جست‌وجوی استاد و پژوهشگر

• Data Compression
• Medical Image Processing
• Cryptography
• +۵ مورد دیگر

Huseyin Kocak is a Professor at the University of Miami in the College of Arts and Sciences with a joint appointment in Mathematics and Computer Science. His scholarly work bridges theoretical mathematics with practical applications in data compression and security, establishing him as a significant contributor to both computational mathematics and applied computer science. Dr. Kocak's research program encompasses several interconnected domains of computational science: Advanced data compression techniques for medical imaging and color photography Integration of encryption protocols within compression algorithms Mathematical modeling of dynamical systems and chaos phenomena Development of specialized algorithms for medical diagnostics and genomic analysis Theoretical foundations of differential and difference equations with biological applications Analysis of Dr. Kocak's publication trajectory reveals a strategic evolution from fundamental mathematical research toward increasingly applied computational techniques. His early work focused on rigorous theoretical problems in dynamical systems, particularly homoclinic orbits in differential equations as evidenced by his 2021 publication on Shilnikov Saddle-Focus Homoclinic Orbits. More recently, his research has centered on solving critical healthcare challenges through innovative computational approaches, with his 2025 paper addressing FDA compliance requirements for medical image compression. His most significant contribution appears to be the development of BWIC (Burrows-Wheeler Inversion Coder), which demonstrates superior performance compared to industry standards like JPEG 2000 across multiple image types, particularly for medical applications where data integrity is paramount. Dr. Kocak's scholarly impact extends beyond pure compression research through his innovative work combining security with compression efficiency. His concurrent encryption approach, which uses the inversion frequency vector as a secure key, represents a paradigm shift in how data security is implemented within compression pipelines, offering substantial computational savings while maintaining robust security.

• Embedded Systems
• Fault Tolerance
• Precision Agriculture
• +۵ مورد دیگر

Maurizio Rebaudengo is a Full Professor at the Department of Control and Computer Science (DAUIN) of the Polytechnic University of Turin. He is a member of the PIC4SeR Interdepartmental Center for Service Robotics and holds expertise in embedded systems, fault tolerance, and sensor network applications. Research Interests: Embedded systems, fault tolerance, precision agriculture, RFID technology, wireless sensor networks, and system dependability Scientific Awards: Ramamoorthy Best Paper Award (1997) Leadership Roles: Program Chair for the 4th International EURASIP Workshop on RFID, Committee Member for Public Administration Agreements (2020-2024) Projects: Scientific Director for HONEY (Hybrid ONline tEchnologY for particle therapy), FDM (Food Digital Monitoring), IDEM (Internet of Data for Environmental Monitoring), and OPLON (Healthy Longevity Opportunities). Teaching: Course lecturer for Electronic Calculators, Computer Science, Systems Programming, and Cybersecurity at both undergraduate and postgraduate levels. His work spans IoT applications in agriculture and healthcare, focusing on low-cost sensor networks , RFID-based traceability , and cyber-physical system resilience . Recent publications emphasize particulate matter monitoring and secure communication protocols in wireless environments.

Bartolomeo Montrucchioمشاهده پروفایل

استاد

• Computer Vision
• Quantum Computing
• Image Processing
• +۵ مورد دیگر

Bartolomeo Montrucchio is a Full Professor of Information Processing Systems (ING-INF/05) at the Department of Control and Computer Engineering (DAUIN) of the Polytechnic University of Turin. He is a member of the Interdepartmental Center Photonext - PoliTo Interdepartmental Center on Applied Photonics and serves as deputy director at the Interuniversity Center of Regional Interest for the Training of Secondary School Teachers (CIFIS) since July 2012. Additionally, he has held an adjunct professor position at the University of Illinois at Chicago during July 2008. Professor Montrucchio's research spans several cutting-edge areas with a primary focus on quantum computing, computer vision, and sensor networks. His work encompasses image processing, scientific visualization, parallel and distributed systems, and wireless sensor networks. He actively contributes to European research initiatives including the EQUO (European QUantum ecOsystems) project as Scientific Responsible. His research bridges theoretical computer science with practical applications across multiple industries. His publication record shows a strong trajectory toward quantum technologies, with numerous recent publications focusing on quantum machine learning, quantum algorithms for financial applications, and quantum applications in cybersecurity. His work demonstrates increasing emphasis on practical implementations of quantum computing in real-world scenarios, particularly in industrial settings and telecommunications. Best student paper award at BIOSIGNAL2002, conferred by EURASIP, Italy (2002) Associate Editor of IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2019-present) Professor Montrucchio actively supervises numerous PhD students working on quantum computing applications across various domains including finance, cybersecurity, traffic optimization, and industrial use cases. His teaching portfolio includes courses on Quantum Computing, Parallel and Distributed Computing, and Image Processing and Computer Vision across multiple degree programs including Computer Engineering, Biomedical Engineering, and Quantum Engineering. He leads multiple research projects funded by both competitive calls and commercial contracts, with a significant focus on quantum technologies since 2019. His patent portfolio includes several inventions related to tire manufacturing processes and visual rehabilitation for telemedicine.

Armin Alaghiمشاهده پروفایل

استادیار

• Embedded Systems
• Digital Circuits
• Mathematics
• +۷ مورد دیگر

Armin Alaghi serves as a Research Scientist at Oculus Research (Redmond, WA) and holds an Affiliate Assistant Professor position at the University of Washington. His dual affiliation enables valuable knowledge transfer between cutting-edge industrial research and academic pursuits in computer systems engineering. Dr. Alaghi's research spans the intersection of embedded systems, digital circuits, and mathematics. His primary focus involves building low-power augmented reality (AR) and virtual reality (VR) systems while developing novel computation methods for unreliable beyond-CMOS technologies. His previous research contributions include significant work in stochastic computing (where he developed the STRAUSS synthesis methodology), reliable Network on chip (NoC) design, FPGA testing methodologies, NoC testing techniques, artificial neural networks implementations, asynchronous circuit design, and multi-valued logic systems. He has made his spectral-transform-based synthesis tool publicly available on GitHub, demonstrating commitment to open research. Analysis of Dr. Alaghi's publication record reveals a clear research trajectory from foundational circuit-level work toward practical applications in AR/VR systems. His publications from 2020-2025 demonstrate expertise spanning computer architecture, security for immersive technologies, neural network compression techniques, and homomorphic encryption methods. A recurring theme throughout his work is the exploration of quality-energy tradeoffs and error-resilient computing approaches, with increasing focus on security aspects of AR/VR systems in his most recent work. Dr. Alaghi maintains active connections with the broader research community, as evidenced by his Erdős number of 3 (Armin Alaghi John P. Hayes Frank Harary Paul Erdős) and his ongoing contributions to open-source research tools. His GitHub repository for stochastic computing synthesis shows community engagement with multiple contributors. At Oculus Research, Dr. Alaghi applies his theoretical expertise to practical challenges in next-generation AR/VR system development. His work bridges academic research with real-world product development, particularly in addressing energy efficiency challenges for wearable computing platforms through innovative circuit design approaches.

Eric Howardمشاهده پروفایل

پژوهشگر ارشد

• Quantum Physics
• Machine Learning
• Gravitational Waves
• +۴ مورد دیگر

Dr. Eric Howard is a Research Fellow at Macquarie University , affiliated with the School of Engineering , School of Mathematical and Physical Sciences , and School of Computing . His research spans interdisciplinary domains at the intersection of quantum physics, machine learning, and AI-driven systems. Key research themes include: Quantum cryptography for Industry 4.0 security Machine learning in IoT temperature sensing Adversarial AI in cybersecurity 6G wireless communication optimization Quantum information processing Deep learning for data imputation Recent publications demonstrate a focus on emerging technologies, with articles on quantum Bayesian inference , 6G signal processing , and smart city IoT systems . His collaborative work extends to blockchain-enabled supply chain visibility and generative AI applications in programming. Research collaborations span institutions in India (AIP Publishing) and Australia, with technical contributions to quantum dynamics, neural network applications, and nanosensor development.

Ünal ÇAVUŞOĞLUمشاهده پروفایل

دانشیار

• Cybersecurity
• Network Security
• Intrusion Detection Systems
• +۶ مورد دیگر

Prof. Dr. Ünal Çavuşoğlu is an Associate Professor at the Department of Software Engineering, Faculty of Computer and Information Sciences, Sakarya University. With a doctorate in chaos-based encryption algorithms (2016) and a master's degree comparing network simulation tools (2014), his research focuses on cybersecurity, machine learning, and chaos theory. He has contributed extensively to intrusion detection systems, IoT security, and cryptographic protocols. Education: Doctorate (2016), Master's (2014), and Bachelor's (2011) in Computer Engineering. Research Interests: Cybersecurity frameworks, machine learning adaptation for threat detection, chaotic encryption, and IoT communication protocols. Recent Work: 2025 publications on homomorphic encryption and LSTM-based intrusion detection demonstrate cutting-edge applications of deep learning in security domains. His 2019-2024 publications reveal a trajectory from foundational chaos theory to applied IoT and cloud security solutions. Key methodologies include genetic algorithms, fractional calculus, and hybrid encryption systems.

• Biometrics
• Digital forensics
• Face recognition
• +۷ مورد دیگر

Christoph Busch is Professor at the Department of Information Security and Communication Technology , Norwegian University of Science and Technology (NTNU), Gjøvik, Norway. He leads research on trustworthy biometric systems, digital forensics, and privacy-preserving technologies. His research spans biometrics , face recognition , presentation-attack detection , synthetic-data generation , homomorphic encryption , and deepfake detection . Recent work focuses on morphing-attack detection, fairness-aware quality assessment, and secure template protection. He employs deep learning, vision transformers, and cryptographic techniques to build robust, privacy-centric identity systems. Professor Busch has co-authored over 60 peer-reviewed articles (2020-2025) in leading venues such as Nature Reviews Electrical Engineering , IEEE Transactions on Information Forensics and Security , IEEE Access , and Applied Cognitive Psychology . A clear trend is the integration of synthetic data to improve generalisation and fairness, alongside advancing attack-detection capabilities against morphing and deepfake threats. He serves on editorial boards and conference organising committees, including BIOSIG and IET Biometrics, and is actively involved in European biometrics policy discussions. He mentors a growing team of doctoral and master’s researchers working on next-generation secure identity technologies.

Corey Clarkمشاهده پروفایل

استادیار

• Artificial Intelligence
• Game Development
• Human Computation
• +۴ مورد دیگر

Corey Clark, Ph.D., serves as Deputy Director of Research and Assistant Professor in the Department of Computer Science and Engineering at Southern Methodist University's Lyle School of Engineering. He leads the Human and Machine Intelligence (HuMIn) Game Lab, pioneering research at the intersection of gaming, artificial intelligence, and human computation to solve large-scale problems in healthcare, education, and national security. Dr. Clark holds a Ph.D., M.S., and B.S. in Electrical Engineering from The University of Texas at Arlington, where he graduated Magna Cum Laude for his undergraduate degree. His doctoral research focused on nanoscale modeling and simulation techniques for Molecular Beam Epitaxy and Chemical Vapor Deposition of exotic materials. His research spans Artificial Intelligence, Game Development, Human Computation, Distributed Computing, Machine Learning, Computational Biology, and Educational Technology. Clark is renowned for transforming commercial video games into distributed computing platforms through human computation, enabling breakthroughs in medical diagnostics and educational technology. His technical innovations in HTML5/JavaScript multithreading have been featured at major international game conferences. Analysis of Clark's 15 most recent publications (2022-2024) reveals a dominant focus on generative AI applications integrated with gaming mechanics, particularly for knowledge graph enhancement, medical diagnostics, and computational thinking education. Key trends include explainable AI systems, human-AI collaboration through gameplay, blockchain applications, and privacy-preserving machine learning, demonstrating consistent innovation in applying game-based approaches to real-world problems. Dr. Clark has secured over $1.7 million in competitive research funding, including: Human Computation for Ocular Tomography Analysis ($62,924) with Retina Foundation Cryptocurrency Transactional Analysis via Gaming ($60,000) with Raytheon Game-Based Adult Literacy (XPrize) ($480,000) Flexible Electronics for Airborne Laser ($820,000) with Missile Defense Agency Networked C4ISR Chip ($850,000) with US Army As CTO for Dallas-based game technology companies, Clark has helped raise over $12 million in startup funding. His HuMIn Game Lab currently develops immersive gameplay systems for cancer treatment research using crowdsourced computation and machine learning, with recent projects including therapeutic discovery platforms and blockchain-based task completion systems.

• Digital Signal Processing
• Cryptography
• System Identification
• +۳ مورد دیگر

Kazys Kazlauskas is an Affiliated Scientist at the Image and Signal Analysis Group of the Vilnius University Institute of Data Science and Digital Technologies . His research focuses on Digital Signal Processing , Cryptography , and System Identification , with significant contributions to spectrum estimation , deadzone compensation , and key-dependent S-box generation in encryption systems. Research Trends : His work spans Wiener systems , nonlinear modeling , frequency analysis , and noise reduction , particularly in block cipher systems and adaptive control . Collaborations : Frequent collaborator with Rimantas Pupeikis , Gytis Vaicekauskas , and Robert Smalius , especially in cryptography and signal processing applications. Grants & Projects : No explicit grants are listed, but his involvement in publications suggests participation in institutional research initiatives at Vilnius University.

Lisovenko Iryna Dmytrivnaمشاهده پروفایل

استادیار

• Parallel and Distributed Computing
• GPU Computing
• Automatic Program Parallelization
• +۳ مورد دیگر

Lisovenko Iryna Dmytrivna serves as Assistant Professor in the Department of Computer Systems and Networks at Yuriy Fedkovych Chernivtsi National University since 2002, following her 2000 diploma in Computer Systems and Networks from the same institution. Her professional trajectory includes software engineering at a municipal medical institution (2000–2002) and ongoing contractual collaboration with Elogic Commerce since 2018. Her academic credentials include: Yuriy Fedkovych Chernivtsi State University, Faculty of Physics, Department of Computer Science, specialty "Computer Systems and Networks" (2000) Dr. Lisovenko's research centers on parallel and distributed computing, emphasizing automatic parallelization techniques, GPU-accelerated non-graphical computing, and structural analysis of program intermediate representations. She concurrently investigates specialized computer systems for data stream processing and develops methodologies for enterprise accounting automation, bridging theoretical computer science with business process optimization. Her scholarly output demonstrates sustained innovation in high-performance computing architectures. Analysis of her 15 most recent publications (2012–2021) reveals three dominant research thrusts: GPU-based parallelization (40% of works, including Kalyna encryption and bitonic sorting implementations), algorithmic optimization for diverse hardware (33%, covering sorting networks and structural matrices), and applied systems for real-world problems (27%, spanning smart home control, social media analysis, and enterprise automation). This evolution reflects increasing focus on practical GPU applications while maintaining core expertise in parallel algorithm design. She actively contributes to academic development through teaching Parallel and Distributed Computing, Economic and Legal Aspects of Enterprise Automation, and DevOps/DevNet courses, while authoring 12+ methodological manuals including "Parallel and Distributed Computing: Laboratory Workshop" (2022) and "System Administration of Linux OS" (2021). Her professional development includes certifications in Constitutional Law, Finance and Investment, DevNet Associate, and All Digital Week initiatives (2020–2021).

• Computer Science
• Cybersecurity
• Network Security
• +۷ مورد دیگر

Sencun Zhu is an Associate Professor in the Department of Computer Science and Engineering, specializing in cybersecurity, network security, and privacy-preserving technologies. With over 183 research outputs and an h-index of 51, Zhu's work spans wireless sensor networks, Android security, federated learning, and intrusion detection systems. Key Research Areas: Cybersecurity, wireless sensor networks, adversarial machine learning, privacy-preserving analytics, and Android vulnerability detection. Projects: Led multiple NSF-funded initiatives including "Combating Worm Propagation in Emergent Networks" (2007-2013), "Obfuscation-Resilient Software Plagiarism Detection" (2013-2017), and "Reputation-Escalation-as-a-Service" (2016-2020). Recent Trends: Focus on backdoor attacks in AI models, edge computing privacy solutions, and honeypot technologies leveraging large language models. Collaborations: Active in cybersecurity and sensor networks, with partnerships across academia and industry.

Sanaul Hoqueمشاهده پروفایل

مدرس ارشد

• Computer Vision
• Biometrics
• Security Systems
• +۶ مورد دیگر

Dr. Sanaul Hoque is a Senior Lecturer in Secure Systems Engineering at the University of Kent's School of Engineering and Digital Arts, where he also serves as Course Lead for Electronic and Computer Engineering. His research focuses on biometric security systems, computer vision, and pattern recognition applications with over 79 publications documented in the Kent Academic Repository. Dr. Hoque's primary research interests include: Computer Vision and Pattern Recognition Biometrics and Security Systems Document Analysis and Modeling Encryption and Secure Systems Multi-Expert Fusion Techniques EEG-based Biometric Recognition His extensive publication record spanning over two decades demonstrates expertise in developing innovative biometric security solutions. Recent work focuses on neural network applications for security systems, explainable presentation attack detection, and EEG-based biometric recognition. His research shows a consistent trajectory toward more sophisticated and explainable biometric security systems that address real-world challenges in authentication and identification, with his most recent publication appearing in 2025. Dr. Hoque has maintained productive research collaborations with colleagues including Farzin Deravi, Konstantinos Sirlantzis, and Gareth Howells, resulting in numerous co-authored publications across various domains of biometric security. His work has appeared in reputable journals including Sensors, IEEE Access, and Pattern Analysis and Applications. As Course Lead for Electronic and Computer Engineering, Dr. Hoque plays a significant role in curriculum development and student mentorship within the engineering program at Kent. His expertise bridges theoretical computer science with practical security applications, particularly in biometric systems and secure document modeling.

Oh Jin Kwonمشاهده پروفایل

استاد

• Image Processing
• Image Coding
• Digital Watermarking
• +۷ مورد دیگر

Professor Oh Jin Kwon is a faculty member in the Department of Electronic Engineering at Sejong University since 1999. His research focuses on image/video analysis, compression algorithms, image quality enhancement, fusion techniques, watermarking, and steganography. He has developed patented algorithms for region adaptive image coding, image watermarking, backward compatible HDR image coding, and progressive image coding. Education: Ph.D. in Electrical and Computer Engineering from University of Maryland, College Park (1994) M.S. in Electrical Engineering from University of Southern California, Los Angeles (1991) B.S. in Electronic Engineering from Hanyang University, Seoul (1984) His extensive research includes image processing , watermarking , and cyber resilience . Recent publications explore deep learning applications in cybersecurity , image coding standards , and 360-degree imaging . His work has been published in Electronics (Switzerland) , Applied Sciences (Switzerland) , Drones , and other journals. Scientific Awards & Grants NSF Grant 91-00655 DACA 76-92-C-0079 DACA 76-89-C-0019 DACA 76-92-C-0009 Professor Kwon has advised numerous PhD and MS students in areas like Point Cloud Coding , JPEG Privacy & Security , and AI-based image coding . He leads research projects funded by institutions including the Korea Aerospace Research Institute and Electronics and Telecommunications Research Institute . His laboratory, the Video Communication Research Lab , focuses on JPEG systems standards , image security , and smart store technologies . Current research includes operator-friendly interface technology for unmanned vehicles and composite material cultural heritage data encryption.

• Computer Graphics
• VR/AR/MR
• Physics-Based Animation
• +۷ مورد دیگر

Oh-Young Song is a Professor in the Department of Software at Sejong University's Ocean Humanities College, where he has been a faculty member since 2006. He also serves as a Researcher at the eXtended Reality Research Center and directs the Sejong University Graphics Lab, which focuses on natural phenomena simulation and related applications in special effects and animation. Sejong University, Department of Software (2006-present) Adobe Systems, Visiting Professor (2013-2014) Seoul National University, Automation and Systems Research Institute (2004-2006) Song earned his educational credentials from Seoul National University: B.S. (1998), M.S. (2000), and Ph.D. (2004), all in Electrical Engineering and Computer Science. His research spans computer graphics, VR/AR/MR, physics-based animation, fluid simulation, and deep learning . His work bridges theoretical computer graphics with practical applications in healthcare, IoT, and special effects. Song has developed physics-based animation techniques used in movies and games, with particular expertise in fluid simulation where he holds a US patent for simulating detailed fluid movements using derivative particles. His recent research increasingly integrates AI and deep learning approaches with traditional computer graphics techniques. Analysis of his 15 most recent publications (2021-2024) reveals a strategic expansion of his research into healthcare applications, with significant work in medical image analysis, gastrointestinal disease detection, and secure patient data transmission. His research shows strong interdisciplinary collaboration, particularly between computer graphics and medical informatics, with consistent publication in high-impact journals across computer science and healthcare domains. Song's scholarly achievements include 49 research outputs with 1922 citations and an h-index of 20. His most notable scientific achievement is the US-patented technique for simulating detailed fluid movements using derivative particles, with related papers published in ACM Transactions on Graphics. US Patent for Method of Simulating detailed movements of fluids using derivative particles 49 research publications across computer graphics, VR/AR, and medical AI domains 1922 total citations with h-index of 20 As an educator, Song teaches courses including Advanced Computer Graphics, Algorithms and Practice, and Physics Coding for General Public. He advises graduate students through Master's thesis research and Graduation Research and Career courses. His lab, the Sejong University Graphics Lab, actively collaborates with industry on physics-based animation techniques for special effects and animation in movies and games. Current research directions indicate growing emphasis on integrating extended reality technologies with healthcare applications, particularly in medical simulation and diagnostic support systems.

• Physics-Based Animation
• Character Animation
• Computer Graphics
• +۷ مورد دیگر

Professor Song Oh-young is affiliated with Sejong University as a faculty member in the Ocean Humanity College , Department of Software . He leads the Sejong University Graphics Lab , which focuses on physics-based animation for movies/games and natural phenomena simulation. PhD in Computer Science from Seoul National University (2004) Postdoctoral Fellow at Seoul National University (2004-2006) Current research spans Computer Graphics , Medical AI , IoT Security , and Deep Learning Applications in healthcare and agriculture. His recent publications (2023-2024) emphasize AR/VR for emergency training , medical imaging , and IoT optimization . The Graphics Lab actively collaborates with industry on special effects and simulation techniques. He has contributed to 3D graphics , chaotic encryption , and real-time fluid dynamics over two decades.