جست‌وجوی استاد و پژوهشگر

• Materials Science
• Bioelectronics
• Biomedical Engineering
• +۵ مورد دیگر

Shuo Li is a Professor in the Department of Macromolecular Engineering at ETH Zürich, Switzerland. His research focuses on innovative biomaterials, bioelectronic systems, and implantable medical devices. Key areas include bioresorbable materials for transient electronics, flexible/stretchable sensors, and soft robotics applications. His work integrates materials science with biomedical engineering to address challenges in tissue integration, real-time diagnostics, and programmable drug delivery. Recent projects emphasize wireless implantable sensors for continuous monitoring of physiological parameters such as blood flow, oxygen saturation, and pH levels in surgical flaps and organ grafts. He has pioneered 3D shape-morphing displays using liquid metal actuators and developed self-healing elastomeric switches for haptic interfaces. His research spans biomaterial synthesis, optoelectronics, and additive manufacturing of soft materials. Publications highlight advancements in bioresorbable platforms for drug delivery, light-controlled actuation systems, and optical probes for in vivo pharmacology. His interdisciplinary approach bridges material design, device fabrication, and clinical applications, with a focus on translating lab innovations into practical medical solutions. Advising and grants: No specific advisees or grant details listed in the provided text. However, his extensive publication record indicates active collaboration with research groups in bioelectronics, soft robotics, and biomedical engineering. Labs/Teams: Likely affiliated with ETH's Macromolecular Engineering lab and collaborate with multidisciplinary teams in materials science, robotics, and medical device development.

Stuart Manglesمشاهده پروفایل

استاد

• Laser-Plasma Physics
• High-Intensity Lasers
• Particle Acceleration
• +۵ مورد دیگر

Professor Stuart Mangles is a leading academic in laser-plasma physics at Imperial College London's Department of Physics, part of the Faculty of Natural Sciences. His research focuses on high-intensity laser interactions, plasma-based accelerators, and applications in quantum electrodynamics (QED), X-ray imaging, and material science. He leads projects like the EuPRAXIA initiative, developing compact particle accelerators. Recent work includes experiments on radiation reaction effects, muon production, and ultrafast X-ray imaging of dynamic phenomena. Mangles' lab leverages cutting-edge laser facilities to explore topics ranging from warm dense matter to medical irradiation techniques. Research Highlights: Developing laser wakefield accelerators for compact, high-brightness X-ray sources Investigating quantum effects in ultra-high intensity laser-plasma systems Pioneering applications in radiobiology and industrial imaging Advancing shock dynamics and material phase transitions understanding His work bridges fundamental physics with applied technologies, with significant contributions to the European Strategy for Particle Physics and international collaborations.

Mandy Plumbمشاهده پروفایل

دانشیار

• Motor Control
• Neurodevelopmental Disorders
• Pediatrics
• +۳ مورد دیگر

Mandy Plumb is an Associate Professor in Clinical Exercise Physiology at the School of Science and Technology, University of New England (UNE), Armidale Campus. Her work integrates neuroscience, motor control, and sports science to address critical gaps in pediatric neurodevelopmental disorders and female athlete development, with strong community engagement through The Female Co initiative. Education: Bachelor of Clinical Exercise Physiology (2023), University of New England PhD in Orthopaedic Surgery (2005), University of Aberdeen, Scotland, UK BSc (Hons) in Sports Science (2000), University of Wales, Bangor, UK Research Interests: Dr. Plumb's primary focus spans two interconnected domains: (1) Pediatric neurodevelopmental disorders, where she investigates motor proficiency, sleep patterns, and mental wellbeing in children with ADHD, Autism, and Developmental Coordination Disorder using fNIRS brain imaging and biomechanical analysis; and (2) Female athlete development, particularly for Aboriginal and Torres Strait Islander women and girls from remote Australia, through The Female Co's holistic programs combining athletic testing, strength conditioning, and recovery monitoring. Her work bridges clinical exercise physiology with community-based interventions to address health disparities. Publication Trends: Analysis of her 15 most recent publications (2019-2024) reveals three dominant research thrusts: motor control in neurodevelopmental disorders (35% of articles), sports injury epidemiology in cricket (27%), and female athlete performance optimization (20%). Methodologically, she increasingly employs neuroimaging (fNIRS) alongside biomechanical analysis, with growing emphasis on community-level interventions and health equity for underserved populations. Scientific Awards: Senior Fellow, Higher Education Academy Advising and Grants: Dr. Plumb has successfully supervised 3 PhD, 50 Master's, and 46 Honours students to completion, with current mentorship of 1 MPhil and 1 Master's candidate. Her research is supported through strategic partnerships with Exercise and Sports Science Australia (serving on Course Accreditation Committee since 2021), Sports Medicine Australia, and The Female Co, focusing on grants related to neurodevelopmental interventions and athlete development programs for remote communities. Labs and Teams: As Board Member and Athletic Performance Lead for The Female Co, she directs comprehensive programs including baseline athlete testing, sleep monitoring, strength and conditioning, and recovery protocols for emerging female athletes from discrete remote regions. Her campus-based work utilizes UNE's motor control laboratories equipped for fNIRS, motion capture, and biomechanical analysis, with strong ties to the Applied Agricultural Remote Sensing Centre for community health mapping.

Al Bovikمشاهده پروفایل

استاد مهمان

• Digital Video
• Visual Neuroscience
• Deep Learning
• +۳ مورد دیگر

Al Bovik is a Visiting Professor at the University of Texas at Austin's Department of Electrical and Computer Engineering, part of the College of Engineering. His research focuses on digital video, visual neuroscience, and deep learning, with an emphasis on developing perceptual theories for high-quality streaming video and virtual/augmented reality systems. He has pioneered advancements in video quality assessment, compression, and AI-generated media evaluation. He has received prestigious awards including the IEEE Edison Medal, Primetime Emmy, and membership in multiple national academies. Bovik co-founded the IEEE Transactions on Image Processing and established the IEEE International Conference on Image Processing in 1994, which he chaired. His influential books include The Essential Guides to Image and Video Processing . Key Research Contributions: HDR/SDR video quality metrics, perceptual artifact detection, and AI-driven quality assessment frameworks. Labs/Teams: Leadership in IEEE initiatives and collaborations in media quality and signal processing. His work bridges theoretical research with practical applications in video streaming, medical diagnostics, and user-generated content analysis.

Georg Grohمشاهده پروفایل

استاد مدعو

• Applied Computer Science
• Social Signal Processing
• Social Network Analysis
• +۴ مورد دیگر

Georg Groh is an Adjunct Professor at the Technical University of Munich (TUM), affiliated with the TUM School of Computation, Information and Technology . His research focuses on modeling social context, social interaction mediated by IT systems, and ML-based natural language processing. He holds a doctorate (2005) and habilitation (2012) from TUM, with prior studies in physics and computer science. Key research areas include social signal processing, network analysis, and bias detection in AI systems. Notable awards include the 2019 Supervisory Award and 2016 Honorary Teaching Certificate. His work bridges computational methods with societal impacts, particularly in health informatics and ethical AI. Recent projects explore LLM hallucination detection, bias profiling, and cross-lingual text classification. Education: PhD in Computer Science (2005), TUM Habilitation in Computer Science (2012), TUM Studies in Physics (University of Kaiserslautern) and Computer Science (Universities of Hamburg, Kaiserslautern, TUM) Research Interests: Groh’s work spans social computing, NLP, and ethical AI . Current projects address bias in language models, hate speech detection, and data-driven health interventions. His methodologies emphasize contextual analysis of social interactions, leveraging ML and graph-based techniques. Awards: 2nd place Supervisory Award (2019) Best Paper Awards (2016, 2008) Advising & Grants: Advised on projects like Nutrilize (nutrition recommender system) and contributed to EU-funded initiatives on mHealth systems. Active in designing AI systems for dietary logging and stress management.

Slim Essidمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Signal Processing
• +۵ مورد دیگر

Slim Essid is a Full Professor at Télécom Paris and coordinator of the Audio Data Analysis and Signal Processing (ADASP) group. He holds a PhD and HDR from Université Pierre et Marie Curie (UPMC). His research focuses on machine learning, artificial intelligence, and signal processing applied to temporal data analysis, including multiview learning, representation learning, and structured prediction. Applications span music content analysis (MIR), multimodal perception (e.g., EEG data analysis), and human behavior analysis. He has advised 15 PhD students and collaborated on over 14 post-doctoral projects. Education: PhD in Signal Processing, Université Pierre et Marie Curie (2005) Habilitation (HDR), Université Pierre et Marie Curie (2015) M.Sc. in Digital Communication Systems, Télécom ParisTech (2002) Engineer Degree, École Nationale d’Ingénieurs de Tunis (2001) Research interests emphasize multimodal learning, self-supervised representation learning, and audio-visual fusion. Key projects include sound-prompted segmentation, zero-shot audio captioning, and EEG-based auditory attention decoding. Over 150 peer-reviewed publications exist across conferences like NeurIPS, ICML, and journals like IEEE Transactions. Active in reviewing for top-tier venues and advising French/EU research projects. Labs/Teams: Member of the Signal, Statistics and Learning (S2A) research team and the Information Processing and Communication Laboratory (LTCI).

Shresth Guptaمشاهده پروفایل

پژوهشگر ارشد

• Biomedical Signal Processing
• Photoplethysmography (PPG)
• Artificial Intelligence in Healthcare
• +۷ مورد دیگر

Shresth Gupta is a Research Fellow in the School of Mathematics and Physics at the University of Surrey, affiliated with the Mathematics at the Interface Group. His research lies at the intersection of biomedical signal processing, artificial intelligence, and healthcare innovation, with a focus on photoplethysmography (PPG)-based monitoring for non-invasive diagnostics. Education: PhD in Electronics and Telecommunication Engineering, International Institute of Information Technology, Naya Raipur, India (2023) M.Tech in VLSI Design, CSVTU, Bhilai, India (2014) B.E. in Electronics and Telecommunication Engineering, CSVTU, Bhilai, India (2011) His research interests include biomedical signal processing , PPG signal analysis , machine learning for healthcare , wearable health monitoring , and telemedicine . He specializes in developing AI-driven models for cuffless blood pressure estimation, early diabetes detection, cerebral infarction screening, and PPG signal denoising and compression. His work leverages advanced signal processing techniques such as TQWT, DCT, and Savitzky-Golay filtering, combined with machine learning models like Random Forest, LSTM, and CNNs. The recent publications reflect a strong trend in leveraging PPG signals for non-invasive, continuous health monitoring . His research spans from fundamental signal enhancement (denoising, compression) to clinical applications (diabetes, hypertension, stroke). The work consistently targets real-world deployment in wearable devices, emphasizing robustness, accuracy, and compliance with clinical standards like the British Hypertension Society benchmarks. Scientific Awards: No awards listed in the provided text. Shresth Gupta has not published any information about advising students or securing research grants in the given content. However, his extensive publication record in high-impact journals and conferences (IEEE, Springer) indicates active research engagement. He is involved in interdisciplinary teams working on healthcare technology innovation, particularly within the Mathematics at the Interface Group at the University of Surrey, which likely fosters collaboration between mathematics, physics, and medical applications. His future work is expected to further advance AI-powered, wearable-based diagnostic systems for chronic disease management.

Neill Campbellمشاهده پروفایل

استاد

• Visual Computing
• Machine Learning
• Computer Vision
• +۱۳ مورد دیگر

Neill Campbell is a Professor of Visual Computing and Machine Learning in the Department of Computer Science at the University of Bath . He is the Director of the Centre for the Analysis of Motion, Entertainment Research and Applications (CAMERA) and co-director of the Centre for Mathematics and Algorithms for Data (MAD) . He holds an external position as Honorary Associate Professor at University College London and is a Royal Society Industry Fellow. His research spans visual computing, machine learning, and their applications in graphics, vision, and healthcare. His educational background includes a Master of Engineering and a Doctor of Philosophy in Engineering from the University of Cambridge, with his PhD focusing on Automatic 3D Model Acquisition from Uncalibrated Images. Neill Campbell’s research interests lie at the intersection of shape modeling , machine learning , and computer vision . He develops probabilistic and deep learning models to understand and generate visual content, with applications in digital humans, virtual production, biomechanics, and medical imaging. His work emphasizes uncertainty quantification, generative modeling, and alignment learning using Gaussian processes and Bayesian nonparametrics. He leads interdisciplinary projects that bridge computer science and mathematical sciences. The recent publications reflect a strong trend in probabilistic modeling , geometric deep learning , and medical applications . Topics include Gaussian process-based shape modeling, anomaly detection in safety-critical systems, and sparse approximations for geometric representations. His work increasingly integrates theoretical machine learning with real-world applications in health, engineering, and creative industries. Royal Society Industry Fellow Neill Campbell actively supervises PhD students across multiple Centres for Doctoral Training (ART-AI, SAMBa, CDE) and leads significant research grants such as MyWorld (UKRI Strength in Places Fund) and REMODEL (EPSRC). His group collaborates with industry leaders like Rolls-Royce, NVIDIA, Adobe, and DNEG, and he supports student internships and industrial placements. He is also involved in spin-out activities, including contributions to Forceteck Ltd. He leads the Visual Computing Group and is deeply embedded in research centers including CAMERA , MAD , and MyWorld . His team includes postdoctoral researchers and PhD students working on 3D reconstruction, biomechanics, inverse problems, and generative models, fostering a collaborative and interdisciplinary research environment.

Peter Hommelhoffمشاهده پروفایل

استاد

• Dielectric Laser Acceleration
• Nanophotonics
• Ultrafast Electron Dynamics
• +۴ مورد دیگر

Peter Hommelhoff is a Professor in the Chair of Laser Physics at Friedrich-Alexander University Erlangen-Nürnberg (FAU) . His research focuses on dielectric laser acceleration , nanostructured electron sources , and quantum nanophotonics . Key Research Areas: Quantum-coherent control of free electrons Attosecond electron pulse generation Ultrafast dynamics in 2D materials (graphene, hexagonal systems) On-chip photonic particle acceleration Light-driven electron emission from nanotips Quantum interference in electron-photon interactions Recent Publications highlight advancements in dielectric laser accelerators (Nature, 2023), auto-ponderomotive beam control (Phys. Rev. Lett., 2024), and non-classical electron emission (Nature Physics, 2024). His work also explores graphene valley control and Bloch electron interferometry for material band-structure analysis. Laboratory Context: The Chair of Laser Physics at FAU investigates nanostructured electron sources , photonic control of charged particles , and quantum applications in electron microscopy and sensing. Collaborations span quantum nanophotonics , attosecond science , and integrated photonic circuits .

Irene Rocchiمشاهده پروفایل

دانشیار

• Experimental Soil Mechanics
• Advanced Geotechnical Testing
• Laboratory Soil Characterisation
• +۱۲ مورد دیگر

Irene Rocchi is an Associate Professor in the Department of Environmental and Resource Engineering, specializing in Geotechnics & Geology at the Technical University of Denmark (DTU). Her research integrates experimental soil mechanics with innovative engineering solutions, focusing on ground characterization, soil behavior across scales, and sustainable geotechnical practices. She leads key projects such as SoIA (Soil is alive) and B-test, contributing to advancements in geotechnical instrumentation and interdisciplinary soil science. PhD, City University of Hong Kong (2010–2014) MSc in Civil Engineering, Politecnical School of Turin (2007–2009) Bachelor in Civil Engineering, University of Bologna (2004–2007) Her research interests center on experimental soil mechanics, with a strong focus on laboratory and field characterization, unsaturated soils, micro-scale analysis, and the influence of biological factors on soil behavior. She emphasizes innovation and the translation of research into practical engineering applications, particularly in flood protection, ground improvement, and sustainable infrastructure. The recent publications reflect a consistent trend in advanced geotechnical testing, probabilistic modeling, and interdisciplinary biogeotechnics. Her work spans from fundamental soil behavior studies to applied technologies like digital twins and energy storage in geomaterials, demonstrating a strong integration of mechanics, sustainability, and innovation. Semper Ardens Excellence Grant (Carlsberg Foundation) InnoExplorer Grant (B-test project) Irene Rocchi actively supervises PhD students and contributes to major research projects at DTU. She has been involved in industrial collaborations and has led funded projects focusing on sustainable underground construction, soil swelling, and infrastructure performance. Her work bridges academic research and real-world engineering challenges. She is involved in the SoIA research group and contributes to DTU’s Sustainable Geotechnics initiative, where she develops new sensing technologies and promotes interdisciplinary approaches to soil science. Her lab focuses on advanced soil testing, NMR-based homogeneity assessment, and biologically influenced soil mechanics.

Ralf Brownمشاهده پروفایل

پژوهشگر

• Machine Translation
• Computational Linguistics
• Digital Forensics
• +۵ مورد دیگر

Ralf Brown is a Principal Systems Scientist at Carnegie Mellon University's School of Computer Science, affiliated with the Language Technologies Institute (LTI). His research focuses on machine translation , language identification , and digital forensics , with notable contributions like the open-source CMU-EBMT system and the LTI LangID Corpus for 2000+ languages. Academic Roles: Research faculty since 1993, teaching courses like Coding & Algorithms Bootcamp and MIIS Capstone Project . Research Interests: Multilingual processing, example-based translation, low-resource languages, and text mining. Scientific Contributions: Authored 15+ publications on EBMT, corpus indexing, and context-sensitive translation. Developed tools for digital forensics (corrupted ZIP recovery) and language identification at scale. Awards: IJCAI Distinguished Paper Award Allen Newell Award for Research Excellence Open-Source Contributions: Key developer of darktable image editor Maintainer of the Interrupt List and other technical resources

Mauro Rodriguezمشاهده پروفایل

استادیار

• Computational Fluid Dynamics
• Multiphase Flows
• Viscoelasticity
• +۳ مورد دیگر

Mauro Rodriguez is an Assistant Professor of Engineering at Brown University's School of Engineering. His research focuses on computational fluid dynamics, multiphase flows, viscoelasticity, and high-performance computing. He holds a position at Barus & Holley 441 and can be reached at mauro_rodriguez@brown.edu. His research interests include studying fluid-structure interactions, cavitation bubble dynamics, and inertial effects in complex fluids. Rodriguez explores applications ranging from biomedical engineering (e.g., pulmonary alveolus deformation under ultrasound) to exascale computing for multiphysics simulations. His work often involves numerical modeling and rheometry techniques to characterize material properties. Recent publications highlight advancements in simulating cavitation phenomena, bubble collapse mechanics, and GPU-accelerated algorithms. Rodriguez’s research bridges theoretical fluid dynamics with practical engineering challenges, leveraging high-performance computing resources to tackle multiscale problems. No scientific awards or grants are explicitly listed in the provided materials. His advising activities and lab affiliations remain unspecified.

Joonsik Hwangمشاهده پروفایل

استادیار

• Compression/Spark Ignition Engines
• Alternative Fuels
• Advanced Combustion
• +۳ مورد دیگر

Joonsik Hwang is an Assistant Professor at the Michael W. Hall School of Mechanical Engineering, Mississippi State University (MSU), USA. He holds positions in both the Center for Advanced Vehicular Systems (CAVS) and the Mechanical Engineering department. His research focuses on advanced propulsion systems, spray dynamics, and combustion optimization, particularly in compression ignition engines and alternative fuels. Education: Dr. Hwang earned his Ph.D., M.S., and B.S. in Mechanical Engineering from the Korea Advanced Institute of Science and Technology (KAIST), Republic of Korea, in 2017, 2013, and 2011, respectively. Research Interests: His work emphasizes plasma-assisted ignition, biofuel combustion, soot particle characterization, and high-speed optical diagnostics. He employs CFD simulations and experimental techniques like transmission electron microscopy (TEM) and 3D tomography to study fuel spray behavior and engine performance. Publications: His research spans combustion optimization, fuel injection dynamics, and emission reduction. Recent trends include machine learning for spray modeling, hydrogen jet analysis, and cold-start engine performance. His articles address both fundamental combustion science and practical applications in automotive systems. Awards: 2017 KAUST Travel Fellowship, 2017 ISEES Best Thesis Award, 2016 KSAE Research Award Lab: He directs the Advanced Propulsion & Spray Laboratory at MSU, focusing on innovative propulsion technologies and sustainable fuel systems. His lab collaborates with institutions like Sandia National Laboratories and the Engine Combustion Network (ECN).

• Computer Vision
• Artificial Intelligence
• Machine Learning
• +۶ مورد دیگر

Dr. Chris Thomas Conly is an Assistant Professor in the Department of Computer Science and Engineering at The University of Texas at Arlington (UTA). He holds a PhD in Computer Engineering and a BS in Computer Science, both from UTA. His roles include serving as Director of Undergraduate Computer Engineering (2025–Present) and Co-Director (2023–2024). He previously held positions such as Senior Lecturer (2016–2020) and GTA/GRA (2012–2016). Education: PhD Computer Engineering (2016), BS Computer Science (2006), both from UTA. Affiliations: Member of Tau Beta Pi, Upsilon Pi Epsilon, ACM, and IEEE. Research interests focus on Computer Vision , AI/Machine Learning , and Gesture Recognition . His work includes developing deep learning methods for HEVC video processing, assistive technologies for sign language interpretation, and gesture recognition systems. Teaching interests include programming, senior design projects, and deep learning. Publications span topics like HEVC optimization, CNN-based classification, and assistive technologies, reflecting contributions to computer vision and signal processing. His 15 most recent articles highlight advancements in video compression, neural networks, and gesture analysis. He has received awards such as the Shining Star Teaching Award (2024) and NSF PETRA Doctoral Consortium Awards (2014–2015). He advises numerous students in doctoral and master’s theses, including Isaac Valdez, Evan Cornish, and Minh Tram. Service roles include leading ABET accreditation efforts, curriculum committees, and student organization advising. He mentors in REU programs and contributes to outreach initiatives, emphasizing broadening participation in computing. Labs/Teams: Involved in CSE capstone design projects, robotics competitions (IEEE Region 5), and assistive technology research through collaborations like PETRA conferences.

Aritra Duttaمشاهده پروفایل

استادیار

• Machine Learning
• Federated Learning
• Optimization
• +۷ مورد دیگر

Aritra Dutta is an Assistant Professor at the AI Initiative of the University of Central Florida (UCF), primarily affiliated with the Department of Mathematics and secondarily with the Department of Computer Science. He also holds an affiliation with the Pioneer Centre for AI (P1), Denmark. His research focuses on optimization (stochastic/nonconvex), distributed computing (including federated learning), numerical linear algebra, machine learning, low-rank approximation, and computer vision applications such as image/video analysis and object detection/tracking. Dr. Dutta’s work emphasizes interdisciplinary approaches, blending mathematical rigor with computational efficiency. He actively seeks Ph.D. students and postdocs with strong foundations in mathematics (optimization, linear algebra) or computer science (ML, distributed systems), prioritizing candidates with publication records in top-tier venues. His teaching includes courses in applied mathematics and computational methods. His research outputs span communication-efficient distributed learning frameworks, convergence analysis of optimization algorithms, and vision transformer architectures. Notable projects include GAEA (geolocation-aware conversational models) and MAVREC (multi-view aerial visual recognition). Postdoc opportunities: Open for exceptional candidates. Labs/Initiatives: UCF AI Initiative (UCF Aii), UCF Center for Research in Computer Vision (CRCV). Grants: Competitive research assistantships with tuition support.