Find Academic Supervisors

Marc SchmittView profile

Researcher

• Artificial Intelligence in Finance
• Business Analytics
• Digital Ecosystems
• +5 more

Dr. Marc Schmitt serves as a Research Associate in the Department of Computer Science at the University of Oxford while concurrently leading as Managing Director of the DEIM Research Institute in Germany. His interdisciplinary work bridges academic research and industry applications across artificial intelligence, cybersecurity, and financial systems. Academic Background: PhD in Computer and Information Sciences (AI in Finance), University of Strathclyde MSc in Quantitative Finance, University of Strathclyde MSc in Software Engineering, University of Oxford BA in Business Administration, Technische Hochschule Nürnberg Georg Simon Ohm Dr. Schmitt's research focuses on AI-driven decision-making at the intersection of finance, business analytics, and cybersecurity. His work examines how intelligent systems integrate into organizational structures while addressing systemic risks in digital ecosystems. Recent investigations include generative AI threats in social engineering, no-code AutoML applications, and policy frameworks for AI-enhanced security systems. His publications demonstrate consistent methodological innovation across theoretical and applied domains. Analysis of his publication trajectory reveals growing emphasis on generative AI security implications (2024-2025), with foundational work in business analytics applications (2023). The research shows strong interdisciplinary connections between computer science, financial economics, and human-centered design principles, reflecting his unique background spanning technical and business domains. Prior to academia, Dr. Schmitt held strategic positions including Senior IT Partner for Equity Finance at Siemens Financial Services and management consulting roles at d-fine and Deloitte, where he advised Fortune 500 companies on digital transformation and risk management. His industry experience directly informs his research approach, emphasizing practical implementation challenges alongside theoretical innovation.

Yan HuangView profile

Associate Professor

• Machine Learning
• Cybersecurity Education
• Extended Reality (XR)
• +5 more

Yan Huang is an Associate Professor in the Department of Software Engineering and Game Development at Kennesaw State University (KSU). His work bridges Federated Learning (FL) and Cybersecurity Education , with a focus on personalization and privacy in distributed systems. Research spans Machine Learning , Extended Reality (XR) , and Data Privacy . He has served as Editor of WCMC and Program Co-Chair for CyberSciTech 2020-2024. Research Trends: Recent publications emphasize Federated Learning for non-IID data, VR-based Cybersecurity Education , and Privacy-Preserving Algorithms in IoT and social media analytics. Key subfields include personalized learning architectures, graph learning, and game-theoretic privacy frameworks. Scientific Awards: Excellent Paper Award (Tsinghua Science and Technology, 2021) Best Paper Award (Future Generation Computer Systems, 2019) Best Paper Awards at IEEE SmartWorld 2021, COCOA 2019, and WASA 2019 Grants: Led over $600,000 in NSF and NSA-funded projects, including VR cybersecurity education for K-12 and XR engineering curricula. His lab recruits VR/AR Research Assistants via industry partnerships.

Scott L. NyklView profile

Professor

• Computer Vision
• Real Time 3D Computer Graphics
• Sensor Fusion
• +12 more

Dr. Scott L. Nykl is a Professor in the Department of Computer Science at the Air Force Institute of Technology (AFIT), part of the Graduate School of Engineering & Management. He is a leading researcher in computer vision, real-time 3D graphics, and autonomous aerial systems, with a focus on automated aerial refueling and navigation in GPS-denied environments. Education: Ph.D. in Computer Science, Ohio University (2008–2013), Summa Cum Laude, GPA: 4.0/4.0 M.S. in Computer Science, Ohio University (2011–2012), Summa Cum Laude, GPA: 4.0/4.0 B.S. in Software Engineering, University of Wisconsin–Platteville (2002–2006), Summa Cum Laude, GPA: 3.94/4.0 Dr. Nykl's research interests include computer vision, sensor fusion, interactive virtual worlds, and real-time 3D graphics, with applications in aerospace and defense. His work bridges simulation and real-world deployment, particularly in autonomous aerial refueling using stereo and monocular vision. He has pioneered techniques in pose estimation, occlusion mitigation, and sim-to-real transfer learning. His recent publications and projects show a strong trend toward robust, vision-based navigation systems for unmanned and manned aircraft, with emphasis on reliability, accuracy, and real-time performance. His work frequently appears in IEEE, AIAA, and ION venues, reflecting its high technical and operational relevance. Scientific Awards and Recognitions: 2024 Harold Brown Award – Highest U.S. Air Force scientific honor 2024 General Bernard A. Schreiver Award 2025 AETC Airmen of the Year Multiple Air Force Outstanding Scientist/Engineer Awards (2017–2023) Best Paper Award, ACM SIGGRAPH i3D 2013 Forbes' The Greatest Young Inventors in America (2012) NSF GK-12 Fellow (2006) Dr. Nykl has advised numerous graduate students and collaborated extensively on projects involving automated aerial refueling, 3D reconstruction, and cyber education. He has secured significant research funding, including a $100,000 Ohio Third Frontier grant. His work has led to multiple patents and technology transfers. He leads research integrating virtual worlds, digital twins, and augmented reality for both research and pedagogy. Laboratories and Research Teams: His work is conducted within AFIT’s research ecosystem, involving collaborations with the Air Force Research Laboratory (AFRL), Boeing, and academic partners. He leads projects under the Aerial Refueling Systems Advisory Group (ARSAG) and presents regularly at ION, AIAA, and IEEE conferences.

Alfred TaudesView profile

Professor

• Operations and Supply Chain Management
• Cryptoeconomics
• Blockchain Technology
• +7 more

Alfred Taudes is a Full Professor at the Department of Information Systems and Operations, Institute for Production Management, Vienna University of Economics and Business (WU Vienna). He holds a doctoral degree and a Habilitation from WU Vienna in Business Administration and Management Information Systems, and a Magister degree from Vienna University. He has held assistant professorships at WU and visiting professorships at Augsburg, Münster, Essen, and Tsukuba University, Japan. He joined WU permanently in 1993 and served as head of the Department of Information Systems and Operations from 2010 to 2016. His research spans Operations and Supply Chain Management , Marketing Engineering , Knowledge Management , and the impact of Big Data and Blockchain on production systems. Using Complexity Science and Cryptoeconomics , he investigates digital production, integrated value chains, and market designs. He teaches undergraduate and graduate courses including Operations Strategy, Data Science, and IT seminars in WU’s International Supply Chain Master program, and has also taught at Japanese universities. His recent publications focus on blockchain privacy (e.g., CoinJoin analysis), CBDCs, MiCAR regulation, decentralized federated learning, and digital custody, reflecting a strong trend toward cryptoeconomics and blockchain-based systems in operations and finance. These works appear in top journals and conferences in information systems, security, and operations research. Cooperation Officer of the Year 2013/14 Distinguished Paper Award WI 2009 VHB Best Paper Award Nomination VHB Best Paper Award Dr. Wolfgang Houska - Recognition Award Alfred Taudes has coordinated major research projects such as the WWTF-project “Integrated Demand and Supply Chain Management” and the Special Research Area Adaptive Models in Economics and Management Science. He currently leads the research group on Cryptoeconomics at WU and chairs the scientific board of the Austrian Internet Offensive . His leadership extends to project management in initiatives like the Austrian Blockchain Center and research on decentralized finance and digital assets. He is actively involved in academic service, including organizing conferences like DEXA 2022, serving on editorial boards, and advising on research policy. His lab and research group focus on blockchain applications, digital transformation in operations, and the societal implications of big data.

Anthony HornofView profile

Professor

• Human-Computer Interaction
• Cognitive Modeling
• Eye Tracking
• +9 more

Anthony Hornof is a Professor in the Department of Computer Science at the University of Oregon, part of the College of Arts and Sciences. He has been a faculty member since 1999 and was granted tenure in 2005. His research is centered on human-computer interaction, with strong emphases on cognitive modeling, eye tracking, and assistive technology. He leads an active research laboratory and has secured substantial funding from the National Science Foundation and the Office of Naval Research. University: University of Oregon School: College of Arts and Sciences Department: Department of Computer Science Position: Professor Email: hornof@uoregon.edu, hornof@cs.uoregon.edu Office: 356 Deschutes Hall Phone: (541) 346-1372 Education: B.A. in Computer Science, Columbia University, 1988 M.S. in Computer Science and Engineering, University of Michigan, 1996 Ph.D. in Computer Science and Engineering, University of Michigan, 1999 Research Interests: Dr. Hornof's research lies at the intersection of human cognition and computing. He is particularly interested in understanding and modeling the perceptual, cognitive, and motor processes involved in human-computer interaction. His work uses eye tracking both as an evaluation tool for cognitive models and as a real-time input method for creative expression and accessibility. A major focus is assistive technology, especially developing tools like EyeDraw that enable children with severe motor impairments to create art using only eye movements. He also explores eye-controlled musical compositions, bridging technology and artistic expression. His research is grounded in participatory design, involving end-users directly in the development process. Publication Trends: His recent publications demonstrate a consistent focus on modeling human behavior in complex interactive tasks. Key themes include visual search strategies, dual-task performance, cognitive modeling using eye-tracking data, and accessibility. His work spans top venues in HCI (CHI, TOCHI), cognitive science (CogSci, ICCM), and specialized conferences like ETRA and NIME. There is a strong methodological thread involving data calibration, model validation, and the development of predictive tools for interface design. Scientific Awards: Best Paper Award (Top 1%) at CHI 2014 (two papers) Honorable Mention Paper (Top 5%) at CHI 2010 Siegel-Wolf Award for Best Applied Paper at ICCM 2010 Advising and Grants: Dr. Hornof actively seeks to mentor exceptional undergraduate students, graduate students, and postdoctoral researchers in his lab. He emphasizes rigorous and creative scientific research. He has been awarded over $2.9 million in single-investigator research grants from prestigious agencies including the National Science Foundation (NSF) and the Office of Naval Research (ONR). Notably, he served as an NSF Program Director from 2012 to 2014, contributing to funding decisions for approximately $65 million in research. Labs and Teams: He leads the Human-Computer Interaction Laboratory at the University of Oregon, where interdisciplinary research is conducted on cognitive modeling, eye tracking, and assistive technologies. His team has developed software such as VizFix for visualizing eye-tracking data and has ported the Eyegaze system to Macintosh. The lab fosters collaborations with new media artists and musicians, and engages in participatory design with children who have disabilities.

• Software Engineering
• Artificial Intelligence
• AI Trustworthiness Assessment (SE4AI)
• +5 more

Gias Uddin is an Associate Professor at York University's Lassonde School of Engineering and an Adjunct Professor at the University of Calgary . His research bridges Software Engineering (SE) and Artificial Intelligence (AI) , focusing on AI Trustworthiness Assessment (SE4AI) and AI-Driven Productivity Tools (AI4SE) . PhD in Software Engineering & AI, McGill University (2018) MSc in Software Engineering, Queen’s University (2008) BSc in Computer Science & Engineering, Bangladesh University of Engineering and Technology (2004) His research explores: Metamorphic Relations for LLM Hallucination Detection AI-Enhanced Software Documentation Foundational Models for Runtime System Modernization Developer-Centric AI Tooling Recent article trends show expertise in LLM Trustworthiness , Low-Code Platforms , and IoT Developer Communities . Awards include Distinguished Paper at FSE 2025 , multiple IBM Champion recognitions, and York Research Award . He leads the Data Intensive Software Analytics (DISA) Lab and mentors PhD students in SE-AI Intersections .

Pradip SharmaView profile

Associate Professor

• Cybersecurity
• Artificial Intelligence
• Blockchain
• +5 more

Dr. Pradip Sharma is an Associate Professor of Cybersecurity & AI at the University of Aberdeen, UK, within the School of Natural and Computing Sciences, Department of Computing Science. He is a globally recognized academic and researcher with expertise in Cybersecurity, Artificial Intelligence, Blockchain, and Edge Computing. His research interests span multiple domains including Cybersecurity, Blockchain, Edge Computing, Software-defined Networking, and IoT Security. Dr. Sharma's work focuses on developing innovative solutions for security challenges in emerging technologies, with particular emphasis on privacy-aware AI systems, secure data sharing frameworks, and intelligent network security mechanisms. His interdisciplinary approach bridges theoretical foundations with practical implementations across healthcare, smart mobility, and consumer electronics domains. Senior Fellowship Advance HE (SFHEA) IEEE Senior Member (SMIEEE) Dr. Sharma actively supervises doctoral researchers and is accepting new PhD students in Computing Science. His funded research portfolio exceeds £1M from sources including EPSRC, Innovate UK, and international agencies. Current projects include 'Secure, Privacy-aware, and Trusted Data Share in Smart Mobility' (EPSRC, £200K), 'ZECURE Data Exchange Platform' (Innovate UK, £236K), and 'Quantum-resistant Cybersecurity' (Royal Embassy of Saudi Arabia, £73K). He also serves as an editor for leading journals and is a regular keynote speaker at international conferences.

Freek J. BeekmanView profile

Professor

• Biomedical Imaging
• Nuclear Imaging
• Image Reconstruction Algorithms
• +12 more

Prof. Freek J. Beekman is a Full Professor and head of the Biomedical Imaging section within the Department of Radiation Science & Technology at Delft University of Technology (TU Delft), Faculty of Applied Sciences. He is a leading figure in biomedical imaging, with extensive contributions to nuclear imaging technologies, including SPECT, PET, and CT. His research spans detector development, image reconstruction algorithms, hybrid photonic imaging, and the application of artificial intelligence in medical imaging. Research Interests: His work focuses on advancing imaging modalities through innovations in hardware (e.g., multi-pinhole collimators) and software (e.g., deep learning for attenuation correction). He has pioneered ultra-high-resolution imaging systems, particularly for preclinical and clinical SPECT, and has developed integrated platforms like U-SPECT-BioFluo. His recent research explores glymphatic delivery of nanoparticles, infection imaging, and AI-driven reconstruction techniques, reflecting a strong translational focus. Publication Trends: His most recent publications (2021–2023) emphasize deep learning in SPECT, multi-isotope imaging, high-resolution ex vivo systems, and applications in neuroimaging and oncology. The articles demonstrate a consistent focus on improving image quality, resolution, and clinical utility through physics-informed and AI-enhanced methods. Scientific Awards: NWO Physics Valorization Prize Innovation of the Year Award by the World Molecular Imaging Society (2015, 2018) Edward Hoffman Memorial Award (2017) Bruce Hasegawa Memorial Award (2021) FOM Valorization Award (2013) TU Delft Entrepreneurial Award (2010) Advising and Grants: While specific student names are not listed, his leadership in large collaborative projects and supervision of numerous publications suggests active mentoring. He has secured significant funding through national and international grants, evidenced by his invention of over 20 patent families and successful technology transfer. His founding and leadership of MILabs BV (sold to Rigaku) highlights his impact on commercialization and industry-academia collaboration. Labs and Teams: He leads the Biomedical Imaging research group at TU Delft, which develops cutting-edge imaging systems such as VECTor (SPECT-PET) and EXIRAD-HE. His teams have produced technologies used globally in academic and pharmaceutical research, contributing to tracer development and therapeutic innovation.

Robin CrockettView profile

Researcher

• Document Forensics
• Academic Integrity
• Contract Cheating
• +9 more

Dr Robin Crockett is the University Academic Integrity Lead at the University of Northampton, based in the Academic Registry. He is a mathematician-ethicist actively engaged in research and professional development in academic integrity, document forensics, and the detection of contract cheating and AI-generated text. He is a member of the European Network for Academic Integrity (ENAI), co-founder of the Midlands Integrity Group (UK), and has advised UK policymakers on legislation to ban essay mills. He holds Chartered Scientist and Chartered Mathematician status. MPhil, The Management of Electricity Supplies via Storage as Hydrogen, Cranfield University Master, Energy Conservation and the Environment, Cranfield University PhD, Electrostatic Damage to Semiconductor Devices, University of Southampton Master, Natural & Electrical Sciences, University of Cambridge Bachelor, Natural & Electrical Sciences, University of Cambridge Dr Crockett's research centers on document forensics and academic integrity, with core interests in Fourier theory, time-series analysis, and stylometry for identifying contract cheating. His work increasingly addresses the challenges posed by generative artificial intelligence in education. He applies mathematical and statistical methods to analyze linguistic cues, writing styles, and embedded information in student submissions. His recent publications highlight a strong trend toward understanding and mitigating academic misconduct in the AI era. Topics include AI-text detection uncertainties, forensic stylometry, and policy development for generative AI misuse. Earlier work includes environmental research on radon remediation and signal processing applications in telecommunications. Chartered Scientist Chartered Mathematician Dr Crockett has supervised PhD students, including Believe Nwamae in Computing. He has secured internal research funding, such as the Small Grants Scheme for Early Career Researchers at the University of Northampton for a project on AI-synthesized text detection. He has been an Academic Visitor at Loughborough University and served on the Turnitin Advisory Board, indicating active collaboration and external engagement. He frequently presents at academic events and contributes to policy discussions. He is affiliated with research networks including the European Network for Academic Integrity (ENAI) and the European Geosciences Union (as a former Scientific Officer). His work is supported by institutional and collaborative projects focused on advancing machine discernment of academic misconduct.

• Network Performance
• Computer Networks
• Cloud Computing
• +7 more

Dr. Theophilus A. Benson is a Professor of Electrical and Computer Engineering at Carnegie Mellon University (CMU) and CMU-Africa. His research focuses on improving network performance and availability in data centers, clouds, and edge networks. He leads projects addressing the digital divide in Africa through initiatives like the African Internet Observatory (AIO), which analyzes connectivity challenges and infrastructure resilience. His work spans programmable networks (eBPF/P4), CDN optimizations, and network management frameworks. Education: B.S. from Tufts University, Ph.D. from University of Wisconsin-Madison, Postdoc at Princeton University. Research Interests: Network state management, programmable substrates, digital equity, measurement systems, and network security. His group develops tools like NetEdit (eBPF management), JSBench (mobile web performance), and the African Internet Observatory's probe network. Recent Trends: Publications emphasize eBPF management frameworks, African network analysis, and data-driven CDN improvements. Key projects include subsea cable impact studies, QUIC protocol analysis, and deploying measurement probes across Africa. Awards: NSF CAREER Award, Google/FA Faculty Awards, SIGCOMM Test of Time Award, and DARPA ISAT membership. Advising & Grants: Active in mentoring MS/PhD students and postdocs. Current grants include NSF funding for data-driven web performance and IoT security. Collaborations with Meta and industry partners enhance real-world system deployments. Labs & Teams: Leads the AIO initiative with local African stakeholders. Research group includes collaborators from National Taiwan University and partnerships with institutions like TU Delft (keynote on eBPF).

Fabrizio LombardiView profile

Professor

• Fault-tolerant computing
• VLSI CAD
• Testing
• +7 more

Fabrizio Lombardi is the ITC Endowed Professor at Northeastern University's Department of Electrical and Computer Engineering, part of the College of Engineering. He previously held faculty positions at Texas Tech University, University of Colorado-Boulder, and Texas A&M University. He earned his B.Sc. from the University of Essex (1977), M.Sc. and Ph.D. from the University of London (1982). His research focuses on fault-tolerant computing, VLSI CAD, quantum computing, and configurable computing systems. He has led major projects like the NSF-funded Neural-Network-based Stochastic Computing Architectures for Machine Learning . He holds leadership roles including President of the IEEE Nanotechnology Council (2022-2023), IEEE Computer Society Vice President (2021), and IEEE PSPB member. His 200+ publications span IEEE Transactions on Computers, Nanotechnology, and Design & Test. Awards include IEEE Fellow, Søren Buus Outstanding Research Award, and multiple research fellowships. His work bridges theory and application, emphasizing defect-tolerant nanosystems and energy-efficient computing hardware. Recent innovations include approximate computing methodologies and secure PUF-based hardware designs.

Stefan NagyView profile

Assistant Professor

• Software Engineering
• Software Quality Assurance
• Computer Systems
• +5 more

Stefan Nagy is an Assistant Professor at the Kahlert School of Computing at the University of Utah . He holds a Ph.D. in Computer Science from Virginia Tech (2022) and a B.S. in Computer Science from the University of Illinois Urbana-Champaign (2016). His primary research focuses on Software Engineering , Software Quality Assurance , and Computer Systems , with specific interests in program analysis, automated bug discovery, and efficient quality assurance for opaque systems. He teaches courses such as CS 4440: Introduction to Computer Security and CS 5963/6963: Applied Software Security Testing . His recent publications (2025) include work on fuzzing frameworks for binary-to-C decompilers, automated API harness generation, and kernel fuzzing configuration optimization. He advises students in these areas and collaborates with groups like the Utah Software Security Group. He is affiliated with the FuTURES 3 Lab and maintains a research website with full publication details. His work addresses challenges in closed-source software analysis, security ethics, and digital forensics.

Tommy LöfstedtView profile

Associate Professor

• Machine Learning
• Computer Vision
• Medical Image Analysis
• +4 more

Tommy Löfstedt is an Associate Professor at Umeå University , affiliated with the Department of Computing Science and the Department of Mathematics and Mathematical Statistics. His research focuses on machine learning , computer vision , and medical image analysis , with applications in life sciences, radiation therapy, and biomedical imaging. He leads multiple research projects, including AI-driven delineation in radiation therapy, quantitative MRI for radiotherapy, and machine learning for plant nutrient uptake. Current research emphasizes structured regularization methods to improve model interpretability and robustness. Key applications include medical image segmentation , Alzheimer's classification , and uncertainty estimation in MRI . Recent publications highlight his work on morphological regularization , adversarial attack mitigation , and multi-task learning in medical imaging contexts. His projects span 2022–2026 with funding for pediatric oncology automation and gynecological cancer staging. Affiliated with both computing and mathematical departments, he bridges algorithm development with applied mathematical frameworks in medical and life science domains.

• Wireless Communications
• Network Security
• Quality of Experience (QoE)
• +7 more

Tasos Dagiuklas is a Professor in the Department of Computer Science and Technology within the School of Engineering and Technology at the University of Bedfordshire. With over 168 publications spanning from 1995 to 2025, he has established himself as a leading researcher in telecommunications and network systems. His extensive publication record demonstrates continuous scholarly contribution across multiple decades in the field. Professor Dagiuklas' research focuses on wireless communications, edge computing, 5G/6G networks, quality of experience (QoE), and federated learning . His work bridges theoretical networking concepts with practical applications, particularly in multimedia delivery and security. He has developed significant expertise in video streaming optimization, network security mechanisms, and resource management in emerging network architectures. His research consistently addresses the evolving challenges of modern communication systems, with recent work increasingly focusing on AI integration in networking. Analysis of his recent publications (2023-2025) reveals a strong trend toward edge computing, federated learning, and security applications in next-generation networks. His work demonstrates a strategic shift from traditional networking concerns to more complex systems involving AI integration, energy efficiency, and heterogeneous environments. The publications show consistent collaboration with researchers across multiple institutions, with particularly strong partnerships with Muddesar Iqbal, Ilias Politis, and Stavros Kotsopoulos. Professor Dagiuklas has made substantial contributions to the academic community through his extensive publication record in high-impact venues including IEEE journals and conferences. His work has evolved from foundational networking research to cutting-edge investigations of AI-enhanced communication systems, reflecting the broader trajectory of the field itself. His research demonstrates both technical depth in specific networking challenges and breadth across multiple application domains.

Patrick ParkView profile

Assistant Professor

• Social Network Analysis
• Computational Sociology
• Open Source Software Research
• +5 more

Dr. Patrick Park is an Assistant Professor at the Software and Societal Systems Department within Carnegie Mellon University's School of Computer Science. His work bridges computational and social sciences to analyze network dynamics, digital communication, and open source systems. Current position: Assistant Professor Institution: Carnegie Mellon University Department: Software and Societal Systems Park's research focuses on social network analysis, behavioral modeling, and computational sociology. Key contributions include studies on network diversity, geospatial visualization techniques, and digital communication patterns across civilizations. His recent publications (2023-2024) highlight expertise in network visualization, social contagion, and open source innovation. Earlier work spans topics like organizational classification, user behavior paradoxes, and cross-cultural communication networks.