Find Academic Supervisors

Manik Varma is a Distinguished Scientist and Vice President at Microsoft Research India, and an Adjunct Professor at the Indian Institute of Technology Delhi. He is a Fellow of the Indian Academies of Science (IASc, INSA, NASI), the Indian National Academy of Engineering (INAE), and the Association for Computing Machinery (ACM). He has received prestigious awards such as the Shanti Swarup Bhatnagar Prize and Microsoft Gold Star Award. Education : BSc in Physics from St. Stephen's College (David Raja Ram Prize) BA in Theoretical Physics from the University of Oxford (Rhodes Scholar) DPhil in Computer Vision and Machine Learning from the University of Oxford (University Scholar) Post-doctoral Fellow at the Mathematical Sciences Research Institute (MSRI), Berkeley Visiting Miller Professor at UC Berkeley His research focuses on Machine Learning (Extreme Classification, Resource-efficient ML, Supervised Learning), Information Retrieval (Computational Advertising, Dense Retrieval, Recommender Systems), and Computer Vision (Image Search, Object Recognition). Recent work includes graph-regularized encoders, label variance reduction, and multimodal classification frameworks. His publications span extreme classification algorithms like NGAME , SiameseXML , and DECAF , with applications in IoT, web search, and recommendation systems. He leads a research group at Microsoft Research India and advises PhD students at IIT Delhi. Scientific Awards : Shanti Swarup Bhatnagar Prize (Government of India) Microsoft Gold Star and Achievement Awards WSDM 2019 Best Paper Prize BuildSys 2019 Best Paper Runner-up Fellow of ACM, IASc, INSA, NASI, INAE He has supervised numerous PhD students, including Sonu Mehta and Suchith Prabhu, and collaborates with institutions like Microsoft Research India, IIT Delhi, and UC Berkeley. His research has led to scalable solutions for billion-label classification and resource-constrained IoT applications.

• Machine Learning
• Deep Learning
• Information Retrieval
• +16 more

Christian Rupprecht is an Associate Professor at the Department of Computer Science, University of Oxford, specializing in computer vision and machine learning. His research focuses on unsupervised learning, 3D reconstruction, and visual understanding. His work includes contributions to conferences such as GCPR'25, ICCV'25, and CVPR'25, with papers spanning topics like correspondence estimation, animal pose modeling, and synthetic data generation. He leads projects within the prestigious Visual Geometry Group (VGG). Notably, his paper VGGT received the Best Paper Award at CVPR'25. His research integrates deep learning and geometric modeling, emphasizing robustness and generalization in visual systems. Best Paper Award at CVPR'25

• Computer Vision
• Machine Learning
• Unsupervised Learning
• +4 more

Adriana Tapus is a Full Professor at ENSTA Paris, affiliated with Institut Polytechnique de Paris, leading the Autonomous Systems and Robotics Laboratory (SAR) within the Computer Science and Systems Engineering Unit (U2IS). She holds an HDR (Habilitation) and a PhD from EPFL, Switzerland, with postdoctoral experience at USC. Her research focuses on socially assistive robotics, human-robot interaction (HRI), and personalized therapy for individuals with physical/cognitive impairments. She directs the IP Paris Doctoral School and coordinates national/international projects like the EU-funded ENRICHME and SWEET. Education: PhD in Mobile Robotics, EPFL (2005) Habilitation (HDR), ENSTA Paris (2011) M.S. Computer Science, University Joseph Fourier Engineer, Politehnica University of Bucharest Research Interests: Tapus pioneers socially assistive robotics, integrating machine learning, human modeling, and multimodal communication (verbal/non-verbal/para-verbal). Her work addresses adaptive therapies for vulnerable populations using robotics, physiological data interpretation, and context-aware interaction. Key themes include: Human-robot cooperation and trust Emotion recognition and expression Personalized rehabilitation systems AI ethics and human-centered design Publications: Over 150 articles, with recent work exploring humor in HRI, teleoperation trust models, and cross-cultural intelligent vehicles. Notable 2025 contributions include studies on robot laughter efficacy and multimodal facial expression frameworks. Awards: 2025: 4 IROS papers accepted 2016: 25 Women in Robotics recognition 2010: Romanian Academy Award Multiple conference best paper awards (RO-MAN, ICRA, etc.) Advising & Grants: Supervised over 20 PhD students and led projects like EU Horizon 2020 ENRICHME. Current students focus on teleoperation dynamics, robot humor, and haptic interfaces. Active in editorial roles (IJSR, THRI) and conference organization (HRI General Chair 2019). Labs/Teams: Founder of RoboticsByDesign lab and co-initiator of the Hi! Paris interdisciplinary AI center. The SAR lab develops systems for healthcare, education, and human-robot collaboration.

• Robotics
• Human-Robot Interaction
• Machine Learning
• +7 more

Ronald McGarvey is a Full Professor at IÉSEG School of Management since 2022, with prior roles including Associate Professor with Tenure at the University of Missouri (2013-2022) and Senior Operations Researcher at RAND Corporation (2002-2022). He holds a Ph.D. in Industrial Engineering and Operations Research from Pennsylvania State University and an H.D.R. in Industrial Engineering from the University of Paul Sabatier, France. Education : H.D.R. (2024), Industrial Engineering, University of Paul Sabatier Ph.D. (2002), Industrial Engineering and Operations Research, Pennsylvania State University His research focuses on Operations Research and Robust Optimization applied to diverse domains: Healthcare Logistics : Modeling access disparities in rural obstetric care for American Indian populations Environmental Sustainability : Analyzing biomass energy systems, forest carbon impacts, and waste management frameworks Network Design : Developing optimization models for supply chain resilience, military logistics, and urban transit safety Policy Analysis : Evaluating multi-state environmental collaborations and localized food systems His publications demonstrate strong interdisciplinary applications of mathematical programming and spatial optimization to real-world challenges in healthcare access, energy sustainability, and transportation systems. Key Collaborations : Working with researchers in public health (Thorsen, Noble), environmental science (Aguilar), and engineering (Mirzaee, Gutierrez-Lopez)

• Operations Research
• Robust Optimization
• Sustainable Systems
• +3 more

Stefano NASINI is an Associate Professor at the University of Lille 3, specializing in Quantitative Methods within the Economics and Mathematics Sciences. He holds a HDR (Habilitation à Diriger des Recherches) from the University of Lille 3 (2021), a Ph.D. in Statistics and Operations Research from the Polytechnic University of Catalonia (2015), and a Master in Statistics (2011). His research focuses on optimization, complex networks, statistical inference, and microeconomic applications. He has held academic positions including a post-doctoral role at IESE Business School (2014–2016) and a visiting researcher role at the University of Lisbon (2014). His work spans scheduling optimization, network analysis, financial contagion modeling, and energy system planning. Key contributions include specialized algorithms for large-scale optimization problems and frameworks for decentralized portfolio management. He is a member of the LEM research group and teaches courses in optimization, econometrics, and social network analysis at the Grande École and MSc levels. Publications highlight interdisciplinary applications, including network-based diffusion models, multi-market financial strategies, and dynamic choice analysis. His research bridges theoretical advancements in operations research with practical challenges in economics, energy, and transportation systems. No scientific awards are explicitly listed in the provided materials. His advising roles and grants are not detailed here, but his extensive publication record reflects active collaboration within academic and applied domains.

• Optimization
• Complex Networks
• Statistical Inference
• +3 more

Fabian Suchanek is a full professor at Institut Polytechnique de Paris, specifically affiliated with Télécom Paris. He leads research in the Data, Intelligence, and Graphs (DIG) team within the Computer Science department. His academic career focuses on bridging artificial intelligence with structured knowledge representations. Suchanek's research interests span artificial intelligence, knowledge bases, and natural language processing, with particular emphasis on knowledge graph construction , rule mining , knowledge-based language models , and explainable AI . His work demonstrates how structured knowledge can enhance machine learning systems, particularly large language models, by providing factual grounding and interpretability. The research group he leads develops practical systems that address real-world knowledge management challenges. His recent publications showcase a strong trajectory in knowledge-intensive AI, with notable contributions to knowledge graph completion, rule mining techniques, and neural approaches to knowledge base validation. The research demonstrates increasing integration between symbolic and neural approaches to AI. Best Student Paper Award at KR 2024 for work on contextual reasoning Best Demo Award of IJCAI 2024 for rule mining in knowledge graphs French Open Research Award for the YAGO project Best Paper Award of ESWC 2021 for Neural Knowledge Base Repairs Suchanek has secured significant research funding, evidenced by his active recruitment of PhD students for knowledge-based language model research. He has held visiting positions, including at Nanyang Technological University (June-September 2023), and is recognized internationally through keynote invitations such as the Singapore ACM SIGKDD Symposium 2023. He has deliberately stepped back from administrative duties at Institut Polytechnique de Paris to focus on research. His laboratory maintains strong industry connections through open-source software projects including the YAGO knowledge base, AMIE for rule mining, STACI for explainable AI, and several other tools that have become standard in knowledge representation research.

• Artificial Intelligence
• Knowledge Bases
• Natural Language Processing
• +3 more

Catherine Pinel is a Research Director (DR2) at the Institute for Research on Catalysis and Environment of Lyon (IRCELYON, UMR 5256), a joint research unit of the French National Center for Scientific Research (CNRS) and Claude Bernard University Lyon 1. She has held this senior research position since October 2008, following progression from CR1 (1998-2008) and CR2 (1994-1998) roles at the same institution. Her academic journey includes postdoctoral research at Cambridge University (1992-1993) under Professor S.V. Ley and with Professor M. Lemaire (1993-1994). Her educational foundation includes: Diplôme Universitaire de Technologie in Chemistry from Paris XI University (1986) Engineering Degree from École Nationale Supérieure de Chimie de Paris (1989) Advanced Studies Diploma in Organic Chemistry from Paris VI University (1989) PhD in Organic Chemistry from Paris VI University (1992) on chiral ruthenium complexes and enantioselective reductions Habilitation à diriger des recherches from Lyon I University (1999) on catalysis and fine chemistry Dr. Pinel's research pioneers sustainable catalytic processes with emphasis on biomass valorization, green chemistry, and heterogeneous catalysis. Her work bridges fundamental catalyst design with industrial applications, particularly in hydrogenation, oxidation, and biorefinery processes. Current focus areas include catalytic conversion of biomass-derived platform molecules (glucose, succinic acid, polyols), development of bimetallic catalysts, and valorization of hemicellulose streams. Her approach integrates advanced catalyst characterization with reaction engineering to create environmentally benign chemical transformations. Analysis of her recent publication trajectory (2019-2025) reveals evolving expertise from fundamental organometallic chemistry toward applied sustainable catalysis. Key trends include increasing focus on biomass-derived feedstocks (glucose, succinic acid, polyols), development of metal-carbide/nitride catalysts, and optimization of aqueous-phase reactions for industrial biorefineries. Her work demonstrates strong interdisciplinary collaboration across catalysis, materials science, and green chemistry, with growing emphasis on circular economy principles and renewable chemical production. No scientific awards were explicitly mentioned in the source materials. Dr. Pinel actively contributes to academic training through graduate instruction at University of Lyon (Master 2 'Catalysis and Physical Chemistry' since 2007) and University of Savoie (M2 courses in New Catalysts in Organic Chemistry since 1999 and Coordination Chemistry since 2012). While specific grant details aren't provided, her extensive publication record across high-impact journals indicates sustained research funding. She maintains collaborative networks within IRCELYON and internationally, particularly in biomass conversion and catalyst characterization. As a core researcher at IRCELYON (celebrating 60 years of catalysis research in 2021), she operates within a world-class facility housing specialized equipment for catalyst synthesis, characterization (including in situ techniques), and testing. Her work aligns with the institute's focus on sustainable catalysis for energy transition, air/water depollution, and biomass valorization, contributing to France's strategic research priorities in green chemistry.

• Catalysis
• Green Chemistry
• Biomass Conversion
• +4 more

Dr. Jérôme Verny is an Associate Professor specializing in transport, logistics, and supply chain management. He is the founder and director of the research institute in innovative transport and logistics, as well as the co-founder of the DISC Master's program (Digital & Innovative Supply Chain) in Paris and the Mobility Accelerator. His expertise spans digitalization in logistics, blockchain applications, and sustainable development. Educated at the University of Lille Nord de France (PhD in Economics and Management) and engineering schools like École Nationale des Ponts et Chaussées, he advises both public institutions (OECD, EU) and private enterprises on transportation strategies. Research Interests: Dr. Verny focuses on supply chain innovation, digital transformation, and strategic logistics. His work integrates blockchain technology for supply chain transparency, optimizes last-mile delivery in urban environments, and analyzes the impact of geopolitical actors like China on global trade networks. He also explores sustainable practices in transportation, including CO2 reduction strategies and pandemic response logistics. Awards: Recipient of the 2009 OECD-FIT Young Researcher Prize in Transport. His contributions bridge academic research with practical applications in industry, policy, and international trade. Key Activities: Co-founded the DISC Master’s program and leads research initiatives on blockchain adoption, Arctic shipping routes, and Mediterranean trade dynamics. He actively contributes to conferences such as the International Association of Maritime Economists (IAME) and publishes in journals like Structural Change and Economic Dynamics and International Journal of Shipping and Transport Logistics . Labs/Teams: Directs the Institut de Recherche en Transport et Logistique Innovante and collaborates with institutions like the OECD and European Commission on transport policy. His interdisciplinary approach involves engineering, economics, and data science to address global supply chain challenges.

• Supply Chain Management
• Transportation Systems
• Logistics
• +4 more

Rida Khatoun is a Professor in Cybersecurity at the Computer Sciences and Networks (Infres) Department at Télécom Paris. He holds a M.Sc. in Computer Engineering and a Ph.D. from the University of Technology of Troyes (UTT), France, awarded in 2004 and 2008, respectively. His research focuses on cybersecurity in networks, including cloud computing security, IoT security, vehicular networks security, intrusion detection systems, and blockchain technology. He has taught at Telecom Paris since 2014, Shanghai Jiao Tong University (SJTU) since 2016, and other institutions in China and France since 2005. His work spans theoretical frameworks and practical solutions for network security challenges. Key research areas include DDoS attack detection, vehicular communication security, and cryptographic protocols. He leads the Cybersecurity and Cryptography (C²) research team and is affiliated with the Laboratoire Traitement et Communication de l'Information (LTCI). His contributions include developing secure routing protocols (e.g., ASROP), statistical trust systems in wireless networks, and blockchain-based authentication for IoT. He has authored over 115 publications, including peer-reviewed articles and conference proceedings, with recent work addressing vehicular platooning security, TLS handshake optimization for C-ITS, and machine learning for cyberbullying detection. Rida’s academic activities include teaching courses on network security protocols, wireless network fundamentals, and QoS mechanisms. He collaborates internationally, contributing to smart city cybersecurity architectures and 6G programmable communications. His research emphasizes practical cybersecurity solutions for emerging technologies, ensuring robust protection against evolving threats in vehicular, IoT, and cloud environments.

• Cybersecurity
• Network Security
• Cloud Computing Security
• +6 more

Daniel Varro is a Professor affiliated with McGill University (Faculty of Engineering, School of Computer Science), with strong ties to Budapest University of Technology and Economics and Linköping University. He is a leading researcher in model-driven engineering, cyber-physical systems, and software engineering, actively contributing to top-tier conferences such as MODELS, ICSE, and ASE. His research focuses on model-based systems engineering (MBSE) , automated model generation , model transformations , and constraint-based consistency checking . Recently, his work has expanded into integrating large language models (LLMs) and machine learning into modeling workflows, including model querying, domain modeling, and bug detection. The recent publications reveal a strong trend toward AI-augmented modeling, logic-based solvers (e.g., Refinery), and safety assurance of autonomous systems (e.g., COLREGs compliance). His work bridges formal methods with practical software engineering challenges in industrial and safety-critical domains. Scientific Awards: No specific awards mentioned in the text. Advising and Grants: While no explicit list of students or grants is provided, his mentorship in the Doctoral Symposium and repeated leadership roles suggest active supervision and likely grant funding. He has led projects on automated model generation, model quality, and AI integration in modeling. Labs and Teams: Daniel Varro is associated with research groups focused on model-driven engineering and software evolution, likely leading or co-leading teams working on the VIATRA and Refinery frameworks for model transformation and solving.

• Model-Based Systems Engineering
• Cyber-Physical Systems
• Software Engineering
• +12 more

Xavier Brusset is a Professor in Supply Chain at SKEMA Business School since 2016, where he also serves as Director of the PRISM Research Center since 2017. Previously, he held professorial positions at Toulouse Business School (2015-2016) and ESSCA School of Management (2009-2015), where he was responsible for the Master 2 in Purchasing and Supply Chain Management program. His academic journey includes a PhD in Management Sciences from Université Catholique de Louvain (2010) and a Habilitation à Diriger des Recherches from Université Paris Ouest Nanterre La Défense (2016). His research spans multiple critical areas in supply chain management, with particular focus on supply chain resilience, blockchain applications, weather risk management, and pandemic impacts on supply chains. Brusset has developed innovative approaches to understanding how supply chain partners interact, how information affects their behavior, and how external disruptions like weather anomalies and pandemics impact operational efficiency. His work bridges theoretical models with practical applications, often developing decision-support tools for managers facing complex supply chain challenges. Brusset's publication record shows a clear evolution of research interests, beginning with foundational work on supply chain contracts and information sharing, then expanding to weather risk management, and most recently focusing on pandemic disruptions and blockchain applications. His 15 most recent publications (2018-2025) demonstrate increasing sophistication in modeling complex supply chain phenomena, with particular emphasis on network effects, ripple effects, and multi-echelon optimization under disruption scenarios. Editorial board member of Logistics Research Editor of International Journal of Retail and Distribution Management (2022-2023) Recognized EU expert for CINEA research projects evaluation Organizer of the Colloquium on European Research in Retailing (CERR) Reviewer for multiple top journals including International Journal of Production Economics As an advisor, Brusset has supervised doctoral students including R. Alkhudary (co-director, Université Paris 2 Panthéon-Assas) and V. Capocasale (rapporteur). His professional experience extends beyond academia to include industry roles in financial markets and logistics technology, having co-founded WebLogistix, a platform for sharing logistics information in Argentina. His research has practical applications across multiple sectors, particularly in retail, food supply chains, and manufacturing, where he develops tools to help managers mitigate risks and optimize operations under uncertainty.

• Supply Chain Management
• Logistics
• Operations Management
• +6 more

Stefania Dumbrava is an Associate Professor of Computer Science at ENSIIE (École Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise) and a permanent member of the ACMES team in the SAMOVAR laboratory at Télécom SudParis, Institut Polytechnique de Paris. She is also actively involved in the Property Graph Schema Working Group and the European Research Network on Formal Proofs (EuroProofNet). Education PhD in Computer Science, Université Paris-Sud (2016) MSc in Computer Science, Jacobs University Bremen (2012) BSc in Mathematics, Jacobs University Bremen (2010) Research Interests Dumbrava's research lies at the intersection of formal methods and data management . She designs and verifies algorithms and systems for graph databases , with emphasis on property graphs , schema discovery , query optimization , and distributed graph processing . Recently, her work focuses on certifying large-scale distributed graph systems under the ANR JCJC VERDI project (2025–2029). Awards & Honors SIGMOD Best Paper Award 2023 – “PG-Schema: Schemas for Property Graphs” SIGMOD Research Highlight Award 2023 – “Threshold Queries” VLDB 2022 Best Regular Research Paper Runner-Up – “Threshold Queries in Theory and in the Wild” SIGMOD 2025 Distinguished Reviewer Award ICDE 2025 Best Program Committee Member Award EASST Best Software Science Paper Award, ICGT 2025 Students & Grants Dumbrava has supervised numerous research interns and is actively recruiting PhD students for her ANR VERDI project on verified foundations of large-scale distributed graph systems. She has also served on six PhD thesis committees as examiner since 2021. Labs & Teams She leads the ACMES research group within the SAMOVAR laboratory (Télécom SudParis, Institut Polytechnique de Paris), where her team develops formally verified graph-database engines and tools such as GRASP, VerDILog, and DatalogCert.

• Formal methods for databases
• Graph databases
• Property graphs
• +7 more

Marco Di Renzo is a CNRS Research Director (Professor) and Head of the iPhyCom group at the Laboratory of Signals and Systems (L2S) at Paris-Saclay University, France. He is affiliated with both CNRS and CentraleSupélec. His roles include: Member of L2S Management Committee and Board Council Member of the Ph.D. School Admission Committee Academic Vice Chair, ETSI Industry Specification Group on RIS Editorial and leadership roles in IEEE communications journals Education: Laurea (cum laude) and Ph.D. in Electrical Engineering from University of L’Aquila (2003, 2007) Habilitation à Diriger des Recherches from Paris-Saclay University (2013) Research focuses on 6G networks , reconfigurable intelligent surfaces (RIS) , and integrated sensing and communications (ISAC) . He explores electromagnetic theory, machine learning applications, and energy-efficient wireless systems. His work addresses challenges in near-field communications, multi-user MIMO, and holographic beamforming. He advocates for physics-driven design principles in next-gen networks. Key awards include IEEE/IEE Fellowships, the Michel Monpetit Prize, and multiple IEEE Best Paper Awards. He holds international visiting professorships at institutions like the University of Oulu (Finland) and Nanyang Technological University (Singapore). Active in standardization via ETSI ISG RIS and contributes to global initiatives like the ITU 6G Vision. His research bridges theoretical models with practical implementations, emphasizing interdisciplinary collaboration between physics, signal processing, and AI.

• Wireless Communications
• 6G Networks
• Reconfigurable Intelligent Surfaces (RIS)
• +5 more

Edouard Oyallon is a CNRS Researcher at Sorbonne University's MLIA team within the Institute of Intelligent Systems and Robotics (ISIR). His research focuses on machine learning foundations, particularly the symmetries of deep neural networks, and large-scale distributed/decentralized training algorithms. He has contributed to frameworks like Kymatio for wavelet scattering transforms and collaborates on projects such as SHARP (Frugal Learning) and ADONIS (ANR-funded). He advises multiple PhD and postdoctoral researchers and teaches advanced deep learning courses at Institut Polytechnique de Paris (IPP). Grants include the ADONIS project (ANR/Sorbonne) and participation in VHS and CoCa4AI initiatives. His work spans theoretical and applied aspects, with recent emphasis on optimizing LLM training at exascale. He maintains active roles in academic service, including organizing workshops on federated learning and graph machine learning.

• Machine Learning
• Deep Learning
• Distributed Systems
• +5 more

David Gesbert serves as Professor and Director of EURECOM, a leading research institution in Sophia Antipolis, France, specializing in digital sciences. Previously heading the Communications Systems Department, he now directs EURECOM while leading the Foundations & Algorithms research group within the Communication Systems Department. His leadership spans institutional administration and cutting-edge research supervision. Dr. Gesbert's research portfolio demonstrates exceptional depth across communications theory and wireless networking: Communication theory and information theory fundamentals Signal processing for wireless networks with emphasis on robustness Machine learning applications for decentralized network optimization Connected robotics and UAV-enabled flying radio access networks 6G wireless architecture with focus on AI integration Distributed decision making under information uncertainties His publication trajectory reveals a strategic evolution from classical communication theory toward AI-integrated wireless systems, particularly focusing on UAV-aided networks and connected robotics for 6G. Recent work emphasizes learning-based approaches for network optimization under asymmetric information conditions, with growing emphasis on sustainability and green communications. Dr. Gesbert's scientific recognition includes: Fellow of IEEE (2011) and Asia Pacific Artificial Intelligence Association (2021) Thomson-Reuters List of Highly Cited Researchers in Computer Science Multiple Best Paper Awards at IEEE conferences (EW 2017, ICC 2019) ERC Advanced Grant recipient for the PERFUME project on Smart Device Communications 3IA Chair funding for AI for future IoT Networks 2019 Winner of 'Fundamental research project of the year' by French SCS He actively mentors PhD students and researchers, welcoming collaboration in his research domains. His group secures substantial research funding including ERC grants, 3IA Chairs, and participation in major European projects like the WINDMILL ITN Marie Curie project on Machine Learning in Wireless Communications. Dr. Gesbert serves on editorial boards and regularly delivers keynotes at premier international conferences, establishing himself as a thought leader in next-generation wireless communications.

• Communication theory
• Signal processing for wireless networks
• Information theory
• +7 more