جست‌وجوی استاد و پژوهشگر

Yuntian Dengمشاهده پروفایل

استادیار

• Natural Language Processing
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

Yuntian Deng is an Assistant Professor at the University of Waterloo and a Visiting Professor at NVIDIA. He holds affiliations with Harvard SEAS as an Associate and the Vector Institute as a Faculty Affiliate. He completed his PhD in Computer Science at Harvard under Professors Alexander Rush and Stuart Shieber, followed by a postdoc under Yejin Choi. His research focuses on Natural Language Processing and Machine Learning, with notable contributions in chatbot interaction analysis (WildChat), implicit reasoning models, and markup-to-image generation. He has developed influential tools like OpenNMT and WildVis, and his work has been featured in outlets like the Washington Post and used by OpenAI and Anthropic. Education: PhD in CS (Harvard), Postdoctoral Research (University of Washington). Key achievements include the ACM Gordon Bell Prize for GenSLMs, Best Demo Runner-up at ACL 2017, and Best Paper at DAC 2020. His research emphasizes scalable datasets, efficient reasoning techniques, and real-world applications of AI models. Research interests span NLP, machine learning algorithms, and their applications in areas like dialogue systems, generative models, and ethical AI evaluation. Notable projects include WildChat (1M ChatGPT interactions), implicit chain-of-thought reasoning, and neural steganography for text-based information hiding. His articles explore topics ranging from knowledge distillation to diffusion models, with a focus on bridging theoretical advancements and practical implementations. He actively collaborates with industry partners like NVIDIA and maintains open-source tools to advance AI research accessibility.

Jedidiah Crandallمشاهده پروفایل

دانشیار

• Internet Security
• Censorship Resistance
• Network Security
• +۳ مورد دیگر

Jedidiah Crandall is an Associate Professor at Arizona State University's School of Computing and Augmented Intelligence, with an affiliation to the Biodesign Center for Biocomputing, Security and Society. His research focuses on Internet censorship, network security, and privacy-preserving technologies. Crandall collaborates with journalists and activists to expose surveillance mechanisms, particularly in politically sensitive regions like Russia and China. His work includes analyzing VPN vulnerabilities , decentralized censorship systems , and cross-border data flows . He teaches advanced courses in computer network security and advises graduate students on thesis/dissertation research. Research trends in his publications emphasize measuring state-level information control , attack vectors in modern networks , and secure communication technologies . Notable work includes TSPU: Russia's censorship infrastructure and Hidden Links: Analyzing Secret Families of VPN Apps . Crandall's teaching spans courses like Advanced Computer Network Security and Applied Cryptography , reflecting his commitment to preparing the next generation of security professionals. His Censored Planet project tracks global Internet censorship patterns through large-scale measurements.

• Computer Networking
• Distributed Systems
• Network Security
• +۳ مورد دیگر

Georgia Fragkouli is a Researcher affiliated with ETH Zürich's School of Computer and Communication Sciences, working within the Institute of Computer Engineering and Communication Systems. Her role is part of the Professorship for Networked Systems, focusing on advanced networking and distributed systems research. She specializes in analyzing network performance, security, and transparency, with a particular emphasis on BGP convergence dynamics, anomaly detection, and decentralized computing architectures. Her research interests include network protocol validation, machine learning-based traffic analysis, and improving internet transparency through innovative measurement frameworks. She has contributed to projects like MorphIT for packet-level transparency and explored failure mitigation in globally distributed systems. Notable recent work includes studies on transient forwarding anomalies, iBGP convergence effects, and data-plane performance consistency. Her publications span both theoretical advancements and practical implementations, aiming to bridge gaps between networking theory and real-world deployment challenges.

• Cybersecurity
• Blockchain
• Machine Learning
• +۱۲ مورد دیگر

Edgar Weippl is a Professor at the Faculty of Computer Science, University of Vienna, where he serves as Vice Dean and Head of the Research Group Security and Privacy. His work spans cybersecurity, blockchain, and machine learning, with teaching roles in information security and software security courses. Current Positions: Vice Dean (Faculty of Computer Science), Head (Security and Privacy Research Group), Deputy Head (Neuroinformatics & Knowledge Engineering Groups) Research Interests: Cybersecurity, blockchain, IoT security, code obfuscation, privacy technologies, reinforcement learning, and socio-technical systems security Selected Publications: Focus on blockchain privacy, VoWiFi security, code obfuscation, and reinforcement learning applications

Eric TOTELمشاهده پروفایل

استاد

• Network Security
• Intrusion Detection Systems
• Data Confidentiality
• +۳ مورد دیگر

Eric TOTEL is a Professor at Telecom SudParis, specializing in cybersecurity and network security. His research focuses on intrusion detection systems, graph-based anomaly detection, machine learning applications in security, and data confidentiality in distributed systems. He has contributed to projects such as DAMS (DDoS mitigation using deep reinforcement learning), Sec2Graph (novelty detection on graph-structured data), and DAEMON (dynamic autoencoder-based anomaly detection). His work emphasizes scalable solutions for multi-step attack detection and privacy-preserving infrastructure for encrypted DNS logs. Key contributions include developing correlation engines for distributed systems, formalizing invariant-based attack detection in web applications, and exploring static analysis for information flow control. He has authored over 50 peer-reviewed publications and served on program committees for conferences like RAID, CRiSIS, and EuroS&P. His HDR (2012) formalized error-detection techniques applied to intrusion detection. Advising and grants: He collaborates on projects funded by French national research agencies and has mentored students in cybersecurity, AI for defense (CAID conferences), and cloud infrastructure security. His research often bridges theoretical models and practical implementations, with tools like STARLORD for 3D graph visualization of security data.

Long Chengمشاهده پروفایل

دانشیار

• Machine Learning Based Online Abuse Detection
• System and Software Security
• Network Security
• +۳ مورد دیگر

Long Cheng is an Associate Professor at Clemson University's School of Computing, specializing in cybersecurity, IoT security, and machine learning for abuse detection. His work focuses on securing voice assistants, CPS/IoT systems, and network protocols. He holds dual PhDs from Virginia Tech (2018) and Beijing University of Posts and Telecommunications (2012), with postdoctoral research at Singapore University of Technology and Design (2015) and A*STAR (2012–2015). Research Interests: Online abuse detection, system/software security, network security, CPS/IoT privacy, mobile computing. Awards: NSF CAREER Award, Best Paper at AsiaCCS 2022, Distinguished Paper at ACSAC 2020. Grants: NSF grants (RAPID, SaTC-EDU), industry funding from Innova EV, USDOT, and Google. Service: Editorial boards of IEEE TDSC and ACM DTRAP; program chairs/co-chairs for SmartSP 2025, SecDev 2021–2023. Labs & Teams: AI-Cybersecurity Lab, leading research on abuse detection and CPS security. Collaborates with industry partners like Apple, Amazon, and Texas Tech University.

Ahmad Ghafarianمشاهده پروفایل

استاد

• Information Security
• Computer Forensics
• Cybersecurity
• +۵ مورد دیگر

Dr. Ahmad Ghafarian is a Professor of Computer Science in the Mike Cottrell College of Business at the University of North Georgia (UNG), where he has served for over 20 years since 1996. He is a dedicated educator who emphasizes positive teacher-student relationships and has taught a wide range of undergraduate and graduate courses in computer science and cybersecurity. His educational background includes: Ph.D. in Computer Science, University of Glasgow, UK, 1982 M.S. in Computer Science, University of Glasgow, UK, 1974 B.S. in Mathematics, Ferdowsi University of Mashhad, Iran, 1970 Postdoctoral Studies in Information Security, University of Maryland University College, 2007 Graduate Certificate in Information Security, Purdue University, 2003 Dr. Ghafarian's research focuses on digital forensics and cybersecurity, with expertise in computer forensics, malware detection, cloud security, social media privacy, and SQL injection attacks. His work involves empirical studies of security tools and protocols, advancing forensic methodologies and security practices through rigorous experimentation and analysis. His publication record demonstrates a clear evolution from foundational computer science education topics in the 1990s to specialized cybersecurity research since the mid-2000s. Current work emphasizes memory forensics for social media platforms, ransomware detection mechanisms, connected vehicle security, and VoIP system vulnerabilities, reflecting his adaptation to emerging technological threats. No scientific awards were explicitly mentioned in the source material. Dr. Ghafarian has developed comprehensive curricula across 15+ graduate and undergraduate courses including cybersecurity capstones, network security, and computer forensics. His teaching innovations include semester-long projects, ethical case studies, and practical lab components using tools like Kali Linux. While specific grant funding isn't documented, his extensive publication record and curriculum development demonstrate sustained research engagement and academic leadership.

Rahat Masoodمشاهده پروفایل

مدرس

• Cybersecurity
• Privacy Technologies
• Authentication & Authorization
• +۷ مورد دیگر

Dr. Rahat Masood is a Lecturer at the School of Computer Science & Engineering (CSE), UNSW Sydney. Her research focuses on cybersecurity, including privacy-preserving technologies, authentication mechanisms, critical infrastructure protection, and network security analysis. She holds a PhD in Information Security and Privacy from UNSW (Data61-CSIRO, Australia), an MS in Computer and Communication Security from NUST, Pakistan, and a B.Sc. in Software Engineering from the University of Engineering & Technology, Pakistan. Her academic contributions span theoretical and applied cybersecurity domains. Dr. Masood’s educational background includes: PhD: Information Security and Privacy (UNSW, Data61-CSIRO, Australia) MS: Computer and Communication Security (NUST, Pakistan) B.Sc.: Software Engineering (University of Engineering & Technology, Pakistan) Her research interests emphasize privacy technologies, authentication systems, and securing distributed energy resources. Recent work includes developing frameworks for quantifying privacy risks and analyzing social media manipulations. She employs data-driven methodologies and machine learning to address challenges such as WiFi device tracking and federated learning security. In her publications, she highlights trends in privacy controls usability, satirical news detection using multilingual models, and threat modeling for critical infrastructure. These studies underscore her commitment to bridging cybersecurity theory with real-world applications. No scientific awards are mentioned in the provided texts. Her teaching and supervision roles at UNSW are active, though specific student advisees or grant details are not listed. She is affiliated with Data61-CSIRO through her PhD and contributes to interdisciplinary cybersecurity efforts within CSE.

• Artificial Intelligence
• Robotics
• Data Science
• +۴ مورد دیگر

Cecilio Angulo Bahón is a full Professor at the Polytechnic University of Catalonia (UPC), affiliated with the Barcelona School of Industrial Engineering (ETSEIB) and the Department of Systems, Automatics and Industrial Informatics Engineering . He leads research in Artificial Intelligence and Robotics , with significant contributions to healthcare data analytics, digital twins, and human-robot collaboration. His research spans machine learning for medical data harmonization, generative adversarial networks in health informatics, and evolutionary algorithms for control systems. Recent publications focus on synthetic healthcare data generation, climate-resilient agriculture , and UMAP-based data analysis . His work bridges AI theory with practical applications in industrial and healthcare domains. Scientific awards include the Sant Jordi 2023 Digital Polytechnic Initiative Award . He has supervised doctoral candidates like Carlos Flores-Vázquez and N. Raya, with key collaborations at the IDEAI-UPC Intelligent Data Science and AI Research Group and the Institute of Robotics and Industrial Informatics (CSIC-UPC).

Luc Rocherمشاهده پروفایل

پژوهشگر ارشد

• Privacy and Data Protection
• Artificial Intelligence
• Algorithmic Accountability
• +۵ مورد دیگر

Dr. Luc Rocher is a UKRI Future Leaders Fellow and Senior Research Fellow at the Oxford Internet Institute (OII), University of Oxford. They are also affiliated with Kellogg College and Imperial College London’s Data Science Institute. Their work focuses on algorithmic accountability, privacy-enhancing technologies, and the societal impacts of AI. Rocher leads the Synthetic Society Lab, investigating how to make technology accountable to the public, and the Observatory of Anonymity, an international tool assessing re-identification risks. Their research bridges technical and social science approaches, including statistical modeling, adversarial machine learning, and interactive tools. Education: PhD from Université catholique de Louvain (2019), prior roles at Imperial College London, ENS de Lyon, and MIT Media Lab. Awards include the UKRI Future Leaders Fellowship and recognition from institutions like the European Commission and OECD. Rocher has published in top journals/conferences (Nature Communications, Usenix Security, WWW) and contributed to policy discussions on AI regulation. Advising: Current students include Andrew Bean (DPhil), Lujain Ibrahim (DPhil), Juliette Zaccour (DPhil), and others. Grants funded by UKRI, EPSRC, and the John Fell Fund. Research emphasizes privacy risks in digital data, pricing algorithms, and public sector AI systems. Labs/Teams: Synthetic Society Lab (public interest AI), Observatory of Anonymity (global re-identification risks). Recent work includes demonstrating flaws in traditional anonymization methods and advocating for privacy-preserving frameworks.

Dan S. Wallachمشاهده پروفایل

استاد

• Computer Security
• Cybersecurity
• Electronic Voting Systems
• +۳ مورد دیگر

Dan S. Wallach is a Professor of Computer Science and Electrical and Computer Engineering at Rice University, and a Program Manager at DARPA's Information Innovation Office since June 2023. He holds a PhD (1999) and MA (1995) from Princeton University, and a BS (1993) from UC Berkeley. His research focuses on cybersecurity, electronic voting systems, and mobile security. He directed the NSF-funded ACCURATE Center (2005-2011), led the STAR-Vote project, and advised U.S. election security policies including testifying before state and federal committees. He also served on the Air Force Science Advisory Board (2011-2015), USENIX Board (2011-2013), and IEEE Technical Guidelines Committee (2019-2023). Recent work includes developing ElectionGuard cryptographic tools for verifiable elections and analyzing cyber warfare in Ukraine. His 15+ years of teaching include courses like Introduction to Program Design and Election Systems Technologies. Publications span secure voting protocols, smartphone security, and election auditing. Collaborations include Microsoft and VotingWorks on cryptographic voting systems like ElectionGuard and Arlo-CVR-Encryption.

Grzegorz Chrupałaمشاهده پروفایل

دانشیار

• Computational Linguistics
• Artificial Intelligence
• Cognitive Science
• +۳ مورد دیگر

Grzegorz Chrupała is an Associate Professor at the Department of Cognitive Science and Artificial Intelligence , Tilburg University, where he leads research in computational approaches to multimodal communication. Previously, he was a postdoctoral researcher at Saarland University's Spoken Language Systems group and earned his PhD from Dublin City University's School of Computing. His research bridges biological and artificial computation , focusing on enabling machines to learn language from multimodal data (speech, gestures, visual-auditory stimuli) as children do naturally. This involves developing and interpreting deep learning architectures, analyzing emergent representations, and advancing speech technology for under-resourced languages. Key themes include Visually grounded speech modeling Feature attribution and model interpretability Human-inspired learning paradigms BlackboxNLP workshop leadership His recent publications examine speech model reliability , lexical tone encoding , and contextual dependencies in NLP systems. He mentors a team of PhD candidates and alumni working on topics like user-centric interpretability, bioacoustics, and disentangled speech representations. He also serves on the board of the Dutch Open Speech Technology Foundation, chairs Interspeech 2025 tutorials, and contributes as an Action Editor for TACL.

• Cybersecurity
• Cyber Analytics
• Digital Forensics
• +۴ مورد دیگر

Nicole L. Beebe is a Professor at the Alvarez College of Business, The University of Texas at San Antonio , specializing in cybersecurity, cyber analytics, and digital forensics. With over two decades of experience spanning academia, government, and industry, she has contributed extensively to research on insider threats, IoT security, and threat hunting. Ph.D. in Business Administration (Information Technology), UTSA MS in Criminal Justice, Georgia State University BS in Electrical Engineering, Michigan Technological University Her research explores cybersecurity challenges in emerging technologies, including quantum computing, IoT, and large language models. She has pioneered studies on cyberbullying dynamics, forensic automation, and AI-driven threat detection. Recent publications focus on adversarial image obfuscation , VR for security operations , IoT forensic methodologies , and deepfake detection frameworks , reflecting interdisciplinary work at the intersection of security, AI, and digital evidence. 2022 Best Paper Award, Journal of Network & Computer Applications Senior Member, IEEE and ACM Senior Fellow, Information Systems Security Association As an Associate Editor for Computers & Security , she shapes the field through peer review. Her $14M+ in funding from NSF, DHS, and DoD underscores her impact on advancing cybersecurity research and education.

Yongfeng Zhangمشاهده پروفایل

دانشیار

• Machine Learning
• Data Mining
• Information Retrieval
• +۸ مورد دیگر

Yongfeng Zhang is an Associate Professor in the Department of Computer Science at Rutgers University. He is also the Director of the AIOS Foundation . His research focuses on Machine Learning, Data Mining, Recommender Systems, and Explainable AI , with notable contributions to fair and personalized AI, AI for science, and social good. Education and Experience: PhD in CS (2011–2016) from Tsinghua University Postdoc at UMass Amherst (2016–2017) Joined Rutgers as Assistant Professor (2018), promoted to Tenured Associate Professor (2024) Research Interests: Machine Learning, Data Mining, Information Retrieval, Recommender Systems, Natural Language Processing, ML Systems, AI Agents, Explainable AI, Fairness, and AI for Science. Recent Achievements: Received the 2024 ACM SIGIR Test of Time Award, 2024 Presidential Teaching Excellence Award, and multiple NSF grants. He has advised over 15 PhD students and led projects on trustworthy AI, generative recommendation, and causal inference. Awards: 2024 ACM SIGIR Test of Time Award 2021 NSF CAREER Award 2015 Microsoft PhD Fellowship Grants & Labs: Led NSF grants on explainable AI, conversational recommendation, and neural-symbolic AI. Active in the AIOS platform development and multiple research labs.

Catuscia Palamidessiمشاهده پروفایل

استاد پژوهشی

• Privacy
• Data Security
• Information Flow
• +۵ مورد دیگر

Catuscia Palamidessi is a Research Professor and head of the Comete project team (Concurrence, Mobilité et Transactions) at the Inria Saclay - Île-de-France research center. Her work focuses on privacy, security, and information flow on social networks, with particular emphasis on protecting sensitive data while preserving utility. Her primary research interests include differential privacy, location data protection, and the use of machine learning techniques for privacy preservation. She has pioneered work on Local Differential Privacy (LDP) and its integration with generative adversarial networks to balance privacy protection with data utility. Her research addresses the critical challenge of securing personal data without destroying its usefulness for services and statistical analysis. Her most notable achievement is receiving the ERC Advanced Grant in 2018 for her HYPATIA project (Privacy and Utility Allied), which seeks to optimize the security and utility of personal digital data. This €2.2 million grant has enabled her to expand her research team and develop practical privacy solutions. ERC Advanced Grant 2018 for HYPATIA project As leader of the Comete team, she oversees research that has led to practical applications like Location Guard, a browser extension that adds controlled noise to location data to protect user privacy while maintaining service functionality. Her work has established important partnerships with industry leaders like Renault and numerous academic collaborations worldwide.