listed, his leadership roles indicate extensive grant-funded research, including projects on decarbonization technologies, formic acid production, and direct air capture. He has managed CAER’s research programs and led interdisciplinary teams in pilot-scale testing and industrial collaborations. Labs & Teams: Dr. Liu directs IDEA and has historically managed the Combustion Laboratory at Western Kentucky University. He collaborates closely with UK’s Center for Applied Energy Research (CAER), focusing on innovative technologies for energy systems and environmental sustainability.

Burak Sarsilmazمشاهده پروفایل

استادیار

• Distributed Control
• Adaptive Control
• Trajectory Optimization
• +۲ مورد دیگر

Dr. Burak Sarsilmaz is an Assistant Professor in the College of Engineering at Utah State University, specializing in Electrical and Computer Engineering. His research focuses on distributed control of multi-agent systems, adaptive control, and trajectory optimization for aerospace applications. Education: PhD in Mechanical Engineering, University of South Florida (2020) MA in Mathematics, University of South Florida (2020) MS in Aerospace Engineering, Middle East Technical University (2016) BS in Aerospace Engineering, Middle East Technical University (2013) Research: His work bridges control theory and practical applications in autonomous systems, with emphasis on robustness under uncertainty. Recent publications explore novel approaches to cooperative control and optimization in constrained environments. Students: Actively mentors graduate students including Akalu Desta Teklu and Kursad Metehan Gul. Leads the Autonomy, Robotics, Control, and Optimization (ARCO) research group. Awards: Holds a Canada Research Chair in Translational Cancer Research.

Nishant Agarwalمشاهده پروفایل

دانشیار

• Theoretical Cosmology
• Quantum Field Theory in Curved Spacetime
• Inflationary Cosmology
• +۴ مورد دیگر

Nishant Agarwal is an Associate Professor in the Department of Physics & Applied Physics at the University of Massachusetts Lowell (UML). He is affiliated with the Kennedy College of Sciences, contributing to theoretical cosmology and quantum field theory research. His academic background includes a Ph.D. in Astronomy and Space Sciences from Cornell University (2011), and prior degrees from institutions like the Indian Institute of Technology Kanpur and St. Stephen's College, Delhi. Agarwal's research focuses on theoretical cosmology, particularly inflationary models, dark energy, quantum field theory in curved spacetime, and large-scale structure formation. His work explores the interplay between quantum mechanics, gravity, and cosmological observations, with contributions to understanding cosmic microwave background anisotropies and non-Gaussian features in the early universe. His publications span topics ranging from open quantum cosmological systems to constraints on massive gravity theories, reflecting his expertise in both theoretical frameworks and observational implications. Notable contributions include studies on cosmic expansion dynamics and the development of novel methods for analyzing large-scale structure surveys. Education: Ph.D., Astronomy and Space Sciences, Cornell University, 2011 M.S., Astronomy and Space Sciences, Cornell University, 2009 M.S., Physics, Indian Institute of Technology Kanpur, 2006 B.S., Physics, St. Stephen's College, Delhi University, 2004 Agarwal has received several honors, including the Institute for Gravitation and the Cosmos Postdoctoral Fellowship (2014) and a Gravity Research Foundation essay award (2013). His research is supported by grants such as the Templeton Foundation-funded 'CosmoArchaeology: Digging for the Initial State' (2012), emphasizing interdisciplinary exploration of cosmic origins. His work bridges fundamental physics and cosmological observations, with ongoing projects addressing quantum gravitational effects, early universe dynamics, and observational tests of gravity theories. Agarwal collaborates widely, contributing to initiatives like the Sloan Digital Sky Survey III and advancing theoretical methods in cosmology.

• Statistics
• Machine Learning
• Bioinformatics
• +۴ مورد دیگر

Ping Ma is a Professor of Statistics with a courtesy appointment in Computer Science at the University of Georgia. His research focuses on developing innovative statistical and machine learning methodologies for complex high-dimensional data, with applications spanning bioinformatics, computational biology, social network analysis, and anomaly detection in power systems. Research interests include: Statistical Methodology : Nonparametric modeling, optimal transport theory, subsampling techniques, and functional regression for large-scale data Computational Biology : Spatial transcriptomics analysis, single-cell data integration, virology classification, and gene regulatory networks Machine Learning Innovations : Knowledge distillation for LLMs, tensor analysis, quantum-inspired algorithms, and ensemble learning for model robustness His recent publications demonstrate a strong trend toward interdisciplinary applications, particularly in developing AI/statistical tools for biomedical research (47% of recent papers), advancing foundational machine learning techniques (33%), and solving engineering challenges like power grid security (20%). Methodologically, 67% focus on novel algorithm development while 33% refine existing techniques for scalability.

• Geometallurgy
• Resource Technology
• Mineral Exploration
• +۲ مورد دیگر

Jens Gutzmer is Professor and founding Director of the Helmholtz Institute Freiberg for Resource Technology (HIF) at Helmholtz-Zentrum Dresden-Rossendorf. His research focuses on developing sustainable technologies for mineral resource extraction and recycling, with expertise in geometallurgy, mineral characterization, and hydrothermal systems. He holds a visiting professorship at the University of Johannesburg and leads international collaborations in resource technology. Education includes a Diplom in Mineralogy (Technical University of Clausthal-Zellerfeld, 1993) and PhD in Geology (Rand Afrikaans University, 1996). His research investigates mineral deposit formation, resource recovery from secondary sources, and sustainable materials processing. Recent work emphasizes circular economy approaches for critical raw materials. Research encompasses geometallurgical process optimization, 3D mineral quantification, and novel extraction methods. Publications demonstrate consistent focus on resource efficiency, with recent articles exploring electrolyzer recycling, tailings reprocessing, and sustainable electronics design. Awards include: President Award of NRF South Africa (1999) Waldemar E. Lindgren Award (2002) TWAS Award (2007) Mercator Professorship (2003-2004) Directs HIF's research infrastructure including FlexiPlant for recycling 4.0 technologies and metallurgy pilot plants. Leads European Rare Earths Competency Network initiatives and advises Rock Tech Lithium Inc.

En-Hui Yangمشاهده پروفایل

استاد

• Information Theory
• Multimedia Compression
• Digital Communications
• +۳ مورد دیگر

Dr. En-Hui Yang is University Professor in Electrical and Computer Engineering at the University of Waterloo and founding Director of the Leitch-University of Waterloo Multimedia Communications Lab. A world-renowned expert in information theory, he co-developed the Yang-Kieffer algorithm for lossless compression and invented soft decision quantization technology used in smartphones and web browsers. His research spans multimedia compression, digital communications, and deep learning. Education: Ph.D. Electrical Engineering, University of Southern California (1996) Ph.D. Probability and Statistics, Nankai University (1991) B.Sc. Applied Mathematics, HuaQiao University (1986) His transformative work in data compression has impacted millions globally through technologies accelerating data transmission efficiency. Articles focus on optimization of video/image compression standards (HEVC/H.264), channel coding theorems, and novel compression algorithms. Scientific Awards: IEEE Eric E. Sumner Award (2021) Canada Research Chair - Tier 1 (2010, 2017) Fellow of the Royal Society of Canada (2009)

• Biomedical Engineering
• Signal Processing
• Machine Learning
• +۳ مورد دیگر

Dr Tianning Li is a Lecturer in Computing at the University of Southern Queensland's School of Mathematics, Physics and Computing. Affiliated with the School of Agriculture and Environmental Science, their research focuses on biomedical engineering, signal processing, and machine learning applications in clinical settings. Dr Li holds a PhD from USQ, an MAccFin from Adelaide, and a BISM from Nanjing. Core research interests include EEG signal analysis for anesthesia monitoring and epilepsy detection, with emphasis on developing novel signal processing techniques like spectral entropy analysis, synchroextracting transforms, and federated learning approaches. Their work bridges machine learning innovations with clinical diagnostics, addressing challenges in real-time medical signal interpretation and healthcare data efficiency. Recent publications (2021-2025) emphasize advancements in anesthesia depth assessment algorithms, seizure prediction methodologies, and lossless signal compression. Research trends reflect a strong focus on integrating neural networks (CNN-LSTM, 1D CNN) with traditional signal analysis frameworks to enhance clinical decision-making accuracy. No scientific awards are listed, but Dr Li maintains active research collaborations through affiliations with multiple departments. Supervision activities are not detailed in available records, though their work likely involves student contributions to biomedical computing projects. ORCID: 0000-0001-5142-8654 .

Antoine Miechمشاهده پروفایل

پژوهشگر

• Computer Vision
• Machine Learning
• Natural Language Processing
• +۷ مورد دیگر

Antoine Miech is a Researcher at DeepMind's Vision Group , with prior affiliations at Inria and Ecole Normale Supérieure where he completed his computer vision Ph.D. under Ivan Laptev and Josef Sivic . He has collaborated with researchers from Facebook AI and Google during his academic career. Research Interests span video understanding, weakly-supervised machine learning, and multimodal analysis. His work focuses on: Text-video embedding Self-supervised video representation Action localization Anticipatory video modeling Scalable multimodal learning Scientific Contributions include: HowTo100M - A massive dataset of narrated instructional videos MIL-NCE - A novel loss function for video-text alignment MEE - A model for handling heterogeneous data Context Gating - Learnable pooling architecture Awards & Recognition : Google Ph.D. Fellowship (2018) Technical Leadership : Created the LOUPE TensorFlow toolbox for feature pooling and maintained annotated video dataset catalogs. Organized the Data Science Game competition (2016-2017).

• Internal Medicine
• Clinical Quality Improvement
• Cardiovascular Disease Management
• +۳ مورد دیگر

Margaret Izabella Chustecki is an Associate Clinical Professor at the Yale School of Medicine's Department of Internal Medicine. She obtained her MD from Warsaw Medical School (1988) and an MBA from the Yale School of Management (2009). Her clinical practice focuses on improving healthcare efficiency through quality programs achieving NCQA accreditation and implementing initiatives like Meaningful Use and PQRS. She coordinates medical education for trainees while maintaining an active clinical practice. Education: MD - Warsaw Medical School (1988), MBA - Yale School of Management (2009) Clinical Experience: Extensive inpatient/outpatient internal medicine, hospitalist service leadership Practice Management: Founded Internal Medicine of Greater New Haven in 2003 Her research interests center on cardiovascular disease management, diabetes therapies, and healthcare quality improvement. She has led over 30 clinical trials evaluating treatments for cardiovascular conditions, diabetes, COPD, migraines, and osteoarthritis. Key areas of investigation include statin efficacy, anticoagulant therapies, and novel diabetes medications. Dr. Chustecki's clinical trials portfolio demonstrates expertise in cardiology, endocrinology, and gastroenterology. Recent studies focus on residual cardiovascular risk reduction, type 2 diabetes combination therapies, and migraine treatment innovations. Her work bridges clinical practice improvements with rigorous evidence-based research. Teaching contributions include supervising Yale medical students, PA trainees, and residents in both hospital and ambulatory settings. She actively participates in medical education program development and interprofessional team coordination. Labs/Teams: Collaborates with Yale New Haven Hospital teams in clinical trial execution and quality improvement initiatives.