Find Academic Supervisors

Adam A. PorterView profile

Professor

• Software Engineering
• Mobile Application Development
• Software Testing and Quality Assurance
• +3 more

Adam A. Porter is a Professor in the Department of Computer Science at the University of Maryland, affiliated with the University of Maryland Institute for Advanced Computing Studies (UMIACS). He holds a Ph.D. from the University of California at Irvine (1991). His research focuses on software engineering, mobile application development, and empirical studies of software processes. Notable contributions include work on metamorphic testing, software quality assurance, and educational initiatives like the first MOOC on Android development. Education: Ph.D., Computer Science, University of California at Irvine, 1991 Research Interests: Dr. Porter's work spans software testing (e.g., metamorphic testing), mobile application frameworks (Android), and empirical methods to improve software development practices. He emphasizes practical applications, such as improving static analysis tools and exploring human-AI collaboration in intelligence analysis. His research often bridges theory and practice, with contributions to tools like Skoll for distributed quality assurance. Publications: His recent work includes advancements in AI-driven materials modeling, software defect triaging, and metagenomic assembly algorithms. The articles reflect his interdisciplinary approach, combining machine learning with domain-specific challenges in materials science and bioinformatics. Awards: NSF Early Career Award (1995) Dean's Teaching Excellence Award (1995) Senior Member IEEE/ACM (2003/2006) Mobile Learning Fellow (2010) Grants/Advising: He has led projects funded by NSF and industry collaborations, focusing on software testing, mobile systems, and educational platforms. His mentoring includes community outreach programs for underrepresented students. Labs/Teams: Leads research efforts in software engineering methodologies and collaborates on initiatives like the ATAACK Android testbed for cloud-based emulation of mobile systems.

• Security
• Cybercrime
• Ethics
• +3 more

Dr. Daniel Thomas is a Senior Lecturer in Computer and Information Sciences at the University of Strathclyde, where he serves as Director of the Academic Centre of Excellence in Cyber Security Research. His research focuses on the ethical measurement of security and cybercrime, aiming to improve regulatory frameworks and economic incentives. He holds a PhD from the University of Cambridge (2015) and an MA in Computer Science from the same institution (2011). Research Interests: Security metrics, cybercrime economics, infrastructure security, and ethical research practices. He collaborates across disciplines to address systemic issues in cybersecurity and policy. Key Projects: Principal Investigator for 'Influence policing' (2022–2025) and co-investigator on 'Robustness-as-Traceability: Secure and Legal Calibration Workflows in IoT' (2022–2023). His work contributes to UN Sustainable Development Goals related to education and security. Publications: Over 37 articles, including influential works on DDoS attack analysis, cybercrime infrastructure, and ethical AI. Recent focus areas include Russia-Ukraine cyber conflict dynamics and UK government use of targeted advertising. Prizes: CDCD Digital Research Prize (2024), Longlisted for Teaching Excellence Award (2024) Teaching: Courses on cybersecurity, ethics, and security engineering at Strathclyde and Cambridge Grants: EPSRC funding for cybercrime research, industry collaborations on IoT security Labs/Teams: Active in StrathCyber initiatives and collaborates with global networks like the Cambridge Cybercrime Centre. Supervises PhD students exploring topics such as security metrics and adversarial AI.

• Digital Forensics
• Cybersecurity
• Blockchain Technology
• +3 more

Dr. Sean Mckeown is a Lecturer at Edinburgh Napier University's School of Computing Engineering and the Built Environment , specializing in digital forensics, cybersecurity, and AI applications. His research focuses on: Perceptual hashing techniques for forensic analysis Blockchain-based evidence management Incident response tools for Unix systems Forensic challenges with wearables and streaming platforms AI-generated media detection His recent publications examine: Privacy-preserving evidence management using Hyperledger Fabric Adaptive DCT-DWT watermarking for JPEG disk images GenAI dataset diversity in image inpainting detection Spatial encoding in perceptual hashes beyond Hamming distance He supervises postgraduate researchers including Matthew Thomson, and collaborates with colleagues like Bill Buchanan and Gordon Russell on projects involving digital evidence integrity, contraband detection, and forensic tool development.

Xinyu LeiView profile

Assistant Professor

• Distributed Computing
• Mobile Computing
• Data Science
• +6 more

Xinyu Lei is an Assistant Professor in the Department of Computer Science at Michigan Technological University (MTU) , where he joined in Fall 2021. He earned his PhD in Computer Science and Engineering from Michigan State University (MSU) , advised by Prof. Guan-Hua Tu. Prior to MTU, he worked as a Research Assistant at Texas A&M University at Qatar (2013) and a Research Intern at Ford Motor Company (2017). University: Michigan Technological University Department: Computer Science Academic Rank: Assistant Professor PhD Institution: Michigan State University His research focuses on distributed computing , mobile systems , data science , and trustworthy machine learning , with particular emphasis on privacy-preserving protocols for IoT and blockchain technologies. His publications span top venues like ACM MobiCom , IEEE TDSC , and IEEE TIFS , addressing vulnerabilities in cellular IoT, secure blockchain protocols, and federated learning systems. Recent work includes privacy-preserving federated learning in 2023 (TIFS), secure redactable blockchain (TDSC), and IoT data heterogeneity handling (IoT-J). Earlier contributions in 2020-2021 explored Wi-Fi security for smart homes (MobiSys), encrypted geodata queries (ICDE), and Bitcoin payment protocols (CODASPY). Research Grants: NSF CRII: CNS-2153393 ($175K, Sole-PI) Professional Activities: Program Committee: CVPR'24, INFOCOM'24 TPC: BigDataService'20, Workshop Mobicom'19 Dr. Lei teaches graduate and undergraduate courses in applied cryptography (CS 5090), network security (CS/EE 4723), and computer security (CS 4471/5471) at MTU. He also contributes to academic community service through program committee roles at conferences like CVPR, INFOCOM, and WSDM.

Rafael Sa MenezesView profile

Researcher

• Software Verification
• Model Checking
• Cyber-Security
• +5 more

Rafael Sa Menezes is a Research Associate and Ph.D. student at the University of Manchester, specializing in Software Verification and Model Checking. His work focuses on applying formal verification techniques to industrial software systems, including Android applications, firmware, and optimizing verification processes through methods like fuzzing integration. He is a lead developer of ESBMC, a widely used open-source model checker for C and C++ programs. Rafael holds a Master of Science in Informatics from Universidade Federal do Amazonas (2021) and a Bachelor of Science in Computer Science from Federal University of Roraima (2017). His research interests encompass static and dynamic analysis, concurrency verification, and improving the efficiency of verification tools through techniques such as global common subexpression elimination and control-flow graph instrumentation. Collaborations include advancements in branch coverage analysis and concurrent program verification via scheduling and partial order reduction methods. Rafael’s contributions bridge academic research with practical industrial applications, addressing challenges in ensuring software reliability and security across diverse domains. His work has been presented at leading conferences including FSE and TACAS, with publications focusing on tool development and verification optimization strategies.

• Cybersecurity
• Network Security
• Mobile Application Security
• +4 more

Prof. Dr. Zoran Đurić is a full professor at the Faculty of Electrical Engineering, University of Banja Luka, specializing in computer science and informatics. He focuses on cybersecurity, network security, and secure communication protocols. His research includes cryptographic protocols like CryptoCloak, intrusion detection systems, mobile application security, and payment system architectures such as FEIPS. He leads projects like the 'Predictive Model Development' funded by NLB Banka and collaborates with institutions like the City of Banja Luka on IT modernization. Đurić has authored textbooks including Network and Distributed Programming and Java Programming , and has published extensively in journals like Computer Networks and Advances in Electrical and Computer Engineering . Educations: Not explicitly listed in text but inferred through academic rank and publications. Research Trends: Over 20 years of work focuses on practical security solutions for modern systems, including Android vulnerabilities, steganography, and adaptive streaming security. Grants/Projects: Active in EU-funded projects (e.g., 'Resilience Against Emerging Cyber Threats') and industry collaborations (e.g., NLB Banka). Labs/Teams: Head of research groups focused on cyber defense, secure payment systems, and software security tools.

Damien MassonView profile

Associate Professor

• Cyberphysical Systems
• Real-Time Systems
• Embedded Systems
• +3 more

Associate Professor Damien Masson is affiliated with the Cyberphysical Systems Engineering Department (DISC) at ESIEE Paris, part of Université Gustave Eiffel. He co-leads the Embedded Systems apprenticeship program and is a member of the Gaspard-Monge Computer Science Research Laboratory (LIGM), specifically the LRT team. His research focuses on real-time systems, scheduling algorithms, and embedded systems design, as evidenced by his development of the Draw Schedule tool for visualizing task scheduling scenarios. Teaching responsibilities include courses on C programming, operating systems, real-time systems, and algorithms/data structures. He instructs both full-time engineering students and apprentices in network security, embedded systems, and computer science applications. Research contributions include tools for simulating real-time task scheduling policies (EDF, LLF) and teaching materials for Unix/compilation, robotics, and Android development. His work emphasizes practical applications in real-time embedded systems and education.

Yi LiView profile

Associate Professor

• Software Security
• Smart Contracts
• Software Evolution
• +3 more

Yi Li is an Associate Professor at the College of Computing and Data Science (CCDS) , Nanyang Technological University (NTU) , focusing on the security, reliability, and sustainability of modern software systems. Their work bridges blockchain-based decentralized applications and software evolution management. Research Interests : Sustainability of evolving software systems, security/reliability of blockchain applications, semantic history slicing, and compositional analysis. Academic Roles : Associate Professor (2024–Present), Assistant Professor (2018–2024) at NTU, and research internships at Google and Microsoft Research . Scientific Awards : Distinguished Paper Award at NDSS'25 ACM SIGSOFT Distinguished Paper Award at ASE'23 Professional Activities : Co-Chair, Journal-First Track at FSE'25 and APSEC'25 Program Committee roles at ICSE, FSE, ASE, FM, and others (2016–2025) Organizing and reviewing for IEEE/ACM journals Key Publications : 2025: ICSE (SpecGen), FSE (invariant analysis), ISSTA 2024: INFOCOM (LightCross), ASE, ACM Computing Surveys 2023–2014: SPLC, ASE, FM, Dagstuhl Reports Student Advising : Chenguang Zhu (UT Austin, advisor Sarfraz Khurshid), Tai D. Nguyen (SMU, advisor Jun Sun).

Mazdak ZamaniView profile

Associate Professor

• Cybersecurity
• Artificial Intelligence
• Digital Watermarking
• +5 more

Dr. Mazdak Zamani is an Associate Professor of Cybersecurity and Associate Dean of Computer Science and Cybersecurity at Felician University , NJ. He earned his PhD in Computer Science from Universiti Teknologi Malaysia in 2011. His research focuses on Cybersecurity and Artificial Intelligence , with publications spanning video watermarking , IoT authentication , mobile cloud security , and digital forensics . His recent work addresses heterogeneous device authentication and optimized steganography for secure data transmission. 2019 : Video watermarking performance evaluation, data mining for energy systems 2018 : LSB image steganalysis, spatial domain watermarking 2017 : Botnet forensics, illumination normalization for face recognition 2016 : Mobile cloud authentication, image/video watermarking techniques At Felician, he teaches Network Security , Digital Forensics , and Advanced Cryptography . Previously, he served as a Senior Lecturer at Universiti Teknologi Malaysia and as an Assistant Professor at Wenzhou-Kean University .

Laurence Larry D. MerkleView profile

Assistant Professor

• Evolutionary Computation
• Quantum Computing
• Cybersecurity
• +7 more

Dr. Laurence Larry D. Merkle is a Research Assistant Professor of Computer Science in the Department of Electrical and Computer Engineering at the Air Force Institute of Technology (AFIT), where he has served since 2022, following his tenure as Assistant Professor from 2015 to 2022. He conducts computer science research aligned with Air Force and Department of Defense needs and mentors graduate students in master’s and doctoral research. Ph.D. in Computer Engineering, Air Force Institute of Technology, 1996 M.S.C.E., Air Force Institute of Technology, 1992 B.S. in Computer and Systems Engineering, Rensselaer Polytechnic Institute, 1987 Dr. Merkle’s research spans evolutionary computation, quantum computing, cybersecurity, and AI-driven education. He applies evolutionary algorithms to optimize complex systems in defense and engineering, and explores quantum circuit optimization, error mitigation, and hardware security. His work in computer science education includes gamification, robotics in teaching, and curriculum design. His recent publications reflect a strong trend toward quantum computing and defense applications, particularly in space situational awareness and secure quantum hardware. He has also contributed significantly to educational technology, including serious games for networking and pedagogical tools for introductory courses. Best Presentation, AMOS Conference (2019) Order of the Engineer (2019) Best Poster, CISS Education Colloquium (2018) Who’s Who in Engineering Education (2005–2006) Best Paper, ASEE Conference (2005) Air Force Achievement Medal (2000) Dr. Merkle has successfully led funded research projects totaling over $1.1 million as PI or Co-PI. He has chaired 2 Ph.D. and 13 master’s thesis committees and served on 19 additional graduate committees, demonstrating extensive mentorship. His grants focus on evolutionary optimization, quantum computing, and cybersecurity education, often in collaboration with AFRL and other DoD entities. He is actively involved in the AFIT Quantum Information Science (QIS) Seminar series and has contributed to DARPA and AFRL research initiatives in polymorphous computing and high-power microwave systems. His work bridges academic research and military application, particularly in secure and reliable computing systems.

Dongwan ShinView profile

Professor

• Computer Security
• Privacy
• Software Engineering
• +6 more

Dongwan Shin, Ph.D. is a Professor of Computer Science and Engineering at New Mexico Tech (NMT). He serves as Director of the Secure Computing Laboratory (SCL), NSF SFS and S-STEM Programs, and Faculty Advisor for the NMT ACM Student Chapter. His roles include leadership in cybersecurity education and research, including Center of Academic Excellence (CAE) designation for NMT. He has held the Orr Endowed Chair and served as Department Chair (2015–2018). Research Interests : Focuses on cybersecurity, usable security, software engineering, and cloud security. Key areas include access control, malware analysis, cryptography, and privacy-preserving technologies. His work addresses challenges in secure system design, blockchain, and insider threat mitigation. Grants & Projects : CyberCorps SFS Renewal (NSF, PI, 2020–2025) New Mexico SMART Grid Center (NSF, co-PI, 2018–2023) S-STEM Program (NSF, co-PI, 2018–2023) EPSCoR: Sustainable Grid Research (NSF, co-PI) Professional Activities : Program Chair for ACM Symposium on Applied Computing (2017–2020) Guest Editor for IEEE Transactions on Dependable and Secure Computing Leadership roles in TrustCol, CloudApp, and Smart Grid Track conferences Teaching : Offers courses in cybersecurity, cryptography, software engineering, and cloud computing at both undergraduate and graduate levels.

Hamdy SolimanView profile

Professor

• Computer Networks Security
• Neural Networks
• Wireless Sensor Networks
• +5 more

Hamdy Soliman, PhD, is a Professor in the Department of Computer Science & Engineering at New Mexico Tech. His research focuses on computer networks security, neural networks, and wireless sensor networks. He has pioneered a novel encryption algorithm surpassing AES in speed and security against insider attacks, and holds five related security patents. His work in machine learning includes modeling with neural networks (e.g., LVQ, BP, BAM) for big-data management, image processing, and sensor network applications. Research interests span secure mobile networks, cloud computing, and smart sensor systems for environmental monitoring (e.g., forest fire prediction). He has also explored healthcare applications via chatbots and AI-driven medical imaging (e.g., VGG16 for breast cancer detection). Recent work critiques the energy inefficiency of large language models and proposes optimized architectures. Publications emphasize anomaly detection in wireless sensor networks, malware analysis in Android systems, and ensemble learning for social media content moderation. His contributions include routing protocols (e.g., SCWRRHA) and cloud data center failure prediction systems (Failuresim). No scientific awards explicitly listed, but his patent portfolio and prolific publishing reflect industry impact. Advising and grants: While no advisees or grants are explicitly mentioned, his extensive publications suggest active mentoring of student researchers. His work on drone-based search-and-rescue systems (Project Vulture) indicates interdisciplinary collaboration in robotics and emergency response.

• Computer Science
• Programming Languages
• Blockchain Technology
• +3 more

Alvise SPANO' is a Researcher at Ca' Foscari University of Venice, affiliated with the Department of Environmental Sciences, Computer Science and Statistics. He is also part of the Research Institute for Complexity. His academic focus includes Blockchain Programming Languages, Programming Languages, and Information Systems. Research projects include ALGOMOVE for Algorand and the RINmaker bioinformatics tool. He has taught courses like Object-Oriented Programming and Introduction to Programming at both undergraduate and doctoral levels. Research interests span smart contract analysis, type systems, and cybersecurity in distributed systems. He contributed to projects like secure RPL for mobile networks and Android-LEGO interoperability. Funding includes the CEVID 2016 project (Role: LD), collaboratively managed with researchers like Agostino Cortesi and Salvatore Orlando. His work bridges theoretical foundations (e.g., COBOL code typing) with practical applications in wearable systems and bioinformatics. Collaborations include the Blockchain Programming Languages research group with Lorenzo Benetollo and Sabina Rossi.

• Microelectronics
• Analog Filters
• Signal Processing
• +10 more

Nuno Miguel de Figueiredo Garrido is an Assistant Professor in the Department of Information Science and Technology at ISCTE – Instituto Universitário de Lisboa (ISCTE-IUL). He is also an Associate Researcher at the Institute of Telecommunications – IUL, affiliated with the Radio Systems Group. His academic work bridges microelectronics, signal processing, and smart city technologies. PhD in Information Sciences and Technologies, ISCTE-IUL (2012–2015) Bachelor's in Electrical and Computer Engineering, Higher Technical Institute – UTL (1994) His research interests include microelectronics, analog filters, CMOS technology, smart cities, IoT systems, machine learning, and low-power circuit design. He has contributed significantly to adaptive analog filter design for hard disk drives and more recently to smart parking and interactive systems using BLE, Arduino, and Raspberry Pi. The analysis of his recent publications (2018–2024) reveals a strong interdisciplinary focus. Early work centered on high-frequency CMOS transconductors and signal equalization in storage systems. Recent research expands into machine learning for healthcare, NLP for IT automation, and educational tools for programming. His work frequently appears in international conferences such as IEEE ISCAS, INTELEC, and ACM ITiCSE, indicating active engagement in both engineering and computer science communities. Although no formal scientific awards are listed, his work has accumulated 94 Google Scholar citations, with publications in Q2 and Q3 ranked venues, reflecting scholarly impact. Garrido advises students and collaborates on research projects involving port classification automation, kidney disease prediction, and smart urban systems. He has contributed to the development of tools like Jask (question generation for Java code) and Sprinter (a didactic linter), showing commitment to computing education. He is involved in multiple research initiatives related to IoT, smart cities, and embedded systems, particularly those utilizing open hardware and software. His lab and team affiliations include the Radio Systems Group at the Institute of Telecommunications – IUL, where he conducts research on wireless and embedded systems for smart environments.

Seibu Mary JacobView profile

Senior Lecturer

• Mathematics Education
• Engineering Education
• Machine Learning
• +14 more

Dr Seibu Mary Jacob is a Senior Lecturer in Analytical Methods/Engineering Mathematics at the School of Computing, Engineering and Digital Technologies, Teesside University, where she has been since 2014. She is a Senior Fellow of the Higher Education Academy (HEA) and leads the pedagogic research group STEAMEDULAB@TU. She teaches modules including Engineering Mathematics, Probability & Statistics, Statistical Analysis, and History/Philosophy of Mathematics at both undergraduate and postgraduate levels, including Masters project supervision. Education: BSc in Mathematics MSc in Mathematics BEd in Mathematics Education PhD in Mathematics Education (focus: Critical Thinking in Online Engineering Mathematics) Postgraduate Diploma in Computer Applications (PGDCA) Her research lies at the intersection of applied mathematics, statistical modeling, machine learning, and educational technology. She investigates how AI, especially Generative AI, can enhance student engagement, critical thinking, and inclusive learning. Her work also extends into cybersecurity, where she applies machine learning to detect Android malware, spam emails, and cyber-hate using techniques such as graph neural networks, fuzzy systems, and adversarial defense mechanisms. The recent publications reveal a strong trend in applying machine learning to security challenges—particularly in adversarial environments—while maintaining a parallel focus on pedagogical innovation and the impact of digital tools on education. Her interdisciplinary approach combines technical rigor with social responsibility, emphasizing diversity, inclusion, and community impact. Scientific Awards and Recognitions: Senior Fellow of the Higher Education Academy (HEA) Microsoft Certified Educator (MCE) Dr Jacob is actively involved in PhD student supervision and community projects promoting STEM education, especially for marginalized groups. She is passionate about policy development and curriculum internationalization in mathematics and engineering education. Her research has been supported through institutional affiliations and collaborations, particularly with IEEE, where several of her works are published. She leads the STEAMEDULAB@TU research group, which focuses on innovation in digital pedagogy, including projects on collaborative learning models, U-learning, and learner engagement through technology-enhanced environments.