جست‌وجوی استاد و پژوهشگر

Esfandiar Mohammadiمشاهده پروفایل

دانشیار

• Privacy & security in machine learning
• Differential privacy
• Anonymous communication
• +۱ مورد دیگر

Esfandiar Mohammadi is an Associate Professor at the Institute for IT Security, University of Lübeck, leading the Privacy & Security (PrivSec) group and directing the AnoMed competence cluster. He has held tenured faculty positions since 2019 after postdoctoral research at ETH Zürich (2016-2019) and a PhD at Saarland University (2015). University of Lübeck (2015-present) ETH Zürich (2016-2019) Saarland University (2015) His research focuses on privacy-preserving technologies in machine learning, anonymous communication protocols, and formal verification of security properties. Recent work includes advancements in Mixnet scalability and federated learning with differential privacy guarantees. Key publication trends reveal a strong emphasis on privacy-preserving algorithms for machine learning (2024), cryptographic protocols for anonymous communication (2025), and security analysis of decentralized systems (2023-2025). Collaborations span institutions like ETH Zürich, Saarland University, and industry partners EnergieDock/NAECO Blue for the VeDS project. His group includes 11 researchers (5 PhD students) and software engineers working on topics like Differential Privacy Secure Multi-Party Computation Trusted Execution Environments

• Computer Networks
• Unmanned Aerial Vehicles (UAVs)
• Semantic Communication
• +۱۲ مورد دیگر

Gökhan Seçinti is an Assistant Professor in the Department of Computer Engineering at Istanbul Technical University, Faculty of Computer and Informatics. He currently serves as Vice Dean and has previously held the role of Vice Department Head. His research focuses on next-generation wireless networks, UAV communications, semantic communication, and AI-driven networking solutions. Research Interests: His work spans Unmanned Aerial Vehicles (UAVs) , Semantic and Task-Oriented Communication , Software-Defined and Cognitive Networks , 6G Communications , and AI in Networking . He develops practical testbeds for deep learning-based communication architectures and explores digital twin applications in aerial networks. Publication Trends: Recent publications emphasize decentralized UAV service deployment, beam alignment using UWB localization, TDMA scheduling for aerial swarms, and semantic flow control. These reflect a strong trend toward intelligent, adaptive, and context-aware communication systems for IoT and mobility. Best Paper Award, IEEE, 2022 Best Conference Paper, IEEE, 2016 Best Poster Paper Award, IEEE, 2015 Advising and Grants: He has supervised 4 academic works and leads multiple funded research projects, including TÜBİTAK and SRP grants on federated learning in flying networks, semantic VANETs, AI-based intrusion detection, and UAV-assisted IoT for crisis management. Labs and Teams: His work is supported by active research teams at ITU, focusing on testbed development using SDRs, digital twins, and real-world deployment of UAV networks. He collaborates internationally, including past affiliations with Northeastern University.

Ajay Kapurمشاهده پروفایل

استاد

• Human-Computer Interaction
• Artificial Intelligence in Music
• Mechatronic Musical Instruments
• +۵ مورد دیگر

Ajay Kapur serves as Associate Provost for Creative Technologies and Director of the Music Technology program (MTIID) at California Institute of the Arts. With an interdisciplinary background spanning computer science, electrical engineering, and music, he bridges technological innovation with artistic expression through leadership in academic programs and entrepreneurial ventures. His research centers on symbiotic human-machine interaction for artistic creation, particularly exploring computer improvisation with humans through Indian Classical music frameworks. This manifests in developing programmable mechatronic instruments, sensor-based interfaces, and AI-driven systems for musical expression. His work extends traditional techniques while creating new performance paradigms like the globally touring Machine Orchestra and KarmetiK Orchestra. Kapur's recent publications reveal evolving expertise from music robotics to blockchain applications, with significant focus on NFT systems, tokenization, and immersive environments. His scholarly output demonstrates consistent innovation at the intersection of artistic practice and emerging technologies. As an educator and entrepreneur, he has co-founded companies in edtech and AI while authoring foundational texts like Digitizing North Indian Music and Introduction to Programming for Musicians and Digital Artists . His performances at venues including LACMA, Singapore Arts Festival, and the 2010 Winter Olympics showcase practical applications of his research.

Craig A. Chinمشاهده پروفایل

دانشیار

• Digital Signal Processing
• Machine Learning
• Biomedical Signal/Image Processing
• +۷ مورد دیگر

Craig A. Chin is an Associate Professor in the Department of Electrical Engineering at Kennesaw State University. He holds a Ph.D. and M.S. in Electrical Engineering from Florida International University (2006, 2001) and a B.S. in Electrical and Computer Engineering from the University of the West Indies (1995). Research Interests: Digital Signal Processing for Biomedical Applications Machine Learning in Biomedical Signal/Image Analysis Wireless Body Area Networks (WBANs) for Healthcare Network Security in Resource-Constrained Environments Biometric Authentication for Wireless Sensor Networks Innovations in Engineering Education (Cooperative/Active Learning, Humanities Integration) Article Trends: His publications (2001–2019) focus on Biomedical Signal Processing (EMG/Eye-Gaze Integration, Stress Detection), WBANs for mHealth , and Engineering Education Pedagogy . Recent work (2013–2019) emphasizes Cooperative Learning Strategies and Wireshark-based Network Security Labs . Academic Contributions: Craig has taught courses such as Biometrics, Data Communications, Biomedical Instrumentation, and Medical Electronics. He actively explores future research on biometric-driven security for Body Area Sensor Networks and active learning strategies in online education.

Brandon F. De Bruhlمشاهده پروفایل

استاد

• Artificial Intelligence
• Emerging Technologies
• Big Data
• +۵ مورد دیگر

Brandon F. De Bruhl is a Senior Technical Analyst at RAND Corporation and Professor of Policy Analysis at the RAND School of Public Policy. He previously served as a Senior Policy Analyst at the Office of Management and Budget (OMB) and taught at Loyola Marymount University (LMU). His research focuses on the societal impacts of emerging technologies, particularly artificial intelligence (AI), cryptocurrencies, and big data, in contexts of public finance and national security. He holds a B.A. in Political Economics from Seattle University, an M.A. in International Relations from Syracuse University’s Maxwell School, and an M.P.P. from the USC Sol Price School, where he is pursuing a Ph.D. in Public Policy and Management. De Bruhl’s work bridges technology, policy, and security. His research explores how AI and biotechnologies reshape conflict scenarios, military strategies, and public sector operations. Notable themes in his publications include the mitigation of human bias in military intelligence, the sustainability of veteran employment programs, and the application of 5G-era technologies for defense. His interdisciplinary approach integrates technical, ethical, and organizational dimensions of technology adoption. Education: B.A., Political Economics, Seattle University M.A., International Relations, Maxwell School, Syracuse University M.P.P., USC Sol Price School (currently pursuing Ph.D.) Key Research Contributions: His work on AI project failures offers actionable frameworks for avoiding technical and organizational pitfalls. He advocates for stronger public-private partnerships to support veterans and emphasizes the dual-use challenges of biotechnologies in warfare. Advising & Grants: While no formal advisees are listed, his academic role suggests mentorship of graduate students. His research has been supported by federal agencies, though specific grants are not detailed in the text.

Fendy Santosoمشاهده پروفایل

پژوهشگر

• Cybersecurity
• Artificial Intelligence
• Autonomous Systems
• +۱۲ مورد دیگر

Dr. Fendy Santoso is a leading researcher and Cyber-Physical Lead at the Artificial Intelligence and Cyber Futures Institute, Charles Sturt University, Australia. He also holds a Visiting Fellow position at the School of Engineering and Technology, UNSW Canberra, and has held visiting roles at the University of Cambridge and Cranfield University. His work bridges cybersecurity, AI, and autonomous systems, with significant impact in UAV security and cyber-physical resilience. Education: PhD in Electrical Engineering, University of New South Wales (Awarded: 21 Jun 2012) Master of Electrical and Computer Systems Engineering, Monash University (Awarded: 07 Jun 2007) Dr. Santoso’s research focuses on adversarial machine learning, UAV security, intrusion detection in robotic systems, and cyber-secure digital twins. His work integrates AI, control theory, and cybersecurity to enhance the resilience of autonomous systems. He has pioneered research in securing ROS-based platforms and defending against GPS spoofing and DoS attacks in unmanned vehicles. His recent publications (2020–2025) highlight a strong trend in applying deep learning, fuzzy logic, and physics-informed models to detect and mitigate cyberattacks in UAVs and UGVs. Key themes include intrusion detection systems, secure digital twins for agriculture, and intelligent transportation systems enabled by drones. His work is frequently published in IEEE Transactions and top-tier conferences. Scientific Awards and Grants: Vice-Chancellor’s Distinguished Early Career Travel Fellowship, University of Wollongong (2019) ARC Linkage Project Grant (LP230100083) on adversarial machine learning for UAVs (2024) CSIRO-funded AgriTwins project on cyber-secure digital twins for agriculture (2024) Dr. Santoso has secured over AUD 3 million in competitive research funding and actively supervises postgraduate students. He serves as a reviewer for the Australian Research Council and technical program committees of major AI and engineering conferences. His collaborative work spans defence organisations like DSTG and the U.S. Army Ground Vehicle Systems Centre, as well as international academic institutions. He is a Senior Member of IEEE and leads research in labs focused on cyber-physical systems, autonomous robotics, and AI-driven security frameworks. His team develops real-time detection tools for cyberattacks on military and agricultural robots, contributing to critical infrastructure resilience.

Naveen Naik Sapavathمشاهده پروفایل

عضو هیئت علمی

• 5G/Next-G Cellular Networks
• Open Radio Access Network (O-RAN) Architecture and Security
• AI/ML for Wireless Resource Optimization
• +۵ مورد دیگر

Naveen Naik Sapavath is an Assistant Teaching Professor at Northeastern University's Electrical and Computer Engineering department. He holds a PhD from Howard University and a Master's from the Indian Institute of Science (IISc). His research focuses on next-generation cellular systems including O-RAN security, AI/ML-driven wireless optimization, and low-latency communications. He is affiliated with Northeastern's Institute for the Wireless Internet of Things. Education: PhD in Electrical and Computer Engineering, Howard University Master of Engineering in Electrical Engineering, Indian Institute of Science Research Interests: Dr. Sapavath explores cutting-edge areas such as 5G/Next-G networks, cybersecurity in wireless systems, and applying game theory to resource allocation. His work bridges theoretical advancements with practical implementations in AI-driven network architectures. Awards: IEEE CSCloud 2021 Best Student Paper Award Multiple NSF Student Travel Grants Professional Experience: Previously served as Postdoctoral Researcher at UC Davis, Researcher at George Mason University's Next G Lab, and Technical Project Manager at Iowa State University for the NSF-funded ARA project. Serves as reviewer for IEEE journals including Transactions on Cognitive Communications and Networking. Labs/Initiatives: Active contributor to Northeastern's Institute for the Wireless Internet of Things and NSF PAWR program through the ARA project.

Shixiang Zhuمشاهده پروفایل

استادیار

• Machine Learning
• Data Science
• Operations Research
• +۷ مورد دیگر

Shixiang (Woody) Zhu is an Assistant Professor in Data Analytics at the Heinz College of Information Systems and Public Policy, Carnegie Mellon University. He holds a PhD in Machine Learning from Georgia Institute of Technology (2022) and B.S./M.S. in Computer Science from Beijing University of Posts and Telecommunications (2017). His research bridges machine learning, operations research, and statistics, focusing on sequential modeling, human-AI collaboration, and energy systems operations. He has received awards including the IEEE Power & Energy Society Best Paper Award (2025) and was a finalist for the INFORMS Wagner Prize (2021). Education : PhD in Machine Learning, Georgia Tech (2017–2022) B.S./M.S. in Computer Science, BUPT (2010–2017) His research emphasizes spatio-temporal data analysis , decision making under uncertainty , and applications to energy systems, healthcare, and public policy. Notable projects include optimizing police zone design (Wagner Prize finalist) and enhancing grid resilience through robust optimization. He actively collaborates with institutions like Argonne National Laboratory and NSF-funded projects. Awards : Best Paper Award, IEEE Power & Energy Society (2025) Gen-AI Fellows (2024) Finalist, INFORMS Wagner Prize (2021) Advising & Grants : Advises PhD students Zekai Fan, Wenbin Zhou, and others Recipient of Block Center Seed Grant (2024), NSF funding (2024) His work spans energy resilience, public policy optimization, and causal inference in social systems. He co-leads the INFORMS Data Mining Society and reviews for top journals like Operations Research and Management Science.

Shuva Paulمشاهده پروفایل

پژوهشگر

• Machine Learning
• Deep Learning
• Game Theory
• +۱۱ مورد دیگر

Shuva Paul is a Researcher at NREL's Energy Security and Resilience Center , specializing in power systems cybersecurity . His work focuses on collaborative autonomy, computational intelligence, reinforcement learning, game theory, smart grid security , and critical infrastructure protection . Research Interests: Machine learning and deep learning for critical infrastructure systems Event and anomaly detection in power grids Supply chain cybersecurity Cyber-physical energy systems security and resilience Professional Experience: Postdoctoral Fellow, Georgia Institute of Technology (Feb 2021–May 2022) Postdoctoral Research Associate, Washington State University (Jun 2020–Jan 2021) Graduate Intern, NREL (May 2019–May 2020) Graduate Research Assistant, South Dakota State University (2016–2019) Education: PhD, Electrical Engineering, South Dakota State University Master of Electrical and Electronics Engineering, American International University - Bangladesh Bachelor of Electrical and Electronics Engineering, American International University - Bangladesh Advisory and Editorial Contributions: Paul has served as a session chair at IEEE EnergyTech (2013) and IEEE Electro Information Technology (2019) conferences, and as a reviewer for journals like IEEE Transactions on Smart Grid and Neurocomputing . He also acted as a guest editor for the Journal of Sensor and Actuator Networks .

Ole-Christoffer Granmoمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Tsetlin Machines
• +۷ مورد دیگر

Professor Ole-Christoffer Granmo is a distinguished academic at the University of Agder, Norway, where he serves as Professor in the Department of Information and Communication Technology. He is the Founding Director of the Centre for Artificial Intelligence Research (CAIR) at the University of Agder, leading cutting-edge research in artificial intelligence and machine learning. Dr. Granmo obtained his master's degree in 1999 and his PhD in 2004, both from the University of Oslo. His academic journey has been marked by significant contributions to the field of AI, most notably the creation of the Tsetlin machine in 2018, for which he received the AI research paper of the decade award from the Norwegian Artificial Intelligence Consortium (NORA) in 2022. Professor Granmo's research primarily focuses on logical and causal world modeling across multiple modalities including images, sound, and natural language. His work spans logical auto-encoding, convolution, regression, transformer architectures, and reinforcement learning, all with the overarching goal of creating ultra-low-power artificial general intelligence through transparent logical learning and reasoning. His publications reveal a strong emphasis on interpretable AI systems, hardware implementations, and applications across diverse domains including cybersecurity, healthcare, social media analysis, and bioinformatics. AI Research Paper of the Decade (2022) - Norwegian Artificial Intelligence Consortium (NORA) Eight paper awards in machine learning Professor Granmo has coordinated over seven research projects and mentored 55+ master's students and nine PhD students. His leadership extends to co-founding the Norwegian Artificial Intelligence Consortium (NORA) and establishing two companies: Anzyz Technologies AS and Tsense Intelligent Healthcare AS. As an advisor at Literal Labs, he actively bridges academic research with practical industry applications, demonstrating his commitment to translating theoretical innovations into real-world solutions that address complex challenges across multiple sectors.

Ahmed Bin Zamanمشاهده پروفایل

استادیار

• computational biology
• evolutionary computation
• artificial intelligence
• +۱ مورد دیگر

Ahmed Bin Zaman serves as an Assistant Professor in the Department of Computer Science at George Mason University, where his research bridges computational methods with biological discovery. His academic profile emphasizes innovative approaches to protein structure prediction and optimization challenges. His educational foundation includes: PhD in Computer Science, George Mason University (2021) Master of Science in Computer Science, George Mason University (2020) Zaman's research program centers on computational biology, with specialized expertise in evolutionary computation and artificial intelligence applied to protein conformation analysis. He develops stochastic optimization frameworks to enhance protein structure prediction accuracy, focusing on conformational space mapping and decoy ensemble generation. His methodology integrates evolutionary algorithms with multi-objective optimization to navigate complex molecular landscapes, contributing significantly to template-free protein structure determination. His publication trajectory from 2017-2022 reveals distinct research phases: initial work in cybersecurity threat detection evolved into a concentrated focus on computational structural biology. Thirteen protein-related publications demonstrate consistent innovation in conformational sampling techniques, while maintaining methodological rigor through evolutionary computation and machine learning integration. Key contributions include conformation space mapping frameworks and adaptive stochastic optimization systems that address decoy diversity challenges. Professional development shows progression from industry experience at Technext Limited (as team leader/researcher) and lecturing at Metropolitan University to his current academic role. His teaching philosophy emphasizes cultivating independent problem-solving capabilities in students through cognitive tool development.

• Mathematics Education
• Interactive Multimedia in Teaching
• Educational Technology
• +۵ مورد دیگر

Marina Milovanović is a Professor at the University of Singidunum, Faculty of Informatics and Computing, Department of Mathematics. She holds dual doctoral degrees from the Faculty of Science, University of Kragujevac (Department of Mathematics, 2014) and Faculty of Entrepreneurial Business, Union University (2008), along with Master's and Bachelor's degrees from the Faculty of Mathematics, University of Belgrade (2000-2005 and 1995-2000 respectively). Faculty of Science, University of Kragujevac, Department of Mathematics (PhD, 2014) Faculty of Entrepreneurial Business, Union University (PhD, 2008) Faculty of Mathematics, University of Belgrade (Master's, 2000-2005) Faculty of Mathematics, University of Belgrade (Bachelor's, 1995-2000) Svetozar Marković High School, science and mathematics major (1991-1995) Professor Milovanović specializes in Mathematics Education and Educational Technology, with particular expertise in interactive multimedia applications for teaching mathematics. Her research consistently bridges theoretical mathematics with practical educational technology solutions, evolving from traditional multimedia approaches to incorporating cutting-edge AI and machine learning techniques. She has authored multiple books including 'Interactive multimedia in mathematics teaching' (2015) and collections of solved mathematics problems for entrance exams. Her recent publication record through 2025 demonstrates active engagement in interdisciplinary research, particularly at the intersection of educational technology, artificial intelligence, and practical applications in fields ranging from software engineering to medical diagnostics. Her work shows a clear trajectory from foundational educational technology research toward more sophisticated AI-enhanced learning systems. Professor Milovanović has made significant contributions to semantic web applications in education, particularly through Moodle LMS enhancements, and has explored SCADA applications in industrial contexts. Her collaborative research spans multiple countries and institutions, reflecting an international scholarly network. She has extensive experience developing computer tools for engineering education and has published on diverse topics including petroleum industry processes, environmental management, and financial mathematics. Her work demonstrates consistent application of computational approaches to solve domain-specific problems across multiple disciplines.

• Networked Epidemic Modeling
• Graph Signal Processing
• Control Systems
• +۲ مورد دیگر

Victor M. Preciado is a Professor in the Department of Electrical and Systems Engineering at the University of Pennsylvania. His research focuses on network science , control theory , and graph signal processing . Research Interests: Modeling and controlling spreading processes on complex networks Optimization algorithms for time-varying systems Applications in public health and cyber-physical security Selected Publications: Recent work includes machine learning for operator inference (2022), hybrid systems stability analysis (2021), and pandemic modeling frameworks (2021). Earlier contributions focus on spectral analysis of epidemics (2009-2016) and geometric optimization (2014).

Massimo Franceschettiمشاهده پروفایل

استاد

• Mathematical Engineering
• Networked Control Systems
• Information Theory
• +۷ مورد دیگر

Massimo Franceschetti is a Professor in the Department of Electrical and Computer Engineering at the University of California, San Diego (UCSD), with faculty affiliation at Calit2. His research spans mathematical engineering, focusing on control, communication, computation, and sensing, particularly in complex networks and systems. He integrates tools from statistical physics, wave propagation, and information theory to analyze and design networked systems. Born in Naples, Italy, he studied at the University of Naples Federico II and the University of Edinburgh (European exchange program), graduating in 1997. He earned his M.Sc. (1999) and PhD (2003) from Caltech, where he received the Walker von Brimer Award and the C.H. Wiltz Prize for outstanding research and thesis. After postdoctoral work at UC Berkeley (2003-2004), he joined UCSD as faculty and held visiting positions at Vrije Universiteit Amsterdam, EPFL (Switzerland), and the University of Trento (Italy). He became an IEEE Fellow in 2018 and was nominated a Guggenheim Fellow in 2019. His research includes networked control systems , stochastic geometry , electromagnetic information theory , and social dynamical systems . Recent work explores non-invasive emotional contagion in social networks, quantum limits on information entropy, and the physics of wave propagation. His publications bridge information theory , machine learning , and network science , often applying percolation theory and random walks to explain scaling laws and wireless signal behavior. Scientific accolades include the S.A. Schelkunoff Transactions Prize , IEEE Communications Society Best Tutorial Paper Award , and the IEEE Ruberti Young Researcher Prize . He co-authored two books: Random Networks for Communication (2007) and Wave Theory of Information (2018). His students have pursued careers in academia (e.g., IIT-Bombay, Notre Dame) and industry (e.g., Google, IBM, Tesla). He teaches courses on network science , information theory , and control systems , emphasizing data-driven analysis and the physical foundations of communication. His group’s work impacts cyber-physical systems , quantum network coding , and epidemic modeling on networks .

George O'Mahonyمشاهده پروفایل

مدرس

• Cybersecurity
• Cyber Resilience
• Network Security
• +۸ مورد دیگر

Dr. George O'Mahony serves as Head of Department of Computer Science at Munster Technological University (MTU) and is a CONNECT Associate Investigator with Research Ireland. He leads Ireland's Cyber Range infrastructure development and acts as WorldSkills Ireland Expert for Cybersecurity Skill 54, driving national cybersecurity initiatives through academia-industry collaboration. Education: B.E. in Electrical and Electronic Engineering, University College Cork (UCC) Ph.D. in Electrical and Electronic Engineering, University College Cork (UCC), 2021 His research pioneers cyber resilience frameworks for OT/IoT systems, zero-trust architectures, and machine learning applications in anomaly detection. He develops low-complexity security solutions for resource-constrained edge devices, with emphasis on wireless sensor networks, GPS applications, and penetration testing methodologies. His work bridges theoretical innovation with practical infrastructure implementation. Recent publications reveal accelerating focus on quantum-resistant cryptography, MQTT-ZT secure brokers, and unified cyber resilience models. His scholarly output consistently addresses interference detection in wireless networks while expanding into satellite communications security and AI-driven network customization, reflecting strategic adaptation to emerging cyber threats. Research Leadership: CONNECT: Associate Investigator advancing cyber security research NCF Cyber Shock: Co-Principal Investigator Cyber Explore: Principal Investigator at MTU Cyber Range: National infrastructure lead (mobile/cloud) Horizon Telemetry: Core research team member As STEM advocate and Cyber Futures Academy contributor, O'Mahony shapes cybersecurity education through WorldSkills Ireland engagement and industry-focused cyber range deployments that serve academic, governmental, and commercial sectors.