جست‌وجوی استاد و پژوهشگر

• Biometrics
• Face Recognition
• Fairness in AI
• +۳ مورد دیگر

Ana Filipa Sequeira is a researcher affiliated with INESC TEC, Porto, Portugal, and the University of Porto. Her work spans biometrics, fairness in AI, and explainable artificial intelligence. She has contributed to advancements in face recognition, synthetic data applications, and bias mitigation through techniques like knowledge distillation and model compression. Institution: INESC TEC (Porto, Portugal) Research Themes: Face recognition, fairness, explainability, synthetic data, biometric security Her recent publications focus on addressing demographic biases in face recognition systems, developing privacy-preserving explainable methods, and evaluating synthetic data's impact. She collaborates extensively with researchers like Pedro C. Neto, Jaime S. Cardoso, and Naser Damer. Sequeira has participated in organizing and analyzing competitions such as FRCSyn, BIOSIG, and SYN-MAD, emphasizing robust evaluation frameworks. Her work intersects technical innovation with ethical considerations, advocating for responsible AI applications in biometrics.

Suresh Venkateshمشاهده پروفایل

استادیار

• Metamaterials
• Millimeter-Wave and Terahertz Communication
• Antenna Design
• +۴ مورد دیگر

Suresh Venkatesh is an Assistant Professor in the Department of Electrical and Computer Engineering at North Carolina State University. He previously served as a postdoctoral research associate at Princeton University (2018–2022) and earned his Ph.D. in Electrical Engineering from the University of Utah in 2017. His academic journey also includes a Master's degree in Electrical Engineering from NC State in 2010. Education: Ph.D. in Electrical Engineering, University of Utah, 2017 Master's in Electrical Engineering, North Carolina State University, 2010 Research Interests: His work focuses on metamaterials and surfaces at GHz-THz frequencies, millimeter-wave phased arrays, and innovative applications in 5G/6G communication systems. Key areas include antenna design, physical layer security, advanced electromagnetic simulations, and reconfigurable systems using CMOS integration. He explores origami-based platforms for adaptive RF imaging and employs spatio-temporal modulation techniques to enhance wireless security and efficiency. Publications Trends: Recent work emphasizes mmWave and THz communication, with a focus on reconfigurable intelligent surfaces, secure low-latency links, and CMOS-based designs for direct detection receivers and cytometers. His research bridges theoretical concepts with experimental validation, particularly in wavefront manipulation and sparse imaging techniques. Awards and Honors: Mistletoe Research Fellowship (2021) Advising and Grants: Venkatesh contributes to research teams like the NC State 6GNC initiative, which spans 6G technologies. He actively organizes conferences such as the World Microwave Congress 2024 as TPC Co-Chair and participates in IEEE technical committees. His grants and collaborations drive advancements in metamaterials, secure wireless systems, and CMOS-integrated solutions. Labs and Teams: He leads efforts in the NC State ECE Department, focusing on labs involving reconfigurable antennas, computational imaging, and integrated systems. His work intersects with the 6GNC team to develop future communication technologies and secure mmWave/THz systems.

Alexandru G. Bardasمشاهده پروفایل

دانشیار

• Cybersecurity
• Systems Security
• Moving Target Defenses
• +۹ مورد دیگر

Alexandru G. Bardas is an Associate Professor at the University of Kansas in the Department of Electrical Engineering & Computer Science (EECS) and the Institute for Information Sciences (I2S) . He received his PhD from Kansas State University under advisors Xinming (Simon) Ou and Scott A. DeLoach. His research focuses on cybersecurity from a systems perspective , including moving target defenses, security operations center (SOC) metrics, DevOps security, power grid cybersecurity, and defensive technologies for political activists. He explores UDP-based DDoS detection, DNS traffic analysis, and the intersection of AI with cybersecurity, emphasizing foundational knowledge over tool-specific training. Key research areas: Cybersecurity, Systems Security, Moving Target Defenses, SOC Metrics, DevOps Security Recent publications in ACSAC 2024 , USENIX Security 2024/2023 , and IEEE Security & Privacy 2022 Dr. Bardas has received significant recognition including: NSF CAREER Award (2022) for SOC automation Bellows Scholar (2021) at KU NSA SoS Honorable Mention (2023) He actively advises students across disciplines, with graduates now at Sandia National Laboratories , Blue Cross Blue Shield , and Pacific Northwest National Laboratory . Dr. Bardas participates in NSF grant reviews , serves on program committees for SOUPS and MILCOM , and leads outreach initiatives like the GenCyber Summer Camp .

• Biometrics
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

Raghavendra Ramachandra is a Professor at the Department of Information Security and Communication Technology (IIK) , within the Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU) in Gjøvik. His research focuses on biometric systems, particularly in face, fingerprint, and finger vein recognition, with emphasis on presentation attack detection, morphing attack detection, and deep learning applications. Current research projects include: SALT (2022-2026) : Developing privacy-preserving facial biometric authentication systems. OffPAD (2022-2025) : Creating cryptographic tools and presentation attack detection for fingerprint biometrics. SWAN (2015-2020) : Developing biometric countermeasures against presentation attacks. His recent publications demonstrate technical expertise in: Face morphing attack detection using vision transformers and point cloud networks Image fusion techniques for multispectral biometrics GAN-based synthetic data generation for security evaluation Explainable AI approaches for biometric verification Professor Ramachandra also supervises PhD and Master’s students, and has extensive experience in leading national and EU research initiatives.

Jing Zhangمشاهده پروفایل

مدرس

• Computer Vision
• Machine Learning
• Generative AI
• +۵ مورد دیگر

Dr. Jing Zhang is a Lecturer in the School of Computing at the Australian National University (ANU) , within the ANU College of Systems & Society . Previously, he served as a Research Fellow at ANU (2021–2022) and earned his PhD in 2021 under the supervision of Nick Barnes. His academic journey includes a Master’s (2010) and Bachelor’s (2007) from Northwestern Polytechnical University . Education: PhD, Australian National University, 2021 (Supervisor: Nick Barnes) Master’s Degree, Northwestern Polytechnical University, 2010 Bachelor’s Degree, Northwestern Polytechnical University, 2007 Research Interests: Jing Zhang’s research focuses on computer vision and machine learning , with a particular emphasis on generative AI . His work addresses challenges in image, video, and audio generation/editing; explainable model adaptation; out-of-distribution detection; and adversarial attacks/defenses. He explores techniques to enhance model robustness and generalization across diverse domains. Awards & Recognition: CVPR 2020 Paper Award Nominee for “UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders” Teaching & Supervision: Jing Zhang teaches COMP8536: Advanced Topics in Computer Vision (Semester 2, 2024) and ENGN4528/6528: Computer Vision (Semester 1, 2025). He currently supervises 4 PhD students as their primary advisor, focusing on cutting-edge research in computer vision and AI. Professional Contributions: Co-organizer of tutorials on salient object detection (ACCV 2019) and uncertainty estimation (ICCV 2021) Regular reviewer for top venues: CVPR, ICCV, ECCV, TPAMI, IJCV, and others Research Groups: While not explicitly stated, his work is likely affiliated with ANU’s computer vision research groups, focusing on generative AI and robust machine learning systems.

Riccardo Felicettiمشاهده پروفایل

پژوهشگر ارشد

• Fault Detection and Diagnosis
• Fault Tolerant Control
• Optimization
• +۳ مورد دیگر

Riccardo Felicetti is a Research Fellow at the Department of Information Engineering, Università Politecnica delle Marche, within the Faculty of Engineering. He holds a Master's Degree (cum laude) in Computer and Automation Engineering (2016) and a Ph.D. (cum laude) in Information Engineering (2021) from the same university, with a thesis on “Active fault tolerant control for overactuated unmanned vehicles.” He also serves as Senior Tutor, coordinating tutor activities in the Faculty of Engineering. His research focuses on fault detection and diagnosis, fault-tolerant control, and optimization, with applications to unmanned vehicles (e.g., drones, ROVs) and energy management systems. He has contributed to advancements in systems like actuator fault tolerance, vibration-based fault detection, and energy optimization in smart grids. Key technical areas include disturbance observer-based control, adaptive Kalman filtering, and machine learning integration for system identification. His work bridges theoretical control frameworks with practical implementations in aerospace and marine robotics.

Luuk Spreeuwersمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Computer Vision
• Machine Learning
• +۷ مورد دیگر

Dr. Luuk Spreeuwers is an Associate Professor specializing in Datamanagement & Biometrics , with a focus on Artificial Intelligence , Computer Vision , and Machine Learning . His research spans biometric security, face recognition, morphing attacks, and finger vein verification, resulting in over 255 publications and 10 years of active research contributions. He has collaboratively developed datasets like Orchid Flowers Dataset and FLUXSynID , advancing AI applications in biology and forensic science. Research Interests: Face recognition, biometric security, deep learning, morphing attack detection, finger vein biometrics, explainable AI, and historical image analysis. Scientific Awards: Best Paper Award (BIOSIG 2017), Best Poster Award (BIOSIG 2014), Educational Award of Electrical Engineering (2018). Activities: Organized SITB 2025 and IWBF 2024 conferences; delivered invited talks on face recognition and forensic applications; serves as Editor-in-Chief of IET Image Processing . Article Trends highlight his work on: deep learning for biometric security, forensic face recognition, morphing attack detection frameworks, finger vein pattern analysis, and robustness testing in AI systems.

• Operating Systems
• Fault Tolerance
• Cyber-Physical Systems
• +۵ مورد دیگر

Marcus Völp is an Associate Professor and head of the CritiX research group at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT). His research focuses on ultra-reliable operating systems, fault and intrusion tolerant systems for cyber-physical environments, and hierarchical hybridization techniques to construct resilient computing platforms. His work bridges theoretical foundations with practical implementations, particularly in developing dependable systems-on-chip that can withstand faults and intrusions. Research spans formal verification methods, radiation-hardened hardware, blockchain security, and autonomous vehicle safety systems. Recent publications demonstrate advancement in parameterized system verification, radiation effects on routers, and N-version machine learning for autonomous systems. His group maintains strong focus on practical resilience mechanisms for real-time and critical systems across computing layers.

• 3D Integrated Circuits
• Hardware Security
• AI Accelerators
• +۴ مورد دیگر

Krishnendu Chakrabarty is the Fulton Professor of Microelectronics in the School of Electrical, Computer and Energy Engineering at Arizona State University (ASU). He also serves as CTO of the SWAP Hub for the Department of Defense Microelectronics Commons and Director of the ASU Center for Semiconductor Microelectronics (ACME). Previously, he was the John Cocke Distinguished Professor and Chair of Electrical and Computer Engineering at Duke University. Education: B.Tech from IIT Kharagpur (1990), M.S.E. and Ph.D. from the University of Michigan (1992, 1995). His research focuses on 3D integrated circuits, hardware security, AI accelerators, and microfluidic biochips. He has authored 27 books, 930 peer-reviewed papers, and holds 24 patents. His work has been supported by NSF, DARPA, NIH, and industry partners like Intel and NVIDIA. Key awards include NSF CAREER Award, IEEE Technical Achievement Awards, Humboldt Research Award, and Distinguished Alumnus from IIT Kharagpur. He advises 44 PhD graduates and collaborates with industry leaders such as Synopsys and Cisco. His leadership roles include Editor-in-Chief of IEEE Transactions and Fellowships in ACM, IEEE, and AAAS. Research highlights include pioneering test methodologies for 3D ICs, developing AI-driven biochip solutions, and securing hardware against cyber-physical threats. His labs and teams focus on advancing semiconductor technology and healthcare applications through interdisciplinary innovation.

• Computer Vision
• Biometrics
• Artificial Intelligence
• +۸ مورد دیگر

Kiran Raja is an Associate Professor at the Department of Computer Science within the Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology . With a focus on biometric security , computer vision , and educational technology , Raja's academic career spans both technical innovation and pedagogical research. Research interests include: Biometric Security – Face morphing attack detection, deepfake defense, and cancelable template protection Computer Vision – Facial recognition, image generation, and UAV-based person re-identification Medical AI – Healthcare data protection and medical image super-resolution Educational Reform – Redesigning computer science curricula and cross-campus teaching methodologies Recent work trends show a strong emphasis on privacy-preserving AI , ethical biometric systems , and educational technology . Key technical contributions include Vision Transformers for morphing attack detection GAN-based synthetic face morphing datasets Quantization-enhanced models for edge computing Graph Neural Networks for activity recognition Collaborations span institutions like IEEE, Springer, and SPIE, with consistent co-authorship with researchers such as Christoph Busch , Raghavendra Ramachandra , and Haoyu Zhang .

• Biometrics
• Face Recognition
• Face Morphing Attacks
• +۳ مورد دیگر

Haoyu Zhang is a Researcher at the Department of Information Security and Communication Technology, Norwegian University of Science and Technology (NTNU), Gjøvik. His primary research focuses on biometric security with specialization in face recognition systems and countermeasures against morphing attacks. His research program centers on synthetic data generation for biometric security, including techniques like SynMorph for creating morphed face datasets and MIPGAN for identity-prior-driven attack generation. He investigates deep learning architectures such as Vision Transformers and diffusion models for morphing attack detection, while also exploring synthetic ethnicity alteration to address dataset bias and remote photoplethysmography for liveness detection. His work bridges theoretical generative models with practical security applications in face recognition pipelines. Publication analysis from 2021-2025 reveals a cohesive research trajectory advancing morphing attack methodologies through three interconnected strands: attack generation (e.g., MIPGAN, SynMorph), detection frameworks (e.g., Vision Transformer-based detectors), and dataset enhancement (e.g., synthetic ethnicity alteration). His 2025 doctoral dissertation synthesizes these contributions into a comprehensive framework for morphing attack generation, data augmentation, and detection. The work demonstrates consistent collaboration with Ramachandra, Raja, and Busch across IEEE and Springer venues, establishing him as a contributor to biometric security standardization efforts.

• Computer Vision
• Biometrics
• Authentication Systems
• +۳ مورد دیگر

Nuno Gonçalves is a Tenured Assistant Professor at the Department of Electrical and Computer Engineering and Senior Researcher at the Institute for Systems and Robotics (ISR) - Coimbra, University of Coimbra. He also serves as Innovation Manager at the Portuguese Mint and Official Printing Office (INCM) since 2018, focusing on technology transfer and product development. His roles include coordinating the AI group of APDSI and leading research in biometrics, facial recognition, and steganography. PhD in Computer Vision (University of Coimbra, 2008) His research spans computer vision, biometrics, and visual information security, with specific focus on facial recognition, morphing attack detection, presentation attack detection, graphical security, security coding, printer-proof steganography, and robotics. Recent work emphasizes deepfake detection, neural implicit representations, and robust biometric solutions. Article trends reveal expertise in 3D face reconstruction, multimodal deep learning for medical applications, and security-enhancing steganography. He leads projects integrating geometric modeling with neural networks for signed distance functions and develops benchmarks for morphing attack robustness in facial recognition systems. Member, IEEE He has coordinated grants from Fundação para a Ciência e a Tecnologia and private industry partners, including projects like BLOCKDFAKE (2025-2026) for deepfake detection in public administration and VISUAL-ID (2022-2024) for unique visual identities. His lab at ISR-Coimbra collaborates with INCM on security document validation and printer-proof steganography, with patents granted by EUIPO and USPTO.

• Computer Technology
• Information Security
• Biometrics
• +۲ مورد دیگر

Christoph Günther Busch is a Professor at the Department of Information Security and Communication Technology, Norwegian University of Science and Technology (NTNU). His research focuses on biometric security, facial recognition systems, and digital forensics, particularly addressing vulnerabilities in face authentication technologies. Scientific Disciplines: Computer Technology Affiliation: NTNU Research interests include: Face Presentation Attack Detection (anti-spoofing) Image Quality Assessment for biometric systems Analysis of demographic variability in facial recognition Detection of digitally manipulated faces Biometric sensor security Recent publications (2023-2025) emphasize face authentication challenges, including: Remote Photoplethysmography for attack detection Transformers in biometric security Morphing attack detection methods Fairness in image quality assessment Scientific award: German IT-Security Award (2nd prize) in 2022

Christian Rathgebمشاهده پروفایل

استاد

• Biometrics
• Iris recognition
• Face recognition
• +۳ مورد دیگر

Christian Rathgeb is a Professor with the Faculty of Computer Science at Hochschule Darmstadt, Germany, serving as a Principal Investigator in the National Research Center for Applied Cybersecurity (ATHENE) and Program Chair of the International Conference of the Biometrics Special Interest Group (BIOSIG). His research bridges theoretical foundations and practical security applications in biometric systems. Rathgeb's work focuses on biometrics with expertise in iris and face recognition systems, privacy-enhancing technologies, and template protection. His research addresses critical challenges including demographic bias in biometric systems, vulnerability to morphing attacks, and privacy concerns in biometric applications. Notably, his recent work explores synthetic data generation for improving recognition systems and developing robust methods for detecting face manipulation. Analysis of his recent publications reveals a strong trajectory toward addressing emerging threats in biometric security, particularly deepfakes and digital face manipulation. His research increasingly integrates privacy considerations with system performance, reflecting the growing societal importance of ethical biometric applications. The work demonstrates both theoretical rigor and practical implementation value. Member of the European Association for Biometrics (EAB) Member of the IET Biometrics Editorial Board Developer of USIT – University of Salzburg Iris Toolkit v2.0 Author of one of the most downloaded IEEE-TIFS papers Professor Rathgeb actively supervises master's and bachelor's students, with recent successful thesis defenses by Hans Heje and Maciej Salwowski. His student Mathias Ibsen received the Best HAW Promotion Award, highlighting the quality of research conducted under his guidance. Rathgeb maintains extensive collaborations with researchers across Europe, particularly with Christoph Busch and other members of the international biometrics community. As Principal Investigator at ATHENE, Rathgeb leads research teams developing practical security tools with emphasis on privacy-preserving techniques. His group contributes to international standards in biometric security and regularly addresses real-world challenges in authentication systems.

• Computer Science
• Artificial Intelligence
• Biometrics
• +۴ مورد دیگر

Pedro C. Neto is a researcher affiliated with the Department of Computer Science at the School of Engineering, University of Coimbra, Portugal. His work focuses on fairness in artificial intelligence, biometrics, and synthetic data applications in facial recognition systems. Research Interests: Fairness in AI, Face Recognition, Knowledge Distillation, Synthetic Data Evaluation, Biometrics His recent publications (2024–2025) highlight trends in mitigating demographic bias through continuous labeling, synthetic data challenges, and model compression techniques. He has contributed to advancements in morphing attack detection, occluded face recognition, and interpretable biometric systems. Pedro actively participates in academic competitions like the FRCSyn Challenge and MFR 2021, collaborating with international teams. His work intersects computer science, artificial intelligence, and ethical considerations in biometric technologies.