Find Academic Supervisors

Marina GavrilovaView profile

Professor

• Machine Learning
• Biometric Security
• Image Processing
• +4 more

Marina Gavrilova is a Professor and Associate Head (Research and Strategic Planning) in the Department of Computer Science at the University of Calgary. Her research focuses on biometric security, machine learning, pattern recognition, and interdisciplinary computational sciences. She is a co-founder of the Biometric Technologies Laboratory and the SPARCS laboratory, and serves as Founding Editor-in-Chief of Springer's Transactions on Computational Sciences. Her work spans ethical AI frameworks, multimodal biometric systems, and healthcare applications. Dr. Gavrilova holds Senior ACM and IEEE membership statuses and has received prestigious awards including the Canada Foundation for Innovation Grant and the University of Calgary’s U Make a Difference Award. Her editorial roles include positions with IEEE Transactions on Computational Social Sciences, IEEE Access, and multiple biometrics journals. Her research explores emotion-aware de-identification systems, trustworthy AI, and bias mitigation in healthcare machine learning. Key contributions include advancements in generative adversarial networks, fusion strategies for multimodal data, and computational methods for medical imaging. She advocates for ethical AI practices and interdisciplinary collaboration to address societal challenges in security and privacy. Lab affiliations include the Biometric Technologies Lab and SPARCS Lab, which focus on computational security and interdisciplinary research. Ongoing work emphasizes social behavioral biometrics, autonomous systems, and AI-driven healthcare solutions.

• Artificial Intelligence
• Recommender Systems
• Natural Language Processing
• +3 more

Benjamin Uwe Kille is an Associate Professor in the Department of Computer Science at NTNU, affiliated with the Faculty of Information Technology and Electrical Engineering. His research focuses on artificial intelligence, particularly in recommender systems, natural language processing, fairness in AI, and political text analysis. He leads initiatives involving large language models (e.g., SP-BERT for Scandinavian languages) and explores ethical challenges in AI applications like healthcare and education. Kille is actively involved in organizing workshops (e.g., INRA) and contributes to public outreach through lectures and media engagements. Research Interests: His work spans algorithmic fairness, news personalization, political discourse analysis, and generative AI applications in healthcare and public services. Recent studies include detecting political viewpoints in Norwegian texts and ensuring fairness in recommendation systems for previously unseen users. Publications: His recent work addresses topics like transparent fairness mechanisms, news image-text alignment, and Scandinavian language models. He co-authored reports on AI in healthcare (AIFAL project) and presented at venues like ACM RecSys and NorwAI events. Outreach & Teaching: Teaches TDT4215 - Recommender Systems at NTNU. Engages in public discourse via talks at companies (e.g., Nordea, Statsbygg) and media interviews (e.g., Gemini.no, Digi.no). Collaborates with institutions like SINTEF and the Norwegian Directorate of Health on AI applications. Labs & Teams: Active in the NAIL (Norwegian Artificial Intelligence Lab) and NorwAI initiatives, driving advanced AI research and development in Norway.

Gabriel E. HineView profile

Researcher

• Biometrics
• Signal Processing
• Information Security
• +13 more

Gabriel E. Hine is a Postdoc researcher at the Biometric Systems and Multimedia Forensics Lab within the Department of Engineering at Roma Tre University, Italy. He is actively engaged in research at the intersection of signal processing, biometrics, and information security, and contributes to teaching in advanced signal processing and biometric systems. Bachelor’s Degree in Electronic Engineering, Roma Tre University (2013, cum laude) Master’s Degree in Information and Communication Technology Engineering, Roma Tre University (2015, cum laude) PhD in Applied Electronics, Roma Tre University (2018) Research collaboration at Telefonica I+D, Barcelona (2016) Research involvement in EU H2020 ENCASE and PRIN 2011/2012 projects His research focuses on biometric cryptosystems, template protection, and privacy-preserving biometric recognition, with significant contributions to fingerprint, palmprint, EEG, and signature-based systems. He has also conducted influential work on online social media dynamics, particularly analyzing 4chan’s /pol/ forum. The analysis of his recent publications reveals a strong trend in developing secure and unlinkable biometric templates using deep learning, sparse signal representations, and zero-leakage frameworks. His work spans both theoretical formulation and experimental validation on real-world data, particularly in finger-vein and palm-vein recognition. He also explores novel biometric modalities such as in-air 3D signatures and resting-state EEG. Best Paper Runner-Up, ICWSM-17 (2017) Selected as 'Best of Arxiv' paper Widely covered in Nature , MIT Technology Review , The Independent , Vice , and Italian media Hine has served as a lecturer and teaching assistant for courses including 'Biometric Systems' and 'Signal Theory' at Roma Tre University. He has led a didactic laboratory on biometric systems, guiding students in implementing and analyzing biometric recognition solutions. His research is supported by major grants such as EU H2020 ENCASE and PRIN 2011/2012. He collaborates extensively with Prof. Patrizio Campisi and other researchers in the BioMedia4n6 lab. He is a core member of the BioMedia4n6 research group, which specializes in biometrics, data hiding, and blind deconvolution, applying advanced signal processing techniques to multimedia forensics and security challenges.

• Intelligent Sensor Systems
• Autonomous Systems
• Cyber-Physical Systems
• +19 more

Niki Trigoni is a Professor of Computing Science at the University of Oxford, Department of Computer Science, and a Governing Body Fellow at Kellogg College. She leads the Cyber Physical Systems Group and is Director of the EPSRC Centre for Doctoral Training in Autonomous Intelligent Machines and Systems (AIMS), a major interdisciplinary program combining robotics, machine learning, sensor systems, and verification/control. Her research focuses on intelligent and autonomous sensor systems, with applications in indoor positioning, healthcare monitoring, environmental sensing, and smart cities. Key interests include data fusion, inference and learning from sensor data, human-robot interaction, communication protocols for sensor networks, and innovative mobile sensing architectures such as participatory and social sensing. Her recent publications (2020–2023) highlight a strong trend in deep learning-based sensor fusion, particularly using mmWave radar, LiDAR, inertial, and visual data. Work spans human sensing (e.g., mmPoint), localization (e.g., PointLoc, RadarLoc), SLAM (e.g., iMag+), and domain adaptation (e.g., illumination-aware thermal detection). The research demonstrates a consistent focus on robustness in GPS-denied environments and real-world deployment. She has secured external funding, including a 3-year NIST grant for indoor positioning systems for emergency responders. She actively supervises a large cohort of PhD students and research associates, many of whom have gone on to notable careers. Her leadership roles in major conferences such as IPSN and Sensys further underscore her impact in the field. Labs and Teams: Cyber Physical Systems Group EPSRC Centre for Doctoral Training in Autonomous Intelligent Machines and Systems (AIMS)

Andreas HaeberlenView profile

Professor

• Distributed Systems
• Networking
• Security
• +10 more

Andreas Haeberlen is a Professor in the Department of Computer and Information Science at the University of Pennsylvania, where he is a member of the Distributed Systems Lab (DSL) and co-director of the NETS program. He is currently on a leave of absence from Penn to lead the new systems group at Roblox Research, focusing on large-scale distributed systems in cloud and metaverse environments. University: University of Pennsylvania School: School of Engineering and Applied Science Department: Department of Computer and Information Science Academic Rank: Professor Email: ahae@cis.upenn.edu His research centers on distributed systems, networking, security, and privacy, with key interests in differential privacy, fault tolerance, secure network provenance, accountability in federated systems, and synchronous data center architectures. He aims to build practical systems that provide strong, provable privacy and security guarantees for real-world applications. The recent publications reflect a strong trend toward privacy-preserving distributed analytics, resilient cyber-physical systems, and secure, accountable federated infrastructures. His work combines techniques from programming languages, operating systems, and distributed computing to address fundamental challenges in scalability, security, and timing predictability. Key themes include bounded-time recovery, differential privacy in federated settings, and secure provenance for network diagnostics. Scientific Awards: Recipient of the Otto Hahn Medal from the Max Planck Society Recipient of the Ford Motor Company Award for Faculty Advising Recipient of the Lindback Award for Distinguished Teaching He has advised graduate students such as Karan Newatia and Robert Gifford, often in collaboration with Linh Thi Xuan Phan. His research is supported by active projects in differential privacy, synchronous data centers, resilient cyber-physical systems, secure network provenance, and accountability. He leads or co-leads major research initiatives that bridge academic innovation with industrial-scale deployment, particularly in cloud and metaverse platforms.

Bart HengeveldView profile

Assistant Professor

• Internet of Things
• Human-Computer Interaction
• Sound Design
• +3 more

Bart Hengeveld is an Assistant Professor at Eindhoven University of Technology's Department of Industrial Design, specializing in the 'body language' of the Internet of Things and the role of sound in computational technologies. His research focuses on how embedded systems present themselves appropriately in human environments, with particular attention to tangible user interfaces (TUIs), social interaction design, and data embodiment. Academic Background: BSc/MSc in Industrial Design Engineering from Delft University of Technology (2003), PhD at TU/e (2011) Key Roles: Member of the ACM TEI Steering Committee, Program Chair of TEI’16 in Eindhoven Teaching: Awarded two Teacher of the Year titles, oversees courses like 'The Sound of Smart Things' and 'From Idea to Design' Research Interests emphasize sound as a communication medium for ubiquitous technologies, including projects on public displays for nursing homes (R2S system), pedestrian trajectory sonification, and embodied passwords. His work bridges design, computer science, and social sciences, with over 50 publications in venues like TEI, CHI, and Creativity & Cognition. Notable Projects: LOOP (physical data artifact), Slots-Memento (intergenerational storytelling), and LinguaBytes (language learning for toddlers) Awards: Multiple teaching accolades for innovative pedagogy Current affiliations include the Future Everyday research cluster and the Making With… group, exploring speculative design and embodied interaction paradigms.

Boris ŠkorićView profile

Associate Professor

• Quantum Cryptography
• Information Security
• Digital Forensics
• +3 more

Boris Škorić is an Associate Professor in the Security of Embedded Systems (SEC) group at the Department of Mathematics and Computer Science, Technische Universiteit Eindhoven. His research focuses on quantum cryptography, security with noisy data, and collusion-resistant watermarking. He is affiliated with the CREST project and has contributed to advancements in quantum-secure authentication and quantum key distribution protocols. Education : Ph.D. in Physics (Quantum Hall Effect), M.Sc. in Physics His research interests span three core areas: (1) Security with noisy data, addressing challenges in cryptographic primitives using physical measurements; (2) Quantum physics for security, including quantum readout of Physical Unclonable Functions (PUFs) and quantum key recycling; and (3) Collusion-resistant watermarking codes for digital content protection. He has pioneered techniques such as quantum-secure authentication via laser speckle and error correction methods for secure key storage. His publications reflect a strong emphasis on quantum security, including developments in continuous-variable quantum key distribution, entropically secure encryption, and quantum position verification. Recent work explores applications in healthcare data protection and secure communication over turbulent optical channels. Grants & Labs : Active in the CREST project (Collusion-Resistant Embedding and Secure Tracing) and collaborates with industry on quantum-secure technologies. Leads research in the SEC group, mentoring projects on cryptographic protocols and embedded system security.

• Cybersecurity
• Privacy-Preserving Machine Learning
• Secure Multi-Party Computation
• +3 more

Xiaoning (Maggie) Liu is a Lecturer (equivalent to US Assistant Professor) at the School of Computing Technologies, RMIT University, where she earned her Ph.D. in Computer Science. Her research focuses on secure systems to address data privacy and security challenges in machine learning, particularly through secure multi-party computation (MPC) and privacy-preserving machine learning (PPML). She applies these techniques to practical domains like medical diagnostics and mobile image classification. Her design philosophy emphasizes lightweight, fundamental protocols leveraging advanced cryptographic methods, such as function secret sharing and zero-knowledge proofs. Research Interests: Secure multi-party computation and its applications in PPML Privacy-preserving medical diagnostics (e.g., MediSC , CryptMed , OblivGNN ) Secure cloud and edge computing systems ( Sonic , EncSIM , Leia ) Cross-domain encryption and collaborative computation Advising & Supervision: Xiaoning supervises Masters and PhD students in research projects such as intrusion detection systems for healthcare IoT devices, defenses against backdoor attacks in neural networks, and privacy-preserving fairness verification. She emphasizes recruiting self-motivated researchers passionate about impactful security work. Interdisciplinary Contributions: Her work bridges computer systems, cryptography, and machine learning to address real-world challenges in areas like MLaaS, medical data collaboration, and mobile-edge inference. Collaborative frameworks like MediSC and Leia

• Electromagnetic Field Design
• Antenna Engineering
• Computational Intelligence
• +3 more

Rocío Sánchez Montero is an Associate Professor in the Department of Signal Theory and Communications at the University of Alcalá. She holds a PhD from the same institution (2011), focusing on computational intelligence techniques for robust design of radiant devices. Her work is centered in the Radiation and Sensing Group (RSG), addressing challenges in antenna engineering, electromagnetic field optimization, and biomedical applications. Her research interests include antenna design, wireless systems, and bioengineering applications of electromagnetic fields. Notably, she has pioneered methods for exposure mapping using evolutionary algorithms and developed miniaturized antennas for medical and industrial use. Her work integrates computational intelligence with hardware design, emphasizing practical applications in telecommunications and healthcare. Recent publications highlight advancements in wearable antennas, cryogenic radio telescope front-ends, and wireless power transfer for implantable devices. She also contributes to data protection policies, particularly pseudonymization techniques for public administration. Though no formal awards are listed, her prolific output (over 50 publications since 2003) reflects sustained contributions to electromagnetic engineering and interdisciplinary research. She advises through her teaching roles and collaborates on innovative projects at the Yebes Observatory and biomedical engineering interfaces.

Jan Henrik ZiegeldorfView profile

Researcher

• Data Security
• Privacy-Preserving Technologies
• Cryptographic Protocols
• +12 more

Dr. Jan Henrik Ziegeldorf is a researcher at RWTH Aachen University, affiliated with the Institute for Energy Efficient Buildings and Indoor Climate at the EON Energy Research Center (EONERC) and the Communication Systems Group (COMSYS) within the Department of Computer Science. He holds a PhD in Computer Science from RWTH Aachen, earned in 2018, and has been contributing to research in data security and privacy since 2017, initially part-time and then full-time. His research focuses on data security, privacy-preserving technologies, and cryptographic protocols , with applications in blockchain, IoT, cloud computing, and genomics. He has made significant contributions to secure multi-party computation, differential privacy, anonymization, and homomorphic encryption. His work bridges theoretical cryptography with practical system implementations, particularly in constrained environments and decentralized architectures. The recent publications reflect a strong trend in privacy-preserving machine learning, secure blockchain systems, and genomic data protection . These works demonstrate expertise in designing frameworks (e.g., SHIELD, BLOOM) that enable secure computation while maintaining performance, especially in outsourced and distributed settings. His research often targets real-world privacy threats in cloud storage, mobile apps, and decentralized networks. Univention Graduate Award (3rd place) for the best thesis in 2016 FOLKS Award for the best Master's thesis in 2015 Dr. Ziegeldorf has actively advised numerous Master’s and Bachelor’s students on topics ranging from secure localization to blockchain privacy and differential privacy. His service includes program committee roles for IEEE Blockchain conferences and peer review for top-tier journals such as IEEE, ACM, and Elsevier publications. He is involved in collaborative research within the COMSYS group and contributes to interdisciplinary projects linking energy systems, networking, and privacy. He is part of the COMSYS research team at RWTH Aachen, which focuses on communication systems, security, and privacy in networked environments. The group works on both foundational and applied aspects of secure and efficient digital systems, with strong industry and academic collaborations.

• Ethnography
• Qualitative Research Methods
• Public Involvement
• +10 more

Jo White is a Senior Research Fellow and Marie Skłodowska-Curie Fellow at the University of the West of England (UWE Bristol), affiliated with the Health and Social Sciences department. Her work focuses on gender, sexuality, embodiment, and health inequalities, emphasizing qualitative methods and public involvement in research. She leads projects addressing health disparities among marginalized communities, including the ISSMAS initiative targeting Black African and Caribbean stroke patients and the TRUUD project linking urban design to public health. Education: PhD and MA from Goldsmiths, University of London Key Roles: PPI Lead on multiple projects, UWE Lead on ISSMAS, Public Involvement co-lead on TRUUD, and supervisor for doctoral teams. Her research interests span ethnography, co-production methodologies, and global health issues including HIV and maternal health. Notable outputs include the film DARE (awarded Special Mention at the UK Seasonal Short Film Festival) and collaborative projects with UN agencies and international universities. Awards: Marie Skłodowska-Curie Fellowship Special Mention - UK Seasonal Short Film Festival (2019) Directed by Women Festival Shortlist (2019) Jo teaches qualitative research methods and global public health, contributing to UWE’s Flying Faculty program in China. She advocates for public involvement in research to enhance real-world relevance and collaborates with People in Health West of England (PHWE) to integrate community perspectives into healthcare policies.

Antonio PaolilloView profile

Professor

• Real-Time Systems
• Embedded Software
• Robotics
• +3 more

Antonio Paolillo is a Professor in the Department of Informatics and Applied Informatics at Vrije Universiteit Brussel. His research focuses on real-time systems, embedded software, robotics, and synchronization protocols. He leads projects like Brubotics (sustainable human-centered robotics) and FORCES (reliable robotic systems), emphasizing safety, privacy, and performance in human-robot collaboration. Key contributions include the mmPrivPose3D dataset for gesture recognition and sensor-based safety systems. He actively contributes to conferences like ECRTS 2025 and is involved in OS design for embedded platforms. His work bridges theoretical formal verification with practical implementations in multi-core and NUMA architectures. Education details and specific degrees were not explicitly mentioned in the provided text. Research interests span real-time scheduling, hardware-software co-design, and robust embedded systems. Recent articles emphasize privacy-compliant human-robot interaction and compiler transpilation for safety-critical applications. He collaborates internationally in robotics and real-time systems domains. Current projects (2024-2029) include foundational work on embedded software performance, reconfigurable robotics, and conference organization for ECRTS 2025. His work often involves interdisciplinary teams and industry partnerships.

Ruben De SmetView profile

Researcher

• Cryptography
• Zero-Knowledge Proofs
• Data Privacy
• +3 more

Ruben De Smet is a postdoctoral researcher at the Vrije Universiteit Brussel (VUB), specializing in cryptography and zero-knowledge proofs with a focus on data privacy. He holds an MSc in Engineering from VUB (2018) and a PhD in Engineering (2024) focused on privacy-enhancing technologies. His research explores secure peer-to-peer architectures for social networking, emphasizing user consent and data ownership. Education: MSc in Engineering, VUB (2018) PhD in Engineering, VUB (2024) – Thesis: Rapid Prototyping and Deployment of Privacy-Enhancing Technologies His research interests include cryptography optimization for embedded systems (e.g., ARM processors), zero-knowledge proof applications, and privacy-preserving permission management systems. Key contributions include work on secure communication protocols and decentralized architectures. Awards: IACR RWC'21 Cryptohackathon 2nd Prize (2021) Repair Café for Digital Rights - BXL (2020) Professional Activities: Organized workshops on Rust programming for embedded systems (2024) Speaker on zero-knowledge proofs and cryptographic systems (2025) Active in Belgium Rust User Group and Wireless Community initiatives His work bridges theoretical cryptography with practical implementations, aiming to redefine social networking security paradigms.

• Programming Languages
• Program Synthesis
• Program Verification
• +7 more

Jedidiah McClurg is an Assistant Professor in the Department of Computer Science at Colorado State University, with prior faculty appointments at Colorado School of Mines and the University of New Mexico. He received his Ph.D. in Computer Science from the University of Colorado Boulder in 2018, where he was a member of the CUPLV research group under the supervision of Pavol Cerny. His research focuses on programming languages, program synthesis, verification, and their applications in networking, compilers, and distributed systems. His educational background includes an M.S. in Computer Science from Northwestern University (2013) and a B.S. in Electrical Engineering from the University of Iowa (2009). He has completed internships at Microsoft Research (RiSE Group, 2014) and Rockwell Collins (2011, 2013, 2004). McClurg’s research interests include programming languages, formal verification, software synthesis, software-defined networking, compilers, and system security. His work aims to develop tools and techniques that help programmers write more secure, reliable, and efficient code, especially in safety-critical domains. He has led multiple NSF-funded projects, including FMitF and CRII grants, totaling over $1 million in funding. His recent publications span high-impact venues such as PLDI, CAV, DISC, and SOSR, with topics ranging from neural network optimization and regular expression synthesis to network program verification and FEC code generation. These works reflect a consistent trend toward automating correctness, improving performance, and enabling scalable solutions in systems and networking. NSF CRII: SHF: Foundations for Stateful Network Programming ($175,000) NSF FMitF: Game Theoretic Updates for Network & Cloud Functions ($355,000 for him) NSF FMitF: Robust Enforcement of Customizable Resource Constraints ($250,000 for him) NSF GRFP (awarded to student Lauren Baker) He has advised multiple graduate and undergraduate students, many of whom have secured positions at leading tech companies such as Google, Apple, and Amazon. He is actively involved in academic service, having served on program committees for PLDI, SOSR, CAV, and others, and as a reviewer for journals like IEEE/ACM Transactions on Networking (ToN) and ACM Transactions on Software Engineering (TSE). He also contributes to open-source research via GitHub and maintains a strong online academic presence.

Henry HoffmannView profile

Professor

• Self-aware Computing
• Adaptive Computing
• Computer Systems
• +5 more

Henry Hoffmann is Professor and Liew Family Chair of the Department of Computer Science at the University of Chicago. He serves as Chair of the department and leads research in self-aware and adaptive computing systems. His work bridges traditional computer systems areas with control theory and machine learning to create systems that automatically adapt to meet high-level goals. Hoffmann received his Ph.D. from MIT in 2013 under advisors Anant Agarwal and Srinivas Devadas, with his dissertation titled "SEEC: a framework for self-aware management of goals and constraints in computing systems." He earned an S.M. from MIT in 2003 and a B.S. with highest honors and distinction from UNC-Chapel Hill in 1999. Hoffmann's research focuses on developing self-aware computing systems that understand high-level goals and automatically adapt their behavior to meet those goals optimally. His recent work has shifted toward applying these techniques to control machine learning and AI systems, building learning systems that dynamically adapt their internal structure and resource usage to meet accuracy, energy, performance, and security goals at inference time. His interdisciplinary approach combines operating systems, computer architecture, control theory, and machine learning. Analysis of Hoffmann's recent publications reveals a clear trajectory toward increasingly sophisticated applications of self-aware computing principles. His work has evolved from foundational resource management to cutting-edge applications in AI/ML systems, quantum computing, and security. The publications demonstrate a consistent theme of using control theory and machine learning to create adaptive systems that optimize multiple competing objectives like performance, energy efficiency, and reliability. Recent papers show expanding applications into large language models, quantum algorithms, and privacy-preserving techniques. Presidential Early Career Award for Scientists and Engineers (PECASE) 2019 DOE Early Career Award 2015 Samsung Security Hall of Fame recognition IEEE Micro Top Picks Honorable Mention awards FSE Test of Time Honorable Mention ASPLOS Hall of Fame recognition Hoffmann has mentored numerous PhD and Master's students who have gone on to successful careers in academia and industry. His research has secured over $19 million in funding for the University of Chicago. He co-founded Config Dynamics in 2019 to commercialize aspects of his self-aware computing research. His work has practical applications across data centers, edge computing, AI systems, and quantum computing. Hoffmann leads the SEEC (Self-aware, Energy-Efficient Computing) research group at the University of Chicago. The group focuses on developing frameworks and techniques for building self-aware computing systems that can dynamically adapt to changing conditions and requirements. The group maintains strong collaborations with industry partners and other academic institutions, particularly in the areas of quantum computing, AI systems, and energy-efficient computing.