جستجوی استاد راهنمای دانشگاهی

Zohreh Sharafiمشاهده پروفایل

استادیار

• Software Engineering
• Human Aspects of Software Engineering
• Gender Studies in Software Engineering
• +۷ مورد دیگر

Zohreh Sharafi is an Assistant Professor of Software Engineering in the Department of Computer and Software Engineering (GIGL) at Polytechnique Montréal. Previously, she served as a Senior Research Fellow in the Department of Electrical and Computer Engineering at the University of Michigan, Ann Arbor, where she worked with Dr. Westley Weimer and was awarded the prestigious NSERC Postdoctoral Fellowship. Prior to her academic career, she worked as a software engineer at Morgan Stanley, contributing to the firm's electronic trading platform and serving as principal architect of SURF, a market data simulator. Her educational background includes a Ph.D. in Computer Engineering from École polytechnique de Montréal under the supervision of Dr. Giuliano Antoniol and Dr. Yann-Gaël Guéhéneuc, a Master of Applied Science in Software Engineering from Concordia University, and a Bachelor of Computer Engineering from the University of Tehran. Dr. Sharafi leads the SENSE Lab, a multidisciplinary software engineering research laboratory focused on understanding problem-solving strategies developers use during software development, with particular attention to human factors such as gender and native language. Her research combines human-centric design with experimental methodologies, investigating cognitive processes involved in software development using biometric measures including eye tracking and neuroimaging. Current active projects include evaluating trustworthiness perceptions of software artifacts and studying the role of creativity in software engineering tasks. She has made significant contributions to understanding how gender influences program comprehension and code review processes. Her publication record demonstrates a strong focus on empirical methods in software engineering, particularly eye tracking and neuroimaging techniques to study developer cognition. Her work spans program comprehension, code review, requirements engineering, and the impact of human factors on software development processes. She has developed methodological frameworks for conducting eye tracking studies in software engineering and has made notable contributions to understanding how visualization techniques affect software development tasks. NSERC Postdoctoral Fellowship NSERC Discovery Grant Program and Launch Supplements (Sep 2024-Sep 2029) IVADO Startup & Operation Fund (Jan 2022-Jan 2023) Scholarship for Doctoral Studies from Fonds de Recherche du Quebec Distinguished Reviewer Awards from IEEE ICPC 2020 and ACM FSE 2024 Dr. Sharafi actively mentors students including Mahta Amini (PhD Candidate, IVADO Scientifique en résidence 2024 Laureate), Cameron Cherif (PhD Candidate), Sara Yabesi (Master's Student), and Anthonia Njoku (Graduate research intern). She serves on numerous conference organizing committees including as Local Arrangement Chair for SANER 2025, Program Co-chair for SEMLA 2024, and as a reviewer for top-tier journals including IEEE Transactions on Software Engineering and ACM Computing Surveys. Her research is supported by multiple grants focused on understanding human factors in software engineering through empirical methods. At Polytechnique Montréal, Dr. Sharafi directs the SENSE Lab which brings together computer scientists, cognitive scientists, and software engineering researchers to investigate the cognitive aspects of software development. The lab employs advanced methodologies including eye tracking, functional near-infrared spectroscopy (fNIRS), and functional magnetic resonance imaging (fMRI) to study how developers comprehend, navigate, and modify software systems. Current projects examine trustworthiness perceptions in code review, the role of creativity in software engineering tasks, and gender differences in software development processes.

Duminda Wijesekeraمشاهده پروفایل

استاد

• Cybersecurity
• Cyber-Physical Systems
• Digital Forensics
• +۵ مورد دیگر

Duminda Wijesekera serves as Professor in the Department of Cyber Security Engineering and Department of Computer Science at George Mason University, where he was inaugural chairman of the Cyber Security Engineering Department until December 2022. He concurrently held the position of visiting research scientist at the National Institute of Standards and Technology (NIST) from 2007-2022 and maintains status as a fellow at the Potomac Institute of Policy Studies. He leads the Mason Innovation Laboratory at Mason Square, driving translational research in cyber-physical security. His educational foundation includes: PhD in Computer Science, University of Minnesota (1997) PhD in Mathematical Logic, Cornell University (1990) BSc in Mathematics, University of Colombo Professor Wijesekera's research centers on cyber-physical system security , with pioneering work in Intelligent Transportation Systems spanning trains, aircraft, and connected vehicles. His digital forensics innovations establish frameworks for evidence-based scenario reconstruction and error management, while his formal methods research provides mathematical guarantees for safety-critical systems. Current projects address Next G-based edge services, digital twin vulnerability detection, and healthcare security architectures, consistently bridging theoretical rigor with real-world infrastructure protection. Analysis of his 2022-2025 publications reveals intense focus on autonomous vehicle security (38% of recent output), including traffic signal control optimization, ramming attack countermeasures, and CARLA-based scenario validation. Digital forensics using AI (20%) and secure manufacturing/edge computing (27%) constitute other major thrusts, demonstrating how formal verification and machine learning converge to solve complex cyber-physical security challenges across transportation, energy, and healthcare domains. His scientific recognition includes: CCI Impact Award (2022) for groundbreaking cyber-physical security contributions Fellowship at the Potomac Institute of Policy Studies for cybersecurity policy leadership Professor Wijesekera has secured substantial research funding through: NIST grants for health record security frameworks (2014-2015) US Department of Transportation projects on wireless frequency mapping for high-speed rail (2013-2014) Cyber Security Research Alliance funding for trust architectures in cyber-physical systems (2014) Commonwealth Cyber Initiative awards for autonomous vehicle security and energy-efficient manufacturing His industry partnerships with Honeywell and NIST ensure practical impact of theoretical research. The Mason Innovation Laboratory under his direction serves as an interdisciplinary hub for cyber-physical security, integrating researchers from computer science, electrical engineering, and policy studies to develop deployable solutions for transportation networks, power grids, and critical infrastructure protection.

Alyson M. Brooksمشاهده پروفایل

دانشیار

• Galaxy Formation and Evolution
• Galactic Structure
• Cosmological Simulations
• +۵ مورد دیگر

Alyson M. Brooks is an Associate Professor in the Department of Physics and Astronomy at Rutgers University, part of the School of Arts and Sciences. Her research focuses on galaxy formation and evolution, particularly using cosmological simulations to study dark matter dynamics, stellar abundances, and galactic structures. She holds a PhD in Astronomy from the University of Washington (2008) and has held prestigious fellowships, including the Sherman Fairchild Fellowship at Caltech and the Grainger Postdoctoral Fellowship at UW-Madison. Brooks has been recognized with awards such as the 2015 Alfred P. Sloan Research Fellowship and the 2019 Maria Goeppert Mayer Award from the American Physical Society. Her educational background includes a B.A. in Physics with Astronomy from Macalester College (2000) and an M.S. in Astronomy from the University of Washington (2004). Her research interests span topics like the interplay between baryonic processes and dark matter, chemical evolution in dwarf galaxies, and the role of feedback mechanisms in galaxy formation. Brooks is actively involved in outreach, including founding the RU-PREP program to support undergraduate research and mentoring initiatives. Brooks has authored over 100 refereed publications, with recent work exploring the resolved stellar populations of dwarf galaxies using the James Webb Space Telescope and analyzing dark matter halo properties through simulations. Her scientific contributions have advanced understanding of galaxy kinematics, dark matter interactions, and the evolution of galactic structures across cosmic time.

Kamal Sarabandiمشاهده پروفایل

استاد

• Applied Electromagnetics
• Radar Remote Sensing
• Antenna Design
• +۶ مورد دیگر

Kamal Sarabandi is the Rufus S. Teesdale and Fawwaz T. Ulaby Distinguished University Professor of Electrical Engineering and Computer Science at the University of Michigan. He leads the Radiation Laboratory, renowned for research in applied electromagnetics, radar remote sensing, and antenna technology. His academic rank is Professor, and he holds affiliations with the College of Engineering. His research spans radar systems for environmental monitoring (e.g., soil moisture, snowpack), automotive radar for autonomous vehicles, metamaterials for antenna miniaturization, and security applications like concealed weapons detection. He has advised over 60 PhD students, many of whom hold academic or industry leadership roles globally. Awards and Recognition: National Academy of Engineering member, IEEE Picard Medal, Humboldt Award, Ellis Island Medal of Honor, and Stephen S. Attwood Award. His work bridges fundamental science with practical innovations, including NASA collaborations and military/defense applications. Labs and Teams: Directs the Radiation Laboratory, a hub for applied electromagnetics and radar innovation. Collaborates with industry (e.g., Qualcomm, SAIC) and government agencies (NASA, Army Research Lab) on projects like the COMBAT center for autonomous systems. Education: Earned his PhD in Electrical Engineering from the University of Michigan (1989). Alumni of his lab include professors at UW-Madison, Purdue, and international institutions.

Petteri Nurmiمشاهده پروفایل

استاد

• Environmental Monitoring
• Internet of Things (IoT)
• Artificial Intelligence (AI)
• +۷ مورد دیگر

Petteri Nurmi is a Professor of Computer Science at the University of Helsinki, affiliated with the Department of Computer Science and the Helsinki Institute of Sustainability Science (HELSUS). His research focuses on IoT systems, environmental monitoring, AI-driven solutions, and sustainable computing. He leads projects such as the NordForsk-funded initiative (2024-2028) and the Team Finland Knowledge programme (2024-2026), emphasizing large-scale IoT deployments and quantum computing integration. Key research interests include drone-based air quality monitoring, low-cost sensor networks, and AI applications in environmental science. Nurmi has published extensively in top venues like IEEE IoT Journal and ACM workshops. His work bridges technical innovation with societal challenges, such as urban pollution reduction and sustainable resource management. He supervises doctoral students in the Computer Science program and collaborates internationally on projects like underwater plastic detection (SEAGULL) and smart city infrastructure. Nurmi’s contributions to edge computing and pervasive sensing have been recognized through grants totaling over €2M. His lab develops tools for data-intensive systems, including thermal imaging for energy efficiency analysis and AI-driven sensor fusion frameworks.

Justin Wanمشاهده پروفایل

استاد

• Scientific Computing
• Computer Graphics Simulation
• Medical Image Processing
• +۴ مورد دیگر

Justin Wan is a Professor in the Department of Computer Science at the University of Waterloo. His research focuses on scientific computing, medical image processing, computational finance, and machine learning. He holds a Ph.D. from UCLA (1998), an M.A. from UCLA (1995), and a B.Sc. from the Chinese University of Hong Kong (1992). Wan’s work bridges numerical methods, optimization, and deep learning, with applications in financial modeling, medical imaging, and fluid dynamics. His research interests include advanced techniques in scientific computing (e.g., multigrid methods), computer graphics simulation, and medical image enhancement (e.g., CT scan artifact reduction). He has pioneered applications of machine learning to computational finance, including option pricing and hedging using deep neural networks and GANs. His recent work explores denoising diffusion models and multi-agent systems for optimal execution in finance. Publications span topics like volatility surface computation, optimal mass transport for image registration, and parallel solvers for fluid dynamics. His methods address challenges in high-dimensional problems, robust numerical valuation, and scalable algorithms for large datasets. Wan collaborates across disciplines, integrating mathematical rigor with practical engineering solutions.

Samuel Chengمشاهده پروفایل

دانشیار

• Information Theory
• Signal and Image Processing
• Remote Sensing
• +۴ مورد دیگر

Dr. Samuel Cheng is an Associate Professor at the Gallogly College of Engineering , University of Oklahoma , specializing in Electrical and Computer Engineering . He holds a Ph.D. in Electrical Engineering from Texas A&M University (2004), preceded by M.S. and M.Phil. degrees from the University of Hawaii and Hong Kong University of Science and Technology. Education: B.S. (University of Hong Kong, 1995), M.Phil. (HKUST, 1997), M.S. (University of Hawaii, 2000), Ph.D. (Texas A&M, 2004) Professional Experience: Senior Research Engineer at Advanced Digital Imaging Research (2004-2005), prior internships at Microsoft Asia and Panasonic Technologies His research focuses on Information Theory , Signal and Image Processing , and Pattern Recognition , with applications in remote sensing, urbanization analysis, and disaster monitoring. His publications span topics including urban impervious surface mapping , nighttime light analysis , and machine learning for environmental data . His work often integrates multi-source datasets (e.g., Landsat, LiDAR, social media) for spatiotemporal modeling. Technical Expertise: Spectral unmixing, machine learning, thermal remote sensing, GIS integration Key Applications: Power outage detection, vegetation-crime correlation, PM2.5 estimation, smart meter data fusion Dr. Cheng holds three US patents in digital watermarking and is affiliated with IEEE, Sigma Xi, and AAAS. His recent articles demonstrate a trend toward leveraging AI for remote sensing challenges and analyzing urbanization impacts on ecosystems.

Paul Midgleyمشاهده پروفایل

استاد

• Electron Microscopy
• Materials Science
• Crystallography
• +۳ مورد دیگر

Professor Paul Midgley is a leading academic in Materials Science at the University of Cambridge's Department of Materials Science and Metallurgy, serving as Professor since 2007 and Head of Department from 2018–2020. He is a Fellow of Peterhouse College and holds multiple prestigious awards, including the Royal Society Fellowship and the Ernst Ruska Prize. Education: PhD in Physics (University of Bristol, 1991), MSc (Distinction) in Semiconductor Materials (1988), BSc (Hons) Physics (1987). Administration: Director of the Wolfson Electron Microscopy Suite, and active on various University committees including Research, Teaching, and REF. His research focuses on advanced electron microscopy techniques such as convergent beam diffraction, electron tomography, and nanostructure analysis, with applications in nanoscale materials science and 3D reconstruction using compressed sensing. He has pioneered methods like precession electron diffraction and multi-dimensional electron microscopy, contributing to fields like plasmonic nanoparticles and catalytic materials. Key Research Themes: Electron crystallography, nanomaterial characterization, energy materials, and defect analysis in perovskites. Midgley has delivered over 20 invited/plenary lectures globally, including at EUROMAT, the Welch Symposium, and the John Cowley Memorial Lecture. His grant income exceeds £16M as Principal Investigator. Labs/Teams: Leads the Wolfson Electron Microscopy Suite and collaborates internationally on microscopy advancements and materials innovation.

Derek Keirمشاهده پروفایل

دانشیار

• Earth Science
• Structural Geology
• Tectonics
• +۵ مورد دیگر

Dr. Derek Keir is an Associate Professor in Earth Science within the Ocean and Earth Science department at the University of Southampton. He specializes in passive seismology, remote sensing, geochemistry, and field geology to study earthquakes and volcanoes in Africa, Arabia, the Caribbean, and Italy. He leads the Geology and Geophysics research group and serves as Chief Editor of the Structural Geology and Tectonics section in Frontiers in Earth Science , and holds editorial roles in Volcanology and Structural Geology. Education: MSci Geology and Geophysics (Imperial College London, 1998-2002), PhD in Tectonics and Seismology (Royal Holloway University of London, 2002-2006). Previous roles include NERC Research Fellow (University of Leeds, 2007-2011) and Lecturer (University of Southampton, 2011-2015). Research focuses on continental rifting, magmatic systems, and geothermal resources. Notable projects include the South Tanganyika Active Rift Seismicity study (sponsored by Beach Energy) and investigations into the lithospheric structure of the Ontong Java Plateau (NERC-funded). His work combines seismology, InSAR, and geochemical analyses to understand tectonic processes. Publications highlight contributions to understanding volcanic subsidence (Dallol), rift-scale magmatic inflation in Afar, and seismic hazard in the Apennines. Awards include the 2024 Nature Paper (Coevolution of craton margins), Jason Morgan Early Career Award (2011), and Bullerwell Award (2013). Supervises PhD students in INSPIRE programs and collaborates on international projects like the Afar Dallol Drilling initiative. His research bridges field observations with advanced geophysical modeling to advance continental dynamics understanding.

• Machine Learning
• Data Mining
• High-Performance Computing
• +۵ مورد دیگر

Prof. Dr. Fabian Gieseke is a Professor and Chair of Machine Learning and Data Engineering at the University of Münster. He holds a PhD in Computer Science from Carl von Ossietzky University of Oldenburg and a dual degree in Mathematics and Computer Science from the University of Münster. His research focuses on Machine Learning, High-Performance Computing, and their applications in Geosciences, Smart Cities, and Astrophysics. Education: PhD in Computer Science (2012), Carl von Ossietzky University of Oldenburg University studies in Mathematics and Computer Science (2006–2011), University of Münster Research Interests: Data Mining and Machine Learning High-Performance Computing & Distributed Systems Deep Learning Applications in Environmental Science and Astrophysics Geospatial Data Analysis using Satellite Imagery Publications Trends: His recent work emphasizes large-scale environmental monitoring via deep learning, including canopy height estimation, forest biomass prediction, and national-scale tree counting. He also explores interactive systems for geospatial data retrieval and optimization of machine learning models for resource-constrained environments. Advising & Grants: Supervised over 30 theses on topics like satellite image analysis, deep learning on microcontrollers, and data marketplaces for smart grids. Active in securing grants for interdisciplinary projects combining AI with Earth observation. Labs/Teams: Leads the Machine Learning and Data Engineering group at the University of Münster, focusing on scalable AI solutions for real-world challenges in science and industry.

Jennifer L. Westمشاهده پروفایل

استاد

• Biomaterials
• Nanotechnology
• Tissue Engineering
• +۳ مورد دیگر

Jennifer L. West is the Dean of the University of Virginia School of Engineering and Applied Science and holds the Saunders Family Professorship in Engineering. She is a dual professor in Biomedical Engineering and Mechanical and Aerospace Engineering. Dean West has a 30-year record as a researcher, educator, inventor, and entrepreneur, focusing on biomaterials, nanotechnology, and tissue engineering to address unmet medical needs, particularly in cancer therapy. Her education includes a B.S. from MIT (1992) and a Ph.D. from the University of Texas at Austin (1996). Before UVA, she was at Duke University as the Fitzpatrick Family Distinguished Professor of Engineering and Associate Dean for Ph.D. Education. Research Interests: Biomaterials and biosynthesis Nanotechnology and tissue engineering Cancer therapy through engineered materials Scientific Awards: Member of the National Academy of Medicine (2023) Member of the National Academy of Engineering (2016) Over 20 patents, including foundational work for Nanospectra Biosciences’ clinical trials in cancer therapy Grants & Initiatives: Leading UVA Engineering’s focus on research, experiential learning, and entrepreneurship Recipient of a $900,000 grant for character-building education initiatives Labs & Teams: Developed hydrogel platforms for tissue integration, vascularization, and drug delivery Pioneered gold nanoshell-based photothermal cancer therapy

Brian Calderمشاهده پروفایل

استاد پژوهش

• Seafloor Characterization
• Seabed Mapping
• Bathymetric Data Processing
• +۱۲ مورد دیگر

Brian Calder is a Research Professor at the Center for Coastal and Ocean Mapping, University of New Hampshire, with a strong affiliation in Ocean Engineering and Earth Sciences. He holds a Ph.D. and M.S. in Image Analysis and Electronics Communications Engineering from Heriot-Watt University. His academic work is centered on advanced methods in seafloor characterization and hydrographic data processing. Ph.D., Image Analysis, Heriot-Watt University M.S., Electronics Communications Eng, Heriot-Watt University His research focuses on the development and application of computational techniques for seabed mapping, bathymetric uncertainty modeling, and autonomous ocean sensing. He integrates machine learning, signal processing, and remote sensing to improve the accuracy and reliability of marine geospatial data. His work supports navigation safety, coastal zone management, and deep-ocean exploration. Recent publications highlight trends in automated nautical chart generalization, trusted community bathymetry systems, and wireless ocean-of-things networks for volunteer data collection. His article portfolio reveals a strong emphasis on data quality, uncertainty quantification, and algorithmic innovation in hydrography and marine geodesy. Brian Calder has received multiple research grants, primarily from NOAA and the U.S. Navy, supporting projects such as IT support for NOAA personnel at UNH, development of bathymetric uncertainty models, and autonomous mapping using Saildrone technology. These grants reflect sustained funding and recognition in the field of hydrographic science. He teaches graduate courses including Seafloor Characterization , Seabed Mapping , and Doctoral Research , indicating active mentorship and academic leadership. His work is conducted within the Center for Coastal and Ocean Mapping, a leading institution in hydrographic research, where he collaborates extensively with experts like Yuri Rzhanov, Larry Mayer, and Christos Kastrisios.

• Bioprocessing
• Biomedical Engineering
• Bioreactor Engineering
• +۴ مورد دیگر

James M. Piret is a Professor at the University of British Columbia (UBC), affiliated with the School of Biomedical Engineering and the Michael Smith Laboratories. He holds a Sc.D. from MIT (1989), an S.M. from MIT (1986), and an A.B. from Harvard College (1981). His research focuses on bioprocessing, biomedical engineering, and cell therapy biotechnology, with emphasis on optimizing therapeutic cell production and biomanufacturing processes. Education : Sc.D. in Chemical Engineering, Massachusetts Institute of Technology (1989) S.M. in Chemical Engineering, Massachusetts Institute of Technology (1986) A.B. in Chemistry, Harvard College (1981) Professor Piret’s research integrates bioreactor engineering, Raman spectroscopy, and data analytics to advance cell-based therapies for diseases like cancer and diabetes. Collaborations with stem cell biologists (e.g., Drs. Kieffer and Levings) and engineers (Drs. Turner and Gopaluni) drive innovations in bioprocess optimization and device development. His lab emphasizes multidisciplinary approaches to accelerate biotechnology production processes and cell therapy manufacturing. Awards : William F. Meggers Award (2022) R.S. Jane Memorial Award (2015) Cell Culture Engineering Award (2012) Fellow, Chemical Institute of Canada (2004) His work includes developing novel methodologies for CHO cell glycosylation engineering, optimizing fed-batch bioreactor systems, and advancing Raman spectroscopy techniques for real-time cell analysis. The lab actively recruits motivated graduate and postdoctoral researchers to tackle high-impact challenges in biomedical and chemical engineering.

Biondo Biondiمشاهده پروفایل

استاد

• Seismic Imaging
• Geophysics
• Computational Geosciences
• +۶ مورد دیگر

Biondo Biondi is the Barney and Estelle Morris Professor of Geophysics at Stanford University, affiliated with the School of Earth Sciences. He leads the Stanford Exploration Project and holds roles such as Chair of the Geophysics Department (2019–2022) and Director of the Stanford Earth Imaging Project (1998–Present). His research focuses on seismic imaging algorithms, computational geophysics, and fiber-optic sensing technologies. He earned his Ph.D. (1990), M.S. (1987) in Geophysics from Stanford, and M.Sc. in Electrical Engineering from Politecnico di Milano (1984). Dr. Biondi's research emphasizes improving seismic data imaging through advanced computational methods. He pioneered urban seismic monitoring using preexisting telecommunication fibers, enabling cost-effective subsurface analysis. His work integrates machine learning and high-performance computing to address challenges in reservoir imaging, CO2 monitoring, and infrastructure health. Key research areas include distributed acoustic sensing (DAS), ambient noise tomography, and inverse theory applications. He has authored over 180 publications and received awards like the SEG Honorable Mention (2019, 2016, 2009) and the Distinguished Instructor Short Course (2007). His teaching includes courses like 3-D Seismic Imaging and Reflection Seismology, and he advises graduate students in geophysics and computational science. Collaborations span industry (e.g., Schlumberger, Saudi Aramco) and global institutions. Biondi’s administrative contributions include co-directing the Stanford Earth Sciences Algorithms and Architectures Initiative and serving on editorial boards like the SIAM Journal on Imaging Sciences. His lab’s innovations bridge geophysics with emerging technologies, advancing both academia and industry applications in energy, environment, and urban infrastructure.

• Machine Learning
• Deep Learning
• Graph Analysis
• +۶ مورد دیگر

Michalis Vazirgiannis is a Professor at LIX, École Polytechnique (France) leading the Data Science and Mining (DaSciM) group. With academic backgrounds in Physics (Athens University), AI (Heriot-Watt University), and Informatics (Athens University), he has conducted research at Fraunhofer, Max Planck MPI, and INRIA/FUTURS while teaching at institutions across Greece, France, China, and Spain. His research spans Machine/Deep Learning for Graphs (GNNs, graph kernels, embeddings) Text Mining & NLP (Graph-of-Words, biomedical text analysis) Combinatorial Optimization for pandemic forecasting and energy systems Event/Anomaly Detection in time series and sensory data Industrial collaborations with Airbus, Google, Tencent, and BNP . He has supervised 29 completed PhD theses, published over 250 papers, and received prestigious awards including Marie Curie and Tencent Rhino-Bird Fellowships. His team leads the ANR-HELAS Chair (2020-2025) focusing on heterogeneous data deep learning.