جستجوی استاد راهنمای دانشگاهی

Lloyd Nicholas Trefethen is Professor of Numerical Analysis and Fellow of Balliol College at the University of Oxford, a position he has held since 1997. He also has concurrent appointments as Global Distinguished Professor of Mathematics and Computer Science at New York University (2013–2019) and has served as Von Neumann Professor at TU Munich and Matheon Professor at TU Berlin in 2010. Education: PhD (Computer Science/Numerical Analysis), Stanford University, 1982 MS (Computer Science/Numerical Analysis), Stanford University, 1980 AB summa cum laude (Applied Mathematics), Harvard College, 1977 Research Interests: Trefethen’s work centers on numerical mathematics, with particular emphasis on spectral methods , numerical linear algebra , approximation theory , numerical conformal mapping , quadrature , and pseudospectra . His research often bridges rigorous mathematical theory and practical algorithms, most notably through the widely used Chebfun software system. Recent publications illustrate a trend toward developing fast, high-accuracy algorithms for solving classical problems such as the Laplace and Helmholtz equations, rational approximation via the AAA algorithm, and stability analysis in fluid mechanics without traditional eigenvalue techniques. Scientific Awards: Pólya Prize for Mathematical Exposition (SIAM, 2017) Naylor Prize (London Mathematical Society, 2013) Gold Medal (Institute of Mathematics and its Applications, 2011) Fellow of the Royal Society (2005) Member of the US National Academy of Engineering (2007) ERC Advanced Grant (2012–2017) Honorary doctorates from Stellenbosch University and University of Fribourg (2019) Advising & Grants: Trefethen has supervised 24 PhD/DPhil students at MIT, Cornell, and Oxford; twelve have launched academic careers. He has held major grants including an ERC Advanced Grant on “Computing with functions instead of numbers” (€2.4 M, 2012–2017) and EPSRC funding for the Chebfun System (2006–2010). Labs & Teams: He leads the Chebfun Team at Oxford, an interdisciplinary group developing open-source software for numerical computing with functions. The team collaborates globally with researchers in mathematics, computer science, and engineering.

• Numerical analysis
• Applied mathematics
• Approximation theory
• +۶ مورد دیگر

Joseph Alejandro Gallego Mejia is an Assistant Teaching Professor in the Department of Computer Science at Drexel University's College of Computing and Informatics. He holds a PhD with meritorious distinction in Systems and Computing Engineering from the National University of Colombia, along with a Master’s and dual Bachelor’s degrees in Systems and Computing Engineering and Industrial Engineering. PhD in Systems and Computing Engineering, National University of Colombia (Meritorious Distinction) Master of Systems and Computing Engineering, National University of Colombia Bachelor of Engineering in Systems and Computing Engineering, National University of Colombia Bachelor of Engineering in Industrial Engineering, National University of Colombia His research focuses on artificial intelligence, machine learning, computer vision, quantum machine learning, natural language processing, and cybersecurity. He explores robustness estimation, anomaly detection, incremental learning, and scalable software architectures for AI systems. His work bridges theoretical foundations and practical applications in health, remote sensing, and edge computing. The recent publications reflect a strong trend in interdisciplinary AI research, combining machine learning with quantum computing, cybersecurity, and natural language understanding. His work spans domains such as satellite imagery analysis, medical diagnostics, IoT security, and conversational AI, demonstrating a commitment to scalable and robust intelligent systems. Keywords across publications include Computer Science, Machine Learning, Quantum Computing, and Cybersecurity, with subfields ranging from adversarial robustness to hybrid quantum-classical models. Scientific distinctions include: PhD with meritorious distinction, National University of Colombia Postdoctoral fellow, Frontier Development Lab (Trillium), supported by NASA and ESA He has served as a reviewer for top-tier journals and conferences including Neurocomputing, IEEE Access, Radioscience, NeurIPS, and NLDL. Though no formal grants are listed, his postdoc was funded by NASA and ESA, indicating significant external support. He teaches courses in programming, data science, machine learning, deep learning, NLP, and software engineering. He founded the tech company Sammu and mentors students through instruction and research supervision. He is actively involved in research and teaching, contributing to innovative programs in AI and computing education. His lab and team affiliations are not explicitly stated, but his work suggests collaboration with AI, quantum computing, and cybersecurity research groups.

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۱۲ مورد دیگر

IIham ALLOUI is a permanent Lecturer in Computer Science (CNU 27 section) at Savoie Mont Blanc University since 1998, based at Polytech Annecy-Chambéry. She leads research in intelligent software systems at the LISTIC laboratory. Her roles include managing the Competency-Based Approach (CBA) mission for Polytech and overseeing the Pix Digital Skills project for the university. Education : PhD in Computer Science from Université Grenoble II (1992-1996), DEA in Computer Science from Université Grenoble II (1989-1990). Research Themes : Focuses on evolving software systems, model-driven engineering, distributed intelligent systems, and adaptive architectures using formal methods like modal logic, process algebra, and Markov Decision Processes. Her recent work (2015–present) involves designing adaptive 'Wise Object' frameworks for autonomous learning in software systems, with applications in fraud detection and microservice optimization. She co-supervised multiple theses on software architecture refinement, remodularization, and knowledge representation. Grants & Projects : Led or contributed to projects such as OpenCloudware (FUI), EcoCitoyen (AAP), and McWO/COMDA (USMB AAPs), addressing cloud architectures, home automation modeling, and educational innovation. Teaching : Specializes in model-driven engineering, software quality, and formal programming methods. Initiated educational projects like Reflexpro and APC By Karuta to enhance student professionalization and skill-based learning.

• Intelligent software systems
• Model-driven engineering
• Distributed systems
• +۵ مورد دیگر

Pierre Alliez is a Senior Researcher and Team Leader at Inria Sophia Antipolis – Méditerranée, leading the TITANE project-team. He holds roles such as President of the Inria Evaluation Commission and Scientific Coordinator of the Inria-DFKI partnership. His research focuses on Geometry Processing, including mesh compression, surface reconstruction, and optimal transportation. Alliez has authored numerous scientific publications and book chapters, receiving accolades like the Eurographics Young Researcher Award (2005) and ERC grants (IRON, TITANIUM). His academic activities include supervising over 50 PhD students and postdoctoral researchers, and leading projects like GRAPES (Learning and Processing Shapes) and BIM2TWIN (digital twin construction). He has served on editorial boards for Computer Graphics Forum and ACM Transactions on Graphics , and organized major conferences like Pacific Graphics and Eurographics. His work bridges computational geometry, computer graphics, and applied mathematics, with practical applications in 3D printing, cultural heritage, and urban modeling. Education: No specific educational details provided, but has authored a textbook on Polygon Mesh Processing (AK Peters, 2010). Research Interests: Geometry Processing, Mesh Generation, Surface Reconstruction, Optimal Transport, and 3D Data Analysis. Grants & Projects: ANR Pisco, ERC IRON, BIM2TWIN, GRAPES, and collaborations with industries like Dassault Systèmes and Dorea Technology. Labs/Teams: Leads the TITANE team at Inria, contributing to software like CGAL and advancing open-source tools for geometric processing.

• Geometry Processing
• Computer Graphics
• Computational Geometry
• +۵ مورد دیگر

Rehan Syed is a Professor at Queensland University of Technology's School of Information Systems within the Faculty of Science and Engineering. His research focuses on Business Process Management (BPM), Robotic Process Automation (RPA), and Process Mining, with significant contributions to understanding digital transformation challenges in public and healthcare sectors. He has authored/co-authored over 35 peer-reviewed publications in top journals and conferences like BPM, HICSS, and ECIS. Key areas of expertise include leadership in IT initiatives, healthcare data quality, and low-code adoption strategies. Recent work emphasizes RPA's impact on organizational processes and knowledge retention. His research bridges academic theory with practical implementation, often collaborating with institutions like UN agencies and healthcare organizations. Publications span case studies in developing countries, systematic reviews, and curriculum development frameworks for BPM education. His work is cited across disciplines, reflecting its relevance to both academia and industry.

• Business Process Management
• Robotic Process Automation (RPA)
• Process Mining
• +۴ مورد دیگر

Colin D. Smith is a Senior International and Defense Researcher and Professor of Policy Analysis at the RAND School of Public Policy, RAND Corporation. His expertise spans national security, military strategy, Russia and Eastern Europe, U.S.-European relations, NATO, military logistics, and cyber warfare. He has held significant roles in defense research and policy analysis, drawing on decades of military experience. Education: M.A. in National Security Affairs (Russia and the former Soviet Union), Naval Postgraduate School B.S. in Engineering, U.S. Naval Academy Graduate, Amphibious Warfare School Graduate, Marine Corps Command and Staff College (Non-Resident) Graduate, Defense Language Institute CMC Senior Fellow, Center for a New American Security (CNAS) Smith’s research focuses on defense policy and global security challenges, particularly amphibious operations, cyber acquisition, and geopolitical vulnerabilities in semiconductor supply chains. He has led analyses on U.S. Marine Corps logistics, Navy readiness, and the strategic implications of China-Taiwan unification. His work combines operational military insight with rigorous policy analysis. His recent publications reflect a strong trend in defense modernization, strategic competition, and the interplay between technology and national security. Themes include naval survivability, cyber capabilities, reserve force readiness, and critical supply chain dependencies in high-stakes geopolitical environments. Scientific Awards: No awards listed in the provided text. Smith has not advised any named students in the provided material. His grants and funding sources are not explicitly mentioned, though his research is institutionally supported by RAND. He brings extensive operational and policy experience to his academic and research roles. He is actively involved in research teams at RAND, particularly within the National Security Research Division (NSRD), Arroyo Center, and Health Sciences Research Division (HSRD), focusing on defense strategy and international security. He also contributes to public discourse through commentary and expert analysis.

• National Security
• Military Strategy
• International Affairs
• +۱۰ مورد دیگر

Peter Karsmakers serves as Associate Professor at KU Leuven's Department of Computer Science within the Faculty of Engineering Technology, based at the Geel Campus. He coordinates the Declarative Languages and Artificial Intelligence (DTAI) research group and holds leadership roles including coordinator of Research and Education for Computer Science across Geel and Diepenbeek Campuses. Karsmakers earned his PhD in Engineering Science in May 2010, focusing on kernel-based learning algorithms for sparse modeling and efficient predictions from large datasets. His doctoral work established foundations for his current research trajectory in resource-constrained machine learning systems. His research integrates machine learning with signal processing for real-time sensor data interpretation, specializing in anomaly detection from acoustic, radar, and accelerometer signals on embedded devices. Current projects address industrial condition monitoring, elderly care systems, and livestock facility monitoring through three main tracks: acoustic monitoring (e.g., SINS, WATCHDOG), radar-based systems (e.g., FARADAY, NextPerception), and smart electronics for power converters. Recent publications demonstrate strong trends in constraint-guided deep learning architectures for industrial applications, cross-environment robustness in sensor systems, and domain-knowledge integration to reduce data requirements. His work consistently bridges theoretical machine learning with practical implementations in resource-constrained environments. No scientific awards or fellowships were mentioned in the provided materials. Karsmakers supervises over 10 master's theses annually and coordinates a research team of 10 PhD students and a post-doc within DTAI-ADVISE. He has secured approximately 2.3 million euros in funding through VLAIO, EU-ECSEL, and bilateral industry contracts, including 10 active projects such as AutoEdgeML (2024-2028) and Fault Tolerant Neural Networks for Space Applications (2024-2027). He leads the DTAI-ADVISE research group focused on developing software that attaches semantics to sensor data on resource-constrained devices. The team operates across multiple campuses with specialized labs for acoustic monitoring (Geel), radar-based systems (in collaboration with ESAT-TELEMIC), and smart electronics (with Electrical Engineering department), maintaining strong industry partnerships with companies in healthcare, manufacturing, and agriculture sectors.

• Machine Learning
• Deep Learning
• Anomaly Detection
• +۵ مورد دیگر

Arun Rai serves as Regents’ Professor and Howard S. Starks Distinguished Chair at Georgia State University's Robinson College of Business, where he co-founded and directs the Center for Digital Innovation. His career spans interdisciplinary research bridging information systems with societal impact through industry-university collaborations across global sectors. His educational foundation includes: Ph.D. from Kent State University MBA from Clarion University of Pennsylvania M.S. from Birla Institute of Technology & Science Rai's research explores digital innovation , AI governance , and societal impacts of technology through investigations of platform ecosystems, supply chain transformation, and digital solutions for poverty and health disparities. His work uniquely connects technical systems design with behavioral and organizational outcomes across contexts from rural India to global corporations. Recent publications (2023-2025) reveal intensifying focus on AI-human collaboration , digital risk assessment , and platform governance tensions , with growing emphasis on healthcare applications and equity implications. The trajectory shows evolution from organizational IT adoption toward complex sociotechnical systems addressing global challenges. His scientific recognition includes: Fellow of the Association for Information Systems Distinguished Fellow of the INFORMS Information Systems Society LEO Award for Lifetime Exceptional Achievement Rai has mentored over 60 doctoral students (30+ as chair) with alumni now holding leadership positions globally. His research attracts major funding from Apollo Hospitals, China Mobile, IBM, Intel, UPS, and federal agencies, enabling real-world implementations like the Global Supply Chain Solutions Program during UPS's digital transformation. Current initiatives focus on generative AI in education and healthcare IT policy impacts. As director of the Center for Digital Innovation, he cultivates cross-sector partnerships advancing digital transformation through collaborative research on AI governance, platform ecosystems, and societal impact measurement.

• Information Systems
• Digital Innovation
• Artificial Intelligence
• +۴ مورد دیگر

Dr. Ben Swift is a Senior Lecturer at the School of Cybernetics, ANU, specializing in AI, computational art, and cybernetics. He leads the Cybernetic Studio, an interdisciplinary collective exploring cybernetic systems through hardware/software/people collaborations. As a livecoding artist, he performs globally and co-founded the ANU Laptop Ensemble. His research spans generative AI, open-source tools like Extempore, and UX design. Education: PhD in Computer Science (ANU) Projects: Australia's Digital Economy (2022), The Augmented Web (2019) Research focuses on AI creativity, biofeedback interfaces, and computational music. His work bridges technical innovation with artistic expression, evident in projects like TSPNet and adversarial camera systems. Key contributions include Extempore’s development and studies in live coding disruption. Awards unspecified but recognized internationally for interdisciplinary impact.

• Artificial Intelligence
• Machine Learning
• Computational Art & Music
• +۴ مورد دیگر

Dr. Yiran Chen is the John Cocke Distinguished Professor at Duke University's Department of Electrical and Computer Engineering, leading the NSF AI Institute for Edge Computing (Athena) and the Duke Center for Computational Evolutionary Intelligence (DCEI). A global leader in neuromorphic computing, emerging memory systems, and edge AI, he holds prestigious roles including IEEE Fellow and Editor-in-Chief of IEEE Transactions on Circuits and Systems for AI. His research spans machine learning accelerators, security-hardened hardware, and co-design of EDA tools with LLMs. With over 700 publications and 96 patents, he has been awarded 15 paper awards and 17 nominations, including rare Technical Achievement Awards from IEEE societies. He advises over 60 PhD students and 4 postdocs, many of whom hold academic positions worldwide. His work bridges academia and industry, contributing to startups and venture capital through his board roles. Education: B.S. (Tsinghua, 1998) → M.S. (Tsinghua, 2001) → Ph.D. (Purdue, 2005). Career path: Assistant/Associate Professor at University of Pittsburgh (2010–2014) → Duke since 2014. Awards include the ACM SIGDA Outstanding New Faculty Award (2014), NSF CAREER Award (2013), and the Stansell Family Distinguished Research Award (2022). Research focuses on innovations in: (1) Non-volatile memory architectures for AI acceleration, (2) Hardware-software co-design for edge computing, (3) Security in neuromorphic systems, and (4) Large-scale ML for EDA. His group pioneered ReRAM-based accelerators like ReBNN and MARC, and introduced novel edge AI frameworks like Ecco and Prosperity. These works address scalability, energy efficiency, and real-time performance challenges. Key initiatives include the NSF IUCRC for Alternative Sustainable & Intelligent Computing (ASIC), advancing sustainable computing through novel materials and architectures. His leadership in standard-setting bodies like the IEEE Circuits and Systems Society ensures cutting-edge research translates into industry practices. Grants: Lead PIs for multiple NSF AI Institutes and industry partnerships. Labs: Directs the Athena Institute and DCEI, fostering collaboration between academia and industry. Current projects include quantum computing placement algorithms (QPlacer), federated learning frameworks (FedGPT), and neuro-symbolic architectures.

• Emerging memory and storage technologies
• Embedded systems
• Cyber-Physical Systems (CPS)
• +۵ مورد دیگر

Maarten De Vos is a Professor at the Department of Electrical Engineering (ESAT) , KU Leuven , with dual appointments in the Faculty of Medicine and Faculty of Engineering Science . He leads interdisciplinary research at the intersection of artificial intelligence and biomedical signal processing.

• Artificial Intelligence
• Biomedical Signal Processing
• Sleep Research
• +۴ مورد دیگر

Mendel Rosenblum is the Cheriton Family Professor and holds dual appointments as Professor in the Departments of Computer Science and Electrical Engineering at Stanford University. He is a co-founder of VMware Inc. and served as its Chief Scientist for its first decade, playing a pivotal role in designing foundational virtualization technologies. Rosenblum's research focuses on system software, distributed systems, and computer architecture, with notable contributions to virtualization, data center networks, and operating systems. He leads the Platform Lab at Stanford, exploring next-generation data center technologies and high-performance computing systems. Administrative Role: Faculty Director of Stanford Computer Forum (2012–present) Education: PhD (UC Berkeley, 1992), MS (UC Berkeley, 1989), BA (University of Virginia, 1984) His research interests span disk storage management, computer simulation, scalable operating systems, and security. Recent work emphasizes deployable consensus algorithms, programmable smartNICs, and self-programming networks. Rosenblum has authored over 80 publications and holds multiple patents in virtualization and system software. Awards & Recognition: ACM System Software Award (2009) IEEE Computer Entrepreneur Award (2011) ACM Thacker Breakthrough in Computing Award (2018) Member, National Academy of Engineering (2013) He advises PhD and Master's students, including current advisees Sina Jandaghi Semnani and Zixi Liu. Rosenblum teaches advanced courses on web applications, distributed systems, and independent research projects.

• System Software
• Distributed Systems
• Computer Architecture
• +۴ مورد دیگر

Karthik Dantu is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, State University of New York, within the School of Engineering and Applied Sciences. His research focuses on mobile sensor networks, robot networks, networked embedded systems, mobile computing, wireless networks, and embedded operating systems. He leads the Distributed Robotics and Networked Embedded Sensing (DRONES) Lab and has received significant funding including an NSF CAREER Award. Dr. Dantu's educational background includes: PhD in Computer Science from University of Southern California (2009) BE in Computer Science from Sri Jayachamarajendra College of Engineering (1999) His research interests center on algorithmic and systems challenges in Edge Computing Systems, with particular focus on enabling seamless vision sensing in cloud-edge environments. Dantu's work bridges mobile systems and robotics, developing novel approaches for UAV software, visual SLAM, and distributed sensing. His research addresses critical challenges in resource-constrained environments, security, and real-time performance for mobile and robotic systems, with emphasis on practical implementations that solve real-world problems in autonomous systems. Dr. Dantu's publication record shows a strong trajectory in mobile systems and robotics research, with increasing focus on edge computing applications for visual sensing. His recent work demonstrates expertise in adapting visual SLAM to edge environments, securing mobile systems through technologies like Rushmore, and developing novel approaches for UAV software reliability and depth sensing. The research spans theoretical algorithms and practical system implementations, with particular strength in bringing academic research to practical applications in robotics and mobile computing. Dr. Dantu has received several scientific honors: NSF CAREER Award on Enabling Seamless Vision Sensing in Cloud-Edge Systems Outstanding service award from the Office of International Services NSF Travel Grant for SenSys 2005 Conference Travel Grant for SIGCOMM 2002 As an advisor, Dr. Dantu has mentored numerous PhD students to completion, with graduates now working at companies like Samsung Research and Zoox Inc., or continuing academic careers as Assistant Professors. His research is supported by substantial grants including a DARPA OFFSET Sprint 4 award ($470k), an NSF CAREER award ($550k), and multiple NSF collaborative grants totaling over $1.5 million. He serves on numerous conference committees including Mobicom, MobiSys, and ICRA, demonstrating leadership in the mobile systems and robotics research communities. Dr. Dantu leads the Distributed Robotics and Networked Embedded Sensing (DRONES) Lab at UB, which focuses on developing algorithms and systems for mobile sensor networks, robot networks, and embedded sensing applications. The lab's work spans theoretical foundations to practical implementations, with particular expertise in UAV systems, visual SLAM, and edge computing for robotics, maintaining strong collaborations with industry partners and other academic institutions to advance the state of the art in mobile and robotic systems.

• Mobile Sensor Networks
• Robot Networks
• Networked Embedded Systems
• +۸ مورد دیگر

Xueqiang (Brandon) Wang is an Assistant Professor of Computer Science at the University of Central Florida (UCF), where he is affiliated with the Cyber Security and Privacy Cluster. He leads the Security and PRIvacy for smarT systems (SPIRIT) lab, focusing on technical solutions for security and privacy threats in real-world systems. Education Ph.D. in Computer Science, Indiana University Bloomington (2021) Master’s in Computer Science, IIE CAS (2015) Bachelor’s in Computer Science, USTC (2012) Research Interests Security and privacy compliance for software supply chains Mobile and IoT systems security Cybercrime analysis Vulnerability discovery and exploitation Automated security analysis and data-driven mitigation strategies Labs & Teams Lead the SPIRIT Lab at UCF, specializing in security and privacy for smart systems.

• Software Supply Chain Security
• Mobile and IoT Systems Security
• Cybercrime Analysis
• +۳ مورد دیگر

Samar Sabie is an Assistant Professor at the Institute of Communication, Culture, Information and Technology (ICCIT) at the University of Toronto, where she also serves as Program Director for the Technology, Coding, and Society (TCS) program. She holds a graduate appointment at the Daniels Faculty of Architecture, Design, and Landscape, reflecting her interdisciplinary work bridging technology, design, and social justice. She leads the Open Design Collaboratory, a research space focused on critical and community-centered design practices. Education: Doctor of Philosophy, Department of Information Science, Cornell University/Cornell Tech, 2022 Master of Science, Department of Computer Science, University of Toronto, 2017 Master of Architecture, John H. Daniels Faculty of Architecture, Landscape, and Design, University of Toronto, 2015 Honors Bachelor of Science (Architecture and Computer Science), University of Toronto, 2011 Her research investigates design as a socio-material practice that fosters community adaptive capacity toward sustainable change. Drawing from architecture, software engineering, ethnography, and philosophy, she explores participatory design , unmaking , and design for social justice . Her work critically engages with how communities resist, adapt, and reimagine technology in contexts of displacement, scarcity, and inequality. Her recent publications, appearing in top venues like CHI , CSCW , and DIS , reveal a strong thematic focus on unmaking as a design strategy for emancipation and agonism, mobility justice , e-waste practices , and cultural memory through design. These works collectively emphasize community agency, ethical ambiguity, and the political dimensions of design. Scientific Contributions: Director, Open Design Collaboratory Program Director, Technology, Coding, and Society (TCS) Graduate Faculty, Daniels Faculty of Architecture, Design, and Landscape Current Courses: CCT204 Design Thinking I, CCT477 Understanding Users Samar Sabie actively mentors students and collaborates on research focused on humanitarian technology, critical making, and design education. Her projects often involve community engagement, participatory methods, and interdisciplinary teams. She has collaborated with and advised early-career researchers such as Dina Sabie, Awais Hameed Khan, and Taneea Agrawal on topics ranging from IDP shelter dynamics to mobility justice advocacy. Her research is supported by her deep engagement with socio-technical challenges in marginalized contexts, and she continues to push the boundaries of how design can serve as a tool for equity, care, and resistance. Future work appears to be evolving toward deeper philosophical inquiries into destruction, care, and the limits of technology.

• Design for Social Justice
• Participatory Design
• Unmaking
• +۷ مورد دیگر