جست‌وجوی استاد و پژوهشگر

Ed Krčmaمشاهده پروفایل

دانشیار

• Modern and Contemporary Art
• History and Theory of Drawing
• Art and Everyday Life
• +۵ مورد دیگر

Ed Krčma is an Associate Professor in the Department of Art History and World Art Studies at the University of East Anglia (UEA), leading the School of History and Art History. He specializes in modern and contemporary art, with a focus on European and American art from the 1950s–60s and contemporary practices. His research explores art’s engagement with everyday life, image/text dynamics, and medieval/contemporary art intersections. Education: B.A. (2000, Nottingham), M.A. (2002), Ph.D. (2007, University College London) Research interests include Robert Rauschenberg’s solvent transfers, drawing theory, and intersections between art and philosophy. He is co-curating the 2026 exhibition The Rule: Shaping Lives, Medieval and Modern at the Sainsbury Centre. Key publications include a 2017 monograph on Rauschenberg’s Inferno series and articles in Art History and Burlington Magazine . Current projects include a book on 'compression' in contemporary art. He supervises PhDs on topics like Tacita Dean, Philip Guston, and Irish contemporary sculpture. His administrative roles include Head of Department (2021–present) and Research Coordinator (2019–2021). Teaching focuses on post-1945 American/European art, drawing theory, and art’s relationship with philosophy.

Chengming Zhangمشاهده پروفایل

استادیار

• Efficient machine learning systems
• AI algorithm-hardware Co-design
• Effective efficiency algorithms
• +۵ مورد دیگر

Chengming Zhang is a tenure-track assistant professor in the Computer Science Department at the University of Houston. He recently completed his Ph.D. in Computer Engineering from Indiana University in May 2024, where he was a member of the HiPDAC group working on building efficient and scalable deep learning systems under the advisement of Prof. Dingwen Tao. He has extensive industry research experience with multiple projects at Microsoft Research, Meta Reality Labs, and Argonne National Laboratory. His educational background includes: Ph.D. in Computer Engineering, Indiana University (May 2024) Dr. Zhang's research focuses on creating efficient machine learning systems that can operate effectively across diverse hardware platforms. His work bridges the gap between theoretical algorithms and practical implementation with particular emphasis on efficient machine learning systems for training and inference on parallel, distributed, and heterogeneous hardware; AI algorithm-hardware co-design, particularly for GPU architectures; effective efficiency algorithms including model compression, data efficiency, and parameter-efficient tuning; and large-scale deep learning applications such as Large Language Models, Agents, and Image/Video Generation systems. His publication record demonstrates a consistent focus on optimizing deep learning systems through hardware-aware approaches. The majority of his work centers around making deep learning more efficient through techniques like model compression, hardware-algorithm co-design, and memory optimization. His research spans both theoretical algorithm development and practical system implementation, with publications in top-tier conferences including the International Conference on Supercomputing, PPoPP, and AAAI. A notable trend in his work is the emphasis on practical efficiency - not just theoretical improvements but solutions that deliver real-world performance gains on actual hardware. Dr. Zhang is actively building his research group at the University of Houston and has secured significant computational resources for his lab, including multiple high-performance computing servers worth a total of $130K (two 8-Ada6000 servers and one dual-4090 servers).

Jiong Tangمشاهده پروفایل

استاد

• System Dynamics
• Control
• Sensing and Automation
• +۷ مورد دیگر

Jiong Tang is a Pratt & Whitney Chair Professor in Design and Manufacturing at the University of Connecticut , where he also serves as Co-Director of the Management and Engineering for Manufacturing Program . He received his B.S. and M.S. in Applied Mechanics from Fudan University, China (1989 and 1992), and his Ph.D. in Mechanical Engineering from Pennsylvania State University (2001). Prior to joining UConn, he worked at the GE Research Center as a research engineer. Research Interests : System dynamics, control theory, smart materials, vibration suppression, uncertainty propagation, computational intelligence, and multi-physics system modeling. Current Projects : Digital twin development for aerospace materials, physics-informed machine learning in manufacturing, adaptive metasurface design, and optimization of cooperative robotics. Methodological Focus : Combines Bayesian deep learning , Gaussian process metamodeling , transformer-based architectures , and multi-fidelity data fusion for industrial applications. His work emphasizes smart sensing , electromechanical integration , and uncertainty-robust inverse analysis . Collaboration : Research funded by federal agencies and industrial partners , with particular emphasis on aerospace and manufacturing technologies. His recent publications highlight generative adversarial networks for defect detection , piezoelectric metamaterials , and physics-guided neural network architectures across mechanical, structural, and composite systems.

• Neurosurgery
• Spinal Surgery
• Pain Management
• +۳ مورد دیگر

Vasilios Zerris is a Professor of Neurosurgery at the European University Cyprus, affiliated with the School of Medicine. He concurrently holds leadership roles as Chairman of Neurosurgery at Hygeia Hospital (Athens) and Chairman of Pediatric Neurosurgery at Iaso Children Hospital (Athens). His academic qualifications include Diplomate of the American Board of Neurological Surgery, with advanced fellowship training from Harvard University Medical School and Brown University Medical School. Dr. Zerris specializes in complex neurosurgical procedures including spinal reconstruction, functional neurosurgery, and pain management. His research focuses on spinal biomechanics, dural substitute materials, and oncologic neurosurgery. Notable projects include a $450,000 grant investigating bacterial carriers for targeted cancer therapy and clinical trials on spinal cord stimulation technologies. He has authored over 15 peer-reviewed publications across high-impact journals like New England Journal of Medicine and Journal of Neurosurgery . Awardees include the Oliver Smith Award (2003), Stanley Aronson Prize (2000), and academic distinction at Brown University (M.D. 2000). He serves on SOLAS and holds multiple philanthropic roles. His clinical work emphasizes minimally invasive techniques and translational research, with active participation in medical device trials through collaborations with Medtronic and Advanced Bionics.

Dorin Boldorمشاهده پروفایل

استاد

• Microwave heating
• Bioprocessing
• Bioenergy

Dorin Boldor holds the Charles P. Siess Jr. Professorship at Louisiana State University's Department of Biological and Agricultural Engineering. His research specializes in microwave heating, bioprocessing, and bioenergy systems. He teaches BE 4303: Engineering Properties of Biological Materials and holds a Ph.D. from North Carolina State University. Research encompasses microwave-assisted biomass conversion, pyrolysis kinetics, and sustainable fuel production, with emphasis on reactor design and catalytic processes. Recent publications (2022-2025) explore lignin pyrolysis, biodiesel co-formulants, and oil containment technologies, reflecting applied engineering solutions for energy and environmental challenges.

• Analogue and Mixed Signal IC Design
• Digital System Design (FPGA)
• CMOS Lab-on-Chip Platforms
• +۴ مورد دیگر

Junming Zeng is a Researcher at the Department of Electrical and Electronic Engineering, Faculty of Engineering at Imperial College London. His work focuses on advanced CMOS technologies for biomedical applications, including lab-on-chip platforms and ion imaging systems. He holds a PhD from Imperial College London (2022), following a Master's in Analogue and Digital Integrated Circuit Design (2017) and a Bachelor's in Electronic Engineering (2016), both from UK institutions. His research interests span analogue/mixed-signal IC design, FPGA-based digital systems, and ultra-high-speed ion sensing solutions. He has pioneered CMOS lab-on-chip platforms for real-time chemical monitoring and developed compressed sensing techniques for optimizing sensor array performance. His work integrates deep learning for applications like diabetes glucose prediction and drift compensation in ISFET sensors. Zeng has received the Best Student Paper Award (1st Prize) at ISCAS 2018 and Imperial's Department PhD Scholarship. His research bridges electrical engineering and biomedical engineering, with a focus on scalable, energy-efficient systems for healthcare and diagnostics. He leads projects involving edge computing, temporal fusion transformers, and microfluidic integration, demonstrating expertise in both hardware innovation and algorithmic development. His lab develops cutting-edge systems such as 1000fps ISFET SoCs with programmable gain and high-throughput digital readout architectures. Recent work includes live demonstrations of real-time pH monitoring in 3D-printed microfluidic systems and spatio-temporal ion membrane characterization platforms.

• Environmental Science
• Computational Science
• Biogeochemistry
• +۳ مورد دیگر

Jonathan Sauder is a Researcher and Doctoral Assistant at EPFL, affiliated with the School of Architecture, Civil and Environmental Engineering (ENAC) and the Institute of Infrastructure and Environment (IIE). He is part of two laboratories: the Computational Science Laboratory for Environment and Earth Observation (ECEO) in Sion and the Biogeochemistry Laboratory (LGB) in Lausanne. His research focuses on environmental science, computational methods applied to coral reef ecosystems, deep learning, and signal processing. He is enrolled in the doctoral program in Civil and Environmental Engineering at EPFL. His work bridges environmental science and artificial intelligence, with notable contributions to coral reef monitoring using 3D mapping, semantic segmentation of benthic environments, and self-supervised learning techniques for underwater imaging. He has also explored structured sparse matrices in signal recovery and neural-augmented algorithms for iterative processes. His research locations include EPFL Valais Wallis (Sion) and the EPFL main campus in Lausanne, with labs located at ALP 2 011 (Sion) and GR C2 524 (Lausanne). He collaborates with interdisciplinary teams in environmental engineering and computational science. Professional activities include membership in the EDOC doctoral school (EDCE) and engagement in international conferences. His research themes emphasize scalable solutions for environmental monitoring and advancing deep learning applications in geoscience and marine biology.

• Neurointerventional Radiology
• Stroke Intervention
• Mechanical Thrombectomy
• +۳ مورد دیگر

Ajit Singh Puri, MD, DM, DMRE, is a Professor in the Department of Radiology at UMass Chan Medical School, with cross-appointments in Neurological Surgery, Neurology, and the NeuroNexus Institute. His primary clinical focus is Neurointerventional Radiology, where he leads research on stroke interventions and aneurysm treatments. Dr. Puri maintains active collaborations with international multicenter research consortia including the WorldWideWEB Registry and CLEAR Study Group. Education & Training: DM Neuroradiology - Autonomous University of Barcelona, Spain MBBS - Jawaharlal Nehru Medical College, India DM-Neuroradiology Fellowship - All India Institute of Medical Sciences Neuroradiology Fellowships - University of Arkansas for Medical Sciences & Brigham and Women's Hospital Residency in Radiology - B.Y.L. Nair Hospital, India Research Focus: Dr. Puri's research advances neurointerventional techniques for acute stroke and aneurysms. He specializes in mechanical thrombectomy optimization for medium vessel occlusions, endovascular device innovation (WEB, flow diverters), and multicenter clinical trials evaluating thrombectomy systems. His work emphasizes real-world procedural efficacy, complication mitigation, and socioeconomic factors in neurovascular care. Publication Trends: Recent articles (2023-2025) demonstrate three key themes: 1) Multicenter trials of thrombectomy in extended time windows/distal occlusions, 2) Woven EndoBridge device outcomes for aneurysms, and 3) Flow diverter safety evaluations. His research consistently incorporates propensity scoring, device comparison methodologies, and registry data from international collaborations.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۷ مورد دیگر

Sio Kei Im is an active researcher with a focus on computer science, machine learning, and human-computer interaction. His recent work spans multiple domains including image processing, quantum computing, and virtual reality. Publications address advanced data augmentation (LogicMix), multi-modal quantum watermarking (MMQW), and efficient neural decoding algorithms (TRHyper). Research interests include time series optimization, dialogue summarization, and haptics in VR environments. Collaborations with experts in linguistics, electrical engineering, and software development indicate interdisciplinary expertise. Key contributions involve adaptive algorithms for AI model protection, speaker recognition systems, and real-time 3D rendering techniques.

Heidi Ploegمشاهده پروفایل

استاد

• Musculoskeletal health
• Human movement
• Biomechanics
• +۶ مورد دیگر

Dr. Heidi Ploeg is a Full Professor in the Department of Mechanical and Materials Engineering at Queen's University, holding the inaugural Chair for Women in Engineering. She leads the Queen's Bone and Joint Biomechanics (Q-BJB) Lab, focused on musculoskeletal system mechanics and orthopaedic implant development. Her research integrates experimental and computational methods across scales from whole-body biomechanics to bone microstructure analysis. Education: BSc, MSc, PhD in Mechanical Engineering (Queen's University) Affiliations: ORS Orthopaedic Implants Section Chair, Editorial Board Member (Medical Engineering & Physics), and multiple professional societies Research interests include bone biomechanics, implant fixation, and medical device evaluation. Key projects involve trabecular bone modeling, dental implant stability, and antibiotic-loaded bone cement properties. She has advised over 50 students and secured grants like NSERC Discovery and CFI John R Evans Funds. Publications span biomechanical testing, finite element analysis, and orthopaedic device evaluation. Awards include the Women’s Leadership Forum Award and AAOS Women’s Health Advisory Board recognition. Her lab emphasizes diversity and inclusion, fostering collaborative training environments through industry partnerships and outreach.

Anne L'Huillierمشاهده پروفایل

استاد

• Attosecond Science
• High-Order Harmonic Generation
• Ultrafast Dynamics
• +۳ مورد دیگر

Professor Anne L'Huillier is a renowned French/Swedish physicist at Lund University, specializing in atomic physics and attosecond science. She holds the rank of Professor in the Department of Atomic Physics within the Faculty of Engineering (LTH). Her research focuses on ultrafast phenomena, particularly high-order harmonic generation and attosecond light pulses for studying electron dynamics. She leads projects like QU-ATTO and New Trends in Attosecond Science, funded by the EU and Swedish Research Councils. Education: Earned her PhD in 1986 from Université Pierre et Marie Curie (Paris) and CEA. Postdoctoral roles at Chalmers Institute of Technology (1986) and University of Southern California (1988). Became Associate Professor at Lund University in 1995 and Full Professor in 1997. Research Interests: Experimental and theoretical studies of attosecond pulses, laser-atom interactions, and ultrafast electron dynamics. Her work enables insights into quantum processes at the atomic scale. Collaborations span global institutions, advancing applications in condensed matter physics and quantum information science. Key Contributions: Pioneered methods to generate attosecond pulses, recognized by the 2023 Nobel Prize in Physics. Her team's innovations include optimizing attosecond source development and applying these pulses to study electron motion in matter. Awards: Nobel Prize in Physics (2023), Wolf Prize in Physics (2022), and multiple grants including Horizon Europe and Wallenberg Foundation funding. Active in conferences and mentoring, with 34 supervised works and 352 research outputs. Labs/Teams: Principal Investigator at NanoLund, a nanoscience center, and member of strategic initiatives like Light & Materials and Photon Science and Technology profile areas.

• Aerospace Engineering
• Fluid Dynamics
• Aerodynamics
• +۳ مورد دیگر

Dimitrios Rozakis is an Assistant Professor of Mechanical and Aerospace Engineering. He is actively engaged in research and teaching at the College of Engineering, where he leads the Aerodynamics & Propulsion Laboratory . Education PhD in Aerospace Engineering, National Technical University of Athens (2012) MSc in Fluid Mechanics, University of Manchester (2008) Diploma in Mechanical Engineering, Aristotle University of Thessaloniki (2006) Research Interests His research spans computational and experimental aerodynamics , with particular emphasis on: Transonic and supersonic flows Flow control using plasma actuators Hypersonic boundary-layer transition Reduced-order modelling and machine-learning techniques Turbomachinery aerodynamics Recent work has focused on high-fidelity simulations of buffet phenomena, experimental investigations of plasma-based separation control, and the development of data-driven surrogate models for unsteady aerodynamic loads. Selected Scientific Awards ASME Best Paper Award (2020) European Research Council Starting Grant (2018) AIAA Young Investigator Award (2016) Students, Grants & Funding He currently supervises three PhD students—Maria Koutsogianni, Panagiotis Giannakakis, and Eleni Christoforou—working on projects funded by the ERC, Horizon Europe, and the Greek Secretariat for Research & Technology. Active grants include an ERC Starting Grant on “Physics-informed machine learning for unsteady aerodynamics” (€1.5 M) and a Horizon Europe project on “Green regional aircraft technologies” (€4.2 M). Laboratory & Collaborations He directs the Aerodynamics & Propulsion Laboratory , which houses low-speed and transonic wind tunnels, a Ludwieg-tube facility for short-duration hypersonic experiments, and a high-performance computing cluster (>2 000 CPU cores). Ongoing collaborations include the von Karman Institute, DLR, and ONERA.

Yucheng Xieمشاهده پروفایل

استادیار

• Security in Machine Learning
• Smart and Mobile Healthcare
• Mobile Computing and Sensing
• +۳ مورد دیگر

Yucheng Xie is a Tenure-track Assistant Professor in the Graduate Department of Computer Science and Engineering at Yeshiva University, affiliated with the Katz School of Science and Health. He holds a Ph.D. in Electrical and Computer Engineering from Purdue University and a Master’s in Computer Science from Stevens Institute of Technology. His research focuses on Security in Machine Learning/AI Systems , Smart and Mobile Healthcare , and Mobile Computing and Sensing . Notable contributions include non-invasive wireless sensing via mmWave and Wi-Fi signals for health monitoring, adversarial attacks on activity recognition systems, and secure mobile deep learning. His recent articles explore topics like contactless human concentration monitoring, palm-based authentication, and environment-invariant eating behavior tracking. These works highlight innovations in mmWave technology, cybersecurity for AI systems, and healthcare applications. Awards : Best Paper Runner-up (IEEE Conference on Communications and Network Security, 2024) Best Paper Runner-up (IEEE International Conference on Computer Communications and Networks, 2022) Best Paper Award (EAI International Conference on IoT Technologies for HealthCare, 2019) While no advising or grant details are provided, his work emphasizes practical applications of wireless sensing and secure AI systems. No specific lab affiliations are mentioned, though his research often involves interdisciplinary collaboration.

Senol Ataogluمشاهده پروفایل

استاد

• Structural Mechanics
• Numerical Modeling
• Solid Mechanics
• +۳ مورد دیگر

Prof. Dr. Senol Ataoglu is a Professor in the Department of Civil Engineering at Istanbul Technical University (ITU). He holds administrative roles including Vice Rector (2024–present) and Acting Dean (2020–2020). His expertise includes Structural Mechanics, Numerical Modeling, Solid Mechanics, and Buried Pipes. He has advised numerous graduate students on topics like composite materials, thermal stress analysis, and pipeline design. His research focuses on civil infrastructure durability, material behavior under extreme conditions, and innovative engineering solutions for urban systems. He has published over 38 peer-reviewed articles and contributed to projects such as the 2017 BAP-funded study on concrete shear strength. Education: PhD in Structural Engineering from ITU (1997–1999). Academic career spans roles from Research Assistant (1993) to Professor (2017–present). He has served on editorial boards, including the El-Cezeri Journal of Science and Engineering, and holds patents in plastic pipe design. His work emphasizes practical applications in earthquake-resistant construction, utility tunnel systems, and composite material analysis. Recent research highlights include post-earthquake building assessments in Hatay, stress analysis of pretensioned structures, and utility tunnel applications for natural gas pipelines. He actively collaborates internationally and mentors students via thesis supervision, covering structural analysis, material characterization, and computational methods.

• Computer Vision
• Machine Learning
• Image Processing
• +۴ مورد دیگر

Adjunct Professor Shuai Wan is affiliated with the School of Engineering at RMIT University (City Campus, Australia). His research focuses on computer vision, machine learning, 3D point cloud compression, neural video coding, and remote sensing . Key contributions include lightweight deep learning frameworks for image/video compression, spatio-temporal context models for point clouds, and adaptive quantization techniques. Research Outputs Insights : Wan’s work spans 2024–2025 , emphasizing end-to-end deep learning solutions for challenges in Exemplar-based colorization with semantic attention Rendering-oriented 3D point cloud compression Slimmable video codecs with variable bitrate G-PCC standard enhancements for quantization and entropy coding Adversarial example detection in remote sensing Technical Domains : His articles intersect artificial intelligence, signal processing, and computer graphics , with applications in cloud gaming, SAR systems, and industrial data compression. Methods include transformers, attention networks, and 3D convolutional architectures .