جست‌وجوی استاد و پژوهشگر

Olga Vitekمشاهده پروفایل

استاد

• Statistical Science
• Machine Learning
• Mass Spectrometry
• +۵ مورد دیگر

Olga Vitek is a Professor at Northeastern University's Khoury College of Computer Sciences, with affiliated faculty status in the Department of Chemistry and Chemical Biology. Her research bridges statistical science and machine learning with mass spectrometry-based proteomics and systems biology, focusing on developing open-source software tools like MSstats and Cardinal for quantitative proteomic analyses and imaging. Education: PhD in Statistics (Purdue University), Postdoc at the Ruedi Aebersold Lab (Institute for Systems Biology) Leadership: Director of the Barnett Institute for Chemical and Biological Analysis Her work emphasizes: Statistical experimental design Signal detection in complex mass spectrometry data Causal inference in biomolecular networks Reproducible computational infrastructure Recent publications highlight advancements in quantitative proteomics , mass spectrometry imaging , and causal modeling , with applications spanning cancer research, immunology, and clinical diagnostics. Notable trends include deep learning integration for image analysis and open-source tool development for scalable, transparent workflows. Scientific accolades: Elected Fellow of the American Statistical Association 2021 Gilbert S. Omenn Computational Proteomics Award NSF CAREER award Chan-Zuckerberg Essential Open-source Software award Senior Member, International Society for Computational Biology

Ignacio Galiano Zurbriggenمشاهده پروفایل

استادیار

• Power Converter Modelling & Control
• Energy Systems Integration
• Renewable Energy Systems
• +۶ مورد دیگر

Ignacio Galiano Zurbriggen is an Assistant Professor in the School of Sustainable Energy Engineering at Simon Fraser University (SFU), holding a P.Eng. license. His expertise spans power electronics, energy systems integration, and sustainable energy engineering. He completed his Ph.D. in Electrical & Computer Engineering at UBC (2020), followed by M.Sc. degrees from UBC (2013) and SFU (2012), and a B.Sc. in Electrical Engineering from the National University of Córdoba (2010). His research focuses on power converter modeling/control, energy systems optimization, and multi-domain systems. Notable projects include ultra-fast MPPT algorithms for PV systems, LVRT improvements for wind turbines, and GaN-based PFC design. He teaches advanced courses like SEE 895 Special Topics III and serves as an Associate Editor for the IEEE Open Journal of Power Electronics. Recent work emphasizes grid-connected converter dynamics, microgrid optimization, and adaptive control strategies for renewable energy systems. His publications span IEEE Transactions on Power Electronics, Smart Grid, and leading conferences like APEC and ECCE.

• Catalytic Reaction Engineering
• CO2 Hydrogenation
• Methanation Processes
• +۵ مورد دیگر

Prof. Robert Güttel is the Director of the Institute for Chemical Engineering at the University of Ulm. He is a member of the Ulm Center for Thermal and Environmental Technology (UZWR) since 2016 and serves on its executive board. His work focuses on catalytic reaction engineering, particularly in CO2 utilization, methanation, Fischer-Tropsch synthesis, and process intensification. Research emphasizes catalyst design, reaction kinetics, and reactor modeling under dynamic conditions. Educations : Not explicitly stated in the provided text. His academic career is highlighted through his leadership roles and publications. Research Interests : Güttel’s research spans heterogeneous catalysis for CO/CO2 hydrogenation, transient kinetic analysis, polymeric reactors for extraterrestrial applications, and AI-driven reactor design. His team develops advanced catalysts (e.g., Ru/TiO2, cobalt@silica core-shell structures) and investigates novel reactor concepts like fibrous structured catalysts and sorption-enhanced processes. Recent work explores in-situ methanation on Mars and the impact of light on catalytic selectivity. Publications Trends : His 2024–2025 articles focus on low-temperature methanation beyond Earth, AI-based residence time analysis, and deactivation mechanisms. Studies highlight both experimental and computational approaches to optimize catalytic systems for sustainability and industrial relevance. Awards : No specific scientific awards mentioned in the text. Grants/Labs : Leads the Institute for Chemical Engineering at Ulm, collaborating on EU-funded projects related to power-to-X technologies and extraterrestrial chemistry. Active in developing lab-scale reactor systems and industrial partnerships for catalyst testing. Labs/Teams : Directs research groups focused on catalytic reactor design, transient kinetic methods, and sustainable process engineering. Collaborates with institutions on Mars habitat resource utilization and green hydrogen production systems.

Roman Kucمشاهده پروفایل

استاد

• Robotics
• Biomimetic Sensors
• Digital Signal Processing
• +۴ مورد دیگر

Roman Kuc is a Professor of Electrical Engineering at Yale University, affiliated with the School of Engineering & Applied Science. He directs the Intelligent Sensors Laboratory, focusing on biomimetic sensors for robotics and bioengineering. His research explores brain-based devices (BBDs), sonar sensing, and neuromorphic processing inspired by biological systems. He holds a BSEE from Illinois Institute of Technology and a PhD from Columbia University. Dr. Kuc’s work bridges signal processing, robotics, and bioengineering, with applications in autonomous systems and clinical diagnostics. He has published over 200 papers and authored textbooks like Electrical Engineering in Context and The Digital Information Age . Notable honors include an honorary doctorate from the Glushkov Institute of Cybernetics and the Yale Sheffield Distinguished Teaching Award. His research themes include cognitive mapping via sonar echoes, neural network-based classification of environmental features, and biomimetic approaches to echolocation. Recent work emphasizes sensorimotor integration and robust performance in uncertain environments. Scientific awards highlight his contributions to robotics, signal processing, and education. His lab develops systems that emulate biological sensory mechanisms, aiming to advance robotics, medical applications, and assistive technologies.

Nicola McConkeyمشاهده پروفایل

مدرس

• Neutrino Physics
• Quantum Technology
• Detector Development
• +۲ مورد دیگر

Nicola McConkey is an Ernest Rutherford Fellow and Lecturer in Particle Physics at the School of Physical and Chemical Sciences, Queen Mary University of London. She joined the Particle Physics Research Centre in 2024 and leads experimental work in neutrino interactions and detector development. Her affiliations include the Centre for Fundamental Physics and Centre for Experimental and Applied Physics. McConkey is an active member of international collaborations including SBND, DUNE, and MicroBooNE, where she contributed to the assembly of SBND and pioneered high-statistics measurements of electron-neutrino interactions using liquid argon detectors. Her research focuses on three primary domains: neutrino physics (particularly neutrino-argon scattering cross-sections), quantum technology applications for neutrino mass measurement, and liquid argon time projection chamber (LArTPC) detector development. McConkey's investigations aim to advance fundamental particle physics through precision measurements and technological innovation, with emphasis on improving detection capabilities for next-generation neutrino experiments. Publications predominantly explore neutrino interaction dynamics, cross-section measurements, and detector performance optimizations across MicroBooNE, SBND, and DUNE collaborations. Research trends demonstrate consistent focus on refining LArTPC technologies, developing machine learning applications for particle reconstruction, and probing beyond-Standard-Model physics through neutrino interactions. Scientific Awards: Ernest Rutherford Fellowship (2022) McConkey advises two PhD students (Oscar Chow, Yoshita Dabburi) and leads significant research funding including: STFC Grant: 'Piecing together the neutrino mass puzzle' (£431,666; 2024-2027) STFC Outreach Grant: 'Quantum Technologies for Neutrino Mass' (£99,999; 2024-2025) She coordinates research within the Particle Physics Research Centre laboratory and collaborates extensively within the SBND, DUNE, and MicroBooNE international teams, alongside leading the Quantum Technologies for Neutrino Mass collaboration developing novel measurement techniques.

• Biometrics
• Face Recognition
• Fairness in AI
• +۳ مورد دیگر

Ana Filipa Sequeira is a researcher affiliated with INESC TEC, Porto, Portugal, and the University of Porto. Her work spans biometrics, fairness in AI, and explainable artificial intelligence. She has contributed to advancements in face recognition, synthetic data applications, and bias mitigation through techniques like knowledge distillation and model compression. Institution: INESC TEC (Porto, Portugal) Research Themes: Face recognition, fairness, explainability, synthetic data, biometric security Her recent publications focus on addressing demographic biases in face recognition systems, developing privacy-preserving explainable methods, and evaluating synthetic data's impact. She collaborates extensively with researchers like Pedro C. Neto, Jaime S. Cardoso, and Naser Damer. Sequeira has participated in organizing and analyzing competitions such as FRCSyn, BIOSIG, and SYN-MAD, emphasizing robust evaluation frameworks. Her work intersects technical innovation with ethical considerations, advocating for responsible AI applications in biometrics.

Ke Liمشاهده پروفایل

استادیار

• Machine Learning
• Computer Vision
• Algorithms
• +۴ مورد دیگر

Ke Li is an Assistant Professor at Simon Fraser University (SFU) in Vancouver, Canada. He previously worked at Google and the Institute for Advanced Study (IAS) in Princeton. He holds a Ph.D. from UC Berkeley, advised by Jitendra Malik, and a B.Sc. in Computer Science from the University of Toronto. His research focuses on machine learning, computer vision, and algorithms, with contributions to generative modeling, neural rendering, fast nearest neighbor search, and meta-learning. Education: Ph.D. in Computer Science, UC Berkeley (2016) B.Sc. in Computer Science, University of Toronto (2008) Research Interests: Dr. Li explores foundational challenges in machine learning, including: - Generative Modeling : Developing methods like Implicit Maximum Likelihood Estimation (IMLE) to improve generative model training. - Neural Rendering : Innovating techniques like Proximity Attention Point Rendering (PAPR) for dynamic 3D scene representation. - Fast Nearest Neighbor Search : Pioneering algorithms to overcome dimensionality curses. - Learning to Optimize : Automating algorithm design through reinforcement learning. Professional Activities: Organized the IAS Seminar Series on Theoretical Machine Learning with Sanjeev Arora Lead organizer of the BIRS Workshop on 3D Generative Models Reviewer for NeurIPS, ICML, CVPR, and other top conferences Teaching: Recently taught CMPT 726: Machine Learning and CMPT 983: Generative Models at SFU.

Majed S. Fataftahمشاهده پروفایل

استادیار

• Inorganic Chemistry
• Bioinorganic Chemistry
• Materials Chemistry
• +۳ مورد دیگر

Majed S. Fataftah is an Assistant Professor of Chemistry at the University of Illinois, affiliated with the College of Liberal Arts & Sciences. He leads the Fataftah Research Group, focusing on physical inorganic chemistry at the intersection of chemistry, physics, and materials science. His research emphasizes synthetic chemistry to control photophysical properties for quantum information science, magnetic properties for novel materials, and reactivity modeling for catalysis. Education : B.S. in Chemistry & Biochemistry, University of Washington (2013) Ph.D. in Chemistry, Northwestern University (2019) Postdoctoral Fellow, Yale University (2019–2023) Research Interests : Inorganic and bioinorganic chemistry: synthesis, spectroscopy, electronic structure Metal-organic frameworks Molecular magnetism Quantum information science Key Research Themes : Students in his lab develop expertise in synthesizing small molecules/materials, X-ray crystallography, magnetometry, and advanced spectroscopic techniques (EPR, UV-vis-NIR, Mössbauer). Recent work includes studies on nickel-iron clusters, mixed-valence iron complexes, and vanadium-based molecular qubits. Labs/Teams : The Fataftah Group (2024) includes researchers like Garrett, Austin, Mari, Arsha, Joshua, Adrienne, Cayden, and Gwen, though formal student lists are not explicitly documented.

Asier Monevaمشاهده پروفایل

پژوهشگر

• Criminology
• Cybercrime
• Environmental Criminology
• +۴ مورد دیگر

Dr. Asier Moneva is a Postdoctoral Researcher at the Netherlands Institute for the Study of Crime and Law Enforcement (NSCR) and The Hague University of Applied Sciences , specializing in cybercrime , environmental criminology , and situational crime prevention . His work focuses on offender decision-making in cyberspace, cybercrime victimization patterns, and the application of data science to crime analysis. Education : PhD in Criminology (2020), Master in Crime Analysis and Prevention (cum laude, 2017) from Miguel Hernández University. Current Role : Analyzing cybercrime patterns through environmental criminology frameworks and data science methodologies. Moneva's research examines longitudinal offending patterns in cybercrime, particularly through analyses of web defacement archives ( Zone-H data) and hacker behavior. His studies reveal extreme concentration of cybercrime among chronic offenders, with 2.9% of hackers responsible for 68.5% of defacements. He also investigates repeat victimization dynamics in digital environments and the effectiveness of warning banners as deterrents. Recent publications focus on ransomware payment decisions by SMEs, stolen data markets on Telegram, and the intersection of familial relationships with cybercrime involvement. His work combines quasi-experimental designs , crime scripting , and conjunctive analysis to develop prevention strategies.

J. Tyler Meffordمشاهده پروفایل

استادیار

• Electrochemical Engineering
• Materials Science
• Renewable Energy
• +۴ مورد دیگر

J. Tyler Mefford is an Assistant Professor in the Department of Chemical Engineering at the University of California, Santa Barbara , where he leads the Mefford Group. His research focuses on electrochemical engineering, materials science, and renewable energy technologies. Education : BS in Chemistry from Stanford University (2012), PhD in Chemistry from the University of Texas at Austin (2016). The Mefford Group develops redox-active polymers and inorganic electrode materials for applications in electrochemical energy conversion , storage , and chemical separations . Their work integrates material design , operando spectroscopy , microscopy , and computational modeling to study charge transfer at electrified interfaces. Recent publications highlight advancements in aqueous battery technology , bifunctional electrocatalysis , and mixed-conducting polymer electrodes . The group emphasizes interdisciplinary approaches and diversity in research environments. Scientific Awards : 2020 Best In-situ and Operando Characterization Presentation Award, MRS 2016 Excellence in Renewable & Clean Energy Research Award, UT Energy Institute 2016 Nano Portfolio Presentation Award, University of Texas at Austin

Susan D. Hovorkaمشاهده پروفایل

استاد پژوهشی

• Geological Sequestration of Greenhouse Gases
• Sedimentology
• Reservoir Characterization
• +۳ مورد دیگر

Dr. Susan D. Hovorka is a Research Professor at the Bureau of Economic Geology, The University of Texas at Austin, specializing in geological techniques for environmental applications. She focuses on subsurface permeability dynamics in both tight and highly transmissive systems, with a primary emphasis on geological carbon sequestration and CO₂ storage security. Ph.D. in Geology (1990), The University of Texas at Austin M.A. in Geology (1981), The University of Texas at Austin B.A. in Geology (1974), Earlham College Her research addresses critical challenges in carbon geological storage, including: Characterizing salt formations as containment materials Analyzing carbonate fabrics for karst aquifer flow understanding Field CO₂ injection experiments for sequestration assessment Developing composite confining systems for secure CO₂ retention The articles she has contributed to since 2002 demonstrate a consistent focus on: Carbon capture and storage (CCS) technologies Reservoir pressure dynamics and fault permeability Permit-ready site workflows and risk mitigation Geological analogs from petroleum systems Dr. Hovorka actively collaborates with institutions like the Gulf Coast Carbon Center (GCCC) and participates in international CCS initiatives. Her work integrates sedimentology, geophysics, and environmental policy to advance subsurface carbon management solutions.

Vinod Vaikuntanathanمشاهده پروفایل

استاد

• Cryptography
• Fully Homomorphic Encryption
• Lattice-Based Cryptography
• +۴ مورد دیگر

Vinod Vaikuntanathan is the Ford Foundation Professor of Engineering in the MIT EECS department and a principal investigator at MIT CSAIL. He holds a BTech from IIT Madras (2003), and SM/PhD degrees from MIT (2005/2009). His research focuses on cryptography, particularly fully homomorphic encryption (FHE), lattice-based cryptography, and quantum-resistant systems. He co-founded Duality Technologies as Chief Cryptographer. **Education:** BTech in Computer Science (2003), Indian Institute of Technology Madras SM in Electrical Engineering & Computer Science (2005), MIT PhD in Computer Science (2009), MIT **Research Interests:** His work spans FHE (enabling computations on encrypted data), lattice-based cryptography (post-quantum security), and intersections with quantum computing, machine learning, and privacy. He explores applications in secure computation, algorithm design, and cryptographic protocols. **Awards:** Recipient of the Gödel Prize (2022), Simons Investigator (2023), and MacVicar Faculty Fellow (2024). His work on FHE and lattice algorithms has earned widespread acclaim in cryptography and theoretical computer science. **Teaching & Mentorship:** Advanced cryptography courses at MIT (e.g., 6.5630, 6.876J) Advised PhD students (e.g., Sergey Gorbunov, Tianren Liu) and postdocs (e.g., Nir Bitansky, Mark Zhandry) now leading positions in academia and industry **Collaborations:** Organizer of the Charles River Crypto Day and MIT Cryptography Seminar Principal investigator on grants from NSF, DARPA, and Microsoft

Thomas K. Uchidaمشاهده پروفایل

دانشیار

• Biomechanics
• Dynamical Systems
• Musculoskeletal Modeling
• +۷ مورد دیگر

Thomas K. Uchida is an Associate Professor in the Department of Mechanical Engineering at the University of Ottawa, a position he has held since May 2024. Prior to this promotion, he served as an Assistant Professor at the same institution from October 2018 to May 2024. Before joining the University of Ottawa, Dr. Uchida was an Engineering Research Associate (April 2015-August 2018) and Simbios Distinguished Postdoctoral Fellow (July 2012-April 2015) in the Department of Bioengineering at Stanford University. Dr. Uchida's research focuses on the modeling and simulation of dynamic systems, with particular emphasis on human movement biomechanics. His work spans multiple areas including: Simulation-guided design of assistive devices for improving mobility Modelling musculotendon dynamics and energy expenditure Parameter identification and model reduction methods Impact and contact dynamics Development of computational tools for biomechanical analysis He is a co-author of the book "Biomechanics of Movement: The Science of Sports, Robotics, and Rehabilitation" published by MIT Press, and actively contributes to the development of OpenSim, an open-source software platform for modeling musculoskeletal systems and generating simulations of human and animal movement. His work on OpenSim was featured on the cover of PLoS Computational Biology. Dr. Uchida's recent publications demonstrate strong activity in biomechanics, robotics, and computational modeling. His work bridges engineering principles with biological applications, particularly in understanding human movement mechanics. Key trends include applying machine learning to gait analysis, developing enhanced spine models, analyzing human balance stability with time delays, and advancing musculoskeletal simulation techniques. As an academic advisor, Dr. Uchida currently supervises seven graduate students: Firas Baklouti (expected completion August 2025) Shahin Sharafi Kazem Alambeigi Jiawei Gao Yuzhen Yan Manuel Lucas De Oliveira Blake Scott Miller Dr. Uchida collaborates with research teams focused on biomechanics and movement science. His work with OpenSim places him within an international community of researchers developing computational tools for biomechanical analysis, connecting mechanical engineering with biomedical applications in sports, robotics, and rehabilitation.

• Internal Medicine Nursing
• Chronic Obstructive Pulmonary Disease (COPD) Care
• Cultural Competency in Nursing
• +۵ مورد دیگر

Assoc. Prof. Dr. Yasemin CEYHAN is an accomplished academic in nursing, currently serving as an Associate Professor at Kırşehir Ahi Evran University's Faculty of Health Sciences, Department of Nursing. She has been a full-time faculty member since 2013, initially as a Research Assistant (2013-2020) and subsequently as a Doctoral Teaching Member (2020-present). She holds multiple administrative positions including Head of Department (2020-present), Faculty Council Member (2022-present), and Quality Committee Member (2024-present). Dr. CEYHAN completed her Bachelor's Degree in Nursing at Ahi Evran University (2007-2011), followed by a Master's Degree in Nursing at Erciyes University (2012-2015), and earned her Doctorate in Internal Medicine Nursing from Erciyes University (2015-2019). She has completed numerous specialized courses in statistical analysis, meta-analysis, and healthcare research methodology. Her research primarily focuses on Internal Medicine Nursing with particular expertise in Chronic Obstructive Pulmonary Disease (COPD) management, cultural competency in nursing practice, and patient self-management in chronic diseases. She has developed significant expertise in psychometric evaluation of nursing instruments and has contributed substantially to understanding the relationship between cultural sensitivity and nursing care effectiveness. Her work bridges nursing practice with psychological, cultural, and physiological aspects of patient care. Analysis of her publication record reveals a clear evolution from descriptive studies to sophisticated analytical research employing structural equation modeling and randomized controlled trials. Her recent work demonstrates increasing methodological rigor with a focus on mediation and moderation effects in complex patient care scenarios, particularly in COPD management where she examines intricate relationships between symptoms, psychological factors, and self-management behaviors. Poster Presentation 3rd Prize (2014) from Eskişehir Osmangazi University Dr. CEYHAN has successfully supervised multiple Master's theses and currently mentors additional graduate students. She has secured and led several significant research projects funded by TÜBA, TÜBİTAK, and university research funds, focusing on chronic disease management, cultural competency assessment tools, and COPD patient care. Her research portfolio demonstrates a strong commitment to evidence-based nursing practice and instrument development. As an active member of the Turkish Respiratory Research Association (since 2018) and the Turkish Nurses Association (since 2015), Dr. CEYHAN maintains a robust collaborative research network that spans multiple Turkish universities, particularly Erciyes University. Her work reflects a team-oriented research approach with numerous co-authored publications demonstrating interdisciplinary collaboration.

Soumaya Cherkaouiمشاهده پروفایل

استاد

• Artificial Intelligence
• Telecommunications Networks
• Quantum Computing
• +۶ مورد دیگر

Soumaya Cherkaoui is a Full Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal. Previously, she served as a Full Professor at Université de Sherbrooke and held industrial roles as an aerospace project manager. Her research integrates artificial intelligence with telecommunications, focusing on quantum computing, frugal edge intelligence, and applications in connected vehicles and IoT. Current Position: Full Professor, Polytechnique Montréal Prior Academic Role: Full Professor, Université de Sherbrooke Industry Experience: Aerospace Project Manager Research Interests: Convergence of AI and communications, quantum computing for networking, frugal intelligence at the edge, and applications in autonomous vehicles, industrial IoT, and smart grids. She leads government and industry-funded projects, including a $6 million quantum initiative in 2025. Recent Publication Trends: Her 2025–2024 work emphasizes quantum-enhanced anomaly detection (via QGANs), Open RAN slicing with quantum optimization, and reinforcement learning for secure cognitive radio networks. Topics span 5G/6G, vehicular networks, and zero-trust architectures. Scientific Awards: IEEE Communication Society Distinguished Lecturer (2020) ACM Mirela Notare Award (2023) IEEE Bio-Inspired Computing STC Leadership Award (2023) N2Women: Stars in Networking and Communications (2023) Best Paper Awards at IEEE ICC 2017, IEEE LCN 2021, ICCSPA 2024 Advising and Grants: Supervised 3 Master's students in 2024, with research on quantum GANs and federated learning for vehicular networks. Secured grants like the $6 million quantum project (2025) and participated in CFI-QC government funding (2022). Editorial and Leadership: Served as Associate Editor for IEEE, Wiley, and Elsevier journals. Chaired conferences like IEEE LCN 2019 and IEEE ICC2025, and held leadership roles in IEEE Communications Society committees.