Find Academic Supervisors

• Artificial Intelligence
• Digital Engineering
• Cybernetics
• +5 more

Prof. Dr.-Ing. Tobias Miunske serves as Professor of Artificial Intelligence and Digitalization in Mechanical Engineering at Ravensburg-Weingarten University of Applied Sciences (RWU) since 2025 within the Faculty of Mechanical Engineering. His academic foundation includes: 2010-2015: Technical Cybernetics studies at University of Stuttgart 2020: PhD from University of Stuttgart with dissertation "A Scenario-Adaptive Motion Algorithm for the Longitudinal Movement of a Fully Mobile Driving Simulator" Research expertise spans AI-driven motion cueing algorithms, intelligent trajectory generation for automated driving, and real-time simulation systems. His work bridges mechanical engineering with digital platforms, evidenced by industry projects at Porsche Development Center Weissach (2014-2015 real-time visualization systems) and Harro Höfliger (2020-2025 AI platform development for pharmaceutical engineering). Professional trajectory shows progression from University of Stuttgart research assistant (2015-2020, Automotive Mechatronics Chair) to current academic leadership. No scientific awards or student advisement details are documented in available sources. Laboratory affiliations focus on driving simulator technology and AI-integrated mechanical systems development.

• Machine Learning
• Data Analytics
• Artificial Intelligence
• +3 more

Maria-Cristina Marinescu serves as a Lecturer in the Department of Mathematics and Data Analytics at IQS School of Management. With a strong foundation in computational methods and data analysis, she contributes significantly to both teaching and research within the institution. Her academic profile demonstrates consistent scholarly activity with 44 documented scientific production items spanning over two decades. Dr. Marinescu's research interests center on Machine Learning, Data Analytics, and Artificial Intelligence, with notable applications in epidemic modeling, wireless sensor networks, and programming models. Her work bridges theoretical computer science with practical applications addressing real-world challenges in public health, digital well-being, and medical diagnostics. The fingerprint analysis of her work shows strong emphasis on Machine Learning (100%), Learning Systems (100%), and Transportation Models (100%), with substantial contributions to Programming Models (84%) and Wireless Sensor Networks (77%). Her recent publications reveal a trend toward interdisciplinary research that combines computational methods with societal challenges. She has made significant contributions to epidemic modeling during the COVID-19 pandemic, developing methods for accurate incidence rate estimation in Spain and analyzing information gains from multiple epidemic model outputs. Additionally, her work extends to medical applications including research on ocular ischemia and glaucoma, as well as innovative approaches to automated metadata annotation using machine learning techniques. Dr. Marinescu actively leads and participates in multiple research projects including Uncovering patterns of unconscious reactions to fake content (as Principal Investigator), MobilePressure (focused on reducing children's smartphone exposure), and ADAMIQS: Applied Data Analytics and Modelling IQS . These projects demonstrate her commitment to addressing contemporary issues through data-driven approaches while mentoring students and collaborating with interdisciplinary research teams.

• Human-Computer Interaction
• Task Modeling
• User Interface Design
• +3 more

Sybille Caffiau serves as a Lecturer in Data Engineering at ISAE-ENSMA's School of Engineering, affiliated with the LIAS laboratory across both ENSIP (Poitiers) and ISAE-ENSMA (Chasseneuil) campuses. Her research focuses on Human-Computer Interaction with specialization in task modeling and user interface validation. Her research interests span Human-Computer Interaction , Task Modeling , and User-Centered Design . She develops and evaluates tools like K-MADe for modeling user activities, with emphasis on empirical validation of task modeling approaches. Her work bridges cognitive science principles with practical software engineering applications, particularly in educational technology and interactive system design. Analysis of her publication trends reveals consistent contributions to HCI conferences and journals since 2006, with increasing focus on tool development (notably K-MADe) and empirical validation methodologies. Her recent work demonstrates strong interdisciplinary connections between cognitive modeling, software engineering, and educational technology. No scientific awards or fellowships are documented in the available materials. While her collaborative network includes prominent researchers like Laurent Guittet and Patrick Girard, specific details about student advising or research grants are not provided in the source materials. Her thesis work (2009) established foundations for model-driven interactive application design. She operates within the LIAS laboratory's Data Engineering team, contributing to research on interactive systems and task modeling frameworks. The KMADe environment represents her primary software contribution for activity description and task modeling.

Babatunde OlubandoView profile

Adjunct Professor

• Industrial Engineering
• Systems Engineering
• Software Engineering
• +4 more

Dr. Babatunde Olubando serves as an Adjunct Faculty member and Technical Support Specialist in the Department of Industrial and Systems Engineering at Morgan State University's Clarence M. Mitchell, Jr. School of Engineering. Based in Mitchell Engineering Building (Room 215) and Schaefer Engineering Building (Room 310), he leverages dual expertise in academic instruction and technical systems administration to support engineering education and research initiatives. His educational credentials include: Doctor of Engineering in Industrial Engineering, Software and Systems Engineering (Morgan State University, 2011) Master of Engineering in Industrial Engineering (Morgan State University, 2006) Bachelor of Science in Industrial Engineering, Manufacturing (Morgan State University, 2004) Dr. Olubando's research integrates industrial engineering principles with practical technology solutions, focusing on supply chain testbeds, RFID middleware, and web-enabled systems. His work emphasizes accessible tools for manufacturing education and small business applications, combining data analysis with software engineering to solve real-world operational challenges. Fluency in Yoruba further supports cross-cultural research collaboration. Recent publications demonstrate a clear shift toward applied technology development, with 2023 works concentrating on low-cost RFID systems and university-industry supply chain testbeds. This builds upon his foundational 2009 research in sociological modeling frameworks, reflecting an evolving trajectory from theoretical systems modeling to tangible engineering implementations. Professional recognition includes: Certified Six Sigma Green Belt (CSSGB) His technical capabilities span object-oriented analysis, web design (HTML/CSS/WordPress), and social media systems, enabling effective translation of complex engineering concepts into educational and operational tools. Current work focuses on expanding web-enabled supply chain applications through university partnerships.