جست‌وجوی استاد و پژوهشگر

Xiaodong Wuمشاهده پروفایل

استاد

• Algorithm Design
• Biomedical Image Analysis
• Geometric Optimization
• +۳ مورد دیگر

Xiaodong Wu serves as Professor in Electrical and Computer Engineering at the University of Iowa College of Engineering, with a joint appointment in Radiation Oncology. He directs research at the Iowa Institute for Biomedical Imaging, Iowa Initiative for Artificial Intelligence, and Iowa Technology Institute, having joined the university in 2005. His academic credentials include: PhD in Computer Science and Engineering, University of Notre Dame (2002) MS in Computer Science, Peking University (1995) BS in Computer Science, Peking University (1992) Wu's research spans Algorithm Design, Geometric Optimization, and Biomedical Image Analysis, focusing on computational methods for medical diagnostics. His work develops AI-driven solutions for computer-aided surgery, data mining, and bioinformatics, emphasizing clinical applicability through algorithmic innovation. Analysis of his 15 most recent publications reveals dominant themes in medical image segmentation using diffusion models and deep learning. Key applications target ophthalmology (retinal imaging, myopia diagnosis), cardiology (takotsubo syndrome analysis), and oncology, with innovations in latent space representations, robust feature extraction, and outlier detection for diagnostic enhancement. No scientific awards were documented in the source material. Regarding academic mentorship, the provided information lists no advised students or specific research grants. Wu leads the Xiaodong Wu Research Group and leverages cross-institute collaborations at the University of Iowa to advance AI applications in medical imaging, particularly through the Iowa Institute for Biomedical Imaging's interdisciplinary framework.

Thomas Kicheyمشاهده پروفایل

مدرس ارشد

• Plant Physiology
• Ecophysiology
• Invasive Species
• +۳ مورد دیگر

Thomas Kichey is a Senior Lecturer HDR at the University of Picardie Jules Verne (UPJV), specializing in ecophysiology and plant physiology within the EDYSAN research unit (UMR 7058). His work focuses on invasive plant species and their ecological impacts under global change, with significant contributions to understanding foliar functional traits in invasion biology. He holds key administrative roles including Head of the Agroecology course in the Master's program in Agronomy, Environment, Territories, Landscape, Forest (AETPF), and serves as International Relations Correspondent for EDYSAN at CNRS. Education: Doctor of Cell Biology Research Focus: Dr. Kichey's research centers on invasive alien species , particularly examining how foliar functional traits drive invasion success in exotic plants. His work spans plant physiology , ecophysiology , and global change biology , with emphasis on leaf economics spectrum dynamics and physiological adaptations in invasive species like Rhododendron ponticum and Acer pseudoplatanus. Recent projects integrate agrivoltaics and crop physiology, demonstrating interdisciplinary innovation. Publication Trends: Analysis of his 15 most recent publications reveals consistent focus on invasive plant mechanisms (75% of articles), with growing emphasis on renewable energy-agriculture interfaces (2023-2025). His work combines field ecology with molecular physiology, predominantly published in high-impact ecology and agronomy journals. Key recurring themes include leaf trait plasticity, invasion impacts on forest ecosystems, and physiological responses to environmental stressors. Advising and Grants: Dr. Kichey has supervised five doctoral theses on topics ranging from forest regeneration to agrivoltaics, securing funding from diverse sources including ADEME, Campus France (PHC Polonium/Ulysses), NSF, and regional councils. Current projects include Displex (2023-2024) on soil functionality impacts and SPECTRIMOINE (2023-2024) on spectral analysis of toxic heritage. Research Infrastructure: As facilitator of EDYSAN's "Functional ecology of forest neo-ecosystems" axis, he leads collaborative work across French Atlantic forests. His international network spans Syracuse University (USA), Lebanese and Tunisian institutions, and European conservation bodies like Conservatoire du littoral, enabling cross-continental studies on invasion dynamics.

• Photonics
• Quantum Computing
• Artificial Intelligence
• +۶ مورد دیگر

Jiaqi Gu is an Assistant Professor at the School of Electrical, Computer and Energy Engineering at Arizona State University. His work bridges photonics, quantum computing, and machine learning to develop next-generation hardware for efficient computing. PhD in Electrical and Computer Engineering, University of Texas at Austin (2023) His research focuses on emerging hardware design (photonics, post-CMOS electronics, quantum), hardware-algorithm co-design , AI/ML algorithms , and electronic-photonic design automation . He explores how photonic and quantum systems can be optimized for AI workloads, with recent work on differentiable photonic simulation, compact optical neurons, and quantum component placement tools. His publications include 20+ papers in 2025 on topics like photonic tensor cores, optical neural networks, and quantum-aware design. Key trends: integrating machine learning with photonic device simulation, optimizing photonic circuits for adversarial robustness, and advancing quantum computer compilation. Scientific awards include: Best Paper at ASP-DAC 2020 Best Poster at NSF Workshop on Machine Learning Hardware 2020 Margarida Jacome Dissertation Prize 2023 Outstanding Dissertation Award 2024 Dr. Gu advises students through EEE 490/590/790 courses and leads the ScopeX research group , which develops tools for photonic and quantum hardware design.

Uwe Hübnerمشاهده پروفایل

استاد

• Materials Science
• Nanotechnology
• Electrocatalysis
• +۱۲ مورد دیگر

Dr. Uwe Hübner is a Professor and Head of Department at the Leibniz Institute of Photonic Technology (IPHT), leading the Competence Center for Micro- and Nanotechnologies. His work bridges nanomaterial synthesis, quantum device fabrication, and optical biosensing, with recent publications spanning electrocatalysis, superconducting resonators, and X-ray imaging. His research interests focus on micro/nanofabrication techniques for quantum and optical devices photocatalytic materials for environmental remediation label-free biosensors and impedance circuit design high-harmonic generation for sub-nanometer imaging Recent publications highlight his contributions to porous platinum layers for CO2 electroreduction cross-type Josephson junctions for scalable quantum computing imaging diffractometric biosensors with single-image readout soft X-ray coherence tomography in the water window These works emphasize interdisciplinary applications of materials science, quantum physics, and environmental engineering. Labs and teams include the Competence Center for Micro- and Nanotechnologies at IPHT, collaborating with international institutions on quantum devices, metamaterials, and advanced fabrication methods like grayscale electron beam lithography.

Mario Zieglerمشاهده پروفایل

پژوهشگر

• Nanotechnology
• Plasmonics
• Photocatalysis
• +۳ مورد دیگر

Mario Ziegler is a Researcher at the Leibniz Institute for Photonic Technology (Leibniz-IPHT) , where he contributes to the Competence Center for Micro- and Nanotechnologies and the Work group Microsystem and Nanotechnology . His work bridges advanced fabrication techniques with applications in quantum devices, environmental science, and space technology. His research interests include: Nanowire-based plasmonic lasers for nanophotonic circuitry Photocatalytic materials for UV-driven dye degradation Superconducting circuits and Josephson junctions for quantum computing Metasurface engineering for ultrafast laser pulse shaping Robust coatings for space applications Recent publications highlight his focus on hybrid plasmonic-photonic systems, scalable fabrication technologies, and material optimization. His team uses techniques like metastable atomic layer deposition, nanomanipulation-assisted optical characterization, and microlensing gas phase electrodeposition to address challenges in device performance, environmental remediation, and space-grade materials. Collaborators include Uwe Hübner, Ronny Stolz, Matthias Schmelz, and other researchers at Leibniz-IPHT and partner institutions. His work on self-assembled nanowire lasers and cross-type Josephson junctions reflects his role in advancing quantum and optoelectronic technologies. Contact: mario.ziegler@leibniz-ipht.de

Andy Woodsمشاهده پروفایل

استاد

• Environmental Fluid Mechanics
• Renewable Energy Systems
• Carbon Capture and Storage
• +۶ مورد دیگر

Andy Woods is a Professor at the University of Cambridge , affiliated with the Department of Earth Sciences. His work spans fluid mechanics of the environment, focusing on critical energy transition challenges. Geothermal power and thermal energy storage Hydrogen and carbon storage in aquifers Ocean mixing and plastic dispersal Volcanic eruption dynamics Climate-adaptive energy systems Recent publications emphasize CO2 sequestration , subsurface energy storage , and volcanic plume modeling . His research combines theoretical and experimental approaches to address environmental fluid dynamics in natural and engineered systems. Collaborative projects include the Cambridge NERC Doctoral Landscape Awards and partnerships with institutions like the British Antarctic Survey.

Abdelkader Oudaمشاهده پروفایل

دانشیار

• Information Security
• Cryptography
• Network Security
• +۹ مورد دیگر

Dr. Abdelkader Ouda is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Western Ontario, with over three decades of experience in academia and the software industry. He holds a Ph.D. in Computer Science from Western University (2005), an M.Sc. in Computer Science and Pure Mathematics from Ain Shams University (1993), and a B.Sc. (Hons) in the same disciplines from Ain Shams University (1986), graduating with the highest honor (96.80%). His research spans information security, cryptography, network security, big data security and privacy, and data analytics . He leads the Information and Computer Networks Security (iCNS) Research Laboratory, focusing on innovative solutions for IoT, fog–cloud computing, and behavioral biometrics. His recent work includes developing the ADG Engine for synthetic data generation and HSM4SSL for intra-domain security. Dr. Ouda’s publications highlight advancements in authentication protocols, lightweight IoT security frameworks, database benchmarking, and machine translation . His industry experience includes 14 years in software development, project management, and system analysis, which he integrates into his teaching of courses like Software Design, Algorithms & Data Structures, and Information Security. He also contributes to engineering accreditation through the CEAMS application. Key trends in his articles include secure communication in hybrid architectures, energy-efficient IoT protocols, and reinforcement learning for continuous authentication . His work bridges academic theory with practical applications, emphasizing efficiency and scalability in modern computing environments.

• Networks
• eHealth
• Internet of Things
• +۳ مورد دیگر

Marwa Salayma is a Researcher at the School of Computing , Edinburgh Napier University. Her work focuses on Wireless Body Area Networks (WBAN) within the domains of eHealth , Internet of Things (IoT) , and Network Reliability . Research Areas: WBAN optimization, Energy Efficiency, Fault Tolerance Collaborators: Ahmed Al-Dubai, Imed Romdhani, Yaser Nasser Her research explores adaptive protocols for IEEE 802.15.4 MAC layer, emphasizing reliability and power conservation in healthcare applications. She has published in IEEE Transactions on Green Communications and Networking and ACM Computing Surveys . Marwa’s thesis (2018) titled Reliable and Energy Efficient Scheduling Protocols for WBAN was supervised by Prof Ahmed Al-Dubai and Dr Imed Romdhani, contributing to advancements in digitized healthcare systems.

Max Ehrlichمشاهده پروفایل

استادیار مدعو

• Machine Learning
• Computational Imaging
• Video Compression
• +۸ مورد دیگر

Max Ehrlich is an Adjunct Assistant Professor at the University of Maryland in the Department of Computer Science and a research scientist at NVIDIA. His work spans machine learning, computational imaging, and compression technologies. Adjunct Assistant Professor, University of Maryland Research Scientist, NVIDIA Research Interests: Combines machine learning with computational imaging to solve real-world problems. Key areas include video/image compression, land cover segmentation, and explainable AI. Research focuses on first-principles understanding rather than black-box models. Recent Publication Trends: 2025 work on implicit neural representations for video compression, 2024 studies on metadata-driven video enhancement, 2023 contributions to adaptive networks, and earlier work on JPEG artifacts, multi-task learning, and remote sensing. Scientific Awards: 3rd place in 2018 CVPR DeepGlobe challenge Teaching: Instructed CMSC421 Intro to Artificial Intelligence (Spring 2024) and CMSC422 Intro to Machine Learning (Spring 2022). Also served as a mentor for high school students.

Arun Ravindranمشاهده پروفایل

دانشیار

• Cloud Computing
• Edge Computing
• Deep Learning
• +۵ مورد دیگر

Arun Ravindran is an Associate Professor at the University of North Carolina at Charlotte, affiliated with the Department of Electrical and Computer Engineering. He leads research in the AI Systems Lab, focusing on integrating generative AI into systems software for scalable, intelligent solutions. Education: Ph.D. in Electrical and Computer Engineering from Ohio State University (2003) M.S. in Electrical and Computer Engineering from Ohio State University (2000) M.Eng and B.Eng in Electrical Engineering from Birla Institute of Technology and Science, Pilani, India (1997 and 1996) Research Interests: Cloud and Edge Computing Systems Deep Learning Applications in Computer Systems Cybersecurity Electronic Design Automation Generative AI for Cybersecurity and Education Power-Efficient Latency-Critical Systems Projects: Currently involved in an NSF-funded initiative to develop scalable edge infrastructure for real-time AI-driven video analytics. His work emphasizes system prototyping, cross-layer optimization, and machine learning integration. Mentoring & Collaboration: Passionate about mentoring undergraduate and graduate students, innovating in teaching, and collaborating with industry and academia to advance technology applications. Hobbies: Enjoys travel, Argentine Tango, BBQ, and Yoga.

• Wireless Sensor Networks
• Industrial IoT
• Vehicular Ad-hoc Networks (VANETs)
• +۳ مورد دیگر

Tingting Zhang is a Professor at Mid Sweden University's Department of Computer and Electrical Engineering (DET), affiliated with the STC Research Centre. Her work focuses on wireless sensor networks, industrial IoT, and privacy-preserving protocols in vehicular and IoT networks. Research spans VANETs, machine learning for anomaly detection, light field imaging, and secure communication systems. Current projects include PLENOPTIMA, COINS, DAWN, and Smart Industry Sweden. Publications emphasize network reliability, security frameworks for IoT/VANETs, and machine learning applications in sensor networks. She has contributed to patents in wireless communication and video noise reduction. Recent work explores cross-layer optimization, privacy-preserving protocols, and GPU-accelerated light field rendering. Collaborations include institutions in Sweden, Finland, and China.

• Materials Science
• Polymer Chemistry
• Biomaterials
• +۴ مورد دیگر

Tuuva Kastinen is a researcher at the Department of Chemistry and Materials Science, School of Chemical Engineering, Aalto University. He contributes to collaborative projects within the Finnish Center of Excellence in Life-Inspired Hybrid Materials (LIBER) and the FinnCERES Materials Bioeconomy Ecosystem. Affiliation: Aalto University Projects: LIBER (2022–2026), Sammalkorpi’s Academy Project (2022–2024) Research Focus: Computational modeling of polyelectrolyte assembly, biomaterials, and organic solar cell materials His work integrates Materials Science , Surface Chemistry , and Computational Modeling to investigate polyelectrolyte complexation, self-assembly, and optoelectronic properties. Recent publications emphasize pH-dependent assembly , ion-pair interactions , and multi-state electronic coupling in hybrid materials. Key projects include the National Science Centre Poland grant (2018–2023) and Academy of Finland Centres of Excellence funding (2022–2029). Computational resources from CSC IT Centre for Finland and PLGrid were utilized in his studies.

• Machine Learning
• Data Privacy
• Security
• +۶ مورد دیگر

Adam Dziedzic is a Tenure Track Faculty Member at CISPA Helmholtz Center for Information Security , where he co-leads the SprintML group . His research focuses on Secure, Private, Robust, Interpretable, and Trustworthy Machine Learning , with applications to diffusion models, large language models, and collaborative learning. He previously held a Postdoctoral Fellow position at the Vector Institute and the University of Toronto , advised by Prof. Nicolas Papernot. He earned his PhD in computer science from the University of Chicago , advised by Prof. Sanjay Krishnan, and holds BSc and MSc degrees from Warsaw University of Technology in Poland. His work spans privacy attacks on image autoregressive models, dataset inference for large language models, differentially private collaborative learning, and defenses against model extraction. Recent publications (2025–2024) address privacy leakage in generative models, synthetic data calibration, secure noise sampling protocols, and memorization mechanisms in self-supervised and multi-modal architectures. Key contributions include: Developing POST for efficient soft prompt transfer in LLMs with privacy guarantees Proposing NeMo to localize and mitigate memorization in diffusion models Advancing Dataset Inference methods for diffusion and self-supervised models Designing secure multiparty computation protocols for collaborative learning His research leverages techniques like differential privacy , knowledge distillation , and statistical testing to balance utility and privacy across distributed systems.

Andreas Kochمشاهده پروفایل

پژوهشگر

• Computational Modeling
• Compressible Multiphase Flows
• CutDG Methods
• +۳ مورد دیگر

Andreas Koch is a Research Associate at the Professorship of Simulation for Additive Manufacturing at the Technical University of Munich (TUM), Germany. His research focuses on computational modeling of compressible multiphase flows, CutDG methods, and high-performance computing with software development. He holds a Master of Science (M.Sc.) in Mechanical Engineering from TUM (2024). Research Interests Koch's work bridges computational mechanics and machine learning, with emphasis on cut discontinuous Galerkin methods for simulating complex flows and high-performance computing systems. His publications demonstrate expertise in machine learning applications for aerospace systems, including anomaly detection in spacecraft telemetry and deep learning acceleration for spaceborne hardware. Scientific Awards ERC Starting Grant Publications (2024-2013) His research portfolio includes 15 recent publications spanning edge AI solutions for spacecraft , RF synchronization systems, and machine learning frameworks for aerospace applications. Earlier work explores robot perception and geoinformatics implementations.

Kathleen O'Connorمشاهده پروفایل

مدرس

• Syntax
• Phonology
• First Language Acquisition
• +۷ مورد دیگر

Kathleen O'Connor is a Lecturer in English Linguistics at the Department of English Studies (Angellier), Université de Lille. She is a member of UMR 8163 Savoirs, Textes, Langage and holds a doctorate in English linguistics from Charles-de-Gaulle University – Lille 3 (2008). Her academic career spans teaching and research roles in France and the USA, with a focus on syntax, phonology, and language acquisition. 1993: BA in French, magna cum laude, Washington and Lee University 1997-1998: MA in French Literature and Linguistics, Indiana University 2008: Doctorate in English linguistics, Université de Lille 3 Her research explores the syntax-phonology interface, particularly in apposition structures across English, French, and Shingazidja. She investigates learner autonomy, tandem language learning, and phonological development in children. Recent work examines metacognitive strategies in teletandem environments and dialectal features of Northern French. Notable trends in her publications include comparative syntax studies, prosody-syntactic interactions, and applications of Optimality Theory to language acquisition. Awards highlight teaching excellence (1999) and educational innovation (2011). Scientific Awards: Elizabeth C. Garrett Award, Washington and Lee University (1992) Award of Excellence & Peter Cannings Prize, Indiana University (1999) Educational Innovation Award, Université de Lille (2011) She has supervised students at the Language Resource Center (2007-2009) and currently leads English Language Readers at Université de Lille 3. Collaborations include co-authorships with Cyril Auran, Rudy Loock, and Cédric Patin.