Find Academic Supervisors

Christina M. HomrighouseView profile

Senior Lecturer

• Human Resources
• Information Systems
• Technology and Work
• +1 more

Christina M. Homrighouse is a Senior Lecturer in the Department of Human Resource Studies at Cornell University's ILR School. Her expertise spans Human Resources, Information Systems, and the intersection of technology with workplace practices. She specializes in teaching practical skills like career development, software proficiency, and presentation techniques. Education: Bachelor of Science in Psychology and Business from Ithaca College Master of Industrial and Labor Relations from Cornell University Research & Teaching Focus: Ms. Homrighouse emphasizes applied HR technologies and software applications in workplace scenarios. She teaches courses such as Essential and Advanced Desktop Applications, and Human Resource Information Systems. Her work bridges theoretical HR concepts with real-world technical skills. Publications/Awards: No specific articles or scientific awards listed in the provided profile. Grants & Advising: No detailed information on grants or student advising programs provided. Labs/Teams: No affiliated research labs or collaborative teams explicitly mentioned.

Franck CappelloView profile

Academic

• High-performance parallel and distributed computing
• Resilience and fault tolerance at extreme scale
• Lossy compression
• +3 more

Franck Cappello is a distinguished computer scientist currently serving as a Project Manager and Senior Computer Scientist at Argonne National Laboratory and as an Adjunct Research Professor at the University of Illinois at Urbana-Champaign. With over 30 years of research experience, he has made significant contributions to high-performance computing, particularly in the areas of resilience and fault tolerance at extreme scale, lossy compression of scientific data, and AI for science. Dr. Cappello received his Ph.D. from the University of Paris XI in 1994 with highest honors ("très honorable avec les félicitations du jury"). His academic journey includes positions as a Junior Researcher at CNRS (1994-2003), Senior Researcher at INRIA (2003-2013), and Visiting Research Professor at the University of Illinois (2009-2013). His research interests focus on high-performance parallel and distributed computing, resilience and fault tolerance at extreme scale, lossy compression of scientific data, and AI for science. Cappello has pioneered several high-impact software tools including XtremWeb (one of the first Desktop Grid software systems), MPICH-V fault tolerance MPI library, VeloC multilevel checkpointing environment, and SZ lossy compressor for scientific data. His work on the Grid'5000 project has enabled hundreds of researchers to conduct experiments in parallel and distributed computing, resulting in over 2000 research publications and supporting 300+ Ph.D. theses. Dr. Cappello's recent publication record shows a strong integration of AI techniques with traditional HPC approaches, particularly in lossy compression, workflow management, and energy efficiency. His research demonstrates a consistent focus on practical solutions for real-world scientific computing challenges with emphasis on maintaining data fidelity while achieving significant data reduction. The publications reveal growing interest in GPU acceleration, wafer-scale engines, federated learning, and energy trade-offs in compressed I/O systems. IEEE Fellow (2017) 2024 IEEE CS Charles Babbage Award 2024 Europar Achievement Award 2022 ACM HPDC Achievement Award 2021 IEEE Transactions of Computer Award for Editorial Service and Excellence 2018 IEEE TCPP Outstanding Service Award Two R&D 100 awards (2019 and 2021) for innovative software 12 Best papers Finalists/Awards Dr. Cappello has advised 22 Ph.D. students and served on 58 Ph.D. defense juries. He has secured over 60 research grants as main PI or Co-PI, including numerous DOE ECP projects, NSF grants, and European projects. His leadership extends to directing the Joint Laboratory on Extreme-Scale Computing (JLESC), which brings together seven prominent research centers in supercomputing. Currently, he leads the AuroraGPT Evaluation Group, focusing on evaluation methods for Large Language Models as research assistants, and continues to lead resilience and compression research at Argonne's Mathematics and Computer Science Division. Dr. Cappello directs several significant research initiatives including the Joint Laboratory on Extreme-Scale Computing and leads resilience and compression research at Argonne's Mathematics and Computer Science Division. His teams have developed groundbreaking software frameworks like SZ and VeloC that are deployed on exascale systems. Through his leadership of the Grid'5000 project and JLESC, he has fostered international collaboration among researchers working on the frontiers of supercomputing. His current work on error-bounded lossy compression, resilient workflow management, and energy-efficient computing represents the cutting edge of scientific computing research with practical applications across numerous scientific domains.

Christophoros NikouView profile

Professor

• Image Processing
• Computer Vision
• Pattern Recognition
• +12 more

Christophoros Nikou is a Professor in the Department of Computer Science and Engineering at the University of Ioannina, Greece. He holds a Ph.D. in Image Processing and Computer Vision from Université Louis Pasteur - Strasbourg I, France (1999), a DEA in Photonics and Image Processing from the same institution (1995), and a Diploma in Electrical Engineering from Aristotle University of Thessaloniki, Greece (1994). His research interests include: Image Processing Computer Vision Pattern Recognition Biomedical Image Analysis Medical Imaging Machine Learning His recent publications (2022–2024) reflect a strong trend toward deep learning, generative models, and multimodal analysis, particularly in document image analysis, super-resolution, and biomedical applications. He has made significant contributions to visual tracking, segmentation, and image registration, with recent work extending into virtual reality, hypercomplex neural networks, and model compression. Scientific awards include: Best paper award, IAPR/IEEE International Conference on Biometrics (ICB’16), 2016 Best paper award, Bayesian and Graphical Models for Biomedical Imaging (BAMBI’16), 2016 He has supervised numerous students, many of whom have co-authored publications with him, and his research has been supported by collaborations across multiple institutions. He has also co-edited a book on biomedical image processing and contributed to several book chapters. His work spans both theoretical and applied domains, with consistent publication in top-tier IEEE and Springer venues.

• Engineering Design
• 3D Printing
• Mechanical Analysis
• +5 more

Dr. Yılmaz Gür is an Associate Professor at the International University of Sarajevo (IUS), currently serving as Program Coordinator for both the Mechanical Engineering and Industrial Engineering study programs. He earned his PhD in Engineering Design from the University of Leeds (1991-1996), supervised by Prof. Alan De Pennington and Dr. Tim David, with research focused on integrating engineering analysis into design processes. Education: PhD in Engineering Design, University of Leeds His research spans engineering design, 3D printing, composite materials, and finite element analysis. Recent publications highlight innovations in Voronoi lattice composites, gyroid structures, and biomedical applications of 3D printing. He actively contributes to STEM education through additive manufacturing pedagogy. Publications demonstrate expertise in additive manufacturing trends, particularly in mechanical engineering and biomedical prototyping. His work bridges mathematical modeling with real-world fabrication techniques. Scientific Awards: Governmental scholarship for doctoral studies, SCImago Journal Rankings (Q1-Q3) As Program Coordinator, Dr. Gür oversees academic planning while advancing grants in composite material development and educational technology. His research emphasizes practical applications of 3D printing in engineering and medical domains.

Mingzhen WeiView profile

Associate Professor

• Petroleum Engineering
• Enhanced Oil Recovery (EOR)
• Conformance Control
• +5 more

Mingzhen Wei is an Associate Professor in the Department of Geosciences and Geological and Petroleum Engineering at Missouri University of Science and Technology . She holds a Ph.D. in Computer Science from New Mexico Institute of Mining and Technology, and M.S. and B.S. in Petroleum Engineering from Chinese institutions. Research Interests : Data mining, enhanced oil recovery (EOR), conformance control, machine learning applications, and geothermal energy optimization. Teaching : Reservoir simulation, natural gas engineering, and advanced applied reservoir engineering. Awards : 2018 CEC Dean’s Scholar for AI integration in reservoir engineering. Collaborations : Active in cross-disciplinary projects including geothermal energy, CO₂ sequestration, and unconventional oil/gas development.

Eva DarulovaView profile

Associate Professor

• Programming Languages
• Software Verification
• Program Synthesis
• +3 more

Eva Darulova is an Associate Professor at the Department of Information Technology, Uppsala University, and Adjunct Faculty at Max Planck Institute for Software Systems (MPI-SWS). Previously held tenure-track faculty at MPI-SWS and completed her PhD at École Polytechnique Fédérale de Lausanne (EPFL) under Viktor Kuncak. Current research: Applications in numerical/embedded domains, program synthesis, software verification, approximate computing Key projects: Blossom (fuzzing), Lassie (HOL4 tactics), Pine (floating-point loops), LTLTalk (robot instruction), Incarnate (3D printing), Icing (compiler semantics), Flipper (NLP interface), FloVer (error checking), Daisy (accuracy analysis), Rosa (real compiler) Teaching: Program Design (2021/22), Program Synthesis (2021), Program Analysis (multiple years), Advanced Program Analysis (2019), Static Program Analysis (2017), Approximate Computing seminar (2016) Service: Artifact evaluation chair (ASPLOS'22), PC member (ECOOP'22, ESEC/FSE'22, EMSOFT'21, PLDI'21) Research Trends: Focus on numerical computing verification, approximate computing frameworks, and program synthesis techniques. Publications span TACAS, EMSOFT, ISSTA, POPL, CAV, FMCAD, TOPLAS, with emphasis on floating-point error analysis, mixed-precision optimization, and compiler verification. Scientific Recognition: Nominated for EAPLS best paper award (TACAS'21). Co-advisor for Anastasiia Izycheva and mentor for multiple MSc/BSc students including Mustafa Hafidi, Joachim Bard, Nikita Zyuzin, Youcef Merah, Safya Alzayat, Anastasiia Izycheva. Collaborations: Works with researchers at EPFL, MPI-SWS, University of Saarland, University of Washington, and Saarbrücken/Kaiserslautern institutions.

Thomas FritzView profile

Associate Professor

• Software Engineering
• Human-Computer Interaction
• Developer Productivity
• +4 more

Prof. Dr. Thomas Fritz is an Associate Professor of Human Aspects of Software Engineering at the University of Zurich's Department of Informatics within the Faculty of Business, Economics and Informatics. His research focuses on empirically studying software developers through biometric sensing and interaction analysis to enhance productivity and wellbeing. Key domains include developer productivity analytics, interruptibility detection using physiological sensors, and context-aware developer tools. Research interests center on: Developer Productivity/Personal Analytics: Measuring and improving developer efficiency through activity monitoring Biometric Sensing: Using physiological data (e.g., heart rate, EEG) to predict code quality and emotional states Information Needs: Modeling developers' contextual requirements during coding tasks His publications predominantly explore human factors in software engineering, with recurring themes of biometric sensing, developer productivity, and human-centered tool design. Recent work shows increased focus on VR applications for workspace optimization and real-time stress detection in knowledge workers. Awards and honors include: Honorable Mention Awards at CHI 2017 and CHI 2018 ACM SIGSOFT Distinguished Paper Award (2010) 3rd Place in ACM Student Research Competition (2010) He leads the Human Aspects of Software Engineering (HASE) Lab and has advised over 20 PhD/Master's students. Research is funded by Swiss National Science Foundation grants, ABB Software Research Grants, NSERC Collaborative Research grants, and Microsoft SEIF Awards. Current projects include emotion-aware development environments and VR-based productivity tools.

• Human Factors Engineering
• Human-Computer Interaction
• Extended Reality
• +7 more

Heejin Jeong is an Assistant Professor of Human Systems Engineering at The Polytechnic School , Ira A. Fulton Schools of Engineering , Arizona State University . He also holds affiliated faculty appointments with the School of Medicine and Advanced Medical Engineering and the School of Biological and Health Systems Engineering . Education: Ph.D. in Industrial and Operations Engineering, University of Michigan Research Interests: His research focuses on enhancing human decision-making in interactions with autonomous and intelligent systems. He applies methodologies such as experimental studies, human performance modeling, and data analytics to address societal challenges in domains like robotics, healthcare, and emerging technologies. His work includes developing extended reality systems for occupational safety and healthcare rehabilitation training, and advancing human-robot collaboration in Industry 5.0 manufacturing systems. Key areas of interest include: Human Factors Engineering Human-Computer Interaction Extended Reality (XR) Human-Robot Collaboration Healthcare Rehabilitation Training Occupational and Transportation Safety Research Trends: His recent work (2024–2025) spans a wide range of applications including virtual and augmented reality for training, human motion simulation using generative AI, ergonomic risk assessment using computer vision, and AI-enhanced human performance in industrial and occupational settings. A strong emphasis is placed on integrating human-centered design with cutting-edge technologies like digital twins, quantum machine learning, and XR systems. Scientific Contributions: Co-author of the book Human-Centered Metaverse: Concepts, Methods, and Applications (2025) Guest editor for special issues in IISE Transactions on Occupational Ergonomics and Human Factors and Computers & Graphics Teaching & Labs: He teaches courses such as HSE 542 Foundations of Human Systems Engineering and HON 498 Pro-Seminar . He is the director of the HiMER Lab (Human Interaction with Machines, Extended Reality, and Robotics), which focuses on human-centered systems design and evaluation.

Dávid SzabóView profile

Associate Professor

• Sociolinguistics
• French Language and Literature
• Lexicography
• +5 more

Dávid Szabó is a habilitated Associate Professor at the Institute of Romance Studies , Department of French Language and Literature , Eötvös Loránd University. His academic profile bridges sociolinguistics , focusing on argot and slang studies in French-Hungarian contexts, with computer graphics and C# software development . He has contributed to diverse fields, including AI in education , sustainable finance , and real-time graphics APIs . Research Highlights: His work explores the intersection of language evolution and technology, with recent publications on Green Finance , AI-driven educational tools , and parallel processing in graphics programming . He investigates linguistic taboos in Hungarian politics and translation challenges of urban French slang into Hungarian, while developing educational software like StudyHelper. Technical Contributions: Szabó has pioneered the integration of modern C# with graphics APIs (Vulkan, OpenGL) for real-time rendering , creating frameworks for multi-platform applications and shader program development . His technical papers emphasize code efficiency, API abstraction, and GPU optimization.

Quang BuiView profile

Associate Professor

• Digital Transformation
• Health IT
• Artificial Intelligence Adoption
• +5 more

Quang 'Neo' Bui is an Associate Professor of Information Systems at the Saunders College of Business, Rochester Institute of Technology. He holds a PhD from Bentley University and has a BS/MS from Brigham Young University. His research focuses on digital transformation, health IT adoption, and human-centered AI, with publications in top journals like JMIS, JSIS, and Information & Management. He teaches courses in business analytics, enterprise systems (including SAP), and strategic information systems. His certifications include Tableau Desktop Specialist, SAP TERP10, and Oracle Database 10g. Education: BS/MS (Brigham Young University), PhD (Bentley University). Research emphasizes mixed-methods approaches (case studies, regression/PLS models) to explore digital transformation in public/private sectors, health IT solutions, and IT strategy configurations. Notable work includes studies on enterprise architecture adoption and board-level digital awareness. Technical expertise spans data visualization (Tableau), enterprise systems (SAP), database management (Oracle/MySQL), web development (HTML/JavaScript), and cloud platforms (AWS/Azure). Awards: Saunders College Research Fellow (2021/2022), Outstanding Teaching Awards (2017/2021/2024), ICIS DIGIT Best Paper Runner-Up (2024) Teaching: Emphasizes active learning and career-ready skills in areas like business intelligence, ERP systems, and web development Experience: 7+ years teaching enterprise systems, 3+ years as web developer/project manager, and instructional design projects Labs/Initiatives: Involved in iD Lab educational initiatives bridging academia-industry gaps

• Technical Computer Science and Telecommunications
• Biomedical Engineering
• Control Systems
• +3 more

Dr. Eng. Michał Doligalski is an Assistant Professor at the University of Zielona Góra , affiliated with the Institute of Metrology, Electronics and Computer Science and the Department of Computer Engineering and Internet of Things . His primary research interests span Technical Computer Science and Telecommunications (75%) and Biomedical Engineering (25%). He holds an ORCID identifier: 0000-0003-2895-7085 and can be contacted at M.Doligalski@imei.uz.zgora.pl . His office is located in Room 208A of the A-2 Teaching Building (prof. Z. Szafrana 2, 65-516 Zielona Góra). His research focuses on control systems , aerosol therapy technologies , mathematical modeling of fluid dynamics , and PLC-based industrial automation . Recent work includes advancements in precision measurement systems for indoor localization and optimization of medical nebulizer performance. Publications highlight interdisciplinary contributions, blending engineering principles with medical applications. Notable areas include: Development of programmable logic controllers for industrial monitoring Enhanced aerosol delivery methods for respiratory therapies 3D modeling of liquid film dynamics GNSS-based time synchronization in energy-constrained systems No scientific awards or grants were explicitly mentioned in the provided data.

Mark NiswanderView profile

Lecturer

• Information Technology Management
• Enterprise Content Management
• Device Management
• +4 more

Mark Niswander serves as an Adjunct Instructor at the Paul H. O'Neill School of Public and Environmental Affairs, Indiana University, where he teaches SPEA 412 and contributes to technology-focused curriculum development within public affairs education. He holds a Bachelor of Arts in Political Science from the University of North Texas, providing foundational expertise in governance structures that informs his technological applications in public sector contexts. His research interests span critical modern information systems domains including Information Technology Management, Enterprise Content Management, Device Management, Mobile Device Management, Data and Information Systems for Recordkeeping, Desktop Virtualization, and Application Virtualization, with emphasis on practical implementation in governmental and environmental recordkeeping systems. Mr. Niswander's work bridges political science frameworks with emerging technology solutions, particularly focusing on secure data management systems and virtualized application environments for public sector efficiency.

JORGE ALBERTO SUAREZ GAREAView profile

Assistant Professor

• Deep Learning
• Hyperspectral Imaging
• Remote Sensing
• +3 more

Jorge Alberto Suarez Garea is an Assistant Professor at the Department of Electronics and Computing within the Higher Technical School of Engineering at the University of Santiago de Compostela. He holds a PhD from the same institution (2021), specializing in Deep Learning-Based Classification Techniques for Hyperspectral Images in Real Time , supervised by Dr. Francisco Argüello Pedreira and Dr. Dora Blanco Heras. His research focuses on deep learning applications in remote sensing , including real-time hyperspectral image processing, parallel computing frameworks (CUDA, OpenMP, MPI), and environmental monitoring using UAV-based multispectral imagery. He is affiliated with the ARQCOMP Research Group (Computer Architecture), emphasizing interdisciplinary work between computer science and environmental science. Key contributions include developing Galician Rivers Multispectral Anomaly Detection Dataset , hybrid parallel domain adaptation methods, and open-source tools like HypeRvieW for hyperspectral data processing. His work bridges algorithmic innovation with hardware optimization, particularly in GPU-accelerated systems. Research interests span neural networks , domain adaptation , texture analysis , and real-time embedded systems , with a focus on environmental applications such as watershed monitoring and ecosystem anomaly detection.

Cynthia Van HeeView profile

Lecturer

• Computational Linguistics
• Natural Language Processing
• Sentiment Analysis
• +5 more

Cynthia Van Hee is a Senior Researcher and lecturer at Ghent University's LT3 (Language and Translation Technology Team), where she conducts cutting-edge research in computational linguistics and natural language processing. Her work focuses on developing advanced systems for irony detection, sentiment analysis, and cyberbullying detection, with applications across multiple languages and social media platforms. Dr. Van Hee's primary research interests span several interconnected domains within computational linguistics: Sentiment analysis (including implicit sentiment, emotion detection and aspect-based sentiment analysis) Irony and sarcasm detection in social media Cyberbullying detection and classification Multilingual natural language processing Machine learning applications for social media analysis Her recent publications demonstrate a strong focus on irony detection across multiple languages, with particular attention to confidence scoring, explanation generation, and multilingual capabilities. She has also expanded her research into ethical AI considerations, exploring the social implications of language technologies and developing frameworks for virtuous data management. Her work bridges theoretical advances in NLP with practical applications in social media monitoring, news diversity, and healthcare contexts. Dr. Van Hee is actively involved in several major research projects: SentEMO : Developing a multilingual adaptive platform for aspect-based sentiment and emotion analysis NewsDNA : Exploring diversity in news through algorithmization AMiCA : Automatic Monitoring for Cyberspace Applications, focusing on cyberbullying detection As an educator, she teaches several courses including Audiovisual Language Techniques, Natural Language Processing, Project Management, and Desktop Publishing, helping to train the next generation of language technology specialists. Her commitment to knowledge dissemination is further evidenced by her contributions to educational publications explaining language technology fundamentals to broader audiences.

Antonio Perez ManzanoView profile

Part-Time Lecturer

• Educational Technology
• Developmental Psychology
• Health Education
• +3 more

Antonio Perez Manzano is a Part-Time Lecturer in the Department of Developmental and Educational Psychology at the University of Murcia's Faculty of Education. His research focuses on Educational Technology, Health Education, and Accessibility in Education, with a particular emphasis on ICT applications for students with disabilities and organ donation awareness campaigns. He has collaborated with the High Skills research group and previously contributed to the EVASALUD group. Education: Doctorate in Developmental and Educational Psychology from the University of Murcia (2013), supervised by Antonio José de Pro Bueno, Eva Herrera-Gutiérrez, and Manuel Ato García. Research interests include digital pedagogy, multimedia content strategy for scientific promotion, and institutional compliance in digital media. Recent work trends highlight interdisciplinary projects combining health communication, accessibility innovations, and the use of gamification/transmedia in classrooms. Articles emphasize leveraging YouTube and iBeacon technology for educational outreach and policy advocacy. He has explored the intersection of ICT in healthcare training, disability support systems, and legal frameworks for audiovisual content management in scientific institutions. Lab/Team Affiliations: Active member of the High Skills research group, focusing on educational innovation. Past contributions include the EVASALUD group addressing education, values, addictions, and health.