جست‌وجوی استاد و پژوهشگر

• Digital Twins
• Smart Cities
• Blockchain Technology
• +۵ مورد دیگر

Noel Crespi is a Professor and Director of Studies at Telecom SudParis, part of Institut Polytechnique de Paris. He leads research in the NeSS group and is affiliated with SAMOVAR, a prominent research laboratory focusing on networks, systems, and services. His work spans multiple domains in telecommunications, networking, and smart systems. His primary research interests include digital twins for smart cities, blockchain technologies, Internet of Things (IoT) security and applications, 5G/6G networking, and machine learning applications in network management. He has published extensively on these topics, with over 100 publications in top-tier journals and conferences. His recent work shows a strong focus on digital twin applications for urban management, particularly in traffic and air quality monitoring. He has developed modular frameworks for smart city digital twins that integrate real-time data from multiple sources. His research also explores blockchain applications for network security, access control, and service provisioning in next-generation cellular networks. Dr. Crespi has received significant recognition for his work on digital twins, with his 2020 paper "Digital twin in the IoT context" in Proceedings of the IEEE being highly cited. His current research explores the integration of AI with digital twin technologies for sustainable urban development. He has supervised numerous PhD students and collaborates extensively with researchers across Europe and internationally. His work often involves interdisciplinary approaches, bringing together computer science, networking, urban planning, and environmental science. Dr. Crespi has been instrumental in developing frameworks for network digital twins, with applications in traffic management, air quality monitoring, and resource allocation in smart cities. His research demonstrates practical implementations in cities like Madrid, showing measurable improvements in urban management.

Ramya Korlakai Vinayakمشاهده پروفایل

استادیار

• Machine Learning
• Statistical Inference
• Crowdsourcing
• +۲ مورد دیگر

Ramya Korlakai Vinayak is the Dugald C. Jackson Assistant Professor in the Department of Electrical and Computer Engineering at the University of Wisconsin-Madison. She also holds affiliations with the Department of Computer Science and the Department of Statistics at UW-Madison. Her research program bridges theoretical machine learning with practical applications in data science and crowdsourcing. Education: PhD in Electrical Engineering from California Institute of Technology (Caltech), advised by Prof. Babak Hassibi B.Tech in Electrical Engineering with minor in Physics from Indian Institute of Technology Madras (IIT Madras) Dr. Vinayak's research focuses on developing theoretically grounded machine learning tools for reliable inference using data from human sources. Her work spans machine learning theory, statistical inference, and crowdsourcing systems, with particular emphasis on preference learning, metric learning, and robust dataset construction. She has pioneered methods for learning from limited pairwise comparisons, auto-labeling systems, and human-in-the-loop out-of-distribution detection. Her recent publications reveal a consistent trajectory toward building practical machine learning systems that incorporate human feedback while maintaining theoretical guarantees. The pattern shows increasing focus on ethical considerations in AI, particularly regarding bias in generative models and reliable human-AI collaboration frameworks. Scientific Awards: Faculty for the Future fellowship (2013-2015) from Schlumberger Foundation NSF CAREER Award American Family Funding Initiative Award with Fred Sala Dr. Vinayak leads an active research group with multiple PhD students across ECE and CS departments. She has secured significant research funding including an NSF grant for "Uncovering the cognitive and neural fingerprints that make each of us unique" in collaboration with Tim Rogers, Rob Nowak and Brad Postle. She is also co-organizing the MidWest Machine Learning Symposium and NeurIPS tutorials on dataset construction. Her research group operates at the intersection of theory and practice, developing mathematically grounded frameworks that address real-world challenges in dataset construction, human-AI collaboration, and reliable machine learning systems.

• Computer Graphics
• Virtual Reality
• Cultural Heritage Visualization
• +۷ مورد دیگر

Carlos Antonio Andújar Gran is a faculty member at the Faculty of Informatics of Barcelona (FIB), Universitat Politècnica de Catalunya (UPC), where he is affiliated with the Department of Computer Science. He actively contributes to the academic community through teaching and supervising numerous student projects, particularly in advanced computing domains. His research interests center on the application of computer graphics, virtual reality, and artificial intelligence to real-world problems. Key areas include the 3D visualization and virtual reconstruction of cultural heritage, physically accurate rendering, intelligent segmentation of images, and the use of machine learning and reinforcement learning in sports analytics, particularly for padel. His work bridges technical innovation with practical applications in cultural preservation and sports technology. The recent publications under his supervision reflect a strong trend in digital cultural heritage, with multiple projects focused on tools for virtual visits, reconstruction, lighting simulation, and web-based 3D visualization of heritage models. Another significant trend is the application of AI to padel, including ball and player tracking, virtual coaching, and training virtual agents using reinforcement learning. These projects demonstrate a consistent focus on computer vision, interactive systems, and data-driven modeling. Carlos Antonio Andújar Gran has supervised a substantial number of students, guiding both undergraduate and master's theses. While specific grant information is not available in the text, his sustained supervision across many years suggests active involvement in research projects. He plays a key role in mentoring the next generation of computer scientists at UPC. His work is closely tied to the Department of Computer Science at FIB, where he collaborates with other faculty members such as Imanol Muñoz Pandiella, Núria Pelechano Gómez, and Mohammadreza Javadiha on various student projects, indicating a collaborative research environment focused on graphics, AI, and VR applications.

Qiuyu Luمشاهده پروفایل

استادیار

• Ecological HCI
• Computational Design
• Bio-inspired & Biomimetic Design
• +۳ مورد دیگر

Dr. Qiuyu (Luca) Lu is an Assistant Professor (Presidential Young Scholar) at the School of Design of The Hong Kong Polytechnic University and Director of the Interbeing Lab , which focuses on designing intelligence for mutualism between humans, nature, and machines. He holds a Ph.D. in Design and a B.Eng. in Mechanical Engineering from Tsinghua University. Ph.D. in Design, Tsinghua University B.Eng. in Mechanical Engineering, Tsinghua University His research bridges Ecological HCI, Computational Design , and Bio-inspired Engineering , creating sustainable interactive systems that leverage natural processes. Recent projects include: RoboMoRe (2025): LLM-driven robotic morphology optimization Degrade to Function (2024): Programmable eco-degradable interfaces Sustainflatable (2023): Ambient energy harvesting for morphing devices His work has been exhibited internationally at Ars Electronica and the Milan Triennale . Scientific recognition includes a Best Paper Honorable Mention at UIST 2023. Dr. Lu is actively recruiting PhD students and postdocs across disciplines, including design, computer science, mechanical engineering, and materials science, with research tracks in: Experimental Track: Interactive hardware prototyping Computational Track: AI-aided design tools Design Track: User experience frameworks

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.

Mike J. Harmanمشاهده پروفایل

استادیار

• Behavior Analysis
• Autism Spectrum Disorders
• Verbal Behavior
• +۳ مورد دیگر

Mike J. Harman serves as Assistant Professor of Psychology at the University of Northern Iowa within the College of Social & Behavioral Sciences, specializing in behavior analysis with applications to developmental disorders and decision-making processes. His academic credentials include: Ph.D. in Psychology from University of Wisconsin-Milwaukee (2018) M.S. in Psychology from University of Wisconsin-Milwaukee (2015) B.S. in Psychology from University of Wisconsin-Superior (2013) Dr. Harman's research program investigates three interconnected domains: skill acquisition interventions for developmental disorders (particularly autism), covert verbal behavior in complex repertoire development, and parameters influencing delay discounting and impulsive choices. His work bridges experimental analysis with clinical applications, emphasizing methodological rigor in behavior analytic procedures. His 14 recent publications (2018-2024) reveal consistent focus on treatment integrity measurement, verbal behavior mechanisms, and decision-making paradigms across human and animal subjects. The corpus demonstrates strong methodological innovation in single-case designs while addressing clinically relevant questions in autism intervention and behavioral economics. Dr. Harman actively mentors students whose work regularly appears at national conferences and in top behavior analysis journals. He serves on the editorial board of The Analysis of Verbal Behavior and reviews for Behavior Modification , Journal of Applied Behavior Analysis , and other leading publications. He maintains an active research laboratory focused on experimental analysis of behavior, where students conduct hands-on investigations of verbal behavior, delay discounting, and skill acquisition protocols.

Juan Antonio Corrales Ramónمشاهده پروفایل

پژوهشگر ارشد

• Robotics
• Human-Robot Interaction
• Robotic Manipulation
• +۳ مورد دیگر

Juan Antonio Corrales Ramón is a Research Fellow at the University of Santiago de Compostela's CiTIUS laboratory under the prestigious Beatriz Galindo program. Previously, he served as an Associate Professor at Sigma Clermont Engineering School (2014-2020) and conducted research at UPMC/ISIR in France. His academic credentials include a PhD in Automatic Control and Robotics (2011) and a Computer Engineering degree (2005) from the University of Alicante. Dr. Corrales' research centers on robotics with specialized interests in: Human-robot physical interaction for industrial applications Deformable object manipulation and control theory Tactile sensing technologies and sensor fusion Robotic grasping and in-hand manipulation Multi-robot coordination systems His recent publications demonstrate strong focus on adaptive control systems for deformable objects, tactile sensor development, and human-robot collaboration frameworks. He has participated in significant EU projects including: H2020 SoftManBot (soft material handling) H2020 Bots2Rec (recycling robotics) FUI Aerostrip (aerospace applications) Sudoe Commandia (service robotics) Honors include competitive fellowships: FPU Program Fellowship (Spanish Ministry of Education) Beatriz Galindo Program Fellowship (research excellence) At CiTIUS laboratory, he contributes to advanced robotics research with applications in industrial automation, healthcare, and agricultural robotics.

Bodil Holstمشاهده پروفایل

استاد

• Surface Science
• Scientific Instrumentation
• 2D Materials
• +۳ مورد دیگر

Bodil Holst is a Professor at the University of Bergen's Department of Physics and Technology , specializing in surface science and scientific instrumentation development . Her research spans 2D materials , helium atom scattering , and archaeometry applications. She leads projects like Nanometer-Resolution Matter-Wave Lithography (FET-Open), 2D Material Properties (NFR FRIPRO), and Wind Turbine Erosion Prevention (Equinor). Her Nanophysics Group has produced groundbreaking work on graphene's temperature-dependent rigidity and icephobic surfaces . First neutral helium microscope images (2008) Recorded bending rigidity of 2D materials (2018-2021) Developed solid-state conversion techniques for sapphire (2017-2021) Her teaching innovations in classical mechanics explore retrieval practice and digital learning structure , documented in Physics Education and Physical Review Physics Education Research .

Khalil Esperمشاهده پروفایل

پژوهشگر

• Verification and Model Checking
• Energy Optimization
• Real-time Systems
• +۴ مورد دیگر

Khalil Esper is a Researcher at the Department of Computer Science, Faculty of Engineering, Friedrich-Alexander-University Erlangen-Nuremberg (FAU), where he works at the Chair of Computer Science 12 (Hardware-Software Co-Design). His research focuses on verification, energy optimization, and runtime requirement enforcement in embedded systems and MPSoCs. His educational background includes: Informatics Engineering from Aleppo University, Syria (2010-2015) European Master in Embedded Computing Systems (EMECS) from Rhineland-Palatinate University of Technology Kaiserslautern-Landau (Germany) and Norwegian University of Science and Technology (Norway) (2017-2019) Esper's research interests center around verification and model checking, energy optimization on MPSoC, real-time systems and embedded systems, and autonomic computing. His work particularly focuses on runtime requirement enforcement mechanisms for non-functional properties in multi-processor systems-on-chip, with applications extending to medical devices and human-robot interaction systems. He has developed approaches using finite state machines, reinforcement learning, and evolutionary algorithms to ensure system properties are maintained during execution. His publication record shows a strong trend toward applying formal methods and runtime enforcement techniques to increasingly complex systems, with recent work expanding into safety-critical applications like orthoses and human-robot interaction. The interdisciplinary nature of his research bridges computer science, embedded systems engineering, and biomedical applications. Esper has supervised multiple theses including: Sascha H.: Runtime Requirement Enforcement of Non-Functional Requirements on MPSoCs Using Fuzzy Logic (2022) Iana S.: Feedback-Based Control of Non-functional Program Execution Properties on Linux (2023) Philipp L.: Runtime Requirement Enforcement of Functional and Non-Functional Requirements of a Knee Orthosis Based on a Digital Twin (2024) Avinash N.: Runtime Requirement Enforcement of Safety Properties of an Ankle Orthosis Based on a Digital Twin (2024) Zhiyi T.: Generation of Environment FSMs Using Machine Learning Techniques (2025) Moustafa A.: Runtime Requirement Enforcement of Safety Properties of Human-Robot Interaction Based on a Digital Twin (2025) Florian K.: Runtime Requirement Enforcement of Safety Properties of Human-Robot Interaction (2025) He has been actively teaching courses on Approximate Computing and Embedded Systems since the 2021/2022 academic year, demonstrating his commitment to academic instruction alongside his research activities. Esper is involved in the InvasIC research project, part of the DFG Transregional Collaborative Research Center 89 on Invasive Computing, which explores novel approaches to resource management in parallel computing systems.

Matthias Beckerمشاهده پروفایل

استاد

• Human-Computer Interaction
• Simulation and Modeling
• Distributed Systems
• +۶ مورد دیگر

Matthias Becker is a Professor at the Institute for Practical Computer Science within the Faculty of Electrical Engineering and Computer Science at Leibniz University Hannover, where he has been a core member of the Human-Computer Interaction group since 2019. He serves as Internship Coordinator for Computer Science and Computer Engineering and holds key roles in the Computer Science Examination Board and Selection Committee, actively shaping academic governance and student development. His academic journey began with PhD studies at the University of Bremen (1996-2000) supported by a DFG grant, followed by a postdoctoral permanent position at Leibniz University Hannover (2000-2019), an Associated Assistant Professor role at École des Mines de Nantes (2000), and a Habilitation in Computer Science in 2013. This foundation enabled his transition to a full professorship in 2019. Becker's research spans Human-Computer Interaction, Simulation and Modeling, and Bio-inspired Computing, with applications in agriculture, renewable energy, and manufacturing. His work integrates distributed systems, optimization algorithms, and wireless sensor networks to solve complex real-world problems, such as greenhouse monitoring, wind farm logistics, and tire noise reduction. Recent publications reveal a strategic focus on practical validation of simulation models and cross-domain applications of nature-inspired algorithms. His 15 most recent publications (2018-2024) demonstrate consistent innovation in applying simulation techniques to offshore wind farm installation, agricultural pest management, and sports science. These works emphasize real-world validation, collaborative problem-solving, and the development of domain-specific optimization frameworks that bridge theoretical algorithms and industrial implementation. As Internship Coordinator, Becker facilitates critical industry-academia connections for students, while his examination board responsibilities ensure rigorous academic standards. His leadership in the Human-Computer Interaction group drives research on interactive systems for agriculture, energy, and health, with particular emphasis on user-centered design in complex operational environments like wind farm logistics and greenhouse automation.

Syon Bhanotمشاهده پروفایل

دانشیار

• Behavioral Economics
• Public Policy
• Experimental Economics
• +۵ مورد دیگر

Syon Bhanot is an Associate Professor of Economics at Swarthmore College , with additional appointments as an Adjunct Associate Professor at the Wharton School (University of Pennsylvania). He specializes in behavioral economics , public economics , and experimental economics , focusing on pro-social behavior , decision-making , and development economics . Academic Affiliate, Office of Evaluation Sciences Board Member, Busara Center for Behavioral Economics Senior Researcher, MIT Applied Cooperation Initiative Co-Founder, Philadelphia Behavioral Science Initiative Member, American Economic Association His research emphasizes field experiments using behavioral science concepts to influence decision-making, with applications in public policy , poverty reduction , and environmental sustainability . Recent publications explore topics like political messaging effects , administrative burden reduction , and social norm influences on conservation behavior. His work has appeared in journals like The New England Journal of Medicine , Journal of Development Economics , and Organizational Behavior and Human Decision Processes . He is a frequent media commentator in outlets including the New York Times , NPR , and The Philadelphia Inquirer , with notable contributions on quarantine compliance and vaccine hesitancy . His interdisciplinary approach bridges economics with environmental studies and public health .

Shengcheng Yuمشاهده پروفایل

پژوهشگر

• Software Testing
• GUI Testing
• Mobile App Testing
• +۵ مورد دیگر

Dr. Shengcheng Yu is a Postdoctoral Researcher at the TUM School of Computation, Information and Technology (CIT) of the Technical University of Munich (TUM) , affiliated with the Chair of Software Engineering & AI . He earned his bachelor's and Ph.D. from Nanjing University (NJU) in 2020 and 2024, respectively. Research Focus: His work bridges Software Testing with Artificial Intelligence , concentrating on GUI Testing , Mobile App Testing , Crowdsourced Testing , and GUI Automation . His methodologies integrate Image Recognition , Reinforcement Learning , and Large Language Models (LLMs) to enhance automated testing frameworks. Publications Trends: His recent studies (2023-2024) emphasize AI-driven testing tools , including vision-based GUI testing , LLM-based test script generation , and deep image-text fusion for crowdsourced test reports . Earlier work (2021) established foundations in cross-platform testing and screenshot understanding. Team Affiliation: Collaborates with Prof. Dr. Chunyang Chen and researchers such as Lukas Roschel , Wenchao Gu , and Yanqi Su .

• AI Security
• AI Safety & Alignment
• Cooperative AI
• +۶ مورد دیگر

Sahar Abdelnabi is an AI Security Researcher at Microsoft and will join the ELLIS Institute Tübingen as a Faculty/Principal Investigator. She is co-affiliated with the Max-Planck Institute for Intelligent Systems and Tübingen AI Center , leading the COMPASS Research Group focused on safe, aligned, and steerable AI agents with emphasis on security, human-AI interaction, and cooperative systems. Her research spans three pillars: (1) Probing AI failures through biases, emergent risks, and misuse scenarios; (2) Developing defenses like white-box control methods and reasoning enhancements; and (3) Leveraging AI for societal good through scientific discovery. Key contributions include coining indirect prompt injection vulnerabilities (2023), pioneering generative AI watermarking (2020), and receiving the ACL2025 Best Paper Award for work on LLM sampling heuristics. PhD in Computer Science (2019-2024) from CISPA Helmholtz Center , advised by Prof. Dr. Mario Fritz MSc in Computer Science from Saarland University Research Highlights Her work bridges AI security and safety with sociopolitical implications, focusing on prompt injection , cooperative multi-agent systems , and contextual integrity . She has been recognized by policymakers and industry leaders, including NIST , OWASP , and Microsoft's AI Bug Bounty Program . Scientific Awards Best Paper Award at ACL2025 Best Paper Award at AISec'23 Workshop Spotlight Paper at NeurIPS Datasets and Benchmarks 2024 Academic Leadership She actively contributes to the AI and security communities through: Program Committee: IEEE S&P (2026) , SaTML (2024-2026), USENIX Security (2025) Organized IEEE SaTML'25 LLMail-Inject Challenge Reviewed for top conferences: ICLR , NeurIPS , CVPR

Roberto Calandraمشاهده پروفایل

استاد

• Robotics
• Machine Learning
• Tactile Sensing
• +۳ مورد دیگر

Roberto Calandra is a Full (W3) Professor at Technische Universität Dresden, where he leads the Learning, Adaptive Systems and Robotics (LASR) Lab. Previously, he served as a Research Scientist at Meta AI (formerly Facebook AI Research) and a Postdoctoral Scholar at UC Berkeley’s BAIR Lab under Sergey Levine. His academic journey includes a PhD in Robotics from TU Darmstadt, an M.Sc. in Machine Learning from Aalto University, and a B.Sc. in Computer Science from Università di Palermo. His research bridges Robotics and Machine Learning, focusing on tactile sensing, Bayesian Optimization, and model-based reinforcement learning. He pioneered the DIGIT tactile sensor , now the most widely used tactile sensor in robotics, and advocates for a computational field of Touch Processing to advance haptic understanding. His work emphasizes data-efficient learning, real-world dexterous manipulation, and multimodal perception. Recent publications highlight breakthroughs in tactile sensor design, in-hand object manipulation, and multimodal integration. He organizes workshops on robotics and machine learning (e.g., at NeurIPS, ICRA) and promotes open-source tools like PyTouch and TACTO .

• Explainable AI
• Counterfactual Explanations
• Water Distribution Networks
• +۳ مورد دیگر

Dr. André Artelt is a researcher at the University of Bielefeld within the Faculty of Engineering and affiliated with the Machine Learning Group at the Center for Cognitive Interaction Technology (CITEC). His work focuses on Explainable AI (XAI), particularly counterfactual explanations, and their applications in critical infrastructure like water distribution networks. Current Research: Explainable AI Counterfactual explanations Water network monitoring Physics-informed graph neural networks Scientific Contributions: His recent publications explore reinforcement learning for water pump scheduling, scalable graph neural networks for water systems, and benchmark frameworks like EPyT-Flow. He investigates how training data affects explanation quality and develops tools for robust counterfactual reasoning. Awards: Project Lamarr Fellowship