جست‌وجوی استاد و پژوهشگر

Francisco Correia dos Santosمشاهده پروفایل

استاد

• Computer Science
• Evolutionary Biology
• Economics
• +۱۰ مورد دیگر

Francisco C. Santos is a Full Professor at Instituto Superior Técnico (IST), University of Lisbon, and currently serves as Vice-President of the Portuguese Science Foundation (FCT). He holds a PhD in Computer Science from Université Libre de Bruxelles (ULB), Belgium, where he was a Marie Curie Fellow. His research spans computer science, evolutionary biology, economics, and physics, focusing on cooperation dynamics, environmental governance, network science, and AI's societal impact. He leads the GAIPS and ATP research groups at INESC-ID, Lisbon. Education PhD in Computer Science, Université Libre de Bruxelles (ULB), Belgium (Marie Curie Fellowship) FNRS Senior Researcher at ULB's Machine Learning Group Research Interests His work bridges AI, complex systems, and social dynamics. Key areas include: - Evolution of cooperation and social norms - Climate governance and collective-risk dilemmas - Network science and urban planning - Machine learning and robotics applications Awards Young Scientist Award (German Physical Society) CGD/ULisbon Prize in Computer Science AAAI Blue Sky Award IST Teaching Excellence Awards (multiple) Advising & Grants Supervised over 30 PhD and MSc students, many of whom have gone on to prestigious postdocs and academic roles. Co-headed research groups and led projects funded by FCT-Portugal and EU initiatives. Labs & Teams Leads the Group of Artificial Intelligence for People and Society (GAIPS) and the ATP interdisciplinary group at INESC-ID. Collaborates internationally on AI ethics and environmental policy.

Fabian Theisمشاهده پروفایل

استاد

• Artificial Intelligence
• Computational Biology
• Biomedicine
• +۳ مورد دیگر

Prof. Dr. Dr. Fabian Theis is a Professor of Mathematics in Systems Biology at the Technical University of Munich (TU Munich) and Director of both the Computational Health Center and the Institute for Computational Biology (ICB) at Helmholtz Munich. He specializes in applying artificial intelligence and machine learning to analyze single-cell sequencing data, modeling cellular behavior, and predicting biological outcomes in health and disease. His work bridges computational methods with clinical applications to advance personalized medicine. Education: Master's Degrees in Mathematics and Physics Doctorates in Physics and Computer Science Research interests revolve around AI-driven biological systems analysis, including cellular interaction modeling, disease mechanism prediction, and translational biomedical research. He coordinates initiatives such as the Human Cell Atlas Analysis Working Group, Single Cell Omics Germany (SCOG), and the Munich School for Data Science (MUDS). His leadership spans roles at HelmholtzAI as Science Director and as a guest scientist at global institutions like RIKEN Brain Science Institute (Japan) and FAMU/FSU (USA). Labs/Teams: Leads the Computational Health Center and chairs the Mathematical Modeling of Biological Systems program at TU Munich. Collaborates with interdisciplinary teams in AI and health research.

Rasmus Waagepetersenمشاهده پروفایل

استاد

• Spatial Statistics
• Quantitative Genetics
• Markov Chain Monte Carlo Methods
• +۳ مورد دیگر

Rasmus Waagepetersen is a Professor in the Department of Mathematical Sciences at Aalborg University, affiliated with The Faculty of Engineering and Science. His research focuses on spatial statistics, quantitative genetics, and statistical methodology for spatial point processes. He leads and participates in interdisciplinary projects such as urbanLab (spatial data analysis for urban planning) and studies on microbiome interactions in agricultural systems. Key research areas include spatial point processes, Markov chain Monte Carlo methods, and statistical inference for complex ecological and biomedical data. His work frequently involves collaborations with environmental and biological scientists, as seen in projects analyzing root microbiota assemblies in legumes and climate data for building simulations. Waagepetersen has contributed to methodological advancements in spatial statistics, including goodness-of-fit tests, likelihood-based inference for log Gaussian Cox processes, and quasi-likelihood approaches for case-control point pattern data. His research has been supported by grants from institutions like the Villum Foundation. Key Projects: urbanLab, Klimadata til fugtsimuleringer, Nod factor signaling in plant microbiota. Grants: Multiple projects funded by the Villum Foundation and Danish research councils. His recent publications address topics such as space-time point processes, microbiome data analysis, and statistical modeling in education. Waagepetersen maintains an active research group and collaborates internationally on both theoretical and applied statistical problems.

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 .

Steve Davisمشاهده پروفایل

پژوهشگر ارشد

• Soft Robotics
• Automation
• Biomimetics
• +۴ مورد دیگر

Dr. Steve Davis is a Senior Research Fellow in Robotics at the University of Birmingham and Operational Director of The Birmingham Institute for Robotics. With over 25 years of expertise in robotics, his research focuses on soft robotics, biomimetics, advanced actuators, and robotics applications in healthcare, nuclear decommissioning, and the food industry. He holds a BEng, MSc, and PhD in Robotics from the University of Salford and a PGCert in Academic Practice. Education: BEng in Robotic and Electronic Engineering (1998), University of Salford MSc in Advanced Robotics (1999), University of Salford PhD in Robotics (2005), University of Salford PGCert in Academic Practice (2014), University of Salford Research Interests: Steve’s work spans soft robotics, biomimetic systems, and automation solutions for industries like food manufacturing and healthcare. His innovations include variable stiffness actuators, robotic hands, and grippers designed for safe human interaction. He has pioneered projects such as the Grail Robot for the food industry and contributed to EU-funded initiatives like SMART-E and FAIRSPACE. Publications Trends: His recent work emphasizes soft robotics actuators (e.g., pneumatic muscles, granular jamming grippers) and predictive maintenance methodologies. Collaborations with industry have led to practical automation solutions across sectors. Awards: Fellow of the Higher Education Academy (FHEA) Grants and Supervision: Steve has secured funding from UKRI, EPSRC, Innovate UK, and the EU. He has advised on MSc and PhD projects related to robotics in healthcare, space, and nuclear environments. Notable grants include the EPSRC FAIRSPACE Hub and Innovate UK’s Nuclear Decommissioning project. Labs and Teams: He leads research at the Birmingham Institute for Robotics and collaborates with the EPSRC Centre for Innovative Manufacturing. His work integrates academic research with industrial applications through projects like the Food Robotics Automation Center funded by Yorkshire Forward.

Amit Pujariمشاهده پروفایل

دانشیار

• Biomedical Engineering
• Neurorehabilitation Engineering
• Neuromodulation
• +۵ مورد دیگر

Associate Professor Amit Pujari is a biomedical engineer and neuroscientist at the University of Hertfordshire, leading the Neu(RAL)² Laboratory. He holds an honorary position at the University of Aberdeen and is a Royal Academy of Engineering Industrial Fellow. His work focuses on developing non-invasive neuromodulatory devices for stroke and spinal injury rehabilitation. Education: PhD in Biomedical Engineering, University of Aberdeen (2016) MSc in Biomedical Engineering, University of Strathclyde (2007) BE in Instrumentation & Control Engineering, Pune University (2003) Research Interests: Optimizing neuromodulatory stimuli (vibrotactile/electrical) for rehabilitation, neurophysiological basis of vibration therapy, and assistive technologies. His lab is equipped with advanced tools like high-density EMG systems, TMSi devices, and custom vibration stimulators. Awards: Academy of Medical Sciences’ Top 25 Emerging Leaders (2023) British Science Association Award Lecture (2022) Winston Churchill Memorial Trust Fellowship (2017) Grants/Projects: VECTOR: Randomized controlled trial for Crohn’s disease rehabilitation (2024–2027) SPASMS: Wearable sensor technology for spasticity management (2023–2025) User-led design of neurotechnologies for stroke survivors (2023–2025) Labs: Neu(RAL)² Laboratory focuses on neural systems rehabilitation, housing state-of-the-art equipment for EMG/EEG, TMS, and custom devices.

Shrideep Pallickaraمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Large-Scale Systems
• +۱۲ مورد دیگر

Shrideep Pallickara is a Professor in the Department of Computer Science at Colorado State University, where he also directs the Center for eXascale Spatial Data Analytics and Computing (XSD) . His research is funded by the National Science Foundation, Department of Homeland Security, Environmental Protection Agency, Department of Agriculture, and the UK's e-Science program. Research Interests: His research lies at the intersection of machine learning and large-scale systems, focusing on: Spatiotemporal data management and analytics Extreme-scale storage systems Stream processing for IoT and cyber-physical systems Deep learning over petabyte-scale, high-dimensional datasets Model construction for forecasting natural and urban phenomena His work addresses challenges in computational tractability, resource utilization, and convergence in distributed environments. Systems developed in his lab are deployed in domains such as urban sustainability, agriculture, epidemiology, environmental monitoring, healthcare, and defense. Research Trends in Publications: His recent publications demonstrate a strong focus on scalable analytics for geospatial and environmental data. Key themes include deep learning for soil moisture and salinity prediction, efficient visualization of massive satellite datasets, spatiotemporal search and summarization, and model performance profiling across spatial domains. The work integrates scientific domain knowledge with machine learning and systems innovation. Scientific Awards: NSF CAREER Award Board of Governors Award for Excellence in Undergraduate Teaching OLIE Award N. Preston Davis Award Monfort Professorship Best Paper Award at IEEE/ACM CCGrid 2019 Best Paper Award at BDCAT 2023 Best Paper Award at IEEE Cluster 2012 Best Student Paper Award at IEEE CloudCom 2010 Shortlisted for ACM DEBS-2015 Grand Challenge Award One of the Six Best Papers at ACM/IEEE GRID 2005 Advising and Grants: He advises numerous graduate students, many of whom are co-authors on his publications. His research is supported by major grants from NSF, DHS, EPA, USDA, and UK e-Science, enabling the development of open-source systems such as Granules, NaradaBrokering, Galileo, Funnel, and Spindle. Labs and Teams: He leads the XSD Center, which develops and maintains large-scale open-source software systems involving over 2500 classes and a million lines of code. These systems are used in academic, commercial, and defense applications.

Auke Jan Ijspeertمشاهده پروفایل

استاد

• Biorobotics
• Computational Neuroscience
• Robotics
• +۱۲ مورد دیگر

Auke Jan Ijspeert is a full professor at the École Polytechnique Fédérale de Lausanne (EPFL), where he serves as head of the Biorobotics Laboratory (BioRob). He holds a primary affiliation with the Institute of Bioengineering and a secondary affiliation with the Institute of Mechanical Engineering. His academic leadership and research excellence have established him as a leading figure in bio-inspired robotics and computational neuroscience. B.Sc./M.Sc. in Physics, École Polytechnique Fédérale de Lausanne (EPFL), 1995 Ph.D. in Artificial Intelligence, University of Edinburgh, 1999 Postdoctoral research at IDSIA/EPFL and University of Southern California (USC) SNF Assistant Professor at EPFL, 2002 Promoted to Associate Professor, October 2009 Promoted to Full Professor, April 2016 His research lies at the intersection of robotics, computational neuroscience, nonlinear dynamical systems, and applied machine learning. He investigates animal locomotion and movement control using numerical simulations and robotic platforms, aiming to understand biological principles and apply them to novel robot designs and controllers. His work has led to groundbreaking robots like the salamander-inspired Pleurobot and amphibious robotic systems. He also explores applications in assistive technologies such as exoskeletons and smart furniture for people with limited mobility. The recent publications reflect a strong trend in bio-inspired robotics, neuromechanical modeling, and the use of robots to understand biological locomotion. Key themes include spinal cord modeling for gait control, amphibious and aquatic locomotion, central pattern generators, and the evolutionary transition from swimming to walking. His work integrates neuroscience, biomechanics, and robotics to create physical models that serve both engineering and scientific discovery purposes. Scientific Awards and Honors: IEEE Fellow (2020) Best Paper Prize, CLAWAR 2019 Best Conference Paper Award, SAB 2018 Best Paper Award, IEEE RO-MAN 2014 Best Paper Award, IEEE Humanoids 2007 Overall Best Paper Award, IEEE ICRA 2002 Young Professorship Award, Swiss National Science Foundation Marie Curie Scholarship, European Commission Auke Ijspeert has been actively involved in academic service, serving as an associate editor for IEEE Transactions on Robotics (2009–2013) and Soft Robotics (2018–2021), and as an associate editor for IEEE Transactions on Medical Robotics and Bionics and the International Journal of Humanoid Robotics. He has secured major funding from the Swiss National Science Foundation, Human Frontier Science Program, European Commission (FP7, H2020), Human Brain Project, and other international agencies. He has organized seven major international conferences and served on over 50 program committees. His laboratory, BioRob, is a hub for interdisciplinary research, training students and researchers in biorobotics, and fostering collaboration across neuroscience, robotics, and biomechanics.

Jesse LeCavalierمشاهده پروفایل

دانشیار

• Architectural Design
• Urbanism
• Infrastructure Planning
• +۷ مورد دیگر

Jesse LeCavalier is Associate Professor in the Department of Architecture at Cornell University's College of Architecture, Art, and Planning (AAP), where he also serves as Director of the Master of Science in Advanced Urban Design (M.S. AUD) program. Based in New York City, his academic work bridges architectural design, theory, and urbanism with a specialized focus on logistics and infrastructure. His research explores the spatial, architectural, and social implications of logistical systems, particularly those of large-scale retailers like Walmart. He is the author of The Rule of Logistics: Walmart and the Architecture of Fulfillment (University of Minnesota Press, 2016), a seminal work that investigates how retail logistics reshape buildings, cities, and human behavior. His design research has been exhibited internationally, including at MoMA PS1, the Oslo Architecture Triennale, and the Seoul Biennale for Architecture and Urbanism, with projects such as SHELF LIFE , Alimentary Urbanism , and Machinic Wilderness . LeCavalier’s scholarly writings have appeared in prominent journals such as Places , Public Culture , Harvard Design Magazine , and Cabinet . His recent articles reflect a consistent thematic focus on the intersection of architecture, technology, and material flows, exploring topics from automated fulfillment centers to speculative urban futures. The body of work demonstrates a deep engagement with how digital and physical infrastructures co-constitute contemporary urban environments. Core77 Design Award, Writing & Commentary (2013) ACSA New Faculty Teaching Award (2014) Finalist, MoMA PS1 Young Architects Program (2018) Finalist, Sudbury 2050 Urban Design Competition (2020) Finalist, Tromsø Waterfront Laboratory Open Call (2019) LeCavalier has advised and collaborated with students and design teams on numerous projects, particularly through seminars and design studios such as the Landscapes of Fulfillment seminar at Yale. While formal PhD or Master’s advisees are not listed, his leadership roles indicate active mentorship. He has received funding and support from institutions such as the New York State Council for the Arts. His research is conducted both independently and in collaboration with interdisciplinary teams, often involving engineers, designers, and technologists. His work is supported by a network of labs and collaborative initiatives, including the Landscapes of Fulfillment seminar and projects like Milgram and Test Bed Urbanism , which explore smart cities and digital infrastructure. Future research directions include regenerative urbanism, post-anthropocene landscapes, and the transformation of industrial legacies into public and ecological assets.

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.

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.

• 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.

• Computer Science
• Virtual Reality
• Character Animation
• +۶ مورد دیگر

Núria Pelechano Gómez is a Professor at the Universitat Politècnica de Catalunya (BarcelonaTech) , affiliated with the Faculty of Informatics of Barcelona (FIB) and the Department of Computer Science (CS) . Her work focuses on Virtual Reality , Crowd Simulation , and Character Animation , with a particular emphasis on immersive environments and user interaction. Education: Master's Degree in Innovation and Research in Computer Science (2012) Degree in Computer Engineering (2010) Master's Degree in Computing (2006) Her research explores the integration of Virtual Reality with Artificial Intelligence to enhance user experiences through dynamic crowd modeling, realistic animations, and adaptive navigation techniques. Recent projects highlight her expertise in Motion Matching , Immersive Simulation , and Physics-Based Animation . Key trends in her publications include: Advancements in Virtual Environments and 3D Modeling . Applications of Machine Learning in Navigation Interfaces . Development of Realistic Crowd Behavior and Social Interaction Systems in VR. Focus on User-Centric Design and Embodiment Techniques . Núria has supervised numerous students on topics ranging from Emergency Scenario Modeling to MR Application Development for immersive systems, contributing to the evolution of Immersive Simulation and Game Development methodologies.

• Human Computer Interaction
• User Experience
• Information systems
• +۸ مورد دیگر

Assoc Prof Geraldine Torrisi is the Deputy Head of School (Learning & Teaching) at the School of Information and Communication Technology at Griffith University. With a PhD in Educational Studies and degrees in Science (Physics/Mathematics) and Education, she focuses on Human-Computer Interaction (HCI) , User Experience , and Learning Theory . She is a Senior Fellow of the Higher Education Academy and Griffith Learning and Teaching Academy . Education: PhD in Educational Studies (Griffith University) Masters of Educational Studies (James Cook University) Bachelor of Education (Secondary Science and Maths) (James Cook University) Bachelor of Science (Physics/Mathematics) (James Cook University) Research Interests include Interactive Digital Media , Educational Technology , and Data Literacy . Her 2025 book chapters explore AI's role in education, while 2024-2023 articles address data literacy frameworks and hybrid teaching models. Scientific Awards include Griffith Award for Excellence in Teaching (2011) , Excellence in Teaching Award (2015) , and Senior Fellow of the Higher Education Academy (2018) . She also received multiple Group Learning and Teaching Commendations (2009, 2017, 2019). Grants include The Dignity Project (2024-2025), Promoting Renewable Energy Adoption (2022-2025), and Smart Environmental Sensing (2022-2023). She supervises PhD students on topics like Human-Machine Teaming and Instructional AR Design .

• Economics
• Artificial Intelligence
• Innovation
• +۴ مورد دیگر

Simone Vannuccini is a Teacher-Researcher and Junior Professor in the Economics of Artificial Intelligence and Innovation at the University Côte d'Azur's School of Economics and Management. He is affiliated with the Research Group in Law, Economics, and Management (GREDEG) and the Pole Innovation, Science and Technology (PIST) under the FIT (Firms, Innovation, Territories) team. His research focuses on innovation , artificial intelligence , and industrial policy , with particular emphasis on socioeconomic impacts, technological sovereignty, and global value chains. His recent publications explore themes like robot adoption , AI governance , and strategic autonomy in the European Union . His peer-reviewed articles and conference contributions span topics including multimodal AI systems , disruptive technologies , competition law enforcement , and cyber-physical dynamics . He actively contributes to interdisciplinary research bridging economics , law , and technology studies . Simone Vannuccini participates in collaborative projects such as AI3SD (Artificial Intelligence, Autonomous Systems, and Digital Innovation) and engages in policy discussions on green transitions , budgetary autonomy , and technological multiplier effects . His work integrates theoretical frameworks from Schumpeterian economics with empirical analyses of global innovation trends.