جست‌وجوی استاد و پژوهشگر

• Theorem Proving
• Automated Reasoning
• Formal Methods
• +۱۴ مورد دیگر

Jasmin Blanchette is a Professor of Theoretical Computer Science and Theorem Proving at the Institute for Informatics, Ludwig-Maximilians-Universität München (LMU), where he also serves as Dean of Studies for Computer Science since January 2024. He is additionally affiliated as a guest researcher with the VeriDis group at Loria in Nancy, France. His research lies at the intersection of automated and interactive theorem proving, with a focus on higher-order logic and proof automation. Key projects include the development of tools like Sledgehammer, Nitpick, and Zipperposition, and foundational work on (co)datatypes and higher-order superposition. His recent publications reflect a strong trend in formalizing and verifying automated reasoning techniques, especially in higher-order logic, with applications in proof automation, SMT solving, and logical verification. Articles frequently appear in top venues such as CADE, ITP, and the Journal of Automated Reasoning. CADE 2023 Best Paper Award for 'Verified given clause procedures' FroCoS 2023 Best Paper Award (with Visa Nummelin and Sander Dahmen) IPA Dissertation Award (awarded to his student Petar Vukmirović) Dutch 'cum laude' distinction (awarded to his student Anne Baanen) Dutch Prize for ICT Research 2022 Blanchette has advised numerous PhD and postdoctoral researchers, many of whom are now active contributors to the formal methods community. He has received significant research grants through projects like Matryoshka and Nekoka. He is also the editor-in-chief of the Journal of Automated Reasoning and plays a central role in organizing key conferences such as ITP, CADE, and CPP. He leads an active research group at LMU, consisting of postdocs and PhD students working on topics such as higher-order superposition, formalization of voting systems, categorical logic, and proof search heuristics. The team collaborates closely with international groups, including those at Inria and TU Wien.

Dipanwita Thakurمشاهده پروفایل

استادیار

• Green Artificial Intelligence
• Federated Learning
• Smart Healthcare
• +۴ مورد دیگر

Dr. Dipanwita Thakur serves as Assistant Professor at the Department of Computer Engineering, Modeling, Electronics and Systems (DIMES) at the University of Calabria, Italy since July 2023. She is an active member of the European Cooperation in Science & Technology (COST Action CA22104) focusing on cybersecurity and serves in the IEEE Future Networks Working Group for Artificial Intelligence/Machine Learning. Previously, she held a 15-year Assistant Professor position at Banasthali University, Rajasthan, and has industry experience at TechMahindra and C-DAC. Education: Ph.D. in Smart Healthcare from West Bengal University of Technology, Kolkata M.Tech. in Software Engineering from Banasthali Vidyapith MCA from NIELIT, Government of India B.Sc. from University of Calcutta Her research pioneers Green Artificial Intelligence with emphasis on energy-efficient federated learning and smart healthcare applications. She develops privacy-preserving human activity recognition systems using multimodal data fusion, focusing on performance evaluation and environmental sustainability. Her work bridges theoretical machine learning with practical healthcare solutions, optimizing AI systems for reduced carbon footprint while maintaining clinical efficacy through hardware-algorithm co-design and quantization techniques. Recent publications reveal a strong trajectory toward sustainable AI, with increasing focus on energy-aware federated learning frameworks, multimodal medical segmentation, and non-IID data handling. Her work consistently addresses the critical balance between model accuracy, convergence speed, and energy consumption across edge devices, with growing emphasis on quantization techniques and hardware-algorithm co-design for real-world deployment. Scientific Awards: Elevated to IEEE Senior Member (2024) Dr. B.C. Roy Memorial Scholarship for outstanding 10th Board results (1992) Student Science Seminar Award by West Bengal Government (1990) Dr. Thakur actively mentors students as evidenced by her congratulations to advisee Farwa for paper acceptances. She serves as Associate Editor for Information Fusion (Elsevier) and IEEE Sensors Journal, and holds editorial roles at Scientific Reports. Her research is advanced through COST Action CA22104 and IEEE working groups, though specific grant details aren't listed in the source material. She has organized key workshops including Green-Aware AI 2024 and Green Federated Learning at IJCNN 2025. She leads research within the MONAI community on data quality and federated learning, and contributes to IEEE IoT and Future Networks initiatives. Her work with the COST Action CA22104 Behavioral Next Generation in Wireless Networks connects cybersecurity with sustainable AI development, while her Missouri S&T visiting scholar position focuses on energy optimization for federated learning systems.

Yunming Xiaoمشاهده پروفایل

استادیار

• Computer Systems
• Networks
• Security
• +۳ مورد دیگر

Yunming Xiao is an Assistant Professor at the School of Data Science, The Chinese University of Hong Kong (CUHK), Shenzhen. Previously, he served as a Research Fellow at the University of Michigan and earned his Ph.D. in Computer Science from Northwestern University in 2024. His research focuses on computer systems, networks, and security, with emphasis on security and privacy of Internet services and performance optimization of cloud infrastructure. His work has been recognized with the Best Paper Award at APNet and Best Student Paper Award at ACM EuroSys. Education: Ph.D. in Computer Science, Northwestern University (2024) B.Eng. in Computer Science, Beijing University of Posts and Telecommunications (2019) His research bridges cloud infrastructure and security, where projects like SwiftRDMA, Conspirator, and MegaTE demonstrate innovative approaches to resource scheduling, SmartNIC integration, and traffic engineering at scale. These works highlight his focus on solving real-world performance and security bottlenecks in distributed systems. Scientific Awards: Best Paper Award, APNet'25 Best Student Paper Award, ACM EuroSys'24 Yunming actively collaborates with industry, having interned at Google, Hewlett Packard Labs, Nokia Bell Labs, and Bytedance. He serves on TPCs for major conferences including CCS'26, IMC'26, and IEEE S&P'26.

Hervé Debarمشاهده پروفایل

استاد

• Network Security
• Information Systems Security
• SIEM (Security Information and Event Management)
• +۶ مورد دیگر

Hervé Debar is a Professor and head of the Telecommunications Networks and Services (RST) department at Télécom SudParis. His research focuses on network and information system security, including SIEM systems, automated threat mitigation, SDN security, and resilience against cyber attacks. He coordinates major European projects like NECOMA (EU-Japan cybersecurity collaboration) and PANOPTESEC (industrial control systems security). Research interests span SIEM frameworks, intrusion detection, risk management, and defense mechanisms for critical infrastructures. His work emphasizes practical implementation through projects like MASSIF (SIEM decision support systems) and DEMONS (privacy-aware network monitoring). Recent articles address TLS protocol analysis, DDoS mitigation with SDN, honeypot models, and risk assessment for healthcare systems. He supervises multiple PhD students and collaborates with industry partners via CIFRE theses. His research group is part of SAMOVAR (CNRS UMR 5157). Teaching includes leading the Networks and Systems Security master's program, emphasizing hands-on training with industry partnerships. He actively recruits postdocs and engineers for cybersecurity research.

Azza Abouziedمشاهده پروفایل

دانشیار

• Human-Data Interaction
• Database Systems
• Human-Computer Interaction
• +۷ مورد دیگر

Azza Abouzied is Associate Professor of Computer Science at New York University Abu Dhabi and Global Network Associate Professor at the Tandon School of Engineering. She serves as Vice Provost for Faculty Advancement and Engagement at NYUAD starting September 2024. Her research bridges database systems and human-computer interaction, focusing on intuitive tools for data querying and decision-making in uncertain, collaborative environments. PhD, Yale University (2013) MPhil, Yale University MSc, Dalhousie University BSc, Dalhousie University Her research centers on human-data interaction, designing systems that make data accessible to non-experts. She combines techniques from UI design, machine learning, and databases to build tools that simplify complex data tasks. Her earlier work focused on example-driven querying and synthetic data generation, while her recent work explores in-database prescriptive analytics and decision support in domains like disinformation mitigation and epidemic planning. Her publications span database and HCI venues, with a recurring theme of enhancing usability without sacrificing scalability. She co-founded Hadapt, a Big Data analytics platform, and has led interdisciplinary research through the Human-Data Interaction Lab and the Center for Interacting Urban Networks. Her teaching includes foundational courses such as Database Systems, Operating Systems, and Data, as well as the critical thinking course Techruption. VLDB Test of Time Award (2019) Best Paper Award in Database Systems Honorable Mention in HCI Publications Azza mentors undergraduate capstone students and advises prospective PhDs, research assistants, and postdocs. She is actively involved in academic leadership, having chaired NYUAD’s faculty council in 2024 and co-chaired the SIGMOD 2025 program. Her work emphasizes empowering users to critically engage with data and AI, both in research and education.

Marcus Vetterمشاهده پروفایل

استاد

• Deep Learning
• Medical Technology
• Embedded Systems
• +۴ مورد دیگر

Prof. Dr. Marcus Vetter is the founder and director of the Institute for Applied Artificial Intelligence and Robotics (A²IR) at Mannheim University of Technology's Faculty of Information Technology. His work bridges Deep learning Medical imaging and navigation Embedded systems Real-time computing Software engineering for medical devices He has taught courses including Deep Learning Methods, Image-Guided Medicine, and Embedded Systems. Education Computer Science, Technical University of Mannheim, 1999 Doctorate ('summa cum laude superato') in 'Image-based navigation systems', University of Heidelberg, 2003 Research focuses on AI-driven medical imaging tools, real-time deformation models, and open-source frameworks like MITK. His 15 most recent publications span 6D pose estimation for medical robotics Spectroscopy-based diagnostics Formal software verification Gesture and gaze recognition interfaces UAV drive train optimization Scientific achievements Doctorate with distinction (2003) Co-founder of MITK open-source project Director of A²IR institute since 2007 He has received BMBF grants for real-time deformation models and tracking systems, and has led development of navigation systems for laparoscopic surgery and cardiac ablation procedures.

• Information Security
• Cybersecurity
• Smart Card Security
• +۱۵ مورد دیگر

Konstantinos Markantonakis is a Professor of Information Security in the Department of Information Security at Royal Holloway, University of London, where he also serves as Director of the Smart Card and IoT Security Centre and the Transformative Digital Technologies, Security and Society Catalyst. He is a leading figure in embedded systems and IoT security, with extensive research and consultancy experience. BSc (Hons) in Computer Science, Lancaster University, 1995 MSc in Information Security, Royal Holloway, 1996 PhD in Smart Card Security, Royal Holloway, 2000 MBA in International Management, Royal Holloway, 2005 His research focuses on securing embedded and cyber-physical systems, including smart cards, mobile devices, drones, automotive systems, and IoT. He investigates trusted execution environments, side-channel analysis, secure protocols, and hardware-software binding. His work bridges theoretical security and practical implementation, often uncovering zero-day vulnerabilities in consumer devices. The recent publications highlight a strong trend in trusted computing, remote attestation, secure embedded systems, and privacy-preserving technologies. His research integrates blockchain for secure energy trading, develops frameworks for edge machine learning, and advances forensic techniques for damaged storage media. He also explores covert channels in mobile and cloud environments, demonstrating a deep understanding of both offensive and defensive security. Best Paper Award Markantonakis has led major research projects such as EXFILES (forensic extraction from encrypted smartphones), Future TPM (quantum-resistant trusted modules), and the Academic Centre of Excellence in Cyber Security Research. He has supervised numerous PhD students and delivered keynotes at international conferences. His consultancy work has impacted financial institutions, transport operators, and mobile platform security. He leads the Smart Card and IoT Security Centre, a research hub focusing on practical security for connected devices. The centre conducts cutting-edge research in side-channel attacks, secure application execution, and forensic analysis, contributing significantly to both academic and industrial advancements in cybersecurity.

• Cybersecurity
• Machine Learning
• Internet of Things (IoT)
• +۴ مورد دیگر

Nikos Komninos is a researcher at City, University of London , specializing in cybersecurity, network security, and privacy-preserving systems. His work spans Internet of Things (IoT) , mobile ad hoc networks , and cloud computing security. Research Areas : Cybersecurity frameworks, machine learning for threat detection, quantum-resistant encryption, and privacy-preserving authentication systems. His recent publications focus on ransomware detection under concept drift, DDoS mitigation in IoT, and attribute-based encryption for fog computing. He has contributed to IEEE Transactions and journals like Computers & Security , with a trend toward real-time adaptive security systems and Bayesian risk assessment .

David Vockمشاهده پروفایل

استاد

• Biostatistics
• Health Data Science
• Causal Inference
• +۷ مورد دیگر

David Vock is a Professor at the University of Minnesota in the Division of Biostatistics & Health Data Science . His research focuses on statistical methods for electronic health data, causal inference, dynamic treatment regimes, and clinical trial design. PhD in Statistics, North Carolina State University (2012) MStat in Statistics, North Carolina State University (2009) BA in Mathematics and Chemistry, St. Olaf College (2007) His work integrates machine learning with traditional statistical approaches to analyze censored data in healthcare settings. He specializes in SMART clinical trials for adaptive interventions and semiparametric theory applications. Collaborative projects span transplantation , infectious disease , and cardiovascular research . Recent publications emphasize COVID-19 biomarker analysis , monoclonal antibody efficacy , and health data interoperability . These studies appear in high-impact journals like New England Journal of Medicine and Lancet Microbe . Scientific contributions have earned him membership in the Delta Omega Honorary Society in Public Health . Collaborations include the ACTIV-3/TICO Study Group and interdisciplinary teams in data science and clinical research .

İsmail Arıمشاهده پروفایل

استادیار

• Cloud Computing
• Big Data
• Machine Learning
• +۱۲ مورد دیگر

Dr. İsmail Arı is an Assistant Professor in the Computer Science department at Özyeğin University . He holds a PhD from the University of California, Santa Cruz (2004), MS from University of Maryland (2000), and BS in Electrical & Electronics Engineering from Boğaziçi University (1998).

Kirill Djebkoمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Machine Learning
• Optimization Algorithms
• +۴ مورد دیگر

Kirill Djebko is a researcher at the Chair of Computer Science VI - Artificial Intelligence and Knowledge Systems within the Institute of Computer Science, Faculty of Mathematics and Computer Science at the University of Würzburg . His work spans AI-based optimization systems , autonomous spacecraft operations , and deep reinforcement learning applications. Doctorate completed in 2020 Active in research since 2015 Key projects: KINERGY (heating system optimization), VeriKI (AI verification for space), LeLaR (AI attitude control for nanosatellites) Research focuses on metaheuristics , genetic algorithms , regression algorithms , and deep reinforcement learning for practical applications. His work integrates digital twin modeling , decision support systems , and AI robustness in industrial and space contexts. Recent publications (2024-2016) analyze heating system optimization , spacecraft fault detection , and autonomous nanosatellite operations . These studies emphasize sim-to-real-world transfer , data-driven calibration , and AI quality assurance in complex environments. Current affiliations include the Center for Artificial Intelligence and Data Science (CAIDAS) . Contact details: Email - kirill.djebko@uni-wuerzburg.de | Phone +49 931 31-86405 | Room 03.010, Emil-Fischer-Straße 50, Würzburg.

• Semantic Web
• Knowledge Representation
• Artificial Intelligence
• +۶ مورد دیگر

Deborah L. McGuinness is the Tetherless World Senior Constellation Chair and Professor of Computer, Cognitive, and Web Sciences at Rensselaer Polytechnic Institute (RPI). She serves as founding director of the Web Science Research Center, focusing on next-generation ontology-enabled research infrastructure for interdisciplinary applications. Leaders in Semantic Web and AI research Bridging AI with eScience and healthcare Developer of semantic frameworks for data-intensive resource efforts Her research spans artificial intelligence, knowledge representation, clinical decision support systems, and ontology engineering. She investigates how semantic technologies can enhance AI explainability, data interoperability, and interdisciplinary science. Her recent publications highlight trends in AI explainability frameworks Knowledge graph construction Clinical decision support Commonsense reasoning benchmarks Health informatics Data harmonization Scientific awards include Fellow of the American Association for the Advancement of Science (AAAS) Robert Engelmore Award from the Association for the Advancement of Artificial Intelligence (AAAI) She leads large data-intensive research efforts and has contributed to projects involving blockchain integration with semantic web standards, FAIR data principles, and incentivized research data sharing mechanisms.

Samarjit Chakrabortyمشاهده پروفایل

استاد

• Distributed Embedded Systems
• Hardware/Software Co-design
• Embedded Control Systems
• +۹ مورد دیگر

Samarjit Chakraborty is the William R. Kenan, Jr. Distinguished Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill. He previously held the Chair of Real-Time Computer Systems at the Technical University of Munich (2008–2019) and was an assistant professor at the National University of Singapore (2003–2008). His research spans real-time embedded systems, cyber-physical systems (CPS), and automotive security. Research Interests include distributed embedded systems, hardware/software co-design, low-power systems, energy storage, electromobility, and sensor network-based information processing. His work addresses challenges in scheduling algorithms for autonomous vehicles, timing predictability in automotive networks, and safety-critical controller implementations. Recent Publications highlight advancements in Timing analysis for automotive networks Energy modeling of Bluetooth Low Energy Autonomous vehicle perception computing Security in automotive systems Flexible manufacturing with process dynamics Scientific Awards include the ETH Medal, European DAAD Outstanding Doctoral Dissertation Award, multiple best paper awards at conferences (ISLPED, ICCD, RTCSA, etc.), the 2023 Humboldt Professorship, and IEEE Fellowship. Advising active PhD students: Clara Hobbs, Shengjie Xu, Sharmin Aktar, and postdoc Enrico Fraccaroli. His research is supported by NSF grants and industry partnerships with General Motors, Intel, Google, BMW, Audi, Siemens, and Bosch.

Robert Clementsمشاهده پروفایل

استادیار

• Data Science Education
• AI and Data Ethics
• Machine Learning
• +۲ مورد دیگر

Robert Clements is an Assistant Professor in the Master of Science in Data Science (MSDS) program at the University of San Francisco (USF) and serves as Director of the Center for AI and Data Ethics. After nearly ten years in industry as a data scientist and senior director of data science across Bay-Area companies including Optum, Walmart Labs, UnitedHealthcare, GE Digital, and Verisk Analytics, he returned to academia to focus on education and ethical issues surrounding AI and data. Education PhD in Statistics, University of California, Los Angeles, 2011 MS in Statistics, University of California, Los Angeles, 2009 BA in Mathematics, Humboldt State University, 2006 Research Interests Dr. Clements focuses on data science education , exploring innovative pedagogies that equip students with practical and ethical data skills. He studies the societal impacts of AI and datafication , seeking frameworks to ensure responsible deployment of machine-learning systems. Additional interests include MLOps (the engineering practices that support reliable machine-learning workflows) and applied statistics across diverse domains. His peer-reviewed work to date concentrates on statistical seismology, where he developed advanced residual-analysis and model-evaluation techniques for earthquake-forecast models. These contributions provide rigorous methods for assessing space-time point processes and improve the reliability of seismic hazard assessments. Academic & Professional Service As Director of the Center for AI and Data Ethics, Dr. Clements leads initiatives that create open educational resources, case studies, and student practicum projects centered on ethical AI. He co-hosts the USF Data Science Podcast alongside faculty colleague Cody Carroll, offering guidance to prospective and current MSDS students on program insights, learning strategies, and career development.

• Cyber-physical systems
• Green and sustainable computing
• Mobile and pervasive computing
• +۷ مورد دیگر

Sandeep Gupta is a Professor and Director of the School of Computing and Augmented Intelligence at Arizona State University's Ira A. Fulton Schools of Engineering. He also serves as a Senior Global Futures Scientist. His work bridges computer science, engineering, and healthcare applications with a focus on creating reliable cyber-physical systems that interact safely with humans. Education: Ph.D. from The Ohio State University (1995) Research Interests: Professor Gupta's research spans cyber-physical systems, green and sustainable computing, mobile and pervasive computing, and parallel and distributed computing. His work increasingly focuses on human-in-the-loop systems where AI and humans collaborate safely, particularly in healthcare contexts. Recent research integrates large language models with cyber-physical systems to enhance safety and operational effectiveness in critical applications like medical monitoring and industrial automation. Research Trends: Analysis of Professor Gupta's recent publications reveals a strong focus on operational safety in human-AI collaborative systems, particularly in healthcare applications. His work combines physics-guided models with machine learning to detect "unknown-unknowns" in safety-critical systems, develops LLM-based approaches for medical image classification, and creates frameworks for ethical human-AI collaboration. The research increasingly addresses real-world challenges in diabetes management, epilepsy diagnosis, and industrial automation. Professional Service: IEEE Communication Letters Editorial Board, Area Editor (2008-Present) IEEE Journal on Special Areas in Communications - Issue on Body Area Network, Co-editor (2006-Present) Elsevier COMNET - Computer Network Journal, Reviewer (2008-Present) Technical Advisory Committee Chair for Networks (2005-Present) Advising and Grants: Professor Gupta has secured numerous research grants from NSF, NIH, Intel, Raytheon, and other organizations, totaling millions of dollars. His research portfolio includes projects on smart stadiums, mobile ECG sensing, power-aware scheduling, medical device verification, and sustainable data center management. He actively advises PhD and Master's students through thesis courses and research supervision, focusing on cyber-physical systems and healthcare applications. Labs and Research Groups: Professor Gupta leads research in cyber-physical systems with applications in healthcare, sustainable computing, and mobile networks. His work involves interdisciplinary collaboration across engineering, computer science, and medical domains, particularly through ASU's Global Futures initiatives.