جست‌وجوی استاد و پژوهشگر

Manolis Chiouمشاهده پروفایل

مدرس

• Human-Robot Interaction
• Artificial Intelligence
• Robotics
• +۵ مورد دیگر

Manolis Chiou is a Lecturer (Assistant Professor) in Computer Science at Queen Mary University of London, part of the School of Electronic Engineering and Computer Science. His expertise lies in Human-Robot Teaming and Interaction within Variable Autonomy systems, emphasizing safety-critical and hazardous environments. Prior roles include Research Fellow at the University of Birmingham, leading the human-robot teaming group and co-founding the Extreme Robotics Lab. Education: PhD in Robotics and AI (University of Birmingham, 2017); MSc in Computational Intelligence (University of Sheffield, 2012); BEng in Automation Engineering (University of West Attica, 2011). Research focuses on developing AI/robotics frameworks for seamless human-robot collaboration, drawing on methods from AI, robotics, human factors, and cognitive science. Key themes include trust models in autonomous systems, variable autonomy paradigms, and operator workload management. Recent work explores robot health indicators, neurosymbolic control, and field-tested disaster response applications. Teaching includes modules on Computational Creativity and Machine Learning. His research has produced over 30 publications since 2015, with a focus on advancing mixed-initiative systems and trustworthy AI in robotics.

Manuela Vecchiمشاهده پروفایل

دانشیار

• Astroparticle Physics
• High-Energy Astrophysics
• Cosmic Rays
• +۳ مورد دیگر

Manuela Vecchi is an Associate Professor and Rosalind Franklin Fellow at the University of Groningen's Faculty of Science and Engineering, affiliated with the Kapteyn Astronomical Institute. Her expertise spans astroparticle physics, focusing on high-energy phenomena observed via cosmic rays, gamma rays, and neutrinos. She contributes to major collaborations like the Alpha Magnetic Spectrometer (AMS-02) aboard the International Space Station and the Cherenkov Telescope Array (CTA). Her research includes studies on cosmic ray composition, solar modulation effects, and dark matter searches. She leads an NWO-funded project on antideuterons as probes for new physics and co-leads efforts in CTA camera development. Vecchi's work bridges observational astrophysics and fundamental physics, with publications on topics like gamma-ray transients, pulsar emissions, and cosmic ray antiprotons. Key projects involve analyzing AMS-02 data for antinuclei detection and advancing CTA's capabilities for gamma-ray astronomy. She has supervised PhD students in these areas and teaches advanced astrophysics courses. Her contributions to instrumentation and data analysis underscore her role at the forefront of multi-messenger astrophysics.

Michael Falkمشاهده پروفایل

استاد

• Computational Materials Science
• Metals Processing
• Additive Manufacturing
• +۵ مورد دیگر

Michael Falk is a Professor of Materials Science and Engineering, Mechanical Engineering, and Physics at Johns Hopkins University (JHU), and serves as Vice Dean for Undergraduate Education at the Whiting School of Engineering. He leads initiatives to enhance undergraduate education, curriculum development, and student mentorship. Falk holds a B.S. in Physics (1990) and M.S. in Computer Science (1991) from JHU, followed by a Ph.D. in Physics from the University of California, Santa Barbara. His academic career spans roles at the University of Michigan (2000–2008) and his return to JHU in 2008. Research Interests: Falk’s work focuses on computational materials science, simulating atomic-scale processes in materials undergoing mechanical stress, friction, or thermal changes. Key areas include amorphous/glass materials, metallic glass deformation, and additive manufacturing. He also investigates educational strategies to improve STEM engagement, particularly for underrepresented groups, and advocates for LGBTQ+ inclusion in STEM fields. Notable outreach efforts include partnerships with Baltimore City Schools to boost STEM participation. Articles Overview: Falk’s recent publications explore topics such as socio-environmental factors influencing STEM persistence, structural analysis of disordered materials, and computational models predicting material behavior under extreme conditions. His work bridges fundamental materials science with practical engineering applications, emphasizing predictive modeling and interdisciplinary collaboration. Grants & Partnerships: Falk has secured funding from NSF and DOE for projects like simulation-informed additive manufacturing models and studies on crystal nucleation in composition gradients. His educational research includes NSF-funded initiatives to enhance computing literacy in engineering curricula and improve STEM accessibility in urban schools. Labs & Teams: Falk leads a research group dedicated to computational materials modeling and educational innovation. His collaborations span academic, industrial, and community partners to advance both technical and educational missions.

Semali Pereraمشاهده پروفایل

استاد

• Advanced Separations
• Nanomaterial Engineering
• Carbon Capture
• +۲ مورد دیگر

Semali Perera is Professor of Chemical Engineering at the University of Bath, holding a BSc in Chemical Engineering and PhD from Brunel University. Her research focuses on advanced separations technology and nanomaterials engineering, with applications in environmental protection and medical therapeutics. She serves as Director of the Reaction and Catalysis Engineering research unit and is affiliated with the Centre for Integrated Materials, Processes & Structures. Key research domains include: Design of hollow fibers and monolithic adsorbents for gas separation Development of biodegradable drug delivery systems for cancer treatment Advanced materials for water treatment and resource recovery Process-integrated separation technologies for sustainability Perera's publications demonstrate innovations in adsorption technology and material design. Recent work examines activated carbon microstructures, battery safety systems, and neural network applications in process modeling. Her 2024 research on moisture diffusion modeling combines AI with traditional chemical engineering principles, while work on rare earth recovery addresses critical material sustainability challenges. Honors include: Royal Society Brian Mercer Award for Innovation (2007) Mary Tasker Award for Chemical Engineering Teaching (2002) Perera collaborates extensively with industry through ventures like nanoporous solutions limited, a university spin-off commercializing her adsorbent fiber technology. She coordinates projects including a pioneering near-zero-carbon air conditioning system using atmospheric latent heat and natural light energy.

Hongbiao Dongمشاهده پروفایل

استاد

• Digital Manufacturing
• Solidification Modeling
• AI in Materials Science
• +۳ مورد دیگر

Professor Hongbiao Dong is a FREng Fellow and Professor of Materials Engineering at the University of Leicester, serving as Deputy Head of the School of Engineering and Director of the EPSRC Centre for Doctoral Training in Digital Transformation of Metals Industry (DigitalMetal CDT). His research focuses on integrating AI with materials science to advance sustainable manufacturing, particularly in areas like solidification modeling, digital twins, and metallurgical process optimization. His work has driven industry partnerships with Rolls-Royce, TWI, and others, addressing challenges in aerospace, energy, and subsea engineering. Key contributions include the first multi-scale modeling framework for arc welding (MintWeld) and AI-driven tools for BOF steelmaking. He holds leadership roles in academic and industrial bodies, including Vice Editor-in-Chief of the International Journal of Minerals, Metallurgy and Materials, and chairs committees such as the STFC-ISIS Engineering User Group. Awards include the Royal Academy of Engineering Research Chair and the Metrology for World Class Manufacturing Award. His research team’s innovations include AI-enhanced decision-making for high-value components (e.g., aero-engine parts) and mitigation of pipeline failures via predictive modeling. Current initiatives emphasize reducing carbon footprints through data-driven manufacturing and fostering international collaborations between the UK, China, India, and South Africa. Grants/Positions: EPSRC CDT Director, MintWeld Project Lead Labs/Teams: DigitalMetal CDT, Advanced Solidification & AI Group

Hans Hallenمشاهده پروفایل

استاد

• Nanoscale optical spectroscopy
• Carrier dynamics in semiconductors
• Plasmon resonance
• +۴ مورد دیگر

Professor Hans Hallen is a faculty member in the Physics Department at North Carolina State University. He holds a BS in Engineering Physics from Cornell University (1984), and MS/PhD in Applied Physics from Cornell (1986/1991). His career includes postdoctoral work at AT&T Bell Labs (1991-1993), where he pioneered the scanning Hall probe microscope. Currently, his research focuses on nanoscale optical spectroscopy, microwave propagation, and nano-bioprobes for cellular studies. Research interests include nanoscale carrier dynamics in silicon, gradient-field Raman spectroscopy near metallic nanostructures, and novel material approaches for 3D RF wafer packaging. His work bridges physics, materials science, and engineering with applications in wireless communications and nanoscale imaging. Recent publications (2019-2023) address challenges in mmWave signal blockage prediction using machine learning, dynamic control of optical surfaces via liquid metals, and self-alignment techniques in semiconductor manufacturing. His nano-bioprobe innovations enable intracellular signal transduction studies and nuclear manipulation within cells. Professor Hallen leads interdisciplinary projects involving scanning probe microscopy, molecular deposition with nanoscale resolution, and Raman lidar techniques. His work emphasizes practical applications of fundamental physics discoveries in emerging technologies.

• Nuclear Reactor Modelling
• Neutron Transport
• Fluid Dynamics
• +۴ مورد دیگر

Christophe Demazière is a Professor at Chalmers University of Technology, leading the DREAM task force focused on deterministic reactor modelling. His work integrates neutron transport, fluid dynamics, and numerical methods to advance nuclear reactor simulation tools and safety. He teaches courses on nuclear reactor physics, emphasizing multi-physical and multi-scale system analysis. Active in pedagogical innovation, he co-leads the GRE@ T-PIONEeR project promoting hybrid/flipped learning methods in nuclear education. Research interests span reactor noise analysis for core diagnostics, machine learning applications in nuclear data analysis, and cross-disciplinary collaboration via projects like CORTEX and McSAFER. Member of the American Nuclear Society, he publishes extensively on topics including neutron noise simulations, educational technology, and advanced reactor verification schemes. Notable contributions include development of the CORE SIM+ solver for neutron noise simulations and validation studies using zero-power reactors like AKR-2. His work bridges academic research with industrial needs through partnerships focused on workforce development and knowledge management in the nuclear sector.

Yu Zhongمشاهده پروفایل

استاد

• Advanced Sustainable Materials & Manufacturing
• Solid Oxide Fuel Cells
• Light Alloys (Magnesium, Aluminum)
• +۶ مورد دیگر

Dr. Yu Zhong is a Professor in the Department of Mechanical & Materials Engineering at Worcester Polytechnic Institute (WPI). He holds an affiliated appointment in the Department of Materials Science & Engineering. He earned his Ph.D. in Materials Science from Pennsylvania State University (2005) and an M.S. in Materials Science and Engineering from Sichuan University (2000). Before joining WPI, he worked at Saint-Gobain's High Performance Research Center (2005–2013) and served as an Assistant Professor at Florida International University (2013–2016). Affiliations: Worcester Polytechnic Institute (Current), Florida International University (2013–2016), Saint-Gobain Research Center (2005–2013) Research Interests: Advanced Sustainable Materials & Manufacturing, Solid Oxide Fuel Cells, Light Alloys (Magnesium/Aluminum), Lithium-Ion Batteries, High-Performance Ceramics, Computational Thermodynamics, and Machine Learning in Materials Science. His research focuses on integrating computational methods (first-principles calculations, CALPHAD modeling) with experimental validation to design novel materials. Notable contributions include high-entropy alloys, oxygen transport membranes, and lithium-ion battery materials. Dr. Zhong has authored over 70 peer-reviewed articles, 2 book chapters, and 2 patents. His work is funded by agencies such as DOE, NSF, and the Nuclear Energy University Program. He has received awards including the James Nichols Heald Research Award (2021) and TMS FMD Young Leaders Professional Development Award (2016). Labs/Teams: Integrated Materials and Processes Design (IMPD) Group at WPI, focusing on computational thermodynamics, machine learning, and experimental validation for advanced materials.

Wasim Ahmadمشاهده پروفایل

مدرس ارشد

• Signal Processing
• Machine Learning
• Data Analytics
• +۹ مورد دیگر

Wasim Ahmad is a Senior Lecturer (Associate Professor) in Signal Processing and Machine Learning at the School of Engineering, University of Glasgow. He earned his PhD from the University of Surrey (2011) and held prior academic positions at the University of Hull (2013–2015) and the University of Surrey (2011–2013). He is part of the Communication, Sensing and Imaging (CSI) research group at Glasgow, focusing on applications of signal processing and machine learning in sound modeling, robot audition, healthcare technologies, and IoT-based systems. Education: PhD in Engineering from the University of Surrey (2011), followed by postdoctoral roles at Hull and Surrey before joining Glasgow in 2015. Research Interests: His work spans signal processing for assistive technologies, teleoperation systems, activity recognition, and IoT-enabled healthcare monitoring. He has pioneered projects like radar-based indoor navigation for visually impaired individuals and emotion recognition for human-robot interaction. Publications: Over 40 peer-reviewed articles, with recent focus on edge computing optimization, immersive VR education, and teleoperation interfaces. His work bridges theoretical advancements with practical applications in robotics, healthcare, and education. Grants: Recipient of the University of Glasgow Learning and Teaching Development Fund (2017–2018) for student-staff partnership in assessment innovation. Teaching: Leads courses on real-time systems, microelectronics, and programming, emphasizing hands-on engineering projects. Supervised MSc/PhD students in telerobotics and edge computing. Labs/Teams: Active contributor to the CSI group, collaborating on projects involving sensor networks and AI-driven systems.

• Medical Physics
• Nuclear Medicine
• Positron Emission Tomography (PET)
• +۱۲ مورد دیگر

Professor Andy Welch is a Chair in the Institute for Education in Medical and Dental Sciences at the University of Aberdeen, affiliated with the School of Medicine, Medical Sciences and Nutrition. He holds a PhD in Medical Physics from the University of London and a BSc in Physics from the University of Southampton, with prior academic experience at the University of Utah. His research focuses on advanced imaging techniques in nuclear medicine, particularly PET, SPECT, and CT. BSc Physics, University of Southampton (1987) PhD Medical Physics, University of London (1990) Welch's research is centered on tomographic radiotracer imaging, with applications in oncology, cardiology, and neuroscience. He has pioneered methods in image reconstruction and processing, and his work spans from preclinical models to clinical translation. His recent publications highlight innovations in PET radiomics for cancer prognosis, standardization of preclinical imaging, and metabolic studies in neurodegenerative and cardiovascular diseases. His work often involves interdisciplinary collaboration, particularly with chemists and clinicians in developing novel PET tracers. His scientific contributions are supported by extensive funding, including grants from the MRC, EPSRC, and Chief Scientist’s Office. He has served as Principal Investigator on 15 projects totaling £2.6M and as a named investigator on 25 projects totaling £12.2M. His leadership roles include Director of the John Mallard Scottish PET Centre (1997–2012) and Programme Coordinator for MSc Medical Physics and Medical Imaging since 2016. Principal Investigator: 15 awards, £2.6M Named Investigator: 25 awards, £12.2M Director, John Mallard Scottish PET Centre (1997–2012) Programme Coordinator, MSc Medical Physics & Imaging (2016–present) Welch supervises PhD students and teaches across postgraduate medical physics programs, coordinating multiple courses in radiation, nuclear medicine, and imaging. He is actively involved in institutional governance as Postgraduate Research Coordinator and Athena Swan Lead, promoting equity and research excellence. His affiliations include the Institute of Physics and Engineering in Medicine (MIPEM) and the Higher Education Academy (FHEA), and he is a registered Clinical Scientist with the Health and Care Professions Council (HCPC). His work continues to advance the frontiers of biomedical imaging and its clinical applications.

• Nuclear Instrumentation
• Radiation-Hard Sensors
• Monolithic Active Pixel Sensors
• +۷ مورد دیگر

Vicente González Millán is a full Professor in the Department of Electronic Engineering at the School of Engineering, University of Valencia. His work bridges electronics technology and nuclear physics, with strong involvement in international collaborations such as CERN, AGATA, and NEDA. His research focuses on the development of advanced radiation-hard semiconductor sensors, particularly the MALTA series of monolithic active pixel sensors, for applications in high-energy and nuclear physics experiments. He is actively involved in detector design, signal processing, FPGA-based data acquisition systems, and real-time data analysis techniques. His work supports cutting-edge experiments in nuclear structure, particle detection, and medical physics instrumentation. The recent publications show a consistent focus on detector development, sensor characterization, and data acquisition systems. Key themes include radiation hardness, timing performance, charge calibration, and the use of machine learning for event reconstruction in neutron detection arrays. The work is highly experimental and closely tied to large-scale facilities like CERN and GANIL. He leads or is a core member of two research groups: i2N (Electronic Instrumentation in Medical and Nuclear Physics) and IRIMED (Research in Radiophysics and Nuclear Instrumentation in Medicine), highlighting the dual application of his work in both fundamental physics and medical technology. While no specific awards are listed, his sustained publication record and leadership in major detector projects indicate significant recognition in the field. He also contributes to the development of real-time trigger systems, digital front-end electronics, and FPGA-based solutions for gamma and neutron spectroscopy.

Curtis Thorneمشاهده پروفایل

دانشیار

• Cell and Cancer Biology
• Wnt Signaling
• Kinase Networks
• +۶ مورد دیگر

Curtis Thorne , PhD, is an Associate Professor in the Department of Cellular and Molecular Medicine at the University of Arizona , with additional affiliations at the University of Arizona Cancer Center and the BIO5 Institute . His research focuses on Wnt signaling , kinase networks , and tissue homeostasis , aiming to develop novel drug discovery strategies for cancer. Education : B.S., Biology and Chemistry, Baylor University (2000) Ph.D., Cell and Developmental Biology, Vanderbilt University (2010) Postdoctoral training, American Cancer Society Fellow, UT Southwestern/UCSF Research Interests include Decoding intestinal stem cell behaviors in cancer Quantitative analysis of kinase networks in disease Development of organoid-based drug screening platforms Studying GSK-3 signaling in crypt maintenance Exploring small molecule activators for therapeutic applications Publications highlight his work on Wnt pathway regulation β-catenin signaling in cancer Intestinal organoid models High-throughput drug discovery Notable Awards NIH Pathway to Independence Award Leadership and Training includes Director, Graduate Program in Molecular Medicine Advisor to PhD/MD-PhD students Co-founder of biotech companies ProxyBio and Branch Therapeutics

Mirko Salewskiمشاهده پروفایل

استاد

• Plasma Physics
• Fusion Energy
• Energetic Particle Physics
• +۱۶ مورد دیگر

Mirko Salewski is a Professor in the Department of Physics at the Technical University of Denmark (DTU), specializing in Plasma Physics and Fusion Energy. He is actively involved in international fusion research, working with major tokamaks and stellarators such as JET, ASDEX Upgrade, DIII-D, EAST, MAST, TCV, Wendelstein 7-X, and LHD. He serves as an ITER Scientist Fellow and chairs the ITPA Topical Group on Energetic Particle Physics, coordinating global research efforts to support ITER. Education: Dr. techn. in Plasma Physics, Technical University of Denmark (2020) PhD in Fluid Mechanics, Lund University (2007) MSc in Aerospace Engineering, Technical University of Berlin (2002) BSc in Mechanical Engineering, RWTH Aachen University (1998) Additional studies at University of Washington (2000–2001) and Moscow Aviation Institute (2000) His research focuses on developing advanced diagnostics for energetic particles in fusion plasmas using tomography in velocity- and phase-space. He integrates physics-informed models and neural networks to improve reconstruction accuracy. His work spans experimental diagnostics including fast-ion D-alpha spectroscopy, collective Thomson scattering, neutron and gamma-ray spectroscopy, neutral particle analyzers, fast-ion loss detectors, and ion cyclotron emission. Recent publications emphasize synthetic diagnostics, phase-space tomography, and AI-enhanced modeling, reflecting a strong trend toward data-driven and physics-integrated approaches in fusion research. His work is central to understanding fast-ion behavior in burning plasmas. Scientific Awards: ITER Scientist Fellow Professor Salewski supervises multiple PhD students and leads significant research projects funded by EU and national programs. His projects include fast-ion phase-space tomography in D-T plasmas at JET, AI applications in fusion tomography, and orbit-space sensitivity studies. He teaches courses in Electromagnetism, Plasma Physics, and the Physics of Sports at BSc, MSc, and PhD levels. He is affiliated with key fusion research networks and collaborates extensively with institutions across Europe, the US, and Asia, contributing to the global effort to realize fusion energy.

• Ultrasonics
• Non-Destructive Testing
• Laser-Induced Phased Arrays
• +۳ مورد دیگر

Peter Lukacs is a Research Fellow in the Electronic and Electrical Engineering Department at the University of Strathclyde's Faculty of Engineering. His work focuses on advanced ultrasonic imaging techniques for industrial applications, particularly in additive manufacturing quality control. His research interests center on laser-induced phased arrays, ultrasonic non-destructive testing, and surface acoustic wave spectroscopy. Key areas include volumetric imaging, defect characterization in additively manufactured components, and real-time adaptive data acquisition systems. His publications demonstrate expertise in grating-lobe suppression, sparse array design, and crosstalk mitigation for precision inspection. Lukacs' recent publications reveal a strong focus on applying laser-ultrasound techniques to nuclear fusion reactor components and wire-arc additive manufacturing. His work bridges theoretical array optimization with practical industrial implementation, particularly for near-surface defect detection in aerospace-grade materials. Lukacs serves as Principal Investigator for the EPSRC Doctoral Prize project and Co-investigator for multiple EPSRC-funded initiatives including 'Unveiling the grey area between surface and volume' and nuclear fusion reactor inspection systems. His professional activities include invited talks on adaptive laser-induced phased arrays at international symposia.

Graeme Westمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Data Analytics
• +۹ مورد دیگر

Graeme West is a Professor in the Department of Electronic and Electrical Engineering at the University of Strathclyde, appointed through the Chancellor's Fellowship scheme. He is an academic lead in the University’s Advanced Nuclear Research Centre (ANRC) and is currently seconded part-time to the Alan Turing Institute, where he leads the Critical Infrastructure Theme in the Data Centric Engineering Programme. His work bridges academia and industry, focusing on intelligent systems for energy and nuclear applications. Doctor of Philosophy, Computational Intelligence Methods for Power System Protection Design and Decision Support, University of Strathclyde (2003) Bachelor of Engineering, University of Strathclyde (1998) His research interests lie at the intersection of artificial intelligence and industrial engineering, particularly in intelligent decision support for energy systems. He specializes in applying machine learning, data analytics, and image processing to nuclear asset management, with focus areas including condition monitoring, diagnostics, prognostics, and visual inspection in high-radiation environments. His work supports major nuclear operators such as EDF Energy, Bruce Power, and Sellafield. The recent articles reflect a strong trend toward real-world AI applications in nuclear inspection, emphasizing video denoising, automated defect detection, and explainable AI systems. These works integrate domain knowledge with deep learning to enhance safety and reliability in critical infrastructure. Themes include radiation-affected imaging, predictive maintenance, and intelligent monitoring of reactor components like graphite cores and pressure tubes. While no formal awards are listed, his leadership in high-impact projects and collaborations with national and international partners underscores his recognition in the field. Graeme West supervises research students and leads multiple externally funded projects with organizations like EPSRC, Bruce Power, and EDF Energy. His projects focus on AI-driven inspection, nuclear analytics, and visual monitoring of reactor components. He is also actively involved in professional development, participating in workshops and conferences on AI in engineering and nuclear sustainability. He is affiliated with the Advanced Nuclear Research Centre (ANRC) at the University of Strathclyde and contributes to the Data Centric Engineering Programme at the Alan Turing Institute. His work involves close collaboration with industry partners such as NNL, Sellafield, WideBlue, and Inspecta-hire, forming a robust research network focused on critical infrastructure resilience.