جست‌وجوی استاد و پژوهشگر

David Loمشاهده پروفایل

استاد

• AI for Software Engineering
• Mining Software Repositories
• Data Mining
• +۴ مورد دیگر

David Lo is the OUB Chair Professor of Computer Science and the founding Director of the Center for Research in Intelligent Software Engineering (RISE) at Singapore Management University. He has held significant leadership roles including General Chair of MSR'22 and ASE'16, and Program Committee Co-Chair for ASE'20, FSE'24, and ICSE'25. Lo has championed the field of AI for Software Engineering (AI4SE) since the mid-2000s, demonstrating how data mining, machine learning, information retrieval, natural language processing, and search-based algorithms can transform software engineering data into actionable insights and automation. His research spans Mining Software Repositories (MSR), large language models for code, software testing, smart contract analysis, and developer tooling. His recent publications reveal a strong focus on the intersection of large language models and software engineering, with particular attention to code generation, evaluation, documentation, and the practical implications of AI tools for developers. His work increasingly addresses economic efficiency, privacy concerns, and human factors in AI-assisted development. Two Test-of-Time awards Eleven ACM SIGSOFT/IEEE TCSE Distinguished Paper awards ACM Fellow IEEE Fellow ASE Fellow National Research Foundation Investigator (Senior Fellow) Lo has supervised numerous students and collaborated extensively across the software engineering community. His work on Mining Software Repositories has led to practical tools and insights that have shaped the field. He regularly contributes to major conferences and has served in leadership roles across ASE, ICSE, and FSE communities. As founding Director of the Center for Research in Intelligent Software Engineering (RISE) at SMU, Lo leads a research group focused on advancing AI techniques for software engineering problems, with emphasis on practical applications that address real developer pain points.

Avinash Singhمشاهده پروفایل

مدرس ارشد

• Machine Learning
• Cognitive Neuroscience
• Brain-Computer Interfaces
• +۶ مورد دیگر

Dr. Avinash Singh is a Senior Lecturer at the School of Computer Science at the University of Technology Sydney (UTS), Australia. He serves as co-chair of the IEEE Neuroethics Framework for the Workplace, sponsored by IEEE Brain, and is a member of the IEEE Standards Committee on Unifying Brain-Computer Interfaces (BCI). He also serves as an expert advisor for UNICEF and The Centre of Neurotechnology and Law, UK. Dr. Singh completed his PhD in Computer Science in 2019 at UTS, collaborating with the Technical University of Berlin, Germany, the University of California San Diego, USA, and the US Army Research Lab. Prior to his doctorate, he earned a Master's in Software Systems from Birla Institute of Technology and Science Pilani, India, and earlier degrees in Computer Science and Mathematics from Indian institutions. Working at the intersection of machine learning, cognitive neuroscience, and mixed-reality, Dr. Singh focuses on designing and developing real-world neuroadaptive BCI systems. His research integrates AI technologies with cognitive neuroscience to explore cognitive functions, discover relationships between brain dynamics, evaluate everyday interactions, and develop robust next-generation neuroadaptive BCIs. His work spans areas including neuroadaptive BCI applications for improving interpersonal communication, sensory augmentation for blind individuals, and dream reconstruction from brain signals. Analysis of Dr. Singh's recent publications reveals a consistent focus on developing novel EEG signal processing techniques, creating neuroadaptive interfaces, and applying BCI technology to real-world problems. His work shows increasing integration of deep learning with neuroscience, particularly in the context of cognitive conflict detection, spatial navigation, and assistive technologies for the visually impaired. The research demonstrates strong interdisciplinary connections across computer science, neuroscience, and human-computer interaction. Google TensorFlow Faculty Award (2021) Dr. Singh actively supervises PhD students and has received multiple research grants, including ARC Linkage Projects and NHMRC Ideas Grants. His funded research spans neuro-AI for personalized image generation, sensory augmentation for blind individuals, and ethical frameworks for BCI technology. He leads the UTSxDream Recording project (formerly DreamMachine) and collaborates with international institutions on BCI standardization efforts. Dr. Singh founded the India Future Society, a think tank focused on transhumanism, and actively advocates for the ethical development of neurotechnology. His work bridges academic research with practical applications in assistive technology, human-robot collaboration, and spatial navigation systems.

Yuhiro Iwamotoمشاهده پروفایل

دانشیار

• Fluid Engineering
• Magnetic Fluids
• Thermomagnetic Pumps
• +۳ مورد دیگر

Yuhiro Iwamoto serves as Associate Professor at Nagoya Institute of Technology within the Department of Electrical and Mechanical Engineering, with additional affiliation to the Graduate School of Engineering's Mechanical Engineering Program and the Center for Innovative Young Researchers. His academic foundation includes: Bachelor of Engineering from Doshisha University (2008) Master's degree from Doshisha University (2010) Doctor of Engineering from Doshisha University (2013) Dr. Iwamoto's research centers on fluid engineering phenomena with emphasis on magnetic responsive fluids. His work explores thermomagnetic pumping mechanisms, phase-change behavior in water-based magnetic fluids, and innovative applications of permanent magnet elastomers for energy harvesting and tactile sensing. This research bridges fundamental fluid dynamics with practical implementations in thermal management systems, robotic sensing, and sustainable energy technologies, demonstrating significant contributions to manufacturing technology and mechanical engineering disciplines. Analysis of his recent publications reveals a cohesive trajectory in functional fluid systems, particularly focusing on temperature-sensitive magnetic fluids for self-driving thermal transport and elastomer-based transduction mechanisms. His work consistently integrates material science, electromagnetic principles, and fluid mechanics to develop novel solutions for heat transfer enhancement, energy conversion, and soft robotics applications. His research excellence has been recognized through prestigious awards: Japanese Society of Mechanical Engineers Encouragement Award (2020) for research on thermal conductivity control using silver nanowire magnetic nanofluids Best Presentation Award at the 9th Asia-Pacific Symposium on Applied Electromagnetics and Mechanics (2018) Dr. Iwamoto actively contributes to academic governance as committee member for the Institute of Electrical Engineers of Japan's Special Committee on Electromagnetic Responsive Fluids (2019-2022) and the Japan AEM Society Editorial Committee (2017-2022). His industrial property portfolio includes multiple patents related to magnetic elastomers and thermal transfer systems, reflecting strong industry-academia collaboration. He maintains active membership in eight professional societies including The Japan Society of Applied Electromagnetics and Mechanics and The Japanese Society for Multiphase Flow.

Guohui Zhangمشاهده پروفایل

استاد

• Large-Scale Transportation Systems Modeling and Simulation
• Traffic Control and Operations
• Traffic Detection and Sensor Data Analysis
• +۳ مورد دیگر

Guohui Zhang is a Professor of Civil, Environmental and Construction Engineering at the University of Hawaii, where he has served since 2016, progressing from Assistant Professor (2016-2018) to Associate Professor (2018-2022) before attaining his current rank in 2022. His expertise spans transportation systems engineering with a focus on data-driven solutions for modern mobility challenges. His educational foundation includes: Ph.D. in Civil Engineering, University of Washington, Seattle (2008) M.S. in Systems Engineering, Tsinghua University, China (2003) B.S. in Control Engineering, Harbin Institute of Technology, China (2000) Professor Zhang's research integrates advanced computational methods with transportation theory across six core domains: Large-Scale Transportation Systems Modeling, Traffic Control and Operations, Sensor Data Analysis, Cyber-Transportation Security, Congestion Pricing, and Safety/Security systems. His work frequently employs machine learning and statistical modeling to address real-world problems like urban mobility optimization, disaster evacuation planning, and autonomous vehicle integration. Recent projects demonstrate particular innovation in applying generative adversarial networks to traffic hotspot prediction and Bayesian methods for crash analysis under extreme conditions. Analysis of his 2018-2020 publications reveals a strong shift toward data-intensive methodologies , with 60% of recent work utilizing deep learning or advanced statistical techniques. Key thematic clusters include autonomous vehicle systems (20%), natural disaster response (15%), and impaired driving/crash severity analysis (25%), reflecting his commitment to solving transportation's most pressing safety and efficiency challenges through computational innovation. His scientific recognition includes: 2009 PTV Vision Transportation System Simulation Scientific Award (Germany) 2009 Shining STAR Award from University of Washington's TransNow UTC As Principal Investigator on 8 major grants totaling over $1.2 million, Zhang has led projects for the New Mexico Department of Transportation, SOLARIS Institute, and City of Albuquerque. His research portfolio demonstrates exceptional versatility across domains including traffic microsimulation ($37k), crash database development ($11k), autonomous vehicle intersection control ($220k), and tsunami evacuation modeling. While specific advisees aren't listed, his teaching of graduate courses like CEE 696: Transportation Data Management indicates active mentorship of transportation engineering students. Professional leadership includes Guest Editor roles for IEEE Intelligent Transportation Systems Magazine and Transportation Research Part C , plus active committee service with the Transportation Research Board.

• Machine Learning
• Information Retrieval
• Medical Data Analysis
• +۳ مورد دیگر

Ingemar Johansson Cox serves as a Professor within the Machine Learning section at the Department of Computer Science, University of Copenhagen. His research bridges theoretical machine learning foundations with practical applications across medical data analysis, information retrieval, remote sensing, and sustainability initiatives. His research portfolio emphasizes machine learning applications in high-impact domains, particularly medical data analysis (e.g., early detection of gynecological malignancy using online search activity) and sustainability (e.g., reducing AI's carbon footprint). The Machine Learning section actively contributes to the university's SCIENCE AI Centre, focusing on both algorithmic innovation and real-world problem-solving in biological modeling and environmental monitoring. Recent publication trends reveal expanding work in quantum computing applications for biomolecular modeling, sustainable AI frameworks, and cross-cultural NLP systems. His 2024-2025 output demonstrates strong interdisciplinary collaboration, especially in medical informatics and climate-related AI research. Professor Cox operates within the Department of Computer Science's robust research ecosystem, which includes dedicated compute clusters and specialized initiatives like TreeSense for global tree resource monitoring through remote sensing and deep learning. The department's infrastructure supports large-scale machine learning projects requiring significant computational resources.

• Leadership
• Organizational Behavior
• Workplace Dynamics
• +۳ مورد دیگر

Dr. Saima Ahmad is a Senior Lecturer at RMIT University's School of Management, focusing on cultivating sustainable work environments and investigating leadership's impact on individual well-being. With a PhD in Management from Monash University, her research spans organizational behavior, workplace dynamics, and leadership ethics, addressing critical issues such as bullying, resilience, and digital disruption. She coordinates courses in the RMIT MBA program and serves on editorial boards for the European Management Journal and PLoS One . Education: PhD in Management from Monash University Her research emphasizes positive leadership styles and their influence on employee engagement and organizational sustainability. Recent work explores servant leadership in the construction industry and the role of green human resource management in fostering environmental citizenship. She has pioneered studies on workplace bullying and its mitigation through ethical leadership frameworks. Her scientific awards include the 2022 RMIT GSBL Dean’s Merit Award for HDR Leadership Excellence for her contributions as HDR Coordinator (2022-2024), where she enhanced PhD completion rates and student support systems. She actively supervises Masters and PhD research candidates, focusing on leadership and organizational behavior.

Mariano Ricoمشاهده پروفایل

دانشیار

• Linked Open Data
• Natural Language Processing
• Semantic Web Technologies
• +۳ مورد دیگر

Mariano Rico is an Associate Professor at the Polytechnic University of Madrid (UPM), affiliated with the OEG research group in the Artificial Intelligence Department. Previously, he served as a Senior Researcher at OEG (2016-2020) and held teaching roles at the Autonomous University of Madrid (UAM). His primary affiliations include the UPM's Faculty of Computer Science and the UAM's Computer Engineering Department. Education: PhD in Computer Science (UAM, 2009), MSc in Physics (UAM, 1992), and postgraduate studies in Telecommunications Engineering. He conducted research stays at DERI (Ireland) and Freie Universität Berlin, focusing on Semantic Web and Linked Data. Research interests center on Linked Open Data, Natural Language Processing (NLP), and Semantic Web technologies, with contributions to DBpedia's Spanish branch and projects like Wf4Ever and LIDER. He actively collaborates with institutions in Leipzig, Bielefeld, and Berlin on Linked Data and linguistic applications. Teaching: Coordinates courses in NLP, Linguistic Engineering, and Big Data Visualization at UPM and online programs. Has instructed over 300 UAM faculty through teacher training programs on LaTeX, bibliographic management, and digital scholarly practices. Projects: Lead roles in European and national initiatives including SlideWiki, UpGrid, and Neptune. Current work focuses on NLP applications like text summarization (esT5s) and terminology tools (TermInteract). Labs/Teams: Core member of the OEG group, contributing to semantic web infrastructure and NLP tool development. Maintains international collaborations through AKSW and CITEC groups.

Marcel Justمشاهده پروفایل

استاد

• Cognitive Neuroscience
• fMRI Brain Imaging
• Neural Representation of Concepts
• +۳ مورد دیگر

Marcel Just is the D.O. Hebb University Professor of Psychology and Biomedical Engineering at Carnegie Mellon University, where he also serves as the Director of the Center for Cognitive Brain Imaging. His academic journey began with a B.Sc. in Honors Psychology from McGill University in 1968, followed by a Ph.D. from Stanford University in 1972. Over his distinguished career, Just has pioneered the application of fMRI technology to investigate the neural basis of cognitive processes. His research focuses on understanding how concepts are neurally represented in the brain, with particular emphasis on: How familiar and technical concepts are represented through fMRI-measured brain activation patterns The decomposition of these patterns into meaningful components (e.g., how motor regions represent the action of holding an apple) Applications for diagnosing psychiatric illnesses by detecting alterations in concept representations Assessing how students learn new technical concepts in educational settings Just's work has made significant contributions to both conceptual and language processing research (funded by ONR and NIMH grants) and autism research (funded by NICHD). His laboratory developed the influential frontal-posterior underconnectivity theory of autism, which has shaped understanding of neural connectivity differences in autism spectrum disorders. His research employs machine learning and dimension reduction techniques applied to fMRI data, bridging cognitive psychology with advanced neuroimaging methodologies. This interdisciplinary approach has yielded insights across multiple domains including language comprehension, visual thinking, problem-solving, working memory, social judgment, and multi-tasking. Among his notable scientific awards are: Appointment as University Professor at Carnegie Mellon (2013) Distinguished Scientific Contribution Award from the Society for Text & Discourse (2012) Outstanding Research Award from the Advisory Board on Autism and Related Disorders (2001) NIMH Senior Scientist Award (1997) Throughout his career, Just has mentored numerous researchers and collaborated extensively with colleagues across disciplines. His work has been supported by multiple grants from organizations including the Office of Naval Research (ONR), National Institute of Mental Health (NIMH), and National Institute of Child Health and Human Development (NICHD). These collaborations have led to innovative applications of neuroimaging in understanding both typical cognitive processes and clinical conditions. At the Center for Cognitive Brain Imaging, Just leads a multidisciplinary team that combines expertise in psychology, neuroscience, biomedical engineering, and machine learning to advance the field of cognitive neuroimaging. The center serves as a hub for cutting-edge research that continues to deepen our understanding of the relationship between brain activity and cognitive processes.

• Hardware Security
• Machine Learning for Security
• IoT Security
• +۵ مورد دیگر

Setareh Rafatirad is an Assistant Professor in the Department of Electrical and Computer Engineering at George Mason University's College of Engineering and Computing. Her research spans hardware security, machine learning for security applications, and IoT security systems. Her research interests focus on hardware security, machine learning for security applications, IoT security, side-channel attacks, and malware detection. She has developed innovative approaches for securing integrated circuits, detecting malware using machine learning techniques, and protecting against side-channel vulnerabilities in computer systems. Her work bridges the gap between hardware design and security, creating practical solutions for emerging security challenges in computing systems. Her recent publications demonstrate a strong trend toward applying machine learning techniques to security problems, particularly in hardware and embedded systems. She has made significant contributions to understanding and mitigating side-channel attacks, developing secure machine learning models, and creating efficient security solutions for resource-constrained devices. Her work shows increasing interdisciplinary reach, connecting hardware security with healthcare applications and educational technologies. Dr. Rafatirad has collaborated extensively with researchers including Houman Homayoun, Avesta Sasan, and Sai Manoj P. Dinakarrao. She has secured research funding for projects related to hardware security and machine learning applications, though specific grant details are not provided in the available information.

Pascal Bizarroمشاهده پروفایل

دانشیار

• Accounting Information Systems
• IT Auditing
• Information System Assurance & Control
• +۷ مورد دیگر

Pascal Bizarro, Ph.D., is an Associate Professor in the Department of Accounting and Information Systems at Bowling Green State University (BGSU), part of the Schmidthorst College of Business. He holds a Ph.D. and M.Acc. from the University of Alabama and a B.B.A. in Commercial Engineering from HEC, Liège, Belgium. A Certified Information Systems Auditor (CISA), he specializes in IT Auditing, Accounting Information Systems, and emerging technologies like blockchain. He advises BGSU's Information System Audit and Control (ISAC) programs and serves as president of the Northwest Ohio ISACA Chapter and academic board member of the Northwest Ohio IIA Chapter. Dr. Bizarro's research focuses on cybersecurity, audit technology, data privacy, and blockchain applications in accounting. His work has been published in leading journals such as ISACA Journal , Internal Auditing , and The CPA Journal . Notable contributions include studies on phishing attacks, IoT security, AI in auditing, and XBRL implementation. He has received awards including the Schmidthorst Leadership Council Faculty Excellence Award (2015) and the Primrose Family Professorship (2013–present). His professional certifications and academic leadership roles reflect his expertise in bridging accounting practices with information systems innovation.

Sanda Harabagiuمشاهده پروفایل

استاد

• Natural Language Processing
• Medical Informatics
• Artificial Intelligence for Public Health
• +۳ مورد دیگر

Dr. Sanda Harabagiu is the Research Initiation Chair Professor in the Department of Computer Science at The University of Texas at Dallas (UTD), affiliated with the Erik Jonsson School of Engineering and Computer Science. Her expertise spans natural language processing, medical informatics, and artificial intelligence for public health. She holds dual doctorates in Computer Engineering (University of Southern California, 1997) and Electrical Engineering and Computer Science (University of Rome, 1994), alongside a diploma in Computer Science from the Polytechnic Institute of Bucharest (1983). Her research focuses on advancing technologies for medical data analysis, including automatic extraction of actionable insights from radiology reports and EEG records. Notable projects include the Multimedia Vaccine Informatics System for analyzing social media discourse on vaccines and the development of AI tools for clinical decision support. She has led interdisciplinary collaborations through the Human Language Technology Research Institute (HLTRI), established in 2002 to pioneer advancements in human language processing. Dr. Harabagiu’s honors include the 2019 AMIA Distinguished Paper Award and the 2017 Homer Warner Award. Her work bridges computational linguistics with healthcare, emphasizing applications in public health communication, misinformation detection, and clinical informatics. She has contributed to over 150 publications and served on numerous editorial and organizing committees for conferences such as ACL, AAAI, and AMIA. Education: Ph.D., Computer Engineering, University of Southern California, 1997 Doctorate, Electrical Engineering and Computer Science, University of Rome, 1994 Diploma, Computer Science and Engineering, Polytechnic Institute of Bucharest, 1983 Awards: 2019 AMIA Distinguished Paper Award 2017 Homer Warner Award 2000 NSF CAREER Award 1991-1993 Fondazione Ugo Bordoni Research Award Her research also addresses social media analysis for public health, including frameworks to detect vaccine hesitancy and misinformation. Current projects involve leveraging large language models (LLMs) and multimodal data to understand communication patterns in health-related discourse. She has advised students like Travis Goodwin, contributing to impactful work in clinical informatics and AI ethics.

Muhammad Bilal Zafarمشاهده پروفایل

استاد

• Human-Centric AI/ML
• Fairness in Machine Learning
• Explainable Artificial Intelligence
• +۳ مورد دیگر

Professor Muhammad Bilal Zafar holds a faculty position at Ruhr University Bochum (RUB), where he heads the Chair of AI and Society within the Research Center for Trustworthy Data Science and Security. He is also a Principal Investigator (PI) at the Cluster of Excellence CASA and a member of the Horst Görtz Institute for IT Security. Previously, he worked as a Senior Applied Scientist at Amazon Web Services and a Research Scientist at Bosch Center for Artificial Intelligence. He completed his PhD at the Max Planck Institute for Software Systems (MPI-SWS) and Saarland University, advised by Krishna P. Gummadi and Manuel Gomez Rodriguez. His research focuses on human-centric AI/ML, emphasizing fairness, explainability, and robustness of AI systems. Key contributions include mechanisms for fair classification, bias detection in algorithms, and trustworthy AI applications. He actively engages in mentoring PhD and Master’s students, with current openings for candidates in Computer Science, Mathematics, and related fields. His work bridges theoretical advancements with practical solutions for ethical AI deployment. Notable collaborations include projects with AWS and Bosch, addressing challenges in algorithmic fairness and AI transparency. His publications span top venues like ACL, KDD, NeurIPS, and WWW, highlighting contributions to both foundational and applied aspects of AI ethics.

• Bioinformatics
• Protein Stability
• Molecular Biology
• +۳ مورد دیگر

Amelie Stein is an Associate Professor at the Department of Biology, University of Copenhagen, specializing in Bioinformatics and RNA Biology. Her research focuses on protein stability, molecular mechanisms of disease variants, and computational methods for protein design. She is affiliated with the UCPH Quantum Hub, reflecting interdisciplinary interests in biological systems. Her work integrates bioinformatics tools, mutational scanning, and structural biology to understand protein degradation pathways and their relevance to human diseases such as Lynch syndrome and metabolic disorders. Key research areas include analyzing protein variants using deep learning models (e.g., SSEmb), developing web-based tools like MutationExplorer for 3D visualization, and characterizing disease-linked mutations in proteins such as Parkin and MLH1. Her publications highlight breakthroughs in rapid protein stability predictions, degon mapping, and the interplay between protein toxicity and degradation. No scientific awards are explicitly mentioned in the provided texts. Stein’s research also explores the application of computational approaches to biotechnology and therapeutic development, emphasizing translational applications of her findings. Her lab, linked to the SCARB research group (https://www1.bio.ku.dk/english/research/scarb/), focuses on structural and computational biology, with ongoing projects involving protein quality control networks and enzyme variant analysis. Collaborations span molecular biology, bioinformatics, and interdisciplinary quantum-related research through her UCPH Quantum Hub membership.

Stuart J. Russellمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Probabilistic Reasoning
• +۴ مورد دیگر

Stuart J. Russell is a Distinguished Professor of Computer Science at the University of California, Berkeley, holding the Smith-Zadeh Chair in Engineering. He is also a Professor of Cognitive Science, a Professor of Computational Precision Health at UCSF, and an Honorary Fellow of Wadham College, Oxford. His research spans artificial intelligence, machine learning, probabilistic reasoning, robotics, and AI ethics. Russell co-authored the seminal textbook Artificial Intelligence: A Modern Approach and founded the Center for Human-Compatible AI (CHAI). He has advised international organizations on AI policy and ethics, including roles with the OECD and the Global Partnership on AI. Educations: B.A. (1st class honors) in Physics, University of Oxford (1982) Ph.D. in Computer Science, Stanford University (1986) Research Focus: Russell’s work addresses foundational AI challenges, including safe AI control, long-term societal impacts of AI, and ethical frameworks for autonomous systems. He emphasizes aligning AI with human values and has warned against risks of uncontrolled autonomous weapons. Labs & Affiliations: He leads the Center for Human-Compatible AI, co-directs the Kavli Center for Ethics, Science, and the Public, and collaborates with BAIR (Berkeley AI Research) and the Simons Institute for the Theory of Computing. His interdisciplinary work bridges computer science, philosophy, and public policy.

R Gerald Hughesمشاهده پروفایل

عضو هیئت علمی

• Modern International History
• Contemporary History
• European History
• +۱۰ مورد دیگر

R Gerald Hughes is a Reader in Military History at the Department of International Politics, Aberystwyth University. He specializes in diplomatic history and intelligence history, with a strong focus on modern and contemporary international history, particularly the Cold War, European history, and British foreign policy. His academic roles include being the reviews editor of Intelligence & National Security and editor of the Study Group on Intelligence newsletter. BA (Hons) from University of Stirling PGDip from University of Wales MSc(Econ) from University of Wales PhD from University of Wales (2000) on British policy toward West German Ostpolitik (1955–1967) His research interests span military history, intelligence history, strategic studies, Cold War history, Anglo-German and Anglo-Irish relations, and the history of appeasement. He is currently researching Britain's policy of appeasement and the political and military dimensions of the Anglo-Irish War (1919–1921). His scholarly work contributes to broader themes in international relations and historical understanding of conflict and diplomacy. The trends in his recent publications show a consistent engagement with military thought (e.g., Clausewitz), intelligence operations (especially in South Asia and the British Empire), Cold War history, and contemporary security issues such as cyber warfare and Ukraine conflict. His interdisciplinary approach connects historical analysis with modern strategic challenges. Scientific Awards and Recognition: Fellow of the Royal Historical Society He supervises PhD students in international and diplomatic history, Cold War studies, intelligence history, and military history. His media contributions highlight his role as a public intellectual, particularly on Ukraine-Russia conflict, NATO, and historical parallels in modern warfare. He has also engaged in academic consultancy, notably for the 'Documenting WWII' book series. Labs and Research Groups: Editor, Study Group on Intelligence newsletter Reviews Editor, Intelligence & National Security