جست‌وجوی استاد و پژوهشگر

Guy-Vincent Jourdanمشاهده پروفایل

استاد

• Software Security
• Cybersecurity
• Distributed Systems
• +۶ مورد دیگر

Professor Guy-Vincent Jourdan is affiliated with the School of Electrical Engineering and Computer Science at the University of Ottawa. He holds a Ph.D. from Université de Rennes/INRIA (France, 1995) focusing on distributed systems analysis. Prior to academia, he served as CTO and CEO of Decision Academic Graphics, an Ottawa-based firm. His research interests span software security, cybersecurity (including cybercrime prevention), distributed systems modeling, formal methods, mobile applications, and rich internet applications. Specific technical emphases include phishing detection systems, blockchain fraud analysis, and adversarial machine learning. Professor Jourdan has pioneered tools like D-ForenRIA for reconstructing user interactions in Rich Internet Applications and contributed to cybersecurity frameworks such as HEART for log anomaly detection. His work integrates machine learning techniques with domain-specific challenges in network security and software verification. His publications (2023-2025) reflect advancements in AI-driven vulnerability analysis, blockchain fraud detection, and automated phishing detection systems. Notable projects include SV-TrustEval-C for source code vulnerability analysis and Intellitweet for social media threat detection. While no scientific awards are explicitly listed, his prolific publication record and industry-academia transition highlight sustained contributions to computer science and cybersecurity domains.

Xiongfei Wangمشاهده پروفایل

استاد مهمان

• Power Electronics
• Power System Stability
• Data-Driven Control
• +۳ مورد دیگر

Xiongfei Wang is a Visiting Professor at KTH Royal Institute of Technology in Stockholm, Sweden, and a Digital Futures Fellow. He holds academic leadership roles, including Editor-in-Chief of IEEE Transactions on Power Electronics and chairs in IEEE committees. His research focuses on power electronics systems, stability analysis, and data-driven approaches for energy systems. Previously, he served as a Professor at Aalborg University (2009–2022). His work addresses challenges in power system stability, converter dynamics, and renewable integration. He leads projects like 'Machine Learning for Dynamics Analysis of Power Electronic Systems,' aiming to enhance grid resilience through AI-driven methods. Notable awards include IEEE Fellow (2023), Isao Takahashi Award (2022), and multiple best paper awards. Wang collaborates extensively, organizing conferences and editing journals. His research spans power electronics, grid stability, and smart grid technologies, with a focus on practical applications in energy transition.

Di Buمشاهده پروفایل

دانشیار

• FinTech
• Climate Finance
• Household Finance
• +۳ مورد دیگر

Di Bu is an Associate Professor in the Department of Applied Finance at Macquarie University, leading the Macquarie University FinTech and Banking Research Centre. He holds a PhD in Finance from the University of Queensland (2015). His research focuses on FinTech innovations, climate finance, household finance, and behavioral finance, with an emphasis on embedding sustainability into financial systems. He has secured over AUD 4 million in research funding through ARC Linkage and Discovery projects, focusing on AI-driven credit assessments, Open Banking, ESG analytics, and climate resilience. Education PhD in Finance, University of Queensland (2015) Research Interests Di's work explores belief formation in financial decisions, sustainable lending practices, and climate adaptation tools. He pioneers projects such as AI credit scoring systems, behavioral interventions for sustainable investing, and digital platforms for climate resilience. His interdisciplinary approach bridges industry, government, and academia to address financial and environmental challenges. Projects & Funding AUD 4M+ in grants including two ARC Linkage and one ARC Discovery projects Current initiatives: Greenwashing detection, ESG rating divergence analysis, and climate-resilient finance platforms Labs/Teams Director of the FinTech & Banking Research Centre and affiliated with Data Horizons Research Centre and Frontier AI Research Centre at Macquarie University.

Hamid Krimمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Signal Processing
• +۵ مورد دیگر

Hamid Krim is a Professor in the Department of Electrical and Computer Engineering at North Carolina State University. He leads the Vision, Information and Statistical Signal Theories and Applications (VISSTA) group, focusing on statistical signal/image analysis, data science, and machine learning. His prior roles include Research Scientist at MIT’s Laboratory for Information and Decision Systems and Member of Technical Staff at AT&T Bell Labs. He holds a Ph.D. in Electrical Engineering from Northeastern University, and degrees from the University of Washington and University of Southern California. Education: Ph.D., Electrical Engineering, Northeastern University (MA), 1990s Master's, Electrical Engineering, University of Washington Bachelor's, Electrical Engineering, University of Southern California and University of Washington Research Interests: Machine Learning, AI, Signal Processing, Communications, and Control Systems . His work bridges formal mathematical frameworks with applied problems, emphasizing generative AI, adversarial robustness, and subspace-driven data analysis. Recent innovations include Volterra neural networks and expansive synthesis techniques for data generation. Awards & Recognition: 2000 NSF CAREER Award 2008 IEEE Fellow 2019 IEEE SPS Sustained Impact Paper Award Multiple extended research invitations at top institutions globally Grants & Advising: Leads the VISSTA Lab, collaborating on projects like medical algorithm development (e.g., lung wheeze analysis) and hurricane activity prediction. His work spans interdisciplinary applications in healthcare, robotics, and defense systems. Labs & Teams: Director of the VISSTA Lab, fostering research in signal theory and machine intelligence. Collaborates with academia and industry on cutting-edge AI and sensor fusion technologies.

Raphaël Phanمشاهده پروفایل

استاد

• Security
• Cryptography
• Malicious AI
• +۵ مورد دیگر

Prof Raphaël Phan is a Professor and Deputy Head of the School of IT at Monash University Malaysia. His expertise spans security, cryptography, malicious AI, emotion recognition, motion analysis, and generative AI. He has published over 220 papers and led significant projects including privacy-preserving data mining funded by UK MoD and Malaysian government grants exceeding RM4 million. He co-designed the BLAKE hash function (SHA-3 finalist) and has an h-index of 50. Education: PhD in Cryptography (Multimedia University, 2005), MEngSci (2001), BEng (Hons) Computer Engineering (1999). Research focuses on adversarial AI, brain networks, and secure systems. Current projects include Æmbience: emotion-aware virtual assistants using motion magnification. Supervised 15 PhD graduates and 19 current students. Professional affiliations: Chartered Engineer (IET, UK), HEA Fellow, Board of Engineers Malaysia. Recent work emphasizes causal bias detection in micro-expressions, brain tumor detection via advanced YOLOv8, and generative adversarial networks for medical imaging. His work bridges cybersecurity with neuroscience applications.

Carlisle-Martinمشاهده پروفایل

استاد

• Computer Security
• Programming Languages
• Computer Science Education
• +۳ مورد دیگر

Carlisle-Martin is an Associate Department Head and Professor of Practice in the Department of Computer Science & Engineering at Texas A&M University. They also serve as Director of the United States Air Force Academy Center for Cyberspace Research. Their research focuses on computer security, programming languages, and innovative computer science education techniques. Education: Ph.D., Computer Science, Princeton University (1996) B.S., Mathematics and Computer Science, University of Delaware (1991) Research Interests: Malware analysis and detection Cybersecurity frameworks for DNS and network protocols Visual programming tools like RAPTOR for education Ada language modernization and integration Cybersecurity education through CTF competitions Awards: 2016: Meritorious Civilian Service Award (USAF) 2014: SANS Institute Security Award 2009: ACM Distinguished Educator 2008: Colorado Professor of the Year 2007: Arthur S. Flemming Award Advising & Grants: Known for mentoring through cybersecurity initiatives and leading the USAF Academy's cyberspace research programs. No specific grant details listed, but their work aligns with defense and education funding priorities. Labs/Teams: Directs the USAF Academy's Center for Cyberspace Research, focusing on applied cybersecurity solutions and educational outreach.

• Formal Verification
• Software Testing
• Programming Languages
• +۱۲ مورد دیگر

Alastair F. Donaldson is a Professor and Director of Research in the Department of Computing at Imperial College London, where he leads the FastPL research group. His work bridges formal methods, software testing, and programming languages, with a focus on enhancing the reliability of high-performance and parallel software systems. He has held key roles including Director of Research (since 2023) and previously served as Lecturer (2011–2014), Senior Lecturer (2014–2017), and Reader (2017–2020) before being promoted to Professor in 2020. His research interests include formal verification, compiler testing, GPU programming, concurrency, and fuzzing. He has made significant contributions to the verification of GPU kernels, metamorphic testing of graphics drivers, and the development of tools like GPUVerify and GraphicsFuzz. His work combines theoretical rigor with practical impact, demonstrated by the acquisition of his startup GraphicsFuzz by Google in 2018 and his subsequent roles as Senior Software Engineer and Visiting Researcher at Google. His recent publications reflect a sustained focus on compiler and system reliability, with trends in fuzzing, formal specification, and automated testing of complex systems such as WebGPU, CXL cache coherence, and large language models for code generation. His work increasingly integrates empirical validation with formal techniques to uncover subtle bugs in real-world systems. Scientific awards and recognitions include: 2017 BCS Roger Needham Award EPSRC Early Career Fellowship Fellow of the British Computer Society Best Paper awards at EuroSys 2024, MET 2021, IISWC 2019, IWOCL 2019, and ICST 2016 Best Industry Paper at ICST 2024 ACM SIGSOFT Distinguished Paper at ISSTA 2023 ACM SIGPLAN Most Influential OOPSLA Paper Award (2012 paper), awarded in 2022 Best Student Paper at PPoPP 2014 He has advised numerous PhD students and leads a vibrant research group. He has secured significant research funding and collaborates extensively with industry and academia. His service includes leadership roles such as General Chair of PLDI 2020, PC Chair of ECOOP 2019, and Steering Committee Chair of PLDI (2022–2025). He also serves on the advisory board of PACM-PL and on program committees for top venues including POPL, OOPSLA, PLDI, ICSE, and ISSTA. He leads the FastPL research group, which focuses on the design and implementation of programming tools and techniques for reliable software. The group conducts cutting-edge research in compiler testing, formal methods, and high-performance systems, fostering collaboration across academia and industry.

Hyung Jin Changمشاهده پروفایل

دانشیار

• Human-Robot Interaction
• Computer Vision
• Machine Learning/Deep Learning
• +۶ مورد دیگر

Dr. Hyung Jin Chang is an Associate Professor at the School of Computer Science, University of Birmingham, and a Turing Fellow at the Alan Turing Institute. He holds a Ph.D. and B.S. from Seoul National University. His research focuses on human-centered visual learning, particularly in human-robot interaction, with expertise in computer vision, machine learning, and deep learning. He has been involved in organizing conferences like ECCV and ICCV workshops (e.g., VOTS Challenge, HANDS Workshop) and serves on program committees including AAAI and CVPR. His work spans areas like gaze estimation, domain adaptation, 3D pose estimation, and robotic perception for assistive technologies. Key achievements include receiving the Royal Society Research Grant (2019–2020) and Wellcome Trust funding. Notable contributions include frameworks for unsupervised domain adaptation, gaze estimation models (e.g., RT-Gene), and collaborative learning methods for hand-object reconstruction. He has led projects in medical robotics, personalized dressing assistance, and safety-critical systems like driver attention prediction. His 15 most recent articles (2024–2025) emphasize advancements in diffusion models, domain adaptation, 3D reconstruction, gaze-controllable systems, and generative AI for motion and interaction modeling. These reflect a trend toward integrating multimodal data (vision + language) and bridging theoretical foundations with applied robotics. Awards: Royal Society Grant, Wellcome Trust, Turing Fellowship Grants: Active in securing funding for robotics, vision, and healthcare applications He leads the Personal Robotics Lab and collaborates on projects like the VOTS Challenge for visual object tracking. His research bridges academia and real-world applications in healthcare robotics and human-technology interaction.

Caroline Trippelمشاهده پروفایل

استادیار

• Computer Architecture
• Hardware Security
• Formal Methods
• +۵ مورد دیگر

Caroline Trippel is an Assistant Professor in the Departments of Computer Science and Electrical Engineering at Stanford University. Her research focuses on ensuring correctness and security in computer systems through formal methods, with particular emphasis on hardware verification, memory consistency models, and mitigating vulnerabilities like Spectre/Meltdown. She previously worked at Facebook’s FAIR SysML group before joining Stanford. Education: PhD in Computer Science, Princeton University BS in Computer Engineering, Purdue University Her work has influenced the RISC-V ISA memory consistency model and produced tools like CheckMate, which automatically synthesizes hardware exploits for security verification. She explores privacy-preserving ML, ML-driven hardware optimizations (e.g., neural recommendation), and datacenter reliability. Her research has earned awards including the 2020 ACM SIGARCH Dissertation Award and NVIDIA Fellowship. Key contributions include: Formal analysis of RISC-V memory models Exploitation synthesis frameworks (CheckMate) Hardware-software contracts for security Defenses against microarchitectural side-channel attacks Current projects include: VeriCoder: LLM-enhanced RTL code verification Multi-μPATH synthesis for security validation Near-data processing (RecSSD) for recommendation systems

• Wireless Communications
• 6G Technology
• Signal Processing
• +۷ مورد دیگر

Erik G. Larsson is a Professor and Head of the Division for Communication Systems within the Department of Electrical Engineering (ISY) at Linköping University (LiU), Sweden. He joined LiU in September 2007 and has previously held academic and research positions at the Royal Institute of Technology (KTH), University of Florida, George Washington University, and Ericsson Research. Research Interests: Enabling technologies for 6G wireless communication Statistical inference and signal processing Network science and complex networks Decentralized and federated machine learning over networks Physical layer security and privacy Energy-efficient digital signal processing His research group, active in areas like RadioWeaves and massive MIMO, focuses on robust, efficient, and secure wireless connectivity. Recent publications highlight trends in decentralized learning, resource allocation in wireless networks, and the integration of AI into mobile networks, particularly through projects like 'Turning the Air into an AI Computer' funded by the Knut and Alice Wallenberg Foundation. Scientific Awards and Honors: IEEE Signal Processing Magazine Best Column Award (2012, 2014) IEEE ComSoc Stephen O. Rice Prize (2015) IEEE ComSoc Leonard G. Abraham Prize (2017) IEEE ComSoc Best Tutorial Paper Award (2018) IEEE ComSoc Fred W. Ellersick Prize (2019) IEEE SPS Donald G. Fink Overview Paper Award (2023) IEEE Fellow Member, Royal Swedish Academy of Sciences (KVA) Gyllene Moroten Best Teacher Award (2021) Advising and Grants: He has supervised numerous Ph.D. and Licentiate students, many of whom now hold positions at leading industry and academic institutions. His research is currently funded by major organizations including the Knut and Alice Wallenberg Foundation, Swedish Foundation for Strategic Research (SSF), ELLIIT, Security-Link, Swedish Research Council (VR), and EU Horizon 2020 (H2020-SNS-6GTandem). Previous sponsors include VR, KVA, NSF, ORAU, and multiple EU FP7 and H2020 projects (e.g., MAMMOET, REINDEER, 5G-Wireless). Leadership and Service: He has served as Associate Editor for IEEE Transactions on Communications and IEEE Transactions on Signal Processing, chaired technical committees and steering committees in IEEE Signal Processing Society, and held leadership roles in major conferences such as the Asilomar Conference on Signals, Systems and Computers. He was a Visiting Fellow at Princeton University in 2015.

• Artificial Intelligence
• Data Science
• Computational Creativity
• +۲ مورد دیگر

Hannu Toivonen is a Full Professor of Computer Science at the University of Helsinki, affiliated with the Faculty of Science and the Department of Computer Science. He leads the Discovery Research Group and is part of the Helsinki Institute for Information Technology (HIIT) and the Finnish Center for Artificial Intelligence (FCAI). He obtained his PhD in Computer Science from the University of Helsinki in 1996 and has held his professorship since 2002. His research spans Artificial Intelligence , Data Science , Computational Creativity , and Data Mining , with applications in generative art, automated journalism, and bioinformatics. His research focuses on: Developing AI systems for creative tasks (e.g., poetry, music, and art generation) Cross-lingual natural language processing and unsupervised learning Ethical and societal implications of AI in media and labor Analysis of his 15 most recent publications (2021–2025) reveals a strong emphasis on computational creativity and AI-driven content generation , with interdisciplinary applications in digital humanities, journalism, and biology. Trends include ethical AI frameworks, human-AI collaboration, and innovative evaluation methods for generative systems. Scientific Awards & Honors: Knight, First Class, Order of the White Rose of Finland (2019) Best Applied Research Award, IEEE ICDM (1998) Honorary Member of TKO-äly (2010) Member of Finnish Academy of Science and Letters He has supervised over 20 doctoral theses and secured ~7 MEUR in grants (e.g., EU projects: Embeddia , Newseye ). He leads the Discovery Research Group and collaborates with institutions like VUB (Belgium) as a Francqui International Professor (2025).

Pavan Turagaمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Computer Vision
• +۹ مورد دیگر

Pavan Turaga is a Professor and Founding Director of The GAME School at Arizona State University (ASU), with a joint appointment in the School of Electrical, Computer and Energy Engineering (ECEE). They lead transdisciplinary research and education initiatives spanning gaming, esports, AI-enabled media creation, computer vision, and geometric modeling. Ph.D., Electrical Engineering, University of Maryland (2009) B.Tech., Electronics and Communication Engineering, IIT Guwahati (2004) Research focuses on integrating geometry and topology with machine learning , enabling advancements in: Computer vision for human activity recognition Generative AI for immersive media Health analytics and wearable rehabilitation systems AI ethics and pandemic prediction Key publications span CVPR (2023 spotlight paper PolyINR ), DLGC workshop (2023 best paper), and ICML (2019 work on GAN priors). Recent work explores LMMs , 3D human modeling , and AI for pandemic preparedness . Scientific accolades include: ASU Founders' Day Research Excellence (2025) NSF CAREER award (2015) CVPR 2023 Spotlight paper 2024 X-Prize (Rainforest Challenge) Directed research for students like Rajhans Singh and Ankita Shukla, securing grants from NSF , DARPA , and industry partners (Adobe, Google ATAP). Founded the Geometric Media Lab , emphasizing interdisciplinary collaborations with mathematicians, health scientists, and media artists.

Cesla Amarelleمشاهده پروفایل

استاد

• Migration Law
• Human Rights
• Constitutional Law
• +۵ مورد دیگر

Cesla Amarelle serves as Full Professor and Chairholder of Public Law and Migration Law at the University of Neuchâtel's Faculty of Law. Her academic leadership extends to co-directing the Swiss Center for Migration Law (CDM) and contributing to national research initiatives including the National Center of Competence in Research (NCCR) 'On the Move'. She concurrently holds significant public appointments as Chair of the Institute of European Law at the University of Fribourg and Federal Commissioner for Women's Issues, with recent expert designation to the Federal Round Table on signature collection integrity for 2024. Her academic foundation includes a law degree from the University of Lausanne (1996), LL.M. in European and International Economic Law from the University of Fribourg, and doctoral thesis from the University of Lausanne (2004). Her career progression at the University of Neuchâtel spans assistant professor (2009-2014), extraordinary professor (2015-2016), and full professor positions since 2016, complemented by earlier research roles at Swiss National Science Foundation and University of Fribourg. Professor Amarelle's research centers on migration law frameworks, human rights protections in asylum systems, and constitutional dimensions of European integration. Her work critically examines the intersection of migration governance with digital technologies, climate change impacts, and gender equality. Current projects analyze temporary protection regimes, non-refoulement principles in technological contexts, and the evolving relationship between Swiss migration law and European legal frameworks. Her scholarship consistently bridges theoretical legal analysis with practical policy implementation challenges. Her extensive publication record demonstrates evolving focus from foundational migration law codification toward contemporary challenges including digital discrimination, child rights in emergency contexts, and sustainable finance frameworks. Recent scholarship reflects increasing engagement with technological impacts on migration governance and the humanitarian dimensions of temporary protection systems, while maintaining rigorous analysis of constitutional and European law interfaces. Professor Amarelle actively contributes to academic and public discourse through leadership in the Swiss Center for Migration Law and participation in the NCCR 'On the Move' consortium. Her public service includes significant political roles as Vaud State Councilor for Education (2017-2022) and National Councilor (2011-2017), where she chaired key committees on political institutions and finance while representing Swiss higher education interests nationally. She maintains active engagement with professional associations including the Swiss Conference of Higher Education Institutions and Conference of Directors of Public Education.

• Global Navigation Satellite Systems (GNSS)
• Avionics Systems
• Wireless Communication
• +۷ مورد دیگر

René Jr Landry is a full Professor in the Department of Electrical Engineering at École de technologie supérieure (ETS), Université du Québec, specializing in Global Navigation Satellite Systems (GNSS), avionics, and wireless communication technologies. His academic journey includes a B.Ing. from Polytechnique Montréal, M.Sc. from University of Surrey (UK), and Ph.D. from SupAréo in Toulouse. He maintains active research leadership through two key laboratories: LASSENA (Laboratory of Space Technologies, Embedded Systems, Navigation and Avionics) and LACIME (Communications and Microelectronic Integration Laboratory). His research spans critical aerospace navigation domains including GNSS signal processing, inertial navigation systems, software-defined radio for avionics, radio frequency interference mitigation, and indoor positioning technologies. Landry's work addresses real-world challenges in satellite navigation robustness, precision positioning in urban/denied environments, and next-generation avionic system security. His current projects focus on blockchain-enhanced IoT security, AI-driven GNSS disruption analysis, and adaptive RF front-ends for multi-band avionics applications. Analysis of his recent publications reveals strong emphasis on resilient positioning systems through multi-constellation integration (particularly Iridium-NEXT), blockchain applications for navigation security, and explainable AI techniques for GNSS signal quality assessment. His work increasingly bridges traditional navigation engineering with cutting-edge security and machine learning paradigms. 2014 Prix d'excellence du c.a. pour les services à la collectivité Landry has supervised over 100 graduate students across doctoral, master's, and research projects since 2005, with current supervision extending through Summer 2025. His research funding supports multiple industry partnerships focused on avionics certification, software-defined radio implementations, and next-generation navigation systems. The LASSENA laboratory under his leadership develops certified avionic products from open-source SDR platforms and advances multi-sensor fusion techniques for challenging navigation environments. His research infrastructure includes specialized facilities for GNSS signal simulation, avionics hardware testing, and multi-sensor integration. Current work emphasizes flight-tested validation of RF front-end technologies, blockchain-secured navigation data, and real-time interference mitigation systems for aviation applications.

Mehrdad Nojoumianمشاهده پروفایل

دانشیار

• Security
• Privacy
• Trust
• +۱۰ مورد دیگر

Mehrdad Nojoumian is an Associate Professor at Florida Atlantic University's College of Engineering and Computer Science, specializing in Security, Privacy, Trust, and Human-Autonomy Interaction. His research bridges computer science with FinTech and autonomous systems, focusing on cryptographic protocols, blockchain, and IoT security. PhD, University of Waterloo (Computer Science, 2012) MSc, University of Ottawa (Computer Science, 2007) BSc, Islamic Azad University (Computer Engineering, 2002) His research explores privacy-preserving mechanisms in autonomous systems, trust modeling in blockchain, and cross-disciplinary applications of cryptography. Recent work includes patents on adaptive driving modes and ongoing studies on IoT vulnerabilities and autonomous coordination. Notable awards include the Excellence and Innovation in Undergraduate Teaching Award (2023), NAI Induction (2022), and multiple Best Paper Awards . His publications span journals like Information and Computation and conferences such as GameSec and IEEE Blockchain . He mentors graduate students in cybersecurity bootcamps, high school outreach programs, and collaborative research projects funded by NSF , ARO-AFOSR , and AFRL . His lab emphasizes diversity and inclusion, particularly supporting underrepresented groups in STEM.