Find Academic Supervisors

• Distributed Systems
• Service-Oriented Computing
• Cloud Computing
• +4 more

Winfried Lamersdorf is a full professor in the Department of Computer Science at the University of Hamburg , leading the Distributed Systems (VSIS) research unit. His career spans from IBM's European Networking Centre to leading numerous DFG, EU, and industry-funded projects. Major research interests include: Service-oriented computing (SOA, Web Services) Mobile and ubiquitous systems Agent-oriented software construction Self-organizing systems Context-aware middleware Cloud/edge computing Applications in E-Health, Smart Cities, and Industrial Informatics Recent projects like SANE (Smart Networks for Citizen Participation), CloudAware (context-adaptive mobile cloud systems), and FYPA²C (future production automation) highlight his focus on urban data spaces, energy-efficient mobile systems, and evolutionary software management. His scientific contributions span 200+ publications, with 15 recent articles covering topics such as: Complex event processing Decentralized blockchain coordination Context-aware computation offloading Model-driven production system evolution BDI agent architectures Service composition patterns Advising over 20 PhD students including Heiko Bornholdt (Smart Cities), Philipp Kisters (Distributed Platforms), and Gabriel Orsini (Mobile Clouds, 2016), Lamersdorf has shaped research in distributed applications through long-term collaborations with institutions like TU Munich, HSU Hamburg, and international IFIP committees.

Dimitrios KanelisView profile

Assistant Professor

• Financial Reporting
• Corporate Disclosures
• Information Uncertainty
• +6 more

Dimitris Kanelis is an Assistant Professor in Financial Accounting at Maastricht University School of Business and Economics (SBE). He completed his PhD at Lancaster University Management School (LUMS) and was a 2022 visiting scholar at the University of Michigan's Ross School of Business. His academic work bridges financial reporting, computational linguistics, and corporate governance. Education : International MSc in Management - CATOLICA-LISBON School of Business and Economics MSc in Finance - Lancaster University Management School BSc in Accounting and Finance - University of Macedonia Research Focus : Financial communication and narrative disclosures Information uncertainty in capital markets Machine learning applications in accounting data analysis Interdisciplinary accounting research Publications : 2024 doctoral thesis on narrative disclosures' role in fair value reporting Awards : Associate Fellow of Advance HE (UK) Teaching Experience : Maastricht SBE: Undergraduate Financial Accounting and Postgraduate Advanced Financial Accounting modules Lancaster LUMS: Quantitative Methods, Auditing, and Reporting modules Professional Activities : Participation in Hawaii Accounting Research Doctoral Institute Presentations at European Accounting Association conferences Collaboration with University of Michigan scholars

Radoslava Danailova HristovaView profile

Associate Professor

• Grid Computing
• Cloud Computing
• Business Process Management
• +3 more

Radoslava Danailova Hristova serves as an Associate Professor at the Faculty of Mathematics and Informatics, Sofia University St. Kliment Ohridski, specializing in advanced computational systems. Her work focuses on integrating grid and cloud technologies with business processes and scientific applications. Her research spans Grid Computing , Cloud Infrastructure , and Service-Oriented Architectures , with significant contributions to distributed systems management. Key areas include: Business Process Management in heterogeneous grid environments Performance monitoring frameworks for HPC applications Middleware development for virtual organizations Resource allocation strategies for scientific modeling Analysis of her 15 most recent publications reveals a consistent focus on practical grid/cloud implementations, particularly in evolving middleware infrastructure (2012-2014) and business process integration. Her work bridges theoretical physics applications with enterprise-level distributed systems. No formal scientific awards are documented in available sources. While no current advisees or major grants are explicitly listed, her publications indicate active collaboration with international research teams including EGI (European Grid Infrastructure) and g-Lite middleware developers. Hristova contributes to Sofia University's Grid Farm operations, supporting physics experiments and environmental modeling. Her technical leadership includes developing ROOT services, accounting systems, and security frameworks for distributed scientific computing environments.

Fan YangView profile

Assistant Professor

• Data Mining
• Machine Learning
• Trustworthy AI
• +9 more

Fan Yang is an Assistant Professor in the Department of Computer Science at Wake Forest University. He earned his Ph.D. in Computer Science from Rice University under Dr. Xia (Ben) Hu. His industry experience includes roles at J.P. Morgan AI Research, Visa Research, and Meta AI. Research Focus: Trustworthy AI, emphasizing Interpretable Learning and Model Explainability. He aims to make AI systems auditable, ethical, and robust. Applications: Misinformation Detection, Recommender Systems, Health Informatics, and Financial Forecasting. Interdisciplinary Interests: Collaborations with Neurosciences, Psychology, and Linguistics. Scientific Awards: Received CRII award (IIS Division) and R21 award (NCI) for his research initiatives. Teaching: Instructs courses on Fundamentals of Computer Science (CSC 112) and Machine Learning (CSC 374/674).

• Vascular Diseases
• Perivascular Adipose Tissue (PVAT)
• AMP-activated Protein Kinase (AMPK)
• +5 more

Professor Simon Kennedy is a Professor of Vascular Pharmacology within the School of Cardiovascular & Metabolic Health at the University of Glasgow, where he has been a faculty member since 2006. He currently serves as the Senior Senate Assessor for Student Conduct and holds various administrative roles including membership on the University Court, Education Policy & Strategy Committee, Finance Committee, and Audit and Risk Committee. Additionally, he is actively involved with the British Pharmacological Society, serving on their Finance and Awards Committees, and is a member of the editorial boards of two top-ranking pharmacology journals. Professor Kennedy's primary research focuses on vascular diseases and comorbidities, with particular emphasis on the role of perivascular adipose tissue (PVAT) in vascular function. His work investigates the effects of AMP-activated protein kinase (AMPK) within PVAT and the vascular wall, the impact of hypoxia on sphingosine kinase (SK) expression and function, and the role of connexins in cell communication affecting vascular function in both pulmonary and systemic circulations. His research spans cellular signaling mechanisms and vascular structure and function. Analysis of his recent publications reveals a consistent focus on vascular pharmacology with particular emphasis on AMPK signaling pathways, perivascular adipose tissue function, and vascular responses to various stressors. His work demonstrates strong interdisciplinary collaboration across pharmacology, vascular biology, and biomedical engineering, with increasing focus on translational applications including drug-eluting stent technology and vascular monitoring systems. Professor Kennedy serves as the coordinator for Level 4 of the Pharmacology degree program and teaches various final-year options, including an in vivo skills course funded by a British Pharmacological Society teaching grant. He acts as an academic advisor to approximately 40 undergraduate students and contributes to teaching across multiple degree programs including MBChB and BDS degrees. His external academic engagements include serving as an external examiner at two Russell Group universities and as treasurer of the Scottish Cardiovascular Forum. His research is conducted through the Cellular Signalling & Mechanisms and Vascular Structure & Function research groups, where he collaborates with colleagues within the School of Cardiovascular & Metabolic Health, College of Science and Engineering, and external partners. His work bridges basic science with clinical applications, particularly in understanding vascular pathophysiology and developing therapeutic approaches for vascular diseases.

Hsiang-Jen HongView profile

Assistant Professor

• Cybersecurity
• Blockchain Technology
• Computer Networks
• +4 more

Hsiang-Jen Hong is an Assistant Professor in the Department of Computer Science at Western Washington University, joining in September 2023. His research spans cybersecurity, blockchain technology, and computer networks, with a focus on algorithmic techniques and optimization problems in combinatorial optimization and game theory. Recently, he has explored critical Web3 technologies like Multi-Party Computation (MPC) and Zero-Knowledge Proofs (ZKPs). Prior to WWU, he worked as a postdoctoral associate at the University of Colorado at Colorado Springs, concentrating on cybersecurity and blockchain in distributed systems. He earned his Ph.D. in Computer Science and Information Engineering from National Taiwan University of Science and Technology in 2018. Research Interests : Blockchain Technology Network Security Computer Networking Combinatorial Optimization Game Theory Multi-Party Computation (MPC) Zero-Knowledge Proofs (ZKPs) Scientific Contributions : His work includes publications in prestigious journals like Elsevier Computer Networks and IEEE Transactions on Dependable and Secure Computing, as well as conferences such as IEEE ICDCS and IEEE IWQoS. His research on autonomous routing for payment channel networks was recognized by the Smart Contract Research Forum in Research Pulse Issue 81. Hobbies : Outside academia, he enjoys traveling, cooking, coffee, and independent music.

Alexandra NillesView profile

Assistant Professor

• Sustainable Robotics
• Robotics for Climate Change
• Planning Algorithms
• +9 more

Alexandra Nilles is an Assistant Professor of Computer Science at Western Washington University since Fall 2024. Previously, she was a Postdoctoral Associate at Cornell University's Collective Embodied Intelligence (CEI) Lab from 2021-2024, where she worked under Prof. Kirstin Petersen. Her research focuses on sustainable robotics, distributed AI, and embodied intelligence for environmental applications. Education: PhD in Computer Science (2020) from University of Illinois at Urbana-Champaign, advised by Dr. Steven LaValle; BS in Engineering Physics from Colorado School of Mines. Her work develops minimalist mobile robot systems that leverage embodied intelligence and environmental interactions to reduce resource demands (battery, sensors, communication) while maintaining provable performance guarantees. Applications include under-canopy forestry monitoring, micro-scale medical agents, and carbon-capture auditing. She has published in venues such as ICRA, IROS, IJRR, and WAFR, often addressing scalability challenges in chaotic or constrained environments. Key methodologies span formalized planning algorithms, human-in-the-loop control interfaces, and inflatable soft robotics for collectives. Awards: Cyber-Physical Systems Rising Star (2023) Microsoft Future Leader in Robotics and AI (2023) Nilles received NSF support for robotic mouse toy development during her PhD and served as interim PI for Cornell's CEI Lab through the NSF Career-Life Balance Program. She actively participates in interdisciplinary workshops connecting math, art, and robotics.

Amin KaramiView profile

Associate Professor

• Artificial Intelligence and Data Science
• Big Data Technologies
• Blockchain and Cryptocurrencies
• +4 more

Dr Amin Karami is an Associate Professor in the School of Computer Science and Digital Technologies (CDT) at the University of East London, within the School of Architecture, Computing and Engineering. He serves as course leader for MSc Big Data Technologies and leads postgraduate programs, having secured £1.23 million in funding from the Office for Students to develop inclusive AI and Data Science courses for non-STEM and far-STEM graduates. His research spans Artificial Intelligence, Big Data Analytics, Blockchain, and Optimization, with focus on Industry 5.0 applications. Current work addresses federated learning heterogeneity, smart contract security, healthcare fraud detection, and ethical AI implementation. He develops cloud-based platforms for large-scale data processing and computational intelligence solutions for real-world industry challenges. Recent publications demonstrate strong trends in federated learning techniques, blockchain vulnerability mitigation, and big data applications across healthcare, finance, and social media. His work consistently bridges academic research with industry needs through partnerships with Multiverse and Cambridge Spark, emphasizing practical solutions for credit risk assessment, satellite telemetry, and personalized marketing. Scientific recognition includes: UEL Vice-Chancellor & President Impact & Innovation Award for Industry 4.0 readiness (2023) Fellow of the Higher Education Academy (FHEA) Dr Karami actively supervises UG/PG/PhD students while leading curriculum innovation through externally funded projects. His Chainlink Bootcamp initiative connects academia with industry practitioners, and he serves as external examiner and conference program chair. Significant grant achievements include developing diversity-focused STEM pathways that enhance graduate employability through industry-aligned training in AI and Data Science.

Umar Mukhtar IsmailView profile

Senior Lecturer

• Cyber Threat Intelligence
• Security and Privacy Requirement Engineering
• AI-enabled Cyber Security
• +9 more

Dr. Umar Mukhtar Ismail serves as a Senior Lecturer in the Department of Computer Science and Digital Technologies at the University of East London's School of Architecture, Computing and Engineering. He leads the BSc (Hons) Cyber Security Networks and BSc (Hons) Cloud Computing programmes while teaching core modules including Cyber Security, Security Management, and Advanced Topics in Cyber Security. His research spans critical cybersecurity domains including AI-enabled threat intelligence, security requirement engineering, incident response frameworks, and cloud security management. He specializes in developing security solutions for critical infrastructure, healthcare systems, and supply chains using standards like ISO27001 and NIST frameworks, with particular focus on cyber resilience and threat modeling methodologies. Analysis of his 12 recent publications reveals consistent emphasis on creating structured security frameworks for cloud transparency, incident handling, and supply chain protection. His work increasingly integrates machine learning for malware detection and vulnerability prediction, demonstrating evolving expertise in adversarial AI analysis and ontology-based threat representation across healthcare and critical infrastructure contexts. Scientific recognition includes: Fellow of the Higher Education Academy Dr. Ismail actively contributes to European Union-funded research projects enhancing security in cyber-physical systems and healthcare infrastructure. He currently supervises MSc dissertations and PhD candidates while developing novel approaches to security transparency and audit frameworks, maintaining active collaborations through IEEE, BCS, and ISACA memberships.

Michael WalfishView profile

Professor

• Computer Systems
• Network Security
• Distributed Systems
• +2 more

Michael Walfish is a Professor at the Courant Institute of Mathematical Sciences within New York University . His work focuses on computer systems, network security, and verifiable computation with applications in distributed systems and cybersecurity. Current faculty member (not retired or former staff) Teaching experience includes advanced systems courses like Operating Systems and Honors Operating Systems at NYU Research interests span multiple dimensions: Network security and defense mechanisms Verifiable computation systems Distributed system design Zero-knowledge proofs applications Hardware and software security Recent publications demonstrate strong focus on: Zero-knowledge systems (Zombie, Verifiable ASICs) Web and email security (Pretzel, Yesquel) Probabilistic verification (Less is more) Cryptographic protocols in systems (Cobra, DQE) Scientific recognition: Best Paper Award at SOSP 2017 Distinguished Student Paper Award at Security 2016

Zuzana KubaščíkováView profile

Associate Professor

• Accounting
• Auditing
• Financial Analysis
• +3 more

Zuzana Kubaščíková serves as an Associate Professor in the Department of Accounting and Auditing at the Faculty of Economic Informatics, University of Economics Bratislava, contributing to academic programs in accounting and financial disciplines. Her educational foundation includes: Doctoral studies (2006–2009) at University of Economics Bratislava, Faculty of Economic Informatics, Department of Accounting and Auditing, with dissertation: "Prediction of development using financial statements of microeconomic entities" Master's degree (2001–2006) in Accounting and Audit from University of Economics Bratislava, Faculty of Economic Informatics Specialized training: Financial Management at University of Ljubljana (2009), International Business with French at University Blaise Pascal (2006), Russian Language at Pushkin Institute Moscow (2007, 2009), and Summer University at Asian University Thailand (2009) Certificate of Slovak Chamber of Accountants as Balance Accountant Her research centers on quantitative financial analysis, specializing in predictive modeling of microeconomic entities through accounting data. She integrates auditing principles with computational forecasting techniques, emphasizing practical applications of financial statement analysis for business decision-making. Her work bridges theoretical accounting frameworks with empirical economic forecasting methodologies. As an active academic, she participates in departmental research initiatives and contributes to the educational mission of the Faculty of Economic Informatics through curriculum development and instruction in core accounting disciplines.

Heather ShawView profile

Lecturer

• Digital Behavioral Signatures
• Behavioral Analytics
• Human-Computer Interaction
• +5 more

Dr. Heather Shaw is a Lecturer in Psychology at Lancaster University, specializing in digital behavioral analytics. Her research investigates the intersection of situational and individual factors influencing human behavior through digital signatures, with applications in personalized systems and behavioral change detection. Focuses on interdisciplinary research methodologies Develops ethical frameworks for digital data exploration Creates open-source tools for behavioral measurement Research interests include: Digital behavioral signatures Human-computer interaction Computational reproducibility Ethical AI implementation Behavioral biometrics Smartphone usage analysis Recent publications emphasize: Ethical decision-making in behavioral data research Reproducibility challenges in computational methods Biometric identity through digital behavior Measurement validity in technology scales Behavioral consistency across time Health impact of digital device usage She contributes to academic activities through: Conference participation Peer review for journals Workshop facilitation Expert panel engagements Research group collaborations

• Natural Language Processing
• Large Language Models
• Bias Detection
• +3 more

Zain Muhammad Mujahid is a PhD Fellow at the Department of Computer Science , University of Copenhagen (UCPH). His research focuses on Natural Language Processing with emphasis on Large Language Models (LLMs), bias detection, and fact-checking methodologies. Research Interests Factuality and bias prediction in news media LLM evaluation and error analysis Cross-lingual fact-checking systems Arabic-centric language modeling Evidence attribution in summarization AI safety in multilingual contexts Publications Zain's recent work addresses critical challenges in trustworthy AI, including automating error detection in NLG systems, developing cross-lingual bias detection frameworks (SAFARI), and creating benchmarks like Factcheck-Bench for evaluating automatic fact-checkers. His research also explores bilingual safety evaluation in Kazakh-Russian contexts and cultural adaptation of LLMs for Arabic language processing.

• Public Sector Accounting
• Taxation
• Public Audit
• +5 more

Dennis De Widt is an Associate Professor (Reader) in Accounting and Finance at Cardiff Business School, Cardiff University. His research focuses on public sector accounting and taxation with particular emphasis on public audit, tax administration, and local government finances across multiple countries including the UK, Germany, Netherlands, United States, and South Africa. His research interests encompass Intergovernmental and local government finances , Public budgeting and accounting , Public sector auditing , and Tax policy and administration (including transfer pricing). His work takes an interdisciplinary and internationally comparative approach, examining institutional dimensions of public financial management across different governance contexts. His recent publications reveal a strong focus on cooperative tax compliance models, public sector audit innovation, and the institutional pressures affecting tax administration systems. His research spans both traditional public finance topics and emerging areas where technology intersects with public financial management, such as AI applications in customs classification. Visiting Professorship, Université de Poitiers, L'Institut d'administration des entreprises (IAE), spring 2025 Wiley award Top Cited Article in Financial Accountability & Management, 2023 Fellow of the Higher Education Academy (FHEA) De Widt actively supervises doctoral students and has served as external examiner at institutions including University of Leicester and University of the Witwatersrand. He holds significant grant funding including the Cardiff University-University of Illinois System Grants Programme award (£4,000, 2025) and European Parliament Subcommittee on Tax Matters funding (£12,500, 2022). He contributes to policy through roles as Independent Adviser to the Welsh Government's Local Government Finance Distribution Sub-Group and as Executive Board Member of the British Accounting & Finance Association Special Interest Group for Public Services and Charities. He leads the Public Sector Accounting, Finance and Taxation Research Group (PACCFINTAX) at Cardiff Business School and serves as Associate Research Fellow of the Tax Administration Research Centre at the University of Exeter Business School.

• Machine Learning
• Deep Learning
• Computer Vision
• +7 more

Guy Hembroff serves as an Associate Professor in the College of Computing at Michigan Technological University, where he directs both the MS in Health Informatics program and the interdisciplinary PhD in Computational Science & Engineering program. His academic leadership spans computational health sciences and biomedical data science initiatives. Education: PhD in Computational Science and Engineering, Michigan Technological University MPA in Public Administration, Northern Michigan University BS in Finance and Economics, Michigan Technological University Hembroff's research focuses on human health applications of artificial intelligence, particularly in medical image analysis, natural language processing, and cybersecurity. His work bridges clinical needs with computational solutions through projects like fracture risk prediction from radiographs, lung nodule classification, and mental health intervention modeling. The Biomedical Data Science (BDS) Lab he founded integrates expertise across medicine, data science, and cybersecurity to tackle healthcare challenges. His recent publications demonstrate strong trends in applying deep learning to medical imaging (35%), natural language processing for health literacy (20%), and mental health analytics (15%), with growing emphasis on generative AI applications since 2023. Key methodological approaches include multitask learning, transformer models, and ensemble techniques tailored for healthcare data. Doctoral Advising: Harikrishnan C. (Medical Image Segmentation using AI) Chethana Kadirimangalam (Mental Health Intervention Modeling) Abel Reyes (Medical Image Segmentation and Computer Vision) Tim Van Wagner (Blockchain for Patient Data Auditing) Hembroff leads multiple externally funded research initiatives including the Tick-Talk geographical tick disease monitoring system (MI-SAPPHIRE grant), FHIR-enabled health information exchanges, and mental health intervention optimization models. His BDS Lab maintains active collaborations with Henry Ford Hospital and nonprofit healthcare networks for real-world implementation of health informatics solutions. The Biomedical Data Science Lab operates as a multidisciplinary hub combining clinical expertise with computational innovation. Current projects span physical and mental health domains, with particular focus on disease progression modeling, clinical decision support systems, and secure health data architectures. The lab's work directly informs both graduate curriculum development and healthcare industry partnerships.