جست‌وجوی استاد و پژوهشگر

Thao Nguyenمشاهده پروفایل

استاد

• Biomechanics
• Polymer Engineering
• Materials Science
• +۳ مورد دیگر

Thao (Vicky) Nguyen is a Professor of Mechanical Engineering at Johns Hopkins University, with a secondary appointment in the Department of Materials Science and Engineering. She is co-Deputy Director of the Hopkins Extreme Materials Institute (HEMI). Her research focuses on biomechanics of soft engineering and biological materials, including adaptive polymers, fracture mechanics, and ocular biomechanics related to glaucoma. Key collaborators include the National Eye Institute and National Science Foundation. Nguyen holds a B.S. from MIT (1998), and M.S. and Ph.D. from Stanford (2000, 2004). She previously worked at Sandia National Laboratories. Awards include the James R. Rice Medal (2025), NSF CAREER Award, and multiple ASME honors. Her lab integrates experimental and computational approaches, with notable work on shape-memory polymers and scleral biomechanics. Research interests include collagen growth, liquid crystal elastomers, and architected materials. She leads studies on optic nerve head mechanics, funded by DOD, NEI, and BrightFocus. Nguyen serves on editorial boards for ASME journals and professional societies.

Noura Howellمشاهده پروفایل

استادیار

• Ethical AI
• Emotion AI
• Design Futuring
• +۴ مورد دیگر

Noura Howell is an Assistant Professor in the School of Literature, Media, and Communication at the Georgia Institute of Technology. Her work focuses on ethical AI, emotion AI, and design futuring, emphasizing inclusivity and critical reflection through artistic and technical explorations. She holds a PhD in Information & Management Systems from UC Berkeley and a BS in Engineering from Olin College. Research interests include biosensing technologies, queer/crip design methodologies, and the intersection of embodiment with emerging technologies. Notable projects include the Future Feelings Lab, which critiques emotion AI through participatory audits and fabulative design practices, and investigations into thermal feedback systems and Sufi spiritual practices mediated by technology. Awards include an NSF CAREER Award for reimagining emotion AI, a Google TensorFlow Faculty Award for educational outreach, and the Ralph E. Powe Junior Faculty Enhancement Award. Teaching spans computational media, interaction design, and design futuring courses. Her lab explores speculative design through projects like the Heart Sounds Bench (life-affirming biosensing) and Salaam, an inflatable sculpture addressing Islamophobia. She has collaborated on interdisciplinary STEAM education initiatives like PREMIER artist residencies.

• Distributed Computing
• Distributed Algorithms
• Fault-Tolerance
• +۸ مورد دیگر

Marina Papatriantafilou is an Associate Professor in the Department of Computer Science and Engineering at Chalmers University of Technology and University of Gothenburg. Her research focuses on distributed computing, fault-tolerance, parallel algorithms, and concurrency control. She has contributed to methods for fault-tolerant distributed systems, visualization tools for distributed algorithms, and scalable overlay networks. Her academic roles include teaching advanced courses on distributed systems, computer communication, and operating systems. She advises graduate students in areas like distributed algorithms and parallel computing. Key research interests include lock-free synchronization, memory reclamation, and self-stabilizing systems. She has authored over 100 publications in top-tier conferences and journals, with recent work on data streaming frameworks, energy-sharing optimization, and vehicular network processing. Professional involvement includes roles in program committees for conferences like OPODIS, SWAT, and SSS, plus membership in research evaluation boards for Swedish and European funding agencies. She pioneered educational tools like the Lydian environment for distributed algorithm visualization.

Tony Stockmanمشاهده پروفایل

مدرس ارشد

• Human-Computer Interaction
• Auditory Displays
• Data Sonification
• +۳ مورد دیگر

Dr. Tony Stockman is a Senior Lecturer at Queen Mary University of London's School of Electronic Engineering and Computer Science. His teaching focuses on Database Systems, Interaction Design, and Semi-structured Data Modelling across undergraduate and postgraduate programs. His research interests include Human-Computer Interaction, Auditory Displays, and Data Sonification, with a strong emphasis on accessibility and cross-modal interfaces. Dr. Stockman has contributed to over 100 publications, exploring topics such as biofeedback systems, assistive technologies for visually impaired individuals, and collaborative design methodologies. His work frequently bridges technical innovation with user-centric design principles. Notable projects include the development of non-visual navigation tools like the Audiom web-based map viewer and co-designed haptic wearables for music synchronization. His research also addresses challenges in education technology, such as dyslexia screening through serious games.

Anne McLaughlinمشاهده پروفایل

استاد

• Human Factors Engineering
• Cognitive Aging
• Applied Cognitive Psychology
• +۳ مورد دیگر

Anne McLaughlin is a Professor in the Department of Psychology at North Carolina State University, affiliated with the College of Humanities and Social Sciences. She directs the LACElab (Learning, Aging, and Cognitive Ergonomics), focusing on human factors, cognitive aging, and technology usability. She holds a Ph.D. in Engineering Psychology from Georgia Tech (2007) and has been at NC State since 2007. Her education includes a B.A. in Psychology and English Literature from Trinity University (1998), an M.S. in Engineering Psychology from Georgia Tech (2003), and her Ph.D. from the same institution (2007). Her research integrates cognitive science principles with real-world applications, emphasizing aging populations and technology design. Key research interests include cognitive aid design, augmented/virtual reality applications, human-robot interaction, and medical device usability. Recent work explores diminished reality techniques for attention management, trust dynamics in autonomous systems, and veterinary patient safety culture. Her articles highlight trends in human-centered technology development, particularly addressing individual differences in attention control, automation trust, and healthcare system optimization. She advocates for inclusive design principles to enhance older adults' engagement with technology and improve medical screening accessibility. McLaughlin’s work bridges academic research and practical implementation, with collaborations in healthcare, robotics, and educational technology. Her lab’s focus on aging-related challenges underscores her commitment to improving quality of life through human-centered solutions.

• Communication Security
• Embedded Systems Security
• Design of Embedded Systems
• +۴ مورد دیگر

Alberto Ferrante is a Lecturer and Researcher at the Faculty of Informatics of the Università della Svizzera italiana (USI), affiliated with the IDSIA (Dalle Molle Institute for Artificial Intelligence) USI/SUPSI. His work bridges cybersecurity, embedded systems, and AI applications, particularly in IoT and pest control. He holds a PhD from Università degli Studi di Milano (2006) and an MSc from Politecnico di Milano (2002). Research Interests: Ferrante focuses on Secure communication protocols and embedded systems security Malware detection and resource-optimized hardware solutions Machine learning applications for IoT, including agricultural pest monitoring and healthcare diagnostics Cyber-physical systems design and security-enhanced embedded systems His publications emphasize practical implementations, such as AI-driven UAVs for pest control and low-power drone systems for environmental monitoring. He actively contributes to tech transfer projects with industry partners and participates in major conferences like ICC and Globecom as a TPC member. He teaches the Master’s course Edge Computing in the IoT and collaborates on hardware-software co-design for security-critical systems. His work often integrates real-world constraints like energy efficiency and computational resource limitations. Key contributions include frameworks for dynamic security adaptation in wireless sensor networks and hardware-accelerated security for embedded systems.

Christian Tetzlaffمشاهده پروفایل

استاد

• Computational Neuroscience
• Synaptic Physiology
• Neuromorphic Engineering
• +۴ مورد دیگر

Prof. Christian Tetzlaff holds a W2 Professorship at the Department for Neuro- and Sensory Physiology, University Medical Center Göttingen. He leads the Computational Synaptic Physiology group, focusing on integrating computational methods to understand neural systems' principles and translating these into technologies like robotics and neuromorphic engineering. His work spans scales from synaptic protein interactions to large neural networks, leveraging disciplines such as nonlinear dynamics and machine learning. Educational Background: 2009: Diploma in Physics, Georg-August University Göttingen 2013: PhD in Physics (Dr.rer.nat.), Georg-August University Göttingen Research Leadership & Grants: Principal Investigator in EU Horizon 2020 Projects (Plan4Act, ADOPD, Human Brain Project's FIPPA) Lead in DFG-funded SFB 1286 (Quantitative Synaptology) INRC member (Intel Neuromorphic Research Community) BMBF-funded KISSKI project (2022–present) Research Interests: His lab explores synaptic mechanisms underlying learning, memory consolidation via synaptic tagging-and-capture, and neuromorphic hardware implementations. Recent work emphasizes calcium signaling in synapses, memristive devices for synaptic working memory, and robust trajectory generation using neuromorphic chips like Loihi. Affiliations: Co-coordinator of Plan4Act (2017–2021) and active in the Göttingen Graduate Center for Neurosciences (GGNB). Collaborates globally with institutions like the Weizmann Institute and Columbia University. Laboratory: Visit tetzlab.com for lab activities and open-source tools like Plastic Arbor .

• Construction Engineering
• Simulation Science
• Information Technology in Construction
• +۳ مورد دیگر

Simaan Abourizk, PhD, PEng, is the Dean of the Faculty of Engineering at the University of Alberta and holds the rank of Professor in Construction Engineering and Management. He also served as the NSERC/Alberta Construction Industry Research Chair (1997–2011) and Canada Research Chair in Operations Simulation (2001–2008). His roles include Executive Board membership at the Construction Research Institute of Canada. Education: Doctor of Philosophy in Construction Engineering and Management from Purdue University (1990), Master of Science and Bachelor of Civil Engineering (Honors) from Georgia Institute of Technology (1985 and 1984). Research focuses on advancing simulation technologies for construction and natural resource industries, including: Development of the Simphony simulation environment and COSYE framework Integration of AI, visualization, and scheduling tools (e.g., SmartEst, MTRACK) Optimization of tunneling, modular assembly, and industrial fabrication processes Key awards include the E. Whitman Wright Award (2002), E.W.R. Steacie Memorial Fellowship (2001), and Walter Shanly Award (2001). Current projects emphasize synthetic environments, safety analytics, and data-driven decision support systems in construction. He leads initiatives on risk simulation, resource allocation, and industrial automation.

Michael L. Austinمشاهده پروفایل

مدرس ارشد

• Sound and music in interactive media
• Ludomusicology
• Sound studies
• +۷ مورد دیگر

Dr. Michael L. Austin is a Senior Lecturer in Music and Sound at Edge Hill University, serving as Programme Leader in Music Production since January 2023. He previously held academic roles at Louisiana Tech University, Howard University, and others. His research focuses on sound and music in interactive media, including video games, social media, and smart devices. He is Executive Director of the Society for the Study of Sound and Music in Games and a Research Associate at the Library of Congress's Radio Preservation Task Force. Education: PhD in Humanities (Aesthetic Studies) from the University of Texas at Dallas (2011), MA in Music Theory from UT Austin (2007), and BA in Music Composition from UT San Antonio (2005). Research interests include ludomusicology, cultural representation in media, sound design for UX, and algorithmic bias in emerging technologies. His 2024 monograph Audiovisual Alterity explores identity representation in music videos, while earlier works like Music Video Games: Performance, Politics, and Play (2016) analyze music's role in digital games. Publications span video game music analysis, algorithmic bias, and sound art. His talks include topics like 'Sounding Drag Identities in Video Games' and 'Algorithmic Bias in Emerging Media.' As a sound artist, his work has been exhibited at the Smithsonian and Dallas Museum of Art.

• High-Performance Computing
• Parallel Programming
• Domain-Specific Languages
• +۳ مورد دیگر

Wenguang Chen is a researcher affiliated with Tsinghua University and Pengcheng Laboratory , specializing in computer science and high-performance computing . His work bridges theoretical advancements with practical applications in domain-specific languages , parallel programming , and machine learning . Research Interests include: Development of modular DSLs for numerical methods (e.g., Mat2Stencil) Performance optimization in distributed and parallel systems Compiler frameworks for privacy-preserving AI (e.g., FHE-based neural network inference) Graph algorithms scaling to trillion-edge datasets Applications of Rust in memory-safe pointer analysis Recent Publications span 2014–2025, focusing on: Parallelization strategies for supercomputing Compiler automation tools Extreme-scale data processing Performance variance diagnosis in production environments

• Statistics
• Machine Learning
• Financial Econometrics
• +۵ مورد دیگر

Jennifer Chan is a Professor in the Statistics Department at the University of Sydney's Faculty of Science. She earned her PhD from the University of New South Wales in 1997 and previously lectured at the University of Hong Kong before joining her current institution in 2006. Her research integrates statistical and machine learning models with applications in finance and insurance, including volatility modeling, Bayesian methods, and neural network applications. Her interdisciplinary research focuses on: Generalized linear mixed models and multivariate volatility measures Machine learning techniques for financial risk assessment Bayesian robustness and portfolio optimization Time-series analysis of cryptocurrencies and equity markets Recent publications demonstrate strong focus on Bayesian models in finance (42% of last 15 papers), machine learning applications (33%), and actuarial science (25%), with emerging emphasis on neural networks for financial forecasting. Awards & Honors: Second prize, Natural Science Award of China's Ministry of Education (2008) National Drug Strategy Research Scholarship (1994-1996) She supervises doctoral candidates working on machine learning applications in finance and insurance. Her international collaborations include institutions in Israel, Japan, Malaysia, and the United States.

Saptarshi Dasمشاهده پروفایل

دانشیار

• Two-Dimensional Materials
• Semiconductor Devices
• Field-Effect Transistors
• +۵ مورد دیگر

Saptarshi Das is an Associate Professor in the Department of Engineering Science and Mechanics within the College of Engineering at Pennsylvania State University. His research focuses on cutting-edge semiconductor technology, particularly in the realm of two-dimensional materials for next-generation electronic devices. Das maintains an active research program with numerous publications in high-impact journals including Nature, Nature Electronics, and Nature Communications. Dr. Das's research interests center around two-dimensional materials, semiconductor devices, and nanoelectronics with applications in AI hardware and computing systems. His work explores the fundamental properties and applications of materials like transition metal dichalcogenides (MoS 2 , WSe 2 ), graphene, and other 2D materials for creating novel electronic devices that can overcome limitations of traditional silicon-based technology. His research spans from fundamental material science to practical device implementation, with particular emphasis on developing energy-efficient computing solutions. Analysis of Dr. Das's recent publications reveals a strong focus on 2D material-based transistors, 3D integration techniques, and novel computing architectures. His work demonstrates significant advancements in p-type 2D transistors, monolithic 3D integration, and biomimetic sensor systems. The research shows a clear trajectory toward developing non-silicon computing platforms that could revolutionize AI hardware and low-power electronics. Dr. Das leads an active research group with multiple PhD students and collaborators working on semiconductor device fabrication, characterization, and integration. His laboratory likely has strong connections with Penn State's Materials Research Institute and other interdisciplinary research centers focused on advanced materials and semiconductor technology. His research has attracted significant attention, with multiple mentions in university news and science media outlets highlighting breakthroughs in 2D computing and electronic tongue technology.

Jie Dingمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Statistics
• Scientific Computing
• +۶ مورد دیگر

Jie Ding is an Associate Professor at the University of Minnesota's School of Statistics with graduate faculty appointments in Electrical Engineering, Computer Science, and the Data Science Program. He serves as a core faculty member of the Data Science and AI Hub and holds an Amazon Scholar position with the Amazon AGI Team focusing on foundation model training. His educational background includes a Ph.D. in Engineering Sciences from Harvard University (2017), postdoctoral work at Duke University (2018), and a B.S. from Tsinghua University where he participated in both the Math & Physics Academic Talent Program and Electrical Engineering program. Ding's research sits at the intersection of artificial intelligence, statistics, and scientific computing, with focus areas including Agentic AI for autonomous data science workflows, AI Foundations for interpretability and trustworthiness, Scalable Modeling for broader AI accessibility, Decentralized and Collaborative AI systems, and AI Safety addressing privacy and security concerns. He developed the STAT 8931 Generative AI course with open-source materials available at genai-course.jding.org . His recent publications demonstrate strong activity across multiple AI subfields, particularly in value alignment (MAP framework), AI safety mechanisms, federated learning innovations, and statistical foundations for modern AI systems. The breadth of venues (ICML, ICLR, NeurIPS) indicates significant impact across the AI research community. NSF CAREER Award (2024) Army Early Career Program (Young Investigator) Award (2023) Cisco Research Award (2022-25) AWS Cloud Credits for Research (2021-22) Meta/Facebook Faculty Research Award (2021-22) UMN Thank-A-Teacher Teaching Award (2019-20) Ding leads the Agentic AI for Data Science Benchmark initiative, collaborating with University of Minnesota colleagues and Minnesota industry partners to evaluate AI agent capabilities across healthcare, insurance, retail, energy and other sectors. His research group actively recruits PhD students interested in AI/Statistics intersections, with focus on developing theoretically grounded yet practically impactful AI systems.

Tuğçe Bilenمشاهده پروفایل

استادیار

• Artificial Intelligence
• Computer and Communication Networks
• Digital Twin
• +۴ مورد دیگر

Tuğçe Bilen is an Assistant Professor at Istanbul Technical University's Department of Artificial Intelligence and Data Engineering, within the School of Computer and Informatics. Her research focuses on Artificial Intelligence and Computer and Communication Networks, particularly Digital Twin technologies, 6G wireless systems, and smart IoT applications. PhD in Computer Engineering (2017-2022), Istanbul Technical University Master's in Computer Engineering (2016-2017), Istanbul Technical University Licence in Computer Engineering (2010-2015), Istanbul Technical University Her research explores Digital Twin middleware for smart farms, energy-aware task scheduling in 6G edge networks, aeronautical ad-hoc network optimization, and cloud-based protocol enhancements. Recent work addresses metaverse-driven supply chain optimization and secure routing for aircraft networks. Key publication trends show strong focus on: Digital Twin integration across domains 6G wireless network architectures Adaptive routing algorithms Energy-efficient IoT systems Security in airborne communication Machine Learning for network management Scientific recognition includes: Serhat Özyar Young Scientist of the Year Honorary Award (2023) Doctoral Thesis Award from Istanbul Technical University (2023) TÜBA Doctoral Science Awards-Teknofest (2023) She serves as Principal Investigator for the Unsupervised Learning-Based Management of Ad Hoc Airborne Network Topology project (2024-2026) and holds a patent for Parametric Parsing Based Routing System in Content Delivery Networks (2021). As IEEE member since 2015, she contributes to telecommunications standards.

• Machine Learning
• Computational Biology
• Medical Informatics
• +۹ مورد دیگر

Günter Klambauer is a Professor at the Institute for Machine Learning , Johannes Kepler University Linz, and leads the LIT Artificial Intelligence Lab in Austria. His research bridges artificial intelligence with life sciences , focusing on deep learning applications in retinal imaging , drug discovery , and hydrological modeling . Affiliation: JKU Institute for Machine Learning & LIT Artificial Intelligence Lab Key Research Areas: Medical Imaging AI, Biological Sequence Modeling, Generative Models for Molecules, Time-Series Forecasting His recent publications highlight extended LSTM architectures (xLSTM) for biological sequence modeling, contrastive learning in retinal imaging, and in-context learning for low-data drug discovery. He has pioneered frameworks like TiRex for zero-shot forecasting and LaM-SLidE for spatial dynamical systems. Scientific Awards: Austrian Life Science Award (2012) Award of Excellence (2014) ELLIS Society Scholar (2020) Director, ELLIS Machine Learning for Molecules Discovery Program (2023) Professor Klambauer collaborates extensively on AI-driven biomedical projects , including retinal image analysis and antibody design, while advancing foundational neural network architectures for diverse domains from healthcare to climate modeling.