جست‌وجوی استاد و پژوهشگر

Tommaso Grigolettoمشاهده پروفایل

استاد مدعو

• Quantum Mechanics
• Control Engineering
• Theoretical Physics
• +۳ مورد دیگر

Tommaso Grigoletto is an Adjunct Professor at the Department of Molecular Sciences and Nanosystems, Ca' Foscari University of Venice, and a Postdoctoral Fellow at the Department of Information Engineering, University of Padua. His research focuses on theoretical and numerical methods for complex dynamical systems, particularly quantum and classical probability models. He is part of the Quantum Dynamics, Information and Control group at the University of Padua, led by Prof. Francesco Ticozzi. Education: Ph.D. and Master's degrees in Information Engineering from the University of Padua. Research interests include quantum system control, model reduction techniques, and feedback stabilization strategies. He teaches 'Fundamentals of Automatic Controls' at Ca' Foscari University (2024-2025). His articles explore quantum model reduction, feedback control for quantum systems, and stochastic dynamics. He is actively mentoring students interested in control engineering and quantum systems simulations. Open to collaborative research and thesis supervision in these areas. Professional networks include the Quantum Dynamics group at Padua and academic affiliations with both universities. Engaged in open-source projects like an arXiv update bot for tracking research trends.

Kerstin Bunteمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• XAI (Explainable Artificial Intelligence)
• +۷ مورد دیگر

Kerstin Bunte is a Professor of Machine Learning for interdisciplinary data analysis at the University of Groningen, affiliated with the Faculty of Science and Engineering and the Bernoulli Institute's Intelligent Systems Group. She holds an Honorary Fellowship at the University of Birmingham and leads the Intelligent Systems Group. Her research focuses on interpretable machine learning, interdisciplinary applications (e.g., astrophysics and biomedical data), and visualization techniques. Research Interests: - Machine Learning - Artificial Intelligence - Explainable AI (XAI) - Interpretable Models - Dimensionality Reduction - Data Visualization - Astrophysical Data Analysis - Medical Imaging Awards & Grants: - DSSC XS funding (2023) - NWO VIDI grant (2020) - Rosalind Franklin Fellowship (2016–present) Advising & Students: Supervised PhD students include Elisa Oostwal, Janis Norden, Matteo Marcantoni, and Petra Awad. Research spans topics like tumor segmentation in medical imaging, astrophysical structure detection, and autonomous navigation systems. Labs & Collaborations: Leads the Intelligent Systems Group, collaborating with institutions like the University of Birmingham and the University of Warwick. Work involves interdisciplinary projects combining machine learning with astronomy, biomedical sciences, and robotics.

Barry C. Sandersمشاهده پروفایل

استاد

• Quantum Computing
• Quantum Information Theory
• Quantum Algorithms
• +۳ مورد دیگر

Barry C. Sanders is a Professor and Director of the Institute for Quantum Science and Technology at the University of Calgary. He holds additional roles as Lead Investigator of the Alberta Major Innovation Fund Project on Quantum Technologies, a Thousand Talents Chair at the University of Science and Technology China, and Vajra Visiting Faculty at the Raman Research Institute. His research focuses on quantum computing, quantum algorithms, and optical implementations of quantum information tasks. Sanders has a PhD from Imperial College London (1987) and has held faculty positions at Macquarie University and the Australian National University. Education: BSc (University of Calgary, 1984), PhD (Imperial College London, 1987) Affiliations: Institute for Quantum Science and Technology, Alberta Major Innovation Fund Project His research interests include quantum-limited measurement, nonclassical light, quantum cryptography, and quantum algorithm development. He has pioneered work on Schrödinger cat states, qudit systems, and quantum error correction. Awards include Fellowships from the Institute of Physics, Optical Society of America, and Royal Society of Canada. His work bridges theory and application, with contributions to quantum technology commercialization and interdisciplinary collaborations. Editor-in-Chief, New Journal of Physics Past leadership roles: President of the Australian Optical Society, Founding Co-Chair of the Canadian Association of Physicists Division His recent publications explore quantum speedup in machine learning, topological quantum walks, and fault-tolerant quantum computing architectures.

• Autonomous Systems
• Target Tracking
• Navigation
• +۵ مورد دیگر

Edmund Førland Brekke is a Full Professor at NTNU's Department of Engineering Cybernetics, specializing in autonomous maritime systems. He leads major projects like Autosea, Autosit, Autosight, and SFI Autoship. His research focuses on estimation theory, target tracking, SLAM, and collision avoidance for autonomous ships. He has held roles including Project Manager for key initiatives and was a Research Fellow at NUS's Acoustic Research Lab. Brekke teaches courses on sensor fusion and nonlinear state estimation. PhD: NTNU (2010), MSc: NTNU (2005) Research interests include sensor fusion, maritime navigation, and autonomous system safety. He supervises over 20 PhD students in topics like radar tracking, SLAM, and digital twins. His publications span collision avoidance algorithms, multi-sensor integration, and autonomous vessel control. He co-founded Zeabuz and collaborates on projects like Autoferry and AutoBarge. Recent work emphasizes maritime target tracking, scenario-based collision risk assessment, and sensor fusion for autonomous ferries. His contributions advance autonomous vessel autonomy and regulatory compliance with COLREGs.

Rabah Aoufiمشاهده پروفایل

مدرس ارشد

• Digital Signal Processing
• Microcontroller Systems
• Control Systems
• +۳ مورد دیگر

Rabah Aoufi is a Senior Lecturer in the Department of Engineering Technology & Industrial Distribution at the College of Engineering, Texas A&M University. His primary affiliation includes the Electronic Systems Engineering Technology program. He can be reached at raoufi@tamu.edu and is located in FERM 304AA. His work focuses on digital signal processing, microcontroller systems, control systems, and engineering entrepreneurship. Research interests span embedded systems design, real-time data processing, and innovative educational projects. His publications reflect expertise in both foundational engineering principles (e.g., signal processing fundamentals) and applied technologies (e.g., microcontroller programming and big data frameworks). His articles demonstrate a career-long engagement with evolving technologies—from foundational 1980s multiprocessor architectures to modern big data systems. No scientific awards or grants are explicitly mentioned in the provided materials.

Nima Kalantariمشاهده پروفایل

استادیار

• Computer Graphics
• Computational Photography
• Rendering
• +۵ مورد دیگر

Nima Kalantari is an Assistant Professor in the Department of Computer Science & Engineering at Texas A&M University. He previously held a postdoctoral position at UC San Diego under Ravi Ramamoorthi. His academic journey includes a Ph.D. from UC Santa Barbara (ECE), an M.S. and B.S. from Amirkabir University of Technology (Electrical Engineering). His research focuses on computer graphics, computational photography, rendering, and deep learning, with emphasis on machine learning techniques for image synthesis and material generation. Education: Ph.D., Electrical and Computer Engineering, University of California, Santa Barbara, 2015 M.S., Electrical Engineering, Amirkabir University of Technology, 2009 B.S., Electrical Engineering, Amirkabir University of Technology, 2007 Research Interests: Kalantari's work bridges computer graphics and deep learning, particularly in computational photography, rendering, and view synthesis. Recent projects include 3D relightable face generation, sparse view synthesis with Gaussians, and physics-guided neural networks for fluid dynamics. Awards: 2024 Frontiers of Science Award (SIGGRAPH 2019) TEES Young Faculty Fellow Award (2024) Best Master Thesis Award, IEEE Iran Section (2010) Advising & Labs: Active mentor for 8 current Ph.D./M.S. students and advisor to alumni including Xilong Zhou (Postdoc at MPI for Informatics). His team focuses on projects like PanoDreamer (3D panorama synthesis) and PhotoMat (material generation from flash photos).

Lorenza Violaمشاهده پروفایل

استاد

• Quantum Information Processing
• Quantum Control and Estimation
• Open Quantum Systems
• +۲ مورد دیگر

Lorenza Viola is the James Frank Family Professor of Physics at Dartmouth College, specializing in quantum information science. Her theoretical research focuses on quantum control, noise mitigation, and topological quantum systems. Education includes an MS in Physics from University of Trento (Summa Cum Laude) and PhD in Theoretical Physics from University of Padua. Research encompasses quantum characterization/control of open systems, quantum noise spectroscopy, fault tolerance, model reduction, and topological quantum matter. Current projects investigate non-Markovian dynamics, bosonic zero modes, dissipative phase transitions, and entanglement properties. Honors include APS Fellowship (2014). Service includes Divisional Associate Editor for Physical Review Letters (2018-2024) and Partner Investigator with the Australian Research Council Centre for Engineered Quantum Systems.

Frank L. H. Wolfsمشاهده پروفایل

استاد

• Dark Matter Detection
• Particle Physics
• Detector Technology
• +۳ مورد دیگر

Prof. Frank L. H. Wolfs is a Professor in the Department of Physics and Astronomy at the University of Rochester. His research focuses on experimental particle physics, particularly in dark matter detection using advanced xenon-based detectors. He leads the LUX-ZEPLIN (LZ) experiment, responsible for trigger electronics development and calibration systems. His group has contributed to the Zeplin II (Boulby Mine, UK) and LUX (Sanford Underground Research Facility, South Dakota) projects, advancing detector technologies for underground physics. He also engages in educational outreach via online experiments like the muon lifetime measurement. Prof. Wolfs teaches courses ranging from introductory physics to advanced labs and participates in initiatives like the College Teaching, Learning, and Technology Roundtable. His work emphasizes precision instrumentation and interdisciplinary collaborations in astrophysics and nuclear physics. Research Interests: Direct detection of dark matter Liquid xenon time projection chambers Calibration and data acquisition systems Low-energy nuclear recoils Background reduction techniques Scientific Contributions: Design of the DDC-8DSP trigger system for LZ Development of the HydroX detector concept Advancements in electronic recoil discrimination

• Vehicle Engineering
• Technical Acoustics
• Mechanical Engineering
• +۳ مورد دیگر

Ephraim Gutmark is an Affiliated Professor at the Department of Vehicle Engineering and Technical Acoustics, KTH Royal Institute of Technology. His affiliation is tied to the Vehicle Engineering and Technical Acoustics unit located at Teknikringen 8. Research interests focus on technical acoustics, vehicle engineering systems, and related interdisciplinary fields involving noise and vibration analysis. Specific areas may include fluid-structure interactions, engine acoustics, and automotive system optimization. No awards or grants are explicitly listed in the provided data. Advising and lab affiliations are not detailed in the current information.

Abhinav Kumar Singhمشاهده پروفایل

مدرس

• Power System Dynamics
• Power System Estimation and Control
• Large-scale Integration of Renewables
• +۴ مورد دیگر

Dr. Abhinav Kumar Singh is a Lecturer of Power Systems at the University of Southampton's School of Electronics and Computer Science since 2019. Previously, he held academic roles at the University of Lincoln (2017–2019) and Imperial College London (2015–2017 as Research Associate). His research focuses on real-time estimation and control of power systems, particularly addressing challenges posed by renewable energy integration. Key areas include power system dynamics, decentralized estimation/control methodologies, and modeling of renewable generation systems. Education: B.Tech from Indian Institute of Technology (IIT) New Delhi (2010), PhD in Electrical Engineering from Imperial College London (2015). He leads the 68-bus benchmark system development for IEEE PES and serves as editor for IEEE Transactions on Power Systems and Journal of Modern Power Systems and Clean Energy . Research Projects: PI of National Grid’s £480K 'Economic Ageing of Transformers' (2019–2021), Co-I on UK-China EPSRC-NSFC £780K 'Resilient Operation of Sustainable Energy Systems' (2020–2023). Teaching: Modules include Power System Dynamics, Power Electronics for DC Transmission, and Mathematics for Electrical Engineering. Awards: EPSRC Doctoral Prize (2015), IEEE PES Recognition Awards (2016, 2022), and The President’s Award for Outstanding Research Team (2016). Labs/Teams: Member of the Electrical Power Engineering group and Tony Davies High Voltage Laboratory. Active in IEEE PES Task Forces on Dynamic Estimation and Standard Test Cases.

Kristel Michielsenمشاهده پروفایل

استاد

• Quantum Computing
• Quantum Annealing
• Quantum Simulation
• +۳ مورد دیگر

Prof. Dr. Kristel Michielsen is a Professor of Quantum Information Processing at RWTH Aachen University and holds leadership roles at Forschungszentrum Jülich. She leads the division HPC for Quantum Systems and heads the Jülich UNified Infrastructure for Quantum computing (JUNIQ). As Group Leader of the Research Group Quantum Information Processing, her work focuses on quantum annealing, quantum simulation, and modular hybrid HPC-quantum computing. She is also Spokesperson of the Helmholtz Information Program 1 and a Principal Investigator in Topics 1 and 2. Affiliations: RWTH Aachen University, Forschungszentrum Jülich (IAS/JSC), JUNIQ Key Roles: Head of HPC for Quantum Systems, JUNIQ Director, Quantum Information Processing Group Leader Her research emphasizes quantum computing applications in optimization, benchmarking, and hybrid supercomputing-quantum systems. She pioneers quantum-annealing solutions for real-world problems like power grid partitioning and transportation logistics. Recent work explores error mitigation, noise modeling in D-Wave systems, and quantum-classical workflows.

• Medical Imaging
• Machine Learning
• Computer Vision
• +۳ مورد دیگر

Diana Mateus is a Researcher at Centrale Nantes, affiliated with the LS2N Laboratory. She holds a bachelor's in Electronic Engineering from the University of Javeriana (Colombia), a Master's in Control and Automation from Paul Sabatier University (France), and a PhD in Computer Vision from INRIA Grenoble. After postdoctoral work and eight years as an associate researcher at Technical University of Munich and Helmholtz Zentrum (Germany), she returned to France to join Centrale Nantes via the Connect Talent Program, securing a starting grant for interdisciplinary research in medical image analysis and machine learning. Her research focuses on Milcom —a project integrating multimodal imaging (MRI, CT, ultrasound, PET) with machine learning to advance computational medicine. Key objectives include computer-aided diagnosis, disease knowledge advancement, and improving imaging quality. Collaborations include the hospital's Nuclear Medicine Department, focusing on multiple myeloma, and companies Hera-Mi and Keosys for breast cancer research. She supervises six PhD students and two postdocs, emphasizing synergies between engineering and healthcare. At Centrale Nantes, she benefits from dynamic institutional support, quality students, and complementary team skills. Her lab recently acquired a research-dedicated ultrasound machine to develop machine learning-driven imaging optimization. Living in Nantes, she values its family-friendly environment and proximity to academic and medical networks.

Alejandro Laguna Sanzمشاهده پروفایل

استادیار

• Diabetes Technology
• Glucose Monitoring
• Artificial Pancreas Systems
• +۷ مورد دیگر

Alejandro Laguna Sanz is an Assistant Professor in the Department of Electronic Engineering at the School of Engineering, Universitat de València. His work bridges biomedical engineering and clinical diabetes care, focusing on technological solutions for glucose regulation. His research interests include diabetes technology, artificial pancreas systems, glucose monitoring accuracy, and the impact of exercise on glycemic control. He is particularly active in developing and evaluating predictive algorithms for glycemic management, especially in dynamic conditions such as physical activity and post-bariatric hypoglycemia. His work often combines control theory with clinical validation. The recent publications reveal a strong focus on real-world performance of continuous glucose monitors (CGMs), sex-specific responses in women with type 1 diabetes, and innovative interventions like elastic band resistance training and dual-hormone closed-loop systems. His research increasingly integrates population modeling, in silico studies, and virtual education platforms for artificial pancreas training. He is a member of the CLIDET research group (Clinimetry and Technological Development in Therapeutic Exercise), where he contributes to the design and clinical evaluation of advanced monitoring and control systems for metabolic diseases. Alejandro Laguna Sanz earned his PhD from Universitat Politècnica de València with a thesis on uncertainty in postprandial glucose modeling in type 1 diabetes, supervised by Dr. Paolo Rosseti and Dr. Jorge Bondía Company. He has not received any explicitly listed scientific awards in the provided text. He advises students within his research group, though no specific names are listed. His work is supported by collaborative projects in diabetes technology and engineering, particularly in the development of adaptive control systems and clinical validation of glucose monitoring devices. He is involved in both experimental and simulation-based studies.

David S. Wackمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Biomedical Engineering
• Brain Research
• +۵ مورد دیگر

David S. Wack is an Associate Professor at the University at Buffalo's Jacobs School of Medicine & Biomedical Sciences, Department of Radiology. His research focuses on medical image analysis and neuroimaging, particularly in auditory processing and parameter estimation from PET, MRI, and CT images. He has held academic positions since 1992, progressing from instructor roles to his current rank. His work includes NIH-funded projects on imaging technologies and collaborations with institutions like Canon Medical Systems and UBNS. Education: PhD in Communicative Disorders and Sciences (SUNY Buffalo, 2010) MA in Applied Mathematics (SUNY Buffalo, 1992) BA in Applied Mathematics and Music Performance (SUNY Buffalo, 1989) Research Interests: Development of parametric maps from medical images Machine learning applications in neuroimaging Neuroimaging of auditory and language processing Dynamic image noise reduction and segmentation algorithms Neural markers of top-down compensation in speech processing Recent Projects: NIH-funded self-collimating SPECT breast tomography system 4D flow MRI for intracranial atherosclerotic disease assessment Machine learning for neuroimage classification Grants & Service: Member of Jacobs School faculty council and UB Faculty Student Association board Editorial roles at Frontiers in Neuroscience (Brain Imaging Methods, Decision Neuroscience) Labs & Teams: Buffalo Neuroimaging Analysis Center Collaborations with UBNS, Canon Medical, and VA Western New York Health Care System

• Automotive Engineering
• Fluid Machinery
• Computational Fluid Dynamics
• +۴ مورد دیگر

Alessandro Ferrari is a Full Professor at Politecnico di Torino's Department of Energy (DENERG) and a key member of the Center for Automotive Research and Sustainable Mobility (CARS@PoliTO) . His academic activities span teaching, research, and industrial collaboration, with a focus on automotive engineering, fluid machinery, and sustainable energy systems. Roles : Vice-Rector for Research Model Development, Scientific Director for industrial projects, PhD Thesis Supervisor Teaching : Advanced computational techniques for thermal/hydraulic machines, Computational heat/mass transfer Research : Fuel injection systems, ammonia combustion, cavitation dynamics, flow measurement Research Focus Professor Ferrari specializes in automotive propulsion systems and fluid machinery with emphasis on: Internal Combustion Engine optimization Computational Fluid Dynamics (CFD) modeling Novel fuel injection technologies Sustainable transport solutions His recent publications show strong trends in: Ammonia combustion for carbon-free fuels Real-time injection control using neural networks Cavitation analysis in GDI injectors Flow rate measurement techniques Academic Leadership As a PhD program director for Energetics since 2014, he has directly supervised 4 doctoral students. His industrial collaborations include patents for injection systems and flow measurement devices with commercial partners. Laboratory Involvement Active in the CARS@PoliTO center, he leads research on automotive sustainability and participates in fluid power experimental testing facilities.