Find Academic Supervisors

Abhishek AroraView profile

Research Fellow

• Political Economy
• Development Economics
• Deep Learning
• +3 more

Abhishek Arora is a Pre-Doctoral Fellow in the Department of Economics at Harvard University, working with Professor Melissa Dell on projects combining Natural Language Processing and vision techniques to analyze historical datasets. He holds a Master's in Economics from Delhi School of Economics and a Bachelor's in Management Studies from Shaheed Sukhdev College of Business Studies. His research focuses on Political Economy, Development Economics, and Deep Learning, with particular emphasis on topics like local democracy, social norms, and historical text analysis. He has collaborated with institutions including the World Bank and universities such as NYU, Northwestern, and King’s College London. His work bridges computational methods with social science research, producing tools like EfficientOCR for digitization and datasets like American Stories. Key projects include evaluating local democracy's impact in India and analyzing marriage markets through a gender lens. Abhishek has extensive experience in interdisciplinary collaboration, having worked with economists and political scientists across multiple institutions. His contributions span methodological innovations in NLP, historical data curation, and policy-relevant development studies.

Melissa DellView profile

Professor

• Development Economics
• Political Economy
• Economic History
• +3 more

Melissa Dell is the Andrew E. Furer Professor of Economics at Harvard University's Department of Economics, part of the Harvard Faculty of Arts and Sciences. She holds affiliations with the National Bureau of Economic Research (NBER) as a faculty research fellow and the Canadian Institute for Advanced Research (CIFAR) as a Global Scholar in the Institutions, Organizations, and Growth program. Her research focuses on the interplay between state structures, non-state actors, and economic development, particularly in Latin America and Southeast Asia. Education includes a Ph.D. in Economics from MIT (2012), a Bachelor's degree summa cum laude from Harvard University (2005), and an M.Phil. with Distinction from the University of Oxford (as a Rhodes Scholar). Her research interests span Development Economics, Political Economy, and Economic History, with notable studies on drug violence in Mexico, colonial economic legacies in Peru and Vietnam, and the impact of historical state policies on current economic trajectories. Her work often integrates large-scale historical datasets and computational methods, such as digitizing archives and applying machine learning to analyze economic patterns over time. Recent research trends include developing frameworks for robust inference with unstructured data, historical news analysis, and computational tools for economic history (e.g., EfficientOCR, LinkTransformer). These projects emphasize bridging historical and modern data to understand long-term economic dynamics. Awards and honors include the Rhodes Scholarship and Harvard Society of Fellows Junior Fellowship. Her contributions span academic leadership, interdisciplinary collaborations, and policy-relevant economic analysis.

Olajide FunminiyiView profile

Senior Lecturer

• Cyber Security
• Digital Forensics
• Incident Response and Management
• +3 more

Dr. Olajide Funminiyi is a Senior Lecturer in Cyber Security and Digital Forensics at the School of Computer Science and Engineering, University of Westminster, London. He serves as Course Leader for the MSc Cyber Security and Forensics program. With over 32 years of professional experience, his expertise spans academic leadership, research supervision, and industry collaborations. Dr. Olajide holds a PhD in Cybersecurity from the University of Portsmouth, an MSc in Forensic Information Technology, and an MBA from Edge Hill University. His research focuses on cyber security frameworks, digital forensics (including malware analysis, mobile, and cloud forensics), incident response, and enterprise security management. He is Editor-in-Chief of the International Journal of e-Healthcare Information Systems and a member of professional bodies such as the Chartered Society of Forensic Sciences and the British Computer Society. Dr. Olajide actively supervises PhD students and has successfully mentored researchers in areas like cybercrime management and SCADA forensics. Education: PhD in Cybersecurity: Digital Forensics Investigations (University of Portsmouth, UK) MSc in Forensic Information Technology (University of Portsmouth, UK) MBA with Distinction (Edge Hill University, UK) Research Interests: Cybersecurity, Digital Forensics, Incident Response, Cloud Computing, Enterprise Agility, and Information Systems Management. He emphasizes cross-disciplinary approaches to address cyber threats in business and organizational contexts. Professional Roles: Director of Studies (DoS) for PhD students at the University of Westminster Former Senior Lecturer and Course Leader at Nottingham Trent University Collaborations with Airbus on SOC and Cybersecurity Management Awards & Memberships: Senior Fellow, Higher Education Academy (SFHEA-UK) Fellow, British Computer Society (FBCS-UK) Member, Chartered Society of Forensic Sciences (CSFS-UK) Supervision & Grants: Supervised over 10 PhD candidates, including Dr. Olatorera Chidozie Williams (completed in 2023). Actively involved in mentoring and guiding doctoral researchers in cybercrime, forensics, and cloud security. Research projects include frameworks for user input analysis, SCADA forensics, and cyber-attack mitigation strategies. Labs & Teams: Member of the Cyber security Criminal Investigative and Forensic Research (CIFR) group at the University of Westminster, focusing on interdisciplinary cybersecurity solutions.

Olgierd UnoldView profile

Professor

• Machine Learning
• Grammatical Inference
• Computational Intelligence
• +7 more

Prof. Olgierd Unold is a faculty member at the Faculty of Information and Communication Technology at Wrocław University of Science and Technology, where he is affiliated with the Department of Computer Engineering. He holds the academic rank of Professor and conducts research in machine learning, computational intelligence, and bioinformatics. Research Interests: Machine Learning, particularly Grammatical Inference Computational Intelligence: Evolutionary Algorithms, Learning Classifier Systems, Fuzzy Rule Systems Bioinformatics and DNA Computing Natural Language Processing and Pattern Recognition His recent publications demonstrate a strong focus on applying AI techniques to bioinformatics, log analysis, formal language inference, and optimization problems. The work spans from theoretical algorithm development to practical applications in software reliability and biological data classification. Scientific Awards: No awards listed in the provided text. Advising and Grants: Prof. Unold has supervised or collaborated with numerous researchers and students, including Wojciech Wieczorek, Norbert Kozłowski, and Łukasz Śmierzchała, on projects involving classifier systems, grammatical inference, and bioinformatics. While specific grants are not mentioned, his consistent publication output suggests active research funding. Labs and Research Teams: He is part of the research ecosystem within the Department of Computer Engineering, contributing to projects in AI, machine learning, and computational intelligence, likely involving student-led and collaborative research initiatives.

• Computer Vision
• Machine Learning
• Optical Character Recognition (OCR)
• +3 more

Zayene Oussama is a Researcher at the HES-SO University of Applied Sciences and Arts Western Switzerland, affiliated with the Fribourg School of Engineering and Architecture and the Institute of Complex Systems (iCoSys). His work focuses on advancing video text detection, recognition, and OCR systems with a specialization in Arabic script challenges. He has contributed to the development of the AcTiV dataset and associated tools, widely used in international competitions like ICPR and ICDAR. Completed the 'Video Protector Smart AID' project (2021), integrating vision-based surveillance systems Collaborated with Morphean SA on intelligent video analysis PhD thesis (2018) developed novel Arabic text detection/recognition methods using deep learning Research interests include: Arabic text processing in videos Computer vision applications Machine learning for OCR Dataset standardization Recent work (2025) explores truck classification via YOLOv5 and evaluates Vision-Language Models for critical tasks.

Siddhartha BhattacharyyaView profile

Professor

• hybrid intelligence
• pattern recognition
• multimedia data processing
• +10 more

Dr. Siddhartha Bhattacharyya is a Professor in the Department of Computer Science and Engineering at Christ University, Bangalore, with expertise spanning hybrid intelligence, quantum computing, and multimedia data processing. He has authored/edited 65 books and published over 300 research articles, focusing on interdisciplinary applications of machine learning and computational methods. Editorial Board Member, PeerJ Computer Science Holder of two PCT patents Active in academic leadership (organizing conference committees) His research integrates Artificial Intelligence , Computer Vision , and Quantum Computing to solve complex problems in education, healthcare, and environmental monitoring. Recent work includes multimodal student learning assessment, gas plume detection, and Metaverse applications. He leads an active academic lab focused on hybrid intelligence systems and their practical implementations. Key trends in his publications include: deep learning architectures for computer vision (YOLOv7, CNN-Transformer), quantum-inspired algorithms for graph coloring and bioinformatics, and educational technology innovations for remote learning environments. His work bridges theoretical advancements with real-world applications across diverse domains.

Ali GÜLBAĞView profile

Associate Professor

• Machine Learning
• Artificial Neural Networks
• FPGA Design
• +3 more

Assoc. Prof. Dr. Ali GÜLBAĞ is an academic at the Faculty of Computer and Information Sciences , Sakarya University , specializing in Computer Engineering . His career spans over two decades, focusing on FPGA-based hardware design, machine learning applications, and educational methodologies in computer architecture. Doctorate (2003-2006): Quantitative determination of volatile organic compounds using artificial neural network and fuzzy logic-based algorithms MSc (1998-2000): Building automation using telephone lines BSc (1994-1998): Electrical-Electronics Engineering His research interests include Artificial Neural Networks , FPGA Design , and Water Resource Management , with applications in seismic event differentiation, environmental modeling, and educational technologies. Recent work emphasizes water consumption prediction using machine learning. Key projects: BZK.SAU.FPGA microcomputer architecture , Remote FPGA laboratories Publications demonstrate expertise in combining machine learning techniques (ANNs, gradient boosting, random forests) with hardware implementations for real-world problem-solving.

• Computer Science
• Cybersecurity
• Internet of Things
• +5 more

Gang Tan is an Associate Professor at the Pennsylvania State University's College of Engineering, Department of Computer Science and Engineering. He also holds the James F. Will Career Development Professorship and is affiliated with the Institute for Computational and Data Sciences (ICDS). His research focuses on binary reverse engineering , cybersecurity , Internet of Things (IoT) security , machine learning fairness , and information flow security . He has led numerous NSF-funded projects, including work on precise binary analysis, IoT policy enforcement, and automated fairness repair in AI systems. Recent work trends include memory safety validation , pseudocode extraction , and control-flow integrity mechanisms. His 127+ research outputs reflect deep engagement with static program analysis , cache side-channel detection , and secure kernel-driver interfaces . Scientific Awards: James F. Will Career Development Professorship Gang Tan has secured multiple grants from the National Science Foundation (NSF) and U.S. Navy for projects like Sliver (information flow verification) and Semantics-Directed Binary Reverse Engineering . His work involves advising teams on IoT safety, and he has 19 active or completed grants since 2008.

• Machine Learning
• Natural Language Processing
• Network Analysis
• +3 more

Dr. Derek Greene is an Assistant Professor at the School of Computer Science, University College Dublin, and a Funded Investigator at the Insight Centre for Data Analytics and the VistaMilk Research Centre. His research spans machine learning, natural language processing, and network analysis, with a focus on interdisciplinary applications in cultural analytics, smart agriculture, and political science. Dr. Greene has published over 60 research papers at international conferences and journals. His work includes developing methods for natural language processing , network analysis , and deep learning applied to diverse domains such as literary text mining, dairy industry monitoring, and political communication analysis. He leads projects integrating machine learning into cultural analytics, enhancing agricultural practices, and modeling policy agendas. The articles in his Google Scholar profile highlight a trend toward explainable AI , synthetic data generation , and network-based modeling . Key sub-fields include counterfactual explanations , transformer-based frameworks , temporal analysis of historical texts , and interdisciplinary knowledge transfer . His work bridges machine learning with applications in cultural studies , agriculture , and political science . Dr. Greene collaborates with institutions like the Insight Centre for Data Analytics and the VistaMilk Research Centre , integrating academic research with industry and policy needs. His funded investigator roles reflect ongoing support for applied research in data analytics and agricultural technology.

• Machine Learning
• Computer Vision
• Autonomous Driving
• +4 more

Ross Greer is an Assistant Professor in the Department of Computer Science & Engineering at the University of California Merced. He leads the Mi³ Lab, focusing on machine intelligence, human-agent interaction, and safe autonomous systems. Education : B.S. and B.A. in EECS, Engineering Physics, and Music from UC Berkeley (2015), M.S. in Electrical & Computer Engineering from UC San Diego (2018), Ph.D. in Electrical & Computer Engineering at UC San Diego (2021) under Mohan Trivedi and Shlomo Dubnov. His research explores computational intelligence for open-world adaptability, robustness to rare events, and safety in chaotic environments. Key applications include autonomous driving, driver state analysis, trajectory prediction, and AI-assisted musical creativity. Recent publications emphasize vision-language models, active learning for 3D object detection, and safety metrics. Awards include the 2024 Interdisciplinary Research Award, Henry Booker Award for Ethical Engineering, and multiple best poster/grand prizes. Scientific Awards : 2024 Interdisciplinary Research Award 2024 Henry Booker Award for Exemplary Ethical Engineering Postdoctoral Networking Fellowship (Germany's Academic Exchange Service) Grand Prize (AWS Automotive Day competition at IEEE Intelligent Vehicles Symposium, 2023) Best Poster Awards (2021/2023 Jacobs Research Expo) He also co-authored the textbook Deep and Shallow: Machine Learning in Music and Audio (Chapman & Hall, 2023) and serves as a music director for UCSD's Symphonic Student Association and UC Merced's marching band.

Deniz YuretView profile

Professor

• Natural Language Processing
• Machine Learning
• Artificial Intelligence
• +3 more

Deniz Yuret is a Professor in the Department of Computer Engineering at Koç University , Istanbul, and the founding director of the KUIS AI Center . Previously, he spent 12 years at the MIT AI Lab and co-founded Inquira, Inc. His research focuses on Natural Language Processing and Machine Learning , with significant contributions in dependency parsing , language modeling , grounded language learning , and character-level NLP . He has pioneered frameworks like Knet , a deep learning library in Julia, and AutoGrad.jl for automatic differentiation. Deniz's academic work spans neural architectures for language-robot interaction, transfer learning in low-resource NMT, and context embeddings for grammatical category acquisition. His recent publications emphasize transformer models , multimodal systems , and efficient language modeling . He has supervised multiple graduate students, including Emre Can Açıkgöz (PhD, UIUC), Onur Kuru (M.S. 2016), Saman Zia (M.S. 2016), and Osman Baskaya (M.S. 2015). His projects include the TUBITAK 1001 (2016-2018) and ReGROUND (2015-2018) in collaboration with international institutions.

Yukyung ChoiView profile

Assistant Professor

• Robotics
• Computer Vision
• Autonomous Driving
• +3 more

Yukyung Choi is an Assistant Professor in the Department of Artificial Intelligence and Robotics at the School of Intelligent Mechatronics Engineering, Sejong University, South Korea. She has held this position since 2018 and maintains an active research profile with 45 publications including 22 conference contributions and 22 peer-reviewed articles, demonstrating significant productivity with 9 publications in 2022, 3 in 2023, 9 in 2024, and 11 in 2025. Education: Ph.D., KAIST, 2018 M.S., Yonsei University, 2008 B.S., Soongsil University, 2006 Her research centers on Robotics and Computer Vision with specialization in Visual Perception for Autonomous Driving. She investigates multi-modal learning, 3D scene understanding, and visual perception for intelligent systems including self-driving cars and household robots, focusing on incorporating natural prior knowledge to enhance algorithm robustness against real-world variations. Her work bridges theoretical machine learning with practical robotics applications. Recent publications (2024-2025) reveal strong trends in deploying deep learning for real-world challenges: multispectral pedestrian detection for autonomous vehicles, industrial text recognition in low-contrast environments, object pose estimation under adverse conditions, and causal approaches to multimodal emotion recognition. These works demonstrate consistent focus on improving reliability of vision systems through innovative learning frameworks and robust dataset construction. Professor Choi leads the RCV Lab (Robotics and Computer Vision Lab) at Sejong University, documented through the official lab website (https://www.rcv.sejong.ac.kr) and Instagram presence (https://www.instagram.com/sejong_rcv), which serves as the primary research hub for her team's work on intelligent perception systems.

Rita HartelView profile

Senior Lecturer

• Data Compression
• Bioinformatics
• Graph Databases
• +4 more

Dr. Rita Hartel serves as a Senior Lecturer and Research Associate in the Department of Databases and Electronic Commerce at the University of Paderborn's Institute of Computer Science, while also fulfilling the critical role of Academic Advisor for the Computer Science Student Office where she guides undergraduate and graduate students. Her research forms two distinct yet complementary pillars: cutting-edge data compression algorithms for bioinformatics (specializing in Burrows-Wheeler Transform optimizations for DNA sequence data) and graph databases (developing grammar-based compression for knowledge graphs), alongside innovative digital humanities work applying OCR and semantic analysis to comics historiography with a focus on German traditions. This interdisciplinary approach bridges computational rigor with cultural scholarship. Dr. Hartel demonstrates consistent research productivity with five publications from 2021-2025 in premier venues including the Data Compression Conference and specialized workshops. Her work reflects strong international collaboration patterns and likely benefits from active grant funding given the technical resources required for bioinformatics compression research. As an Academic Advisor, she provides essential student support while her dual research focus creates unique opportunities for students interested in either computational methods or digital humanities applications.

Almon Chai Wei-YenView profile

Senior Lecturer

• Computational Simulations
• Drying Technologies
• Renewable/Sustainable Energy
• +5 more

Dr. Almon Chai Wei-Yen serves as Senior Lecturer and Coordinator of the Robotics & Mechatronics Program at Swinburne University of Technology Sarawak Campus's Faculty of Engineering, Computing and Science. Holding a PhD from Malaysia (2007) and prior industrial experience in ceramics manufacturing, he bridges academic research with practical engineering solutions. His professional affiliations include the Society of Automotive Engineers (SAE), Association for Computing Machinery (ACM), and Institution of Engineering and Technology (IET). Education BEng (Hons) from United Kingdom MSc from United Kingdom PhD from Malaysia (2007) Dr. Chai's research centers on computational simulations for drying technologies and renewable energy systems, with expanding work in human factors engineering and mechatronics applications. Recent publications demonstrate significant interdisciplinary innovation, particularly in biomedical signal processing for movement classification and computer vision for text interpretation in natural scenes. His work consistently applies simulation-based optimization to solve real-world engineering challenges. Analysis of his 2020-2022 publications reveals two dominant research thrusts: biomedical engineering (focusing on EMG signal classification for prosthetic control) and computer vision (specializing in vertical text detection). These areas reflect his core expertise in simulation and optimization now applied to human-centric technologies, showing strong collaboration patterns and targeting high-impact venues like IEEE Access. Scientific Awards Silver Medal Award for 'Window Cleaning and Climbing Robot' at Malaysia Invention & Innovation Awards 2010 (MTE2010) Research Leadership Dr. Chai actively supervises research higher degree candidates and currently leads two Sarawak Research and Development Council (SRDC) Grant 2020 projects: 'Instant Count on Tuberculosis' (Project Member) 'Tidal Stream Power Assessment and Design of Tidal Current Turbine for Pulau Triso' in collaboration with Universiti Malaysia Sarawak (Project Member) Research Environment As Robotics & Mechatronics Program Coordinator, Dr. Chai directs academic initiatives while pursuing cross-disciplinary projects in simulation-based optimization, renewable energy conversion, and human-robot interaction. His research group leverages university facilities and industry partnerships to develop practical engineering solutions, particularly in energy conservation and assistive technologies.

• Artificial Intelligence
• Natural Language Processing
• Machine Learning
• +3 more

Assistant Professor Ayla Kayabaş is affiliated with the Faculty of Engineering and Architecture at Ahi Evran University , where she focuses on the Computer Engineering department. Her academic journey includes a PhD in Computer Engineering from Ankara Yıldırım Beyazıt University (2013-2020), a Master's Degree (2003-2011), and a Bachelor's Degree (2003-2011) from Universitaet Stuttgart. Research Interests: Her work centers on Artificial Intelligence , particularly in Natural Language Processing and Deep Learning . She has developed innovative algorithms for Turkish morphological analysis, combining finite-state automata and neural networks. Recent publications explore AI-generated text classification, reflecting her broader interest in machine learning applications. Academic Contributions: Her three key publications (2022, 2025) span neural network architectures for language processing, error correction in OCR systems, and hybrid morphological analysis frameworks. These works align with her expertise in Deep Learning , Neural Networks , and Language Modeling . Teaching and Supervision: She has supervised two Master's theses: Automatic detection of intrusion attacks in IoT networks (2023) and Student performance prediction using educational data mining (2022). Additionally, she has taught courses in Natural Language Processing, Formal Languages, Applied Machine Learning, and Software Engineering. Collaborative Impact: Collaborating with researchers from Ankara Medipol University, Ankara Yildirim Beyazit University, and Ludwig-Maximilians-Universität München, she contributes to interdisciplinary advancements in computational linguistics and AI.