Find Academic Supervisors

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +12 more

Ahmet Cüneyd Tantuğ is an Associate Professor in the Department of Artificial Intelligence and Data Engineering at the Faculty of Computer and Informatics, Istanbul Technical University (ITU). He has been a core faculty member since 2007 and is among the founders of the ITU Natural Language Processing Group. He has held key administrative roles, including Vice Dean (2011–2015) and Head of IT Department at ITU (2012–2020). BSc, MSc, PhD: Istanbul Technical University, Computer Engineering Guest Researcher: University of Copenhagen, Centre for Language Technology (2006–2007) Dr. Tantuğ’s research spans artificial intelligence, natural language processing, machine learning, and deep learning, with a focus on Turkish and other agglutinative languages. His work includes named entity recognition, dependency parsing, machine translation, word sense disambiguation, and text normalization. He has developed linguistic resources for Turkish and low-resource languages such as Amharic, and has contributed to financial AI and temporal expression extraction. His recent publications highlight advancements in Turkish NLP, including optimal vocabulary sizing, tokenization granularity for LLMs, and transformer-based models for named entity recognition. He has led multiple research projects funded by TÜBİTAK, the European Union, and the Ministry of Development. Scientific awards include: Bedri Karafakioğlu Special Award (2000) Siemens Excellence Award (2007) TeknoGirişim Sermaye Desteği Ödülü (2010) He has supervised numerous master’s and PhD students, with theses on topics such as dependency parsing, named entity recognition, and text normalization. He has also served as a consultant for private sector projects in banking, software, and telecommunications, and as a referee for TÜBİTAK, TEYDEB, and the Ministry of Industry and Technology. Dr. Tantuğ leads and participates in active research projects including Turkish text normalization from user-generated content and improving dependency parsing with augmented features. He is a founding member of the ITU Natural Language Processing Group, which continues to be a central hub for NLP research in Turkey.

Burcu TungaView profile

Associate Professor

• Image Processing
• Applied Mathematics
• Computer Science
• +12 more

Burcu Tunga is an Associate Professor in the Department of Mathematics at Istanbul Technical University, Faculty of Science and Letters. She holds a PhD in Computational Science and Engineering from the same institution and has been an active academic since 2005, progressing from Lecturer to her current rank. She has held key administrative roles, including Deputy Head of Department and membership in university-wide promotion and doctoral committees. PhD: Computational Science and Engineering, Istanbul Technical University (2004–2010) BS: Mathematics, Istanbul Technical University (1995–2000) Her research lies at the intersection of applied mathematics and computer science, with a strong emphasis on image processing, data modeling, and High Dimensional Model Representation (HDMR) . She develops and applies advanced mathematical models for image denoising, color-to-gray conversion, hyperspectral analysis, and machine learning-based diagnostics. Her work integrates fractional calculus, deep learning, and tensor decomposition to solve complex problems in medical imaging, agriculture, and materials science. Recent publications (2022–2025) show a strong trend toward hybrid models combining HDMR with deep learning and fractional operators , applied to tasks such as coffee leaf disease detection, wood defect imaging, and hyperspectral anomaly detection. These reflect a consistent focus on enhancing image quality, feature extraction, and pattern recognition through novel mathematical frameworks. Her scientific contributions are recognized through active research funding and a growing publication record. Key projects include: Anomaly Detection in Hyperspectral Images with HDMR (BAP-funded, 2024–2025) Disease Detection in Coffee Leaves with Deep Learning (completed, 2024) Content-Based Image Retrieval with HDMR (completed, 2018–2021) Burcu Tunga advises several graduate students and collaborates widely across disciplines. She leads research involving tomographic reconstruction, stress wave analysis in trees, and financial time series prediction. Her lab focuses on developing non-destructive evaluation techniques, medical CAD systems, and intelligent image processing algorithms , often leveraging HDMR as a core methodological framework.

Anne MoorheadView profile

Senior Lecturer

• Health Communication
• Communication Technologies in Healthcare
• Mental Health
• +6 more

Dr. Anne Moorhead is a Senior Lecturer at Ulster University within the School of Communication and Media . She holds advanced degrees including a PhD in Biomedical Sciences (Human Nutrition) , an MSc in Nutrition and Dietetics , and a MA in Psychology . As a Registered Nutritionist (Public Health), Chartered Scientist, and Accredited Healthcare Communicator, she bridges expertise in health sciences, technology, and communication. Education: PhD, Biomedical Sciences (Human Nutrition), Ulster University (2005) MSc, Human Nutrition, Ulster University (2001) MA, Food and Welfare Studies, University of Dundee (1999) Her research focuses on healthcare communication technologies in mental health and obesity , with significant contributions to e-health and m-health . Recent work explores self-management interventions for cancer survivors and youth mental healthcare access. She co-developed digital tools for health professionals and investigated AI applications in geriatric and mental health contexts. Notable scientific awards include Best Paper Award (2019) Ulster University Students Union Learning and Teaching Award (2018) UUSU Staff Team of the Year (2018) Dr. Moorhead serves as a Board Member and Section Editor for the Journal of Medical Internet Research . She chairs the NHS Research Ethics Committee (Northern Ireland) and advises the European Association for Communication in Healthcare . Her leadership in multidisciplinary research teams has secured funding and driven impactful international collaborations.

Drago ŽagarView profile

Professor

• Communication Networks and Protocols
• Codes and Coding
• Quality of Service in Networks
• +7 more

Drago Žagar is a Full Professor at the Faculty of Electrical Engineering, Computer Science and Information Technologies (FERIT), University of Osijek, where he also serves as Head of Department. He has been permanently appointed since 2015 and has a long-standing affiliation with the institution since 1990, with brief periods at other units within the same university. His educational background includes a B.Eng. (1990), M.Sc. (1995), and Ph.D. (2002), all from the Faculty of Electrical Engineering and Computing in Zagreb. His research spans key areas in modern networking and information systems, including communication networks and protocols , quality of service , cybersecurity , and IoT applications in agriculture and logistics . His recent work emphasizes energy-efficient monitoring, anomaly detection using machine learning, smart labels for supply chains, and adaptive video streaming. The 15 most recent publications reflect a strong trend in applying sensor networks and data analytics to real-world problems in agriculture, network security, and multimedia systems. The interdisciplinary nature of his work bridges computer networks, industrial informatics, and smart technologies. He has led significant projects such as Smart Label for Measuring and Monitoring Product Storage , IoT Ecosystems for Agriculture , and Boosting Telecommunications Engineering Education under Erasmus+. He also managed national and EU-funded initiatives focused on broadband access in rural areas and IPv6 security. He has mentored numerous students and authored key educational materials, including laboratory manuals in computer networks and electronics. His teaching includes courses on Computer and Mobile Networks and Computer Systems Security . He is actively engaged in research, with publications in journals such as Sensors , Electronics , Journal of Industrial Information Integration , and Telecommunications Systems . His work is indexed in Google Scholar, Scopus, Web of Science, and CRORIS.

Xin LiView profile

Assistant Professor

• Empirical Asset Pricing
• Bond Pricing
• Institutional Investments
• +5 more

Xin Li is an Assistant Professor of Finance at the College of Business, Michigan Technological University. His research focuses on Empirical Asset Pricing, Bond Pricing, Institutional Investments, Fintech, and Market Microstructure. He teaches courses in Asset Pricing, Corporate Finance, Investment, Fixed Income, and Risk Management. His research emphasizes innovative methodologies in financial markets, including the application of dual recognition systems in biosensors and data-driven frameworks for sensor optimization. Recent work explores convolutional neural networks for early-stage gas identification and multi-sensor systems for chemical analysis. Xin Li’s publications span analytical chemistry, sensor technology, and materials science, with notable contributions to electrochemical sensors, nanomaterials, and high-temperature gas detection. His work bridges finance and engineering through interdisciplinary research on Fintech and sensor innovation.

Enzo D'InnocenzoView profile

Assistant Professor

• Econometrics
• Statistics
• Data Science
• +6 more

Enzo D'Innocenzo is a Junior Assistant Professor in Econometrics, Statistics, and Data Science at the Department of Economics, University of Bologna. His primary research focuses on advanced econometric methodologies, including time series analysis, statistical inference, asymptotic theory, score-driven models, and financial econometrics with applications to option pricing. Previously, he served as an Associate Researcher at the School of Business and Economics, Vrije Universiteit Amsterdam. Research Interests: Time Series Econometrics Volatility Modeling (GARCH, Score-Driven) Financial Markets Analysis Option Pricing Theories Extreme Value Theory Dynamic Pricing Strategies Notable Publications: His recent work includes advancements in score-driven models for spatio-temporal data (JASA 2023), dynamic partial correlation networks in financial markets (Journal of Econometrics 2024), and analysis of last-minute hotel pricing strategies (2024). His research bridges theoretical econometric innovation with practical applications in finance and hospitality sectors. Professional Activities: Presenter at NESG Conference 2022 (University of Groningen) Active contributor to econometric journals and conferences Maintains personal academic webpage with research links

• Accounting
• Auditing
• Banking
• +7 more

Dr. Rachel Xi Zhang is an Assistant Professor of Accounting at the National University of Singapore (NUS Business School). She holds a Ph.D. and B.S. from the Wharton School, University of Pennsylvania, and previously worked as an investment banking analyst at Goldman Sachs. Her research focuses on corporate stakeholder information dynamics, institutional investors, governance, financial disclosure, and capital markets. She teaches ACC3705 Valuation and actively publishes on topics such as climate risk hedging, regulatory impacts, and greenwashing. Her work bridges theoretical frameworks with practical corporate finance challenges. Education Ph.D. in Accounting, Wharton School, University of Pennsylvania (2021) B.S. in Economics, Wharton School, University of Pennsylvania Research Interests Dr. Zhang examines how information flows among shareholders, managers, boards, and capital providers. Key themes include institutional investor behavior, governance incentives, climate-related financial disclosures, and market responses to regulatory changes. Her work often addresses real-world implications of transparency and accountability in financial systems. Teaching She instructs ACC3705 Valuation, focusing on valuation methodologies and financial decision-making in dynamic markets. Recent Research Trends Her publications emphasize climate risk mitigation strategies, regulatory inaction costs, and greenwashing detection through earnings call analysis. She explores how real-time market data and disclosure practices influence corporate behavior and investor decisions. Labs/Teams Affiliated with NUS Business School research initiatives on corporate governance and sustainable finance.

Sanjukta ChakrabortyView profile

Assistant Professor

• Inflammation and Lymphatic Pathologies
• Cancer Metastasis
• Microbiome and Metabolic Disorders
• +3 more

Dr. Sanjukta Chakraborty is an Assistant Professor in the School of Medicine at Texas A&M University, specializing in Medical Physiology. She holds a PhD from the Indian Institute of Science and has conducted postdoctoral research at Texas A&M Health Science Center. Her research focuses on inflammation-driven lymphatic pathologies, tumor-lymphatic interactions in cancer metastasis, and microbiome impacts on metabolic disorders. Key interests include liver cancer progression, lymphatic vessel dysfunction in inflammation, and neurotrophic factor regulation of metastasis. Education: BS (University of Calcutta), MS (Banaras Hindu University), PhD (Indian Institute of Science), Postdoctoral Fellowship (Texas A&M Health Science Center). Research Interests: Her lab investigates lymphatic contributions to cancer metastasis (e.g., cholangiocarcinoma and hepatocellular carcinoma), microbiota dysbiosis effects on lymphatic function, and neuroimmune interactions in tumor progression. Collaborations span chemical engineering and microbial pathogenesis at Texas A&M. Awards: Recognitions include the Outstanding Young Investigator Award (Microcirculatory Society), Excellence in Lymphatic Research Award, and Best PhD Thesis Award from the Indian Institute of Science. Advising & Grants: Supervises students like Niyanshi Gaddam and Cole Gowan. Active in CPRIT-funded projects on lymph node metastasis and AHA-funded microbiome studies. Develops bioengineered models and combinatorial therapies targeting tumor-lymphatic crosstalk. Labs/Teams: Dr. Chakraborty leads a multidisciplinary team exploring lymphatic biology, with lab locations in Bryan, TX. Research spans lab-based models, preclinical studies, and translational approaches for clinical intervention.

• Mobile Application Security
• Software Testing
• Reverse Engineering
• +3 more

Aleksandr PILGUN is a Postdoctoral researcher at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), specifically within the TruX department. His research focuses on mobile application security, software testing methodologies, and reverse engineering of Android applications. He has developed tools like ACVTool and ACVCut for code coverage measurement and instrumentation. His work spans from foundational research in mathematical modeling of point distributions (2016) to cryptographic systems on embedded devices (2013), demonstrating interdisciplinary expertise. His recent publications (2020-2024) emphasize Android app security, including black-box testing, instruction-level coverage analysis, and cryptocurrency miner detection. Key outputs include tools for automated testing frameworks and vulnerability detection in third-party Android applications. Awards and grants are not explicitly listed in the provided texts. His research often intersects with practical tool development, as evidenced by GitHub repositories and open-source contributions.

Camelia KuhnenView profile

Professor

• Household Finance
• Labor and Finance
• Neuroeconomics
• +2 more

Camelia Kuhnen is the Boyd White Harris Jr. Distinguished Professor of Finance and Research Director at the Kenan Institute of Private Enterprise at the University of North Carolina's Kenan-Flagler Business School. She holds editorial roles at Management Science and the Journal of Finance , and previously served as President of the Society for Neuroeconomics and the Society for Experimental Finance. A faculty affiliate at the National Bureau of Economic Research (NBER), her interdisciplinary research focuses on household finance, labor economics, and neuroeconomics, exploring how individuals and firms make financial decisions. Dr. Kuhnen earned her PhD in Finance from Stanford University and dual bachelor’s degrees in Neuroscience and Finance from MIT. Her work bridges finance with cognitive and neural sciences, examining topics like risk-taking behavior, socioeconomic disparities, and the psychological underpinnings of economic choices. She has contributed to understanding how dopamine influences investment decisions, the role of self-efficacy in financial delinquency, and the impact of prior choices on portfolio allocations. Her recent research explores wealth and insurance choices, diversity in finance, and the societal implications of financial decisions. She has advised on policy-relevant issues such as economic uncertainty and financial literacy. Dr. Kuhnen’s academic leadership includes roles at the American Finance Association and editorial contributions to top-tier journals, solidifying her influence in both theoretical and applied finance.

Jose M Alcaraz CaleroView profile

Professor

• 5G Networks
• Network Slicing
• IoT Security
• +5 more

Prof Jose M Alcaraz Calero is a Full Professor in Next-Generation Cyber Security at Aston University's School of Computer Science and Digital Technologies. He holds positions within the Department of Software Engineering and Cybersecurity under the College of Engineering and Physical Sciences. His academic credentials include a PhD and MEng, alongside SMIEEE and FHEA honors. His research focuses on 5G networks, IoT security, AI-driven systems, and automated driving technologies. Notable areas of exploration include network slicing, cybersecurity for connected systems, and AI applications in healthcare and environmental monitoring. He collaborates internationally on projects involving smart sensor networks and edge computing solutions. Recent work demonstrates innovations in AI-based odour detection systems using 5G IoT frameworks, stock price prediction via speech models, and autonomous vehicle reference architectures. His research outputs emphasize practical implementations of emerging technologies in real-world scenarios. Prof Alcaraz Calero has contributed 202+ peer-reviewed publications across journals and conferences. His work bridges theoretical advancements with industrial applications, particularly in cybersecurity, telecommunications, and smart systems deployment.

Abolfazl SaghafiView profile

Associate Professor

• Applied Mathematics
• Statistics
• Machine Learning
• +9 more

Abolfazl Saghafi is an Associate Professor in the Department of Mathematics at the University of South Florida, within the College of Arts and Sciences. He holds dual PhDs in Applied Mathematics from Iran University of Science and Technology and in Statistics from the University of South Florida. Education: PhD in Statistics, University of South Florida PhD in Applied Mathematics, Iran University of Science & Technology M.Sc. in Mathematical Statistics, Shahid Beheshti University B.Sc. in Statistics, Azad University His research interests are centered on machine learning, time series classification, BIG data analytics, parametric/non-parametric/Bayesian analysis, and extreme value probability distributions . His work bridges theoretical mathematics with practical applications, particularly in signal processing and data science. In 2011, he resolved a long-standing open problem on Poisson distributions of order k by providing a closed-form solution, marking a significant contribution to applied probability. His recent publications focus on innovative applications of statistical and machine learning methods to real-world problems, particularly in object detection using ground-penetrating radar (GPR) data and improved parameter estimation in financial modeling. These works reflect a strong trend toward interdisciplinary research combining statistics, signal processing, and artificial intelligence. Dr. Saghafi has collaborated with researchers such as S. Jazayeri, S. Esmaeili, and C.P. Tsokos, and holds a U.S. patent for buried object detection systems. His work has been published in journals such as Structural Control and Health Monitoring , Expert Systems with Applications , and Journal of Finance and Data Science . Scientific Awards: He advises students in statistics and applied mathematics, though specific names are not listed. He is affiliated with research teams working on data-driven modeling and signal analysis. His future work is likely to extend into deep learning applications for time series and robust statistical modeling under uncertainty.

David PickernellView profile

Professor

• Small Business and Enterprise Development Policy
• Entrepreneurship
• Economic Development Policy
• +3 more

Professor David Pickernell is a faculty member at the Swansea University School of Management, specializing in Small Business and Enterprise Development Policy. He is affiliated with the Regional Studies Association, the Institute for Small Business and Entrepreneurship, and is a fellow of the Higher Education Academy. Contributions to policy research for entities like the Federation of Small Businesses, OECD, Welsh Assembly Government, and local councils 2018 study on women-owned businesses in the UK with widespread media coverage Over 100 refereed journal articles focusing on SMEs, entrepreneurship policy, and economic development Supervised doctoral research on topics such as entrepreneurial universities, resource curse theory, and university-business interactions His research explores the intersection of entrepreneurship, innovation, and regional development, often employing configurational methodologies like fsQCA. He actively contributes to academic discourse through collaborative workshops and SIGs focused on minority entrepreneurship and social change.

Patrick BahrView profile

Associate Professor

• Type Systems
• Compilers
• Functional Programming
• +4 more

Patrick Bahr is an Associate Professor at the IT University of Copenhagen and Co-Head of Education for the Master of Software Design program. His research focuses on developing programming languages and tools to ensure high-assurance software through formal methods. Education : PhD in Computer Science (2012), University of Copenhagen; MSc in Computational Logic (2009), Dresden & Vienna University of Technology; BSc in Computer Science (2008), Dresden University of Technology Patrick's research spans Type Systems , Compilers , and Functional Reactive Programming (FRP) , emphasizing Modal Types to ensure causality and productivity. His work includes Formal Verification of compiler correctness and Domain-specific Languages for enterprise and financial contracts. Recent publications highlight trends in Graph-Based Compilers , Asynchronous FRP , and Guarded Recursion . His methodologies often integrate Haskell and Agda for verified implementations. Key contributions include Sound-By-Construction Type Systems and Monadic Compiler Calculation . Scientific Awards : Best Contribution to RTA 2010 DIKU Paper of the Year 2012 He actively contributes to program committees (e.g., TFP 2026, ICFP 2024) and has led research projects like Guarded Recursive Types funded by the Danish Independent Research Fund (2015-2019). Collaborations span institutions such as the University of Nottingham and Utrecht University.

• Entrepreneurship
• Leadership
• Micro-enterprise development
• +7 more

Carol Dalglish is a prolific Australian scholar whose work spans entrepreneurship, leadership, and international business education. Based at Queensland University of Technology, she has authored numerous books and refereed articles addressing micro-enterprise development, bottom-of-the-pyramid entrepreneurship, and leadership in multicultural contexts. Her research repeatedly partners with NGOs and co-authors such as Marcello Tonelli and Judy Matthews to investigate sustainable support models for entrepreneurs across sub-Saharan Africa and Southeast Asia. Education & Career: Long-standing academic appointment at Queensland University of Technology Leadership roles in major entrepreneurship and management conferences Repeated visiting and adjunct affiliations with African and European institutions for field research Research Focus: Dalglish investigates how entrepreneurial ecosystems can be engineered to lift people out of desperate poverty. Her studies critique micro-credit as a solitary intervention and demonstrate that transport infrastructure, training, mentoring, and culturally attuned leadership development are equally critical. A second stream explores leadership perception, development, and pedagogy in multicultural classrooms, producing practical guides for students and executives operating in global environments. Publication Trends: Across 56 recorded outputs (1980-2017), her scholarship shifted from early refugee literacy and offender education to rigorous entrepreneurship fieldwork in Mozambique, Ghana, and Tanzania. Co-authored pieces dominate, reflecting team-based ethnography and intervention studies. Journals range from Journal of Asia Entrepreneurship and Sustainability to Philosophy of Management , signalling interdisciplinary reach. Books & Awards: Entrepreneurship at the Bottom of the Pyramid (Routledge, 2017) Leadership: Understanding its Global Impact (Tilde, 2010) Learning in the Global Classroom (Edward Elgar, 2011) Multiple best-paper nominations at AGSE, ANZAM, and Academy of Management Africa conferences Grants & Advising: Chief investigator on Australian Research Council and AusAid linkage grants delivering entrepreneurship training to over 3,000 micro-entrepreneurs in Mozambique. Supervised 15 PhD candidates examining microfinance, social entrepreneurship, and leadership identity; alumni now hold faculty positions in Australia, South Africa, and Thailand. Labs & Teams: Founding member of QUT’s Centre for Social Entrepreneurship and Impact ; leads the Africa Entrepreneurship Research Collective , a cross-institutional network conducting longitudinal field experiments in Ghana, Tanzania, and Uganda.