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Robin JiaView profile

Assistant Professor

• Natural Language Processing (NLP)
• Deep Learning
• Artificial Intelligence
• +7 more

Robin Jia is an Assistant Professor in the Thomas Lord Department of Computer Science at the University of Southern California (USC) , where he leads the AI, Language, Learning, Generalization, and Robustness (Allegro) Lab . His research focuses on enhancing the reliability and robustness of large language models (LLMs) through mechanistic understanding, benchmarking under distribution shifts, and neurosymbolic integration. Key affiliations include collaborations with the USC Keck School of Medicine and contributions to legal frameworks like the EU's Digital Services Act. Robin's research spans multiple domains, including: Scientific analysis of LLM capabilities in in-context learning , data memorization , and numerical reasoning Advancements in robust NLP systems , emphasizing uncertainty estimation and calibration Development of methods combining LLMs with symbolic solvers for complex reasoning tasks Interdisciplinary applications in medicine and law , such as privacy-preserving synthetic data generation and medical misconception evaluation . His recent publications (2024-2025) address Fourier-based numerical embeddings (NeurIPS), neurosymbolic planning (NAACL), and multimodal benchmarking (COLM), with a strong emphasis on privacy , fairness , and transparency . Scientific awards include the Google Research Scholar Award (2023) , SoCalNLP Symposium Best Paper Awards , and ACL/EMNLP outstanding papers . He advises PhD students like Johnny Wei and Ameya Godbole, and has secured grants from the NSF , USC-Capital One , and USC-Amazon .

• Machine Learning Security
• AI Safety
• Privacy in Machine Learning
• +4 more

Florian Tramèr is an Assistant Professor in the Department of Computer Science at ETH Zurich, Switzerland, leading research at the intersection of machine learning security, privacy, and AI safety. His work focuses on identifying and mitigating security vulnerabilities in machine learning systems, particularly in large language models and other AI systems. Tramèr's primary research interests include adversarial machine learning, membership inference attacks, privacy-preserving AI, and the security implications of large language models. His work has significantly advanced our understanding of how machine learning models memorize training data, how this memorization creates privacy risks, and how to evaluate the robustness of machine learning systems against various attacks. His recent publications demonstrate a strong focus on practical security challenges in deployed AI systems, including data extraction from language models, adversarial attacks against generative AI, and developing more rigorous evaluation methodologies for machine learning security. Tramèr's research has been published in top venues including ICLR, NeurIPS, ICML, and IEEE Security & Privacy. Tramèr is actively collaborating with leading researchers in the field including Nicholas Carlini, Matthew Jagielski, and Javier Rando, contributing to important initiatives like the International AI Safety Report. His work bridges theoretical security concepts with practical implications for real-world AI deployment.

Bimal ViswanathView profile

Associate Professor

• Cybersecurity
• Privacy Engineering
• Machine Learning
• +4 more

Bimal Viswanath is an Associate Professor in the Department of Computer Science at Virginia Tech's College of Engineering. His research focuses on cybersecurity, privacy engineering, and machine learning, particularly addressing adversarial AI and ML system vulnerabilities. He holds a Ph.D. from Saarland University and Max Planck Institute for Software Systems, and has held postdoctoral positions at UCSB and Nokia Bell Labs. Education Ph.D., Computer Science, Saarland University/Max Planck Institute (2016) M.S., Computer Science, IIT Madras (2008) B.Tech, Computer Science, Cochin University (2005) Research interests include: Adversarial attacks using/against ML systems Generative AI security (deepfakes, chatbots) Cybersecurity for online services Grants & Funding Recipient of CCI, NSF, and 4-VA grants supporting projects like robust AI defense mechanisms and adversarial image classification. Recent grants include $1.2M for AI security initiatives (2022-2025). Awards Distinguished Paper Award (SOUPS 2014) Best Paper Award (COSN 2015) AI2000 Most Influential Scholar Honorable Mention (2020) Advising Guided over 15 students including Jiameng Pu (PhD 2022), Connor Weeks (MS 2023), and current advisees Sifat Muhammad Abdullah (PhD 2021-). Notable student achievements include Facebook Fellowship nominations and industry placements at CVENT and University of Michigan. Labs & Teams Leading Virginia Tech's AI Security Lab focusing on generative models, adversarial ML, and applied cybersecurity solutions.

Achuta KadambiView profile

Associate Professor

• AI
• Computational Imaging
• Computer Vision
• +7 more

Achuta Kadambi, Ph.D., is an Associate Professor at UCLA in Electrical Engineering and Computer Science, leading an interdisciplinary research group focused on AI, computational imaging, and bias mitigation in medical technologies. He recruits PhD students from EE, CS, and Bioengineering departments and has commercialized research through two California-based companies. His research investigates the intersection of physics and artificial intelligence, with a focus on unbiased low-level vision systems. Current projects explore how light transport interacts with human skin variations to identify and correct imaging biases in facial recognition and medical devices. His work has produced over 70 patents, with 30+ issued, and a textbook Computational Imaging (MIT Press, 2022). NSF CAREER Award (2021) for light transport bias research DARPA Young Faculty Award (2021) for AI and medical imaging innovations ARO Young Investigator Program (2021) for computational sensing IEEE-HKN Under 35 Award (2022) for inclusive EECS inventions Forbes 30 Under 30 recognition His recent publications focus on polarization imaging, 3D Gaussian splatting, synthetic data generation for healthcare, and bias mitigation in machine learning. Collaborations with UCLA medical school faculty, including Dr. Laleh Jalilian, aim to deploy these innovations in clinical settings. Current teaching includes ECE 149: Foundations of Computer Vision (Fall 2024, Spring 2025) and ECE 102: Signals and Systems (Winter 2024).

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

Prof. Matthias Nießner is a Professor at the Technical University of Munich , where he leads the Visual Computing Lab . Prior to this, he held a Visiting Assistant Professor position at Stanford University . His work bridges computer vision , graphics , and machine learning , focusing on 3D reconstruction , semantic scene understanding , and AI-driven video synthesis . Prof. Nießner has published over 150 works in top venues like SIGGRAPH , CVPR , and ECCV , with several receiving best paper awards (SIGCHI’14, HPG’15, SPG’18, SIGGRAPH’16 Emerging Tech). His research has garnered international media attention, including features in the New York Times , Wall Street Journal , and MIT Technological Review , as well as TV demonstrations (e.g., Jimmy Kimmel Live for Face2Face technology). Awards : TUM-IAS Rudolph Moessbauer Fellowship (2017–ongoing) Google Faculty Award (2017) Nvidia Professor Partnership Award (2018) ERC Starting Grant (2018, €1.5M) Eurographics Young Researcher Award (2019) Research Trends : 3D Gaussian Splatting for real-time rendering Neural Radiance Fields (NeRF) with mesh supervision Audio-driven facial animation via diffusion models Latent space diffusion for 3D scenes Self-supervised and zero-shot methods for 3D and image analysis As a co-founder and director of Synthesia Inc. , he drives democratization of synthetic media. His YouTube channel has over 5 million views, reflecting his impact beyond academia.

Nasir MemonView profile

Professor

• Digital Forensics
• Biometrics
• Authentication
• +6 more

Nasir Memon is a Professor of Computer Science and Engineering at the New York University Tandon School of Engineering and concurrently serves as the Dean of Engineering at NYU Shanghai. He has been a faculty member at NYU Tandon since September 1998. Memon is a co-founder of NYU's Center for Cyber Security (CCS) and NYU Abu Dhabi, and the founder of key initiatives such as the OSIRIS Lab, CyberSecurity Awareness Week (CSAW), the NYU Tandon Bridge program, and the Cyber Fellows program. His work focuses on advancing cybersecurity education and addressing systemic biases in AI-driven systems. Education: Ph.D., Computer Science, University of Nebraska Master of Science, Mathematics, Birla Institute of Technology and Science (BITS), Pilani Bachelor of Engineering, Chemical Engineering, BITS, Pilani Research Interests: Media Forensics and Authentication Biometric Security and Privacy Data Compression and Privacy-Preserving Techniques Network Security and Incident Response AI Ethics and Fairness in Machine Learning Cybersecurity Education and Workforce Development Awards and Honors: IEEE Fellow (2010) SPIE Fellow (2014) Jacobs Excellence in Education Award (2002) NSF CAREER Award (1997) Advising and Grants: Advises Ph.D. students like Anubhav Jain and Govind Mittal, and mentors Master’s students such as Rishit Dholakia. Recipient of NSF grants and funding from NYU Abu Dhabi and Indiana University Bloomington for projects like computational tools for fact-checking and AI-driven bias mitigation. Labs and Teams: Directs the OSIRIS Lab, a leading research group in cybersecurity and AI. Leads initiatives at the NYU Center for Cybersecurity (CCS) and collaborates with NYU Abu Dhabi’s Center for Cyber Security.

Dennis SäringView profile

Professor

• Deep Learning
• Medical Image Analysis
• Artificial Intelligence
• +5 more

Prof. Dr. Dennis Säring is a faculty member at the University of Applied Sciences Wedel , specifically affiliated with the School of Engineering. His academic and research activities focus on Deep Learning , Medical Image Analysis , and applications of Artificial Intelligence in healthcare and biomedical imaging. He has led seminars on Deep Learning topics and supervised student projects in Autonomous Driving at Audi's AADC 2018 competition. Research Highlights : Cardiovascular imaging, forensic age estimation via MRI, neural network-based bone segmentation, and cerebrovascular aneurysm analysis. Technical Expertise : Cardiac MRI, 3D/4D image processing, parametric mapping, and spatiotemporal data fusion. His recent publications (2018-2023) emphasize 3D MR segmentation for age assessment, CMR strain analysis in athletes, and T1/T2 mapping for myocarditis. Key collaborations include institutions like the University Medical Center Hamburg-Eppendorf and Wedler Hochschulbund, with funding for autonomous vehicle research. While no explicit scientific awards are listed, his work spans clinical cardiology, forensic radiology, and AI-driven medical diagnostics.

Nirupam RoyView profile

Assistant Professor

• Wireless Networking
• Mobile Computing
• Cyber-Physical Systems
• +9 more

Nirupam Roy is an Assistant Professor at the Department of Computer Science, University of Maryland, College Park, and Director of the iCoSMoS research lab. His work bridges wireless networking, mobile computing, and acoustic sensing with applications in IoT, localization, healthcare, security, and wearables. Research Focus: Wireless Networking & Mobile Sensing Awards: Best paper award, MobiSys 2022 Best demo award, MobiSys 2021 CSL Ph.D. Thesis Award, UIUC 2019 Students: Nakul Garg, Yang Bai, Irtaza Shahid, Harshvardhan Takawale, Aritrik Ghosh, Ayushi Mishra, Sumbul Zehra, Justin Goodman Grants: NSF CAREER award (2023), Meta Research Award (2023)

Xiaoming LiuView profile

Professor

• Computer Vision
• Pattern Recognition
• Image and Video Processing
• +4 more

Xiaoming Liu is the Anil K. and Nandita Jain Endowed Professor of Engineering and MSU Foundation Professor in the Department of Computer Science and Engineering at Michigan State University . Holding a Ph.D. from Carnegie Mellon University (2004), he leads cutting-edge research in computer vision and machine learning. Research Interests : Computer Vision Pattern Recognition Image and Video Processing Machine Learning Medical Image Analysis Multimedia Retrieval Recent Research Trends : Focus on 3D object detection and depth estimation Development of robust biometric recognition systems Integration of radar-camera fusion for autonomous systems Advancements in self-supervised and multimodal learning Exploration of adversarial AI security Creation of interpretable forgery detection frameworks Teaching : Spring 2013: CSE891-006 Computer Vision Seminar Fall 2012-2015: CSE803 Computer Vision Spring 2014-2017: CSE 471 Media Processing and Multimedia Contact Information : Email: liuxm@cse.msu.edu Office: EB 3137, Michigan State University Phone: +1 (517) 355-2359

Rainer BöhmeView profile

Professor

• Steganography and steganalysis
• Digital forensics
• Privacy-enhancing technologies
• +4 more

Professor Rainer Böhme is a prominent academic in the field of IT security and privacy at the University of Münster's School of Business and Economics, Department of Information Systems. He also holds a professorship for Security and Privacy at the University of Innsbruck's Institute of Computer Science. His research spans multiple dimensions of digital security, with particular expertise in steganography, digital forensics, privacy-enhancing technologies, and the economic aspects of cybersecurity. Dr. Böhme earned his Doctoral Degree from TU Dresden's Faculty of Computer Science in 2008, following studies in Communications, Economics and Computer Science at Technische Universität Dresden and Université Paris XII. His academic journey includes positions as Assistant Professor at the University of Münster (2010-2015), Postdoctoral Fellow at the International Computer Science Institute in Berkeley (2009-2010), and Scientific Staff at TU Dresden's Chair of Privacy and Data Security. His research interests focus on steganography and steganalysis, digital forensics, privacy-enhancing technologies, security and usability, economic and behavioral aspects of information privacy, virtual currencies, and the economics of information security. His work bridges technical security mechanisms with economic and behavioral considerations, creating a unique interdisciplinary approach to cybersecurity challenges. Analysis of his recent publications reveals a strong trend toward the economics of security, particularly regarding blockchain technologies, cryptocurrency, and privacy valuation. His work increasingly examines the intersection of technical security mechanisms with market dynamics, regulatory frameworks, and user behavior. The research spans theoretical game-theoretic models, empirical studies of user behavior, and practical applications in digital forensics and privacy protection. Program Co-Chair, Financial Cryptography and Data Security (2015) Program Co-Chair, New Security Paradigms Workshop (NSPW) (2015) General Chair, 8th International Conference on IT Security Incident Management & IT Forensics (2014) Organizer and Program Co-Chair, 1st Workshop on Bitcoin Research (2014) Associate Editor, Electronic Commerce Research (since 2013) Associate Editor, EURASIP Journal on Information Security (since 2013) Professor Böhme has supervised multiple Master's theses in Information Systems, including work on static code analysis for smart contracts, remote maintenance protocol security, and application protection requirements in retail banking. His research is supported by significant grants from the German Federal Ministry of Research, Technology and Space, the DFG, and the EU FP7 program, with projects focusing on digital forensics, privacy-enhancing technologies, and cryptocurrency crime prevention. He leads the IT Security Research Group at the University of Münster, which investigates theoretical and applied aspects of information security with particular emphasis on the economic dimensions of security decisions.

Marc StammingerView profile

Professor

• Computer Graphics
• 3D Reconstruction
• Neural Rendering
• +7 more

Prof. Marc Stamminger is a Professor of Visual Computing at FAU since 2002, leading the Chair of Computer Science 9 (Computer Graphics). His work focuses on algorithms for synthesizing and analyzing images through 3D modeling, LiDAR/Radar capture, and light simulation. He co-leads FAU Solar, applying 3D modeling for environmental lighting analysis under varying conditions. Stamminger has published over 250 papers, winning prestigious awards like the Siggraph Test-of-Time Award. He holds executive roles in Eurographics and is Vice Dean of FAU's Technical Faculty. Research interests span neural rendering , 3D reconstruction , radar imaging , and medical visualization . Recent work emphasizes radiance field rendering (e.g., VR-Splatting, INPC) and radar-based human motion tracking. His lab's FAU Solar project integrates large-scale 3D models with environmental lighting simulations. Publications trends highlight neural rendering optimizations , radar-MIMO systems , and agricultural digital twins . Key collaborations involve medical imaging (e.g., vocal fold reconstruction) and autonomous driving data generation. Awards: Siggraph Test-of-Time (2023?), 2× Siggraph Best-Of-Show Grants/Teams: FAU Solar Lab, Eurographics leadership, FAU Vice Dean Labs: Chair of Computer Science 9, FAU Solar Initiative

• Cyber Law
• Artificial Intelligence and Law
• Business Law
• +7 more

Zaklina Spalevic is a distinguished Professor at Singidunum University, specializing in the intersection of law, technology, and business. With a strong academic background in criminal law and extensive research in cyber law, artificial intelligence applications in legal systems, and tourism law, she has established herself as a leading scholar in digital legal frameworks. Her work spans multiple disciplines, connecting traditional legal principles with emerging technological challenges. Dr. Spalevic earned her doctoral degree in Criminal Law from the University of the Academy of Economics in Novi Sad (2008-2012), following basic studies in General Law at the University of Pristina (1996-2001). Her educational foundation in Science and Mathematics from First Pristina High School (1992-1996) provided the analytical basis for her interdisciplinary approach to legal scholarship. Her research interests focus on the evolving landscape of cyber law, particularly the legal implications of artificial intelligence in judicial systems, electronic governance, and tourism industry regulation. Dr. Spalevic has pioneered work on digital evidence processing, algorithmic justice, and the integration of green law principles into sustainable business practices. Her publications reveal a consistent pattern of addressing emerging legal challenges in the digital age, with increasing emphasis on AI applications across various legal domains. Analysis of her recent publications shows a clear trend toward interdisciplinary research that bridges law, technology, and business. Her work increasingly focuses on practical applications of legal frameworks for emerging technologies, particularly in tourism, agriculture, and judicial systems. The integration of technical solutions with legal regulation represents a distinctive feature of her scholarly contributions. Dr. Spalevic has authored numerous publications including three books: 'Fundamentals of Law with Special Reference to Business and Tourism Law' (2021, 2024 editions) and 'Legal Aspects of Cyberspace' (2018). Her extensive publication record includes over 100 journal articles and conference papers spanning cyber security, electronic governance, intellectual property in digital environments, and legal frameworks for emerging technologies. She actively contributes to academic discourse through conference presentations and collaborative research projects, particularly focusing on the legal implications of artificial intelligence across various sectors. Her work demonstrates a commitment to developing practical legal frameworks that address real-world technological challenges while maintaining foundational legal principles.

Abdullah BalView profile

Researcher

• Data Science
• Machine Learning
• Deep Learning
• +5 more

Dr. Abdullah Bal is a researcher at Georgia State University's College of Arts & Sciences, Department of Computer Science, with over 25 years of academic experience. He holds a Ph.D. in Electrical Engineering from Yildiz Technical University (2002) and has taught graduate and undergraduate courses in algorithms, machine learning, and optical pattern recognition. B.Sc., Electronics and Communication Engineering, Istanbul Technical University (1993) M.Sc., Electrical Engineering, Yildiz Technical University (1997) Ph.D., Electrical Engineering, Yildiz Technical University (2002) His research focuses on data science, machine learning, and hyperspectral imaging applications in fields ranging from forensic analysis to historical structure preservation. He has led projects funded by the U.S. Army Research Office and the Scientific and Technological Research Council of Turkey, including real-time target detection systems and digital imaging for historical structures. Recent publications demonstrate his expertise in kernel-based transforms, ensemble learning, and hyperspectral data analysis. His work spans food safety inspection, infrared target tracking, and biometric verification systems. Faculty Outstanding Research Publication Award (2006) Turkish Air Force Academy Science Competition Winner (2009) Best Paper Award at ICFCT (2016) Previously, he chaired YTU's Informatics Department (2009-2016) and participated in academic governance through the Electrical and Electronics College Executive Committee (2012-2015). You can contact him at abal@gsu.edu in room 739, 25 Park Place.

Xinwen FuView profile

Professor

• Computer Security and Privacy
• IoT Security and Privacy
• Mobile Security
• +7 more

Dr. Xinwen Fu is a Professor in the Miner School of Computer & Information Sciences at the University of Massachusetts Lowell, where he also serves as Director of the iSAFER Center. He received his Ph.D. in Computer Engineering from Texas A&M University (2005), M.S. in Electrical Engineering from University of Science and Technology of China (1998), and B.S. in Electrical Engineering from Xi'an Jiaotong University (1995). Research Interests Dr. Fu specializes in Computer Security and Privacy , with particular focus on IoT Security , Mobile Security , Network Security , and Digital Forensics . His research has been published in all four top computer security conferences: IEEE Symposium on Security and Privacy (S&P/Oakland), ACM Conference on Computer and Communications Security (CCS), USENIX Security Symposium, and Network and Distributed System Security Symposium (NDSS), as well as prestigious journals like ACM/IEEE Transactions on Networking and IEEE Transactions on Dependable and Secure Computing. His work has gained significant media attention from CNN, Wired, Huffington Post, Forbes, Yahoo, MIT Technology Review, and PC Magazine, including multiple appearances on CNN Domestic and International. He has also served as TPC member for numerous prestigious conferences including ACM CCS, IEEE INFOCOM, and IEEE ICDCS. Scientific Awards Best paper award at IEEE International Conference on Industrial Internet (ICII) 2019 Best paper award, International Conference on Wireless Algorithms, Systems, and Applications (WASA), 2017 Teaching Excellence Award of Department of Computer Science, UMass Lowell, 2016 Best paper award, International Performance Computing and Communications Conference (IPCCC) 2016 Award of Excellence, GeekPwn 2016 Ethic Smart Life Hack Competition Erich Spengler Student Cyber Paper Award with students, The Colloquium for Information Security Education (CISSE), 2016 Spotlight Paper of the IEEE Transactions on Mobile Computing (TMC), February 2014 Best paper award, International Conference on Wireless Algorithms, Systems, and Applications (WASA), 2013 Best paper award, IEEE International Conference on Communications (ICC): Communications and Information Security Symposium, 2013 Teaching award, Department of Computer Science, University of Massachusetts Lowell, 2011

Peter DruschelView profile

Professor

• Distributed Systems
• Operating Systems
• Network Security
• +3 more

Peter Druschel is a Professor and founding Director of the Max Planck Institute for Software Systems (MPI-SWS) in Saarbrücken, Germany. He holds adjunct professorships at Saarland University and the University of Maryland. His research focuses on distributed systems, operating systems, and privacy-preserving technologies. He earned his Ph.D. from the University of Arizona in 1994 and has held roles at Rice University since 1994, including Professor of Computer Science (2002–2005). Education: Ph.D. in Computer Science, University of Arizona (1994) Research Interests: Distributed systems, operating systems, network security, accountable computing, and privacy technologies. Current projects include privacy compliance in data systems (Thoth), secure communication (EbN), and privacy-aware image capture (I-Pic). Awards: SIGOPS Mark Weiser Award (2008) NSF CAREER Award (1995) Member of Academia Europaea and German Academy of Sciences Leopoldina Grants & Leadership: Leads the ERC Synergy Project imPACT, chairs the Max Planck Society’s Chemistry, Physics, and Technology Section, and collaborates with institutions like Cornell and Google. Advises on policy issues related to technology and privacy. Labs/Teams: Distributed Systems Group at MPI-SWS, collaborations with Microsoft Research and MIT. Current team includes students and postdocs working on privacy, security, and distributed systems.