جست‌وجوی استاد و پژوهشگر

Rafeef Garbiمشاهده پروفایل

استاد

• Artificial Intelligence
• Medical Image Computing
• Computer Vision
• +۷ مورد دیگر

Dr. Rafeef Garbi is a Professor at the Department of Electrical and Computer Engineering, University of British Columbia, and the Founder/Director of the Biomedical Signal and Image Computing Laboratory (BiSICL). Her multidisciplinary research integrates artificial intelligence, computer vision, and medical imaging for clinical applications in pediatric orthopedics, oncology, and neurology. PhD (Chalmers University, Sweden), MSc (with distinction), Technical Licentiate Research Focus: Specializing in Medical Image Computing and Visual Computing , her lab develops AI-driven solutions for: Automated segmentation and analysis of multi-dimensional biomedical data Clinically-translatable biomarkers for disease assessment Computer-aided intervention systems in surgical contexts Scientific Leadership: UBC Killam Faculty Research Fellow Peter Wall Institute for Advanced Studies Early Career Scholar Senior IEEE Member & Founding IEEE EMBS Vancouver Section Member Key Collaborations: Active in the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society and CAIDA: UBC ICICS Centre for Artificial Intelligence Decision-making and Action. Her team bridges engineering, medicine, and computational biology through translational research.

Liqiang Wangمشاهده پروفایل

استاد

• Big Data Analytics
• High-Performance Computing (HPC)
• Parallel Computing
• +۳ مورد دیگر

Liqiang Wang is a Professor in the Department of Computer Science at the University of Central Florida (UCF), where he directs the Big Data Lab. Previously, he served as faculty at the University of Wyoming (2006-2015). He holds a Ph.D. in Computer Science from Stony Brook University (2006) and spent a visiting research period at IBM T.J. Watson Research Center (2012-2013). His research focuses on big data analytics, high-performance computing, parallel systems optimization, and applying deep learning to detect programming errors and enhance model robustness. Education: Ph.D., Computer Science, Stony Brook University (2006); Visiting Researcher, IBM Watson (2012-2013). Research Interests: Improving accuracy and security of big data models, optimizing parallel computing systems (HPC, Cloud, GPUs), program analysis for concurrency errors, and deep learning applications in anomaly detection and adversarial robustness. Notable projects include scalable LSQR algorithms for seismic tomography and the OpenMP Analysis Toolkit (OAT) for concurrency error detection. Key Awards: NSF CAREER Award (2011), Castagne Faculty Fellowship (2013-2015), UCF Mid-Career Refresh Award (2020), and grants including a $50K NSF CIVIC-PG grant (2022) and Google/Meta donations. Advising and Grants: Supervises over 20 Ph.D./M.S. students and has secured grants totaling over $100K. Notable collaborations include seismic tomography with NCAR and cloud computing optimization. Labs/Teams: Director of UCF’s Big Data Lab, collaborating on projects like Parallel LSQR and Anti-Neuron Watermarking.

Nabil Kahaleمشاهده پروفایل

دانشیار

• Financial Derivatives
• Monte Carlo Methods
• Optimization
• +۳ مورد دیگر

Nabil Kahale is an Associate Professor of Finance at ESCP Business School in Paris. His research focuses on financial derivatives, Monte Carlo methods, optimization, and machine learning. He holds a PhD in theoretical computer science from MIT (1993) and an HDR (French habilitation) from Université Paris 1 Panthéon-Sorbonne (2020), enabling him to supervise PhD students. His academic career includes prior roles in theoretical computer science and consulting for banks. He has published widely in top journals such as Mathematical Finance , Management Science , and SIAM Journal on Computing . Education: Bachelor of Science in Engineering, École Polytechnique (1987) PhD in Theoretical Computer Science, MIT (1993) HDR in Economics, Université Paris 1 Panthéon-Sorbonne (2020) Research Interests: His work bridges finance and computational methods, emphasizing practical applications of stochastic models and algorithmic efficiency. Key areas include derivative pricing, risk management, and the integration of machine learning into financial systems. Professional Contributions: He has served as a consultant for banking institutions and a referee for the French Ministry of Economy and Finance. His research also intersects with social and economic policy analysis, such as evaluating the economic impact of public health measures. Labs/Teams: While no specific lab affiliation is mentioned, his collaborations span interdisciplinary teams in finance, computer science, and applied mathematics through his publications and consulting work.

• Augmented Reality
• Computer Vision
• Human-Computer Interaction
• +۴ مورد دیگر

Dr. Alexander Plopski is an Assistant Professor at the Institute of Visual Computing, Technische Universität Graz. His research focuses on advancing augmented reality (AR) technologies, human-computer interaction (HCI), and optical display systems. He holds a PhD, M.Sc., and BSc in relevant fields. His work emphasizes perceptual optimization in AR displays, eye tracking integration, and accessibility solutions for color vision deficiencies. Key research areas include gaze-contingent AR interfaces, light field manipulation for extended reality, and multimodal interaction techniques. Notable contributions include the development of the 'guitARhero' interactive AR guitar tutorial system and studies on focal distance effects in optical see-through displays. His publications span topics from AR display calibration to gesture recognition using radar sensing. He has explored applications in industrial training, medical AR, and robotic telemanipulation. His work often bridges theoretical perceptual studies with practical system implementations, aiming to enhance user experience and accessibility in AR/VR environments.

Guofu Niuمشاهده پروفایل

استاد

• Semiconductor Devices
• Compact Modeling
• RF Circuit Design
• +۳ مورد دیگر

Guofu Niu is a Professor in the Department of Electrical and Computer Engineering at Auburn University, holding the Ed and Peggy Reynolds Family endowed chair. His research specializes in semiconductor device physics, compact modeling of SiGe heterojunction bipolar transistors (HBTs), FinFETs, and cryogenic electronics for RF and power applications. Key research areas include RF linearity characterization, avalanche effects, thermal noise, and low-temperature device performance. He has developed advanced models (e.g., Mextram) for circuit simulation tools, enhancing the accuracy of semiconductor design workflows. Publications focus on nano-scale device reliability, tunneling currents, and optimization of RF amplifiers, with applications in 5G technology and extreme-environment electronics. Collaborative projects span industry and academia to advance semiconductor modeling frameworks.

Antonis Papapantoleonمشاهده پروفایل

استاد

• Mathematical Finance
• Stochastic Processes
• Lévy Processes
• +۵ مورد دیگر

Antonis Papapantoleon is a Professor of Mathematical Finance at the Delft Institute of Applied Mathematics (DIAM), part of the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at TU Delft. He is also affiliated with the Delft FinTech Lab and serves as an Affiliated Researcher at the Institute of Applied and Computational Mathematics (IACM), FORTH. Previously, he held roles including Assistant Professor at the National Technical University of Athens (NTUA), Juniorprofessor at TU Berlin (2011–2017), and Deputy Professor at the University of Mannheim (2016–2017). His research focuses on stochastic systems, Lévy processes in finance, term structure/LIBOR modeling, systemic risk management, model-free methods, and applications of machine learning in finance. Key contributions include advancements in affine LIBOR models, systemic risk analysis, and copula-based risk allocation. His work has been published in top journals like Annals of Applied Probability , Mathematical Finance , and Finance and Stochastics . His research has been supported by the Hellenic Foundation for Research and Innovation (HFRI), Europlace Institute of Finance, DAAD, MATHEON, and private corporations. He has delivered invited talks globally and co-edited Advanced Modelling in Mathematical Finance (Springer, 2016). Current affiliations include leadership in the Delft FinTech Lab and active participation in international collaborations. His work bridges theoretical stochastic analysis with practical financial applications, emphasizing robust frameworks for risk measurement and derivatives pricing.

Sanat K. Sarkarمشاهده پروفایل

استاد

• Multiple Testing
• Statistical Methodologies
• High-Dimensional Statistical Inference
• +۱ مورد دیگر

Sanat K. Sarkar serves as a Professor in the Department of Statistics, Operations, and Data Science at Temple University's Fox School of Business and Management. An internationally renowned expert, he has pioneered foundational work in multiple testing theory with applications spanning genomics, neuroimaging, and high-dimensional data analysis. His methodological innovations address critical challenges in false discovery rate control under complex dependency structures. Research Interests: Dr. Sarkar specializes in Multiple Testing, Statistical Methodologies, High-Dimensional Statistical Inference, and Multivariate Statistics. His work develops rigorous frameworks for hypothesis testing in modern scientific contexts where thousands of simultaneous tests are performed, ensuring reliable discoveries in fields like genetic association studies and brain connectivity mapping. Key contributions include adaptive FDR procedures and methods for structured hypothesis groups. Publication Trends: Over 2020-2025, his 11 publications demonstrate sustained leadership in refining false discovery rate methodologies. Recent work tackles correlated data (2025), knockoff variable selection (2022), and hierarchical hypothesis structures (2021-2024), reflecting his focus on real-world applicability in biomedical big data. His research bridges theoretical statistics with practical computational solutions. Honors and Awards: Fellow, Institute of Mathematical Statistics Fellow, American Statistical Association Elected Member, International Statistical Institute Musser Award for Research Excellence (Fox School) Multiple Dean's Research Honor Roll Inductions Research Support and Service: Funded continuously by NSF and NSA grants, Dr. Sarkar co-organized the NSF-CBMS conference on Multiple Comparisons and serves on editorial boards of Annals of Statistics , American Statistician , and Sankhya . He regularly delivers invited talks at international venues and mentors junior researchers in statistical methodology development.

Patrick Dallasegaمشاهده پروفایل

دانشیار

• Supply Chain Management
• Industry 4.0
• Lean Construction
• +۷ مورد دیگر

Patrick Dallasega is an Associate Professor in the Department of Industrial Plants at the Faculty of Science and Technology of the Free University of Bolzano (Italy). He holds a PhD from the University of Stuttgart and has been a Visiting Scholar at Chiang Mai University (Thailand) and Worcester Polytechnic Institute (USA). His expertise spans supply chain management, Industry 4.0 integration in SMEs, lean construction methodologies, and sustainable production planning in ETO/MTO environments. He teaches Project Management and Industrial Plants courses in Industrial Mechanical Engineering programs. His research focuses on digital transformation in manufacturing, including smart mobile factories, augmented reality applications for training, and synchronization of production and on-site assembly processes. Collaborative projects like the AR-enhanced industrial training initiative with Memc aim to reduce errors and costs in complex industrial setups. His work emphasizes human-centered technology integration, sustainability, and real-time data utilization for adaptive production strategies. Education Bachelor/Master: Free University of Bolzano (Italy) MSc: Polytechnic University of Turin (Italy) PhD: University of Stuttgart (Germany) Research Interests Professor Dallasega’s research explores the intersection of Industry 4.0 technologies with lean manufacturing principles, particularly in complex Engineer-to-Order (ETO) and Make-to-Order (MTO) sectors. He investigates how digital twin frameworks, augmented reality (AR), and real-time data analytics can enhance supply chain resilience, reduce operational losses, and improve workforce training efficiency. His work also addresses sustainability challenges in mobile and distributed manufacturing systems, emphasizing eco-friendly logistics and smart factory design. Key Projects Recent collaborations include: Development of an AR-based training module to boost procedural knowledge retention in machinery setups Comparative studies on Industry 4.0 adoption in SMEs across Europe and Asia Framework for digital twin-driven quality control in precast manufacturing Grants & Advising No specific grants or student advisees are listed in the provided data. His focus remains on collaborative industry projects and institutional teaching responsibilities. Labs & Teams Involved in cross-disciplinary teams at the Free University of Bolzano, particularly in the NOI Techpark innovation hub. Leads initiatives on smart mobile factories and human-centered robotics applications in manufacturing environments.

• Artificial Intelligence
• Machine Learning
• Software Engineering
• +۶ مورد دیگر

Talal Shaikh is an Associate Professor at Heriot-Watt University's School of Mathematical and Computer Sciences in Dubai. He serves as Director of Undergraduate Studies and Programme Director for BSc Computer Science, BSc CS (AI), and MSc Software Engineering. With a decade of industry experience as a Chief Information Officer and Software Engineer, he bridges practical insights with academic research. Research Interests: Pervasive Computing, IoT/M2M, AI/ML, WiFi Sensing for Healthcare, Financial Machine Learning, Educational Technology Awards: Teaching Excellence Awards (2017/18), Fellow of the Higher Education Academy (FHEA), multiple Learning and Teaching Oscars (2016, 2017, 2018) His work spans Ubiquitous Computing and IoT , focusing on sensor networks and WiFi-based sensing for healthcare. In Artificial Intelligence , he applies ML to robotics, financial analytics, and educational innovation. Recent articles analyze Reinforcement Learning , Emotion Recognition , and WiFi Sensing applications. His teaching emphasizes student-centric learning, with over 100 supervised dissertations achieving distinctions. Collaborations include international conferences and interdisciplinary research in smart environments and adaptive systems.

Brian Dzwonkowskiمشاهده پروفایل

دانشیار

• Coastal Circulation
• Estuarine Dynamics
• Ocean Observing Systems
• +۶ مورد دیگر

Dr. Brian Dzwonkowski is an Associate Professor at the University of South Alabama's Stokes School of Marine & Environmental Sciences and a Senior Marine Scientist at the Dauphin Island Sea Lab. He holds a Ph.D. (2009) and M.S. (2003) in Marine Studies from the University of Delaware, and a B.A. in Mathematics (1999) from The College of New Jersey. Education: Ph.D., Marine Studies (Physical Oceanography), University of Delaware M.S., Marine Studies (Oceanographic Remote Sensing), University of Delaware B.A., Mathematics, The College of New Jersey His research focuses on coastal physical oceanography, examining how tides, winds, and river discharge drive water movement and layering in coastal systems. He investigates interactions between physical processes and biogeochemical cycling, with emphasis on hypoxia, harmful algal blooms, and ecosystem vulnerability to climate change. His work integrates in situ data, satellite observations, and numerical models across spatiotemporal scales. Recent publications highlight his expertise in hurricane-ocean interactions (e.g., J. Phys. Oceanogr. , 2022), shelf hypoxia dynamics (e.g., J. Geophys. Res. Oceans , 2021), and estuarine-shelf exchange processes. Collaborative projects span topics like Vibrio ecology (2024), compound fluvial-marine flooding (2021), and coastal climate resilience. Dr. Dzwonkowski mentors graduate and undergraduate students, including former Ph.D. advisees Steve Dykstra and Jeff Coogan. He contributes to coastal monitoring initiatives via the MyMobileBay.com platform and leads interdisciplinary studies on estuarine restoration (e.g., West Fowl River project).

Jacqueline McClearyمشاهده پروفایل

استادیار

• Astrophysics
• Cosmology
• Weak Gravitational Lensing
• +۴ مورد دیگر

Dr. Jacqueline McCleary is an Assistant Professor of Physics at Northeastern University's College of Science, specializing in observational cosmology with a focus on galaxy clusters and dark matter. She leads research using weak gravitational lensing to study cosmic structures, collaborating on projects like the COSMOS-Web (JWST), SuperBIT (balloon telescope), and LoVoCCS surveys. Her work leverages multi-wavelength data from space, stratospheric, and ground-based observatories. Education: M.S. in Astronomy (New Mexico State University), M.S. and Ph.D. in Physics (Brown University), Postdoctoral Fellow at NASA's Jet Propulsion Laboratory. She transitioned to Northeastern as an ADVANCE Future Faculty Fellow before becoming a tenure-track faculty member in 2022. Research Interests: Dark matter interactions, galaxy cluster dynamics, gravitational lensing techniques, and next-generation observational platforms. Her team develops advanced algorithms and instrumentation for high-resolution imaging. Recent Contributions: COSMOS-Web has enabled unprecedented observations of distant galaxies using JWST, while SuperBIT's stratospheric flights provide diffraction-limited data. Key publications focus on lensing surveys, data reduction techniques, and dark matter-halo relationships. Awards: Recognized as a Northeastern ADVANCE Future Faculty Fellow. Media Engagement: Regularly comments on space exploration, asteroid risks, and cosmic phenomena for public outlets.

Yong-Bin Kimمشاهده پروفایل

استاد

• Integrated Circuit Design
• Nanoelectronics
• High-Speed System Integration
• +۴ مورد دیگر

Yong-Bin Kim is a Professor in the Department of Electrical and Computer Engineering at Northeastern University, part of the College of Engineering. He has held prior positions at Intel Corp., Hewlett Packard Co., Sun Microsystems, and the University of Utah. His research focuses on integrated circuit design, nanoelectronics, bio-chip interfaces, and low-power VLSI systems. He has contributed to initiatives like the HPVLSI Lab and Microsystems and Electron Devices Lab. Education includes a B.S. in Electronic Engineering from Sogang University (Seoul, South Korea), an M.S. from the New Jersey Institute of Technology, and a Ph.D. in Computer Engineering from Colorado State University (1996). Research interests encompass high-speed low-power VLSI design, system-on-chip (SoC), physical VLSI CAD, and nanoelectronics. Specific areas include bio-sensor interface circuits, electronic neuron design, and adaptive robot controllers. Key projects involve compact power-efficient integrated circuits and high-speed transceiver design. Outstanding Paper Award, 2020 IEEE ISOCC South Korean Patent for Autonomous Impedance Calibration (2021) Best Paper Award, 2016 International SoC Design Conference Patent for Improved Receiver Circuit (2020) Patent for Method to Detect Trojan Circuits (2018) Advisees include graduate student Yixuan He. He has led research projects funded by Winchester Technology and Hynix Semiconductor, focusing on semi-self-calibration transceivers and tunable RF inductors. Labs include the HPVLSI Lab and Microsystems and Electron Devices Lab at Northeastern University, which focus on high-speed/low-power IC design and microfabrication technologies.

• Space Physics
• Magnetospheric Dynamics
• Plasma Turbulence
• +۶ مورد دیگر

Brian Walsh is an Associate Professor of Mechanical Engineering at Boston University, with affiliations in the Departments of Astronomy and Electrical and Computer Engineering. He holds a Ph.D. in Mechanical Engineering from Boston University (2011) and a B.A. from Colgate University (2006). His research focuses on experimental space physics and spacecraft instrumentation, particularly studying solar wind-magnetosphere interactions, magnetopause reconnection, and X-ray imaging techniques. His work investigates energy transfer from the Sun to Earth's space environment, with a primary focus on the magnetopause. Walsh develops instruments for NASA and ESA missions, including the LEXI lunar X-ray imager and the CuPID CubeSat. He has contributed to missions like SMILE and pioneered compact solar energetic particle telescopes. His research spans CubeSat-based observations and large-scale space missions, emphasizing cross-scale coupling and global magnetospheric dynamics. Key research interests include plasma turbulence, magnetosheath dynamics, and exosphere variability. Walsh collaborates on projects like the Trans-Heliospheric Survey and the Magnetospheric Constellation (MagCon), aiming to advance understanding of heliospheric plasma behavior. His work also addresses space weather prediction and instrument calibration, such as the Carruthers Observatory Student Solar Monitor (COSSMo). Walsh's recent studies explore solar wind acceleration, ionospheric outflow asymmetry, and the role of recirculated plasmasphere material in ring current dynamics. His contributions to instrumentation and mission design highlight his dual role as a researcher and engineer in aerospace and space physics.

Simon Neillمشاهده پروفایل

استاد

• Marine Renewable Energy
• Wave and Tidal Energy Resource Characterization
• Ocean Modeling
• +۶ مورد دیگر

Simon Neill is a Professor in Physical Oceanography at Bangor University’s School of Ocean Sciences, specializing in marine renewable energy, particularly tidal and wave energy resource characterization. He leads the MSc in Marine Renewable Energy and chairs IEC Technical Specification 62600-201 on tidal energy assessment. His research spans energy resource optimization, environmental impacts, and coastal management. He has secured £multi-million grants, including the £708k NERC-funded Southeast Asia Plastics project and the £7M European Regional Development Fund Smart Efficient Energy Centre. Education: PhD in Estuarine Physics (University of Strathclyde), BEng in Civil Engineering (University of Dundee), PGCertHE (Bangor University). Research Interests: Wave-tidal interactions, marine energy grid integration, sediment dynamics, microplastic dispersal, and climate change adaptation. He is lead sediment scientist at FORCE (Fundy Ocean Research Center for Energy) and contributes to the editorial board of Renewable Energy. Grants & Projects: NERC SEAmap: Marine Plastic Pollution Mitigation (2020-2023) European Regional Development Fund SEEC (£7M, 2019-2023) INTERREG ECOSTRUCTURE: Climate-Resilient Coastal Infrastructure (£3.5M, 2017-2020) Teaching: Module organizer for Marine Renewable Energy (MSc), Ocean Modelling (Undergraduate), and RV Prince Madog cruise. External examiner for Plymouth University’s MSc Marine Renewable Energy (2018-2022). Advising: Supervises PhD students researching underwater noise impacts, remote sensing for energy resources, microplastic dispersal, and estuarine energy modeling. Labs/Teams: Collaborates with FORCE, IEC, and industry partners like Repetitive Energy Ltd and Extra Mussel. Leads multi-institutional projects on estuarine dynamics and plastic pollution.

Yun Seong Songمشاهده پروفایل

دانشیار

• Physical Human-Robot Interaction
• Rehabilitation Robotics
• Wearable Devices
• +۳ مورد دیگر

Dr. Yun Seong Song is an Associate Professor in the Department of Mechanical and Aerospace Engineering at Missouri University of Science and Technology (Missouri S&T), directing the Physical Human-Robot Interaction Laboratory. He holds a Ph.D. from MIT (2012), M.S. from Carnegie Mellon University (2006), and dual B.S. degrees from Seoul National University (2004). Prior to joining Missouri S&T, he conducted postdoctoral research at EPFL (2012-13) and served as a postdoc/lecturer at Georgia Tech (2014-16). Recognized for both research and teaching excellence, he has received the NSF CAREER Award (2021) and Faculty Teaching Award (2019). His research focuses on the intersection of robotics and biomechanics, emphasizing physical human-robot interaction (pHRI), rehabilitation robotics, wearable devices, energy harvesting from human motion, and medical device design. Key projects include developing robots for overground interaction experiments and assistive technologies for mobility support. His lab explores human motor communication through stiffness modulation, haptic feedback systems, and energy-efficient human-assistance mechanisms. Notable achievements include pioneering interactive stairs for energy-efficient mobility and a light-touch based virtual cane for walking assistance. His work integrates mechanical engineering, control systems, and biomedical applications to advance assistive technologies and human-robot collaboration. Education: Ph.D. Mechanical Engineering, MIT (2012) M.S. Mechanical Engineering, CMU (2006) B.S. Mechanical Engineering & B.S.E. Computer Science, Seoul National University (2004) Awards: NSF CAREER Award (2021) Missouri S&T Faculty Teaching Award (2019) Lab Focus: Physical Human-Robot Interaction, Wearable Robotics, Biomechanical Energy Harvesting