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Joe DonndelingerView profile

Clinical Professor

• Engineering Design
• Interdisciplinary Design Feasibility
• Advanced Vehicle Development
• +7 more

Joe Donndelinger is a Clinical Professor of Professional Practice in the School of Engineering and Computer Science at Baylor University. With over 23 years of industry experience in automotive and cutting tool industries, he brings real-world engineering expertise into the academic setting. He teaches core engineering design and global business economics courses, bridging technical and professional skills. His educational background includes an M.S. in Industrial Engineering and a B.S. in Mechanical Engineering, both from the University of Illinois at Urbana-Champaign. Mr. Donndelinger's research focuses on interdisciplinary design feasibility, integrating engineering, marketing, and manufacturing domains. His work emphasizes customer-driven innovation, advanced vehicle development, and quality analytics. He has led numerous R&D projects as Principal Investigator at General Motors, contributing to innovation programs that shape modern vehicle systems. The analysis of his recent publications reveals a strong trend in cross-domain integration, particularly between engineering design and business economics. His work consistently addresses practical challenges in product development, feasibility assessment, and quality optimization, with applications in automotive and industrial systems. Published 25 peer-reviewed articles and 3 book chapters Holds 2 issued U.S. patents, with 3 more pending He has advised multiple engineering design projects and integrates industry practices into his teaching. Though formal student advisement is not detailed, his role in capstone design courses suggests significant mentorship. He has not received publicly listed scientific awards. Mr. Donndelinger is actively engaged in applied research and curriculum enhancement, particularly in professional practice and global communication for engineers. He leads initiatives that connect academic training with industrial needs, particularly through project-based learning and interdisciplinary collaboration. His work supports the development of well-rounded engineers prepared for global business environments.

Jeroen van der VeldenView profile

Associate Professor

• Strategic Management
• Digital Transformation
• Organizational Development
• +5 more

Dr. Jeroen van der Velden is an Associate Professor of Strategy Alignment and Director of the Faculty Research Center for Strategy, Organization & Leadership at Nyenrode Business University. His work focuses on how new technologies reshape organizational structures and daily human interactions, particularly in dynamic environments. He has been affiliated with the university since 2003, teaching courses on strategic management, digital transformation, and change management. His research explores strategy alignment, organizational agility, and the integration of technology into organizational processes. Key themes include digital transformation, organizational ambidexterity, and the role of leadership in managing change. Van der Velden has advised numerous industries, including finance, utilities, and telecom, supporting large-scale transformations at firms like ABN AMRO, ING, Shell, and government bodies. His scholarly contributions span over three decades, with articles addressing strategic frameworks, collaborative technologies, and organizational dynamics. Notable work includes studies on video-mediated communication, hybrid collaboration models, and the interplay of innovation and competitive advantage. He has pioneered user-centered evaluations of information systems and remains a thought leader in strategy execution and organizational adaptation. Van der Velden’s advisory engagements emphasize practical implementations of theoretical frameworks, bridging academic research with real-world organizational challenges. His research center at Nyenrode serves as a hub for interdisciplinary studies on leadership, strategy, and organizational resilience.

Jerry TaltonView profile

Assistant Professor

• Computer Graphics
• Machine Learning
• Human-Computer Interaction
• +3 more

Jerry Talton is an Assistant Professor in the Siebel School of Computing and Data Science at the University of Illinois at Urbana-Champaign (UIUC). He holds a PhD in Computer Science from Stanford University (2011), and BS and MS degrees from UIUC (2003 and 2006, respectively). His research focuses on computer graphics, machine learning, and human-computer interaction, with notable work on emoji-first communication, rating systems analysis, and data-driven design tools. Key contributions include the Opico study on emoji communication in social apps and the Bricolage algorithm for web design transfer. He received the Siebel School Young Alumni Achievement Award (2022). His work spans academic collaborations with institutions like Stanford and industry applications in social media and design. Research interests emphasize user interaction, algorithmic ranking, and leveraging big data for design automation. His publications address challenges in social networks, fluid simulation, and educational outreach through initiatives like Scavenger Hunt, enhancing student retention in computer science.

• Computer Graphics
• Image Processing
• 3D Modeling
• +5 more

George Wolberg is a Professor of Computer Science at the City College of New York (CCNY), affiliated with the Computer Engineering program. His research focuses on computer graphics, image processing, 3D modeling, and multimedia surveillance, with contributions to digital image warping, feature extraction, and algorithmic art. He holds an office at North Academic Center 8/202G and can be reached at wolberg@ccny.cuny.edu. Over his career, Wolberg has explored interdisciplinary applications such as medical imaging for hypertension analysis and robotic page-turning mechanisms for musicians. His work bridges theoretical foundations with practical implementations, including contributions to 3D urban modeling and sensor fusion systems. Notable trends in his publications include advancements in 3D reconstruction techniques (e.g., RGB-D camera calibration), interactive media systems (e.g., smart picture frames), and medical imaging applications. His research also extends to educational resources like Introduction to Image Processing . No scientific awards or major grants were explicitly listed in the provided materials. While no formal advisees are documented here, his extensive publication record reflects collaborative research efforts in computer vision and graphics.

• Aspect-Oriented Programming
• Modularity
• Software Engineering
• +4 more

Gregor Kiczales is a Professor of Computer Science at the University of British Columbia , with a career spanning over three decades. His work focuses on programming language design, modularity, and aspect-oriented programming (AOP). Primary affiliation: University of British Columbia Verification email: gregor@cs.ubc.ca Kiczales' research centers around modularity and aspect-oriented programming , with significant contributions to understanding crosscutting concerns, developing AOP frameworks like AspectJ, and exploring novel abstractions for software systems. His work includes: Foundational research in AOP semantics and implementation Studies on code-design alignment and software architecture Developing registration-based abstractions and late-binding mechanisms Investigating scalability challenges in AOP systems

Chris FietkiewiczView profile

Associate Professor

• Computational Neuroscience
• High Performance Computing
• Neural Simulation
• +7 more

Chris Fietkiewicz is an Associate Professor in the Department of Mathematics & Computer Science at Hobart and William Smith Colleges. He joined the faculty in 2019 and is based in Lansing Hall, with research interests in computational neuroscience and high-performance computing. Research Interests: His work focuses on Computational Neuroscience , particularly the development of neural simulators for educational and clinical applications. He leads the Applied Neural Control Toolkit (ANC Toolkit) , which enables simulation of neural and axonal responses for neuroprosthetic development. His research also spans High Performance Computing , including software optimization, parallel computing, and cluster management tools. Collaborations: He collaborates with Dr. Thomas Mortimer (Case Western Reserve University) on neural stimulation and with Dr. Chen Liu (Tianjin University) on Parkinson’s disease modeling and deep brain stimulation. His publications reflect a strong interdisciplinary focus on biomedical signal processing, control systems, and neuromorphic computing. Publication Trends: His recent work (2016–2022) centers on closed-loop control of pathological neural oscillations, computational models of Parkinson’s disease, and real-time neural simulation. These studies appear in top journals like IEEE Transactions and Biomedical Signal Processing and Control , emphasizing algorithmic innovation and clinical relevance. Scientific Contributions: Co-developer of the ANC Toolkit for neuroscience education. Researcher in neural control systems and HPC optimization. Active contributor to computational models of movement disorders. Advising and Grants: While no formal students are listed, his collaborative projects suggest mentorship of undergraduate and graduate researchers. Grant details are not provided, but his research cluster and web tools indicate funded infrastructure development. Labs and Teams: He is building a research computing cluster and developing web-based batch programming tools, indicating a focus on scalable, accessible computational neuroscience platforms.

Seshadri TirunillaiView profile

Associate Professor

• User-Generated Content (UGC)
• Advertising
• Marketing Strategy
• +7 more

Seshadri Tirunillai is an Associate Professor and the Marvin Hurley Professor of Marketing & Entrepreneurship at the C. T. Bauer College of Business, University of Houston. His research and teaching focus on digital marketing, user-generated content, advertising, marketing strategy, and sales analytics. Education: Ph.D. in Business Administration (Marketing), University of Southern California - Marshall School of Business Masters in Management, Indian Institute of Technology-Bombay, India B.E. (Hons) in Electrical and Electronics Engineering, Birla Institute of Technology and Science, Pilani, India His research lies at the intersection of marketing, data science, and digital platforms. He investigates how user-generated content influences brand perception and stock performance, how offline advertising affects online conversations, and how machine learning can extract strategic insights from big data. His work has been published in premier journals such as Journal of Marketing , Marketing Science , and Journal of Marketing Research . He frequently employs advanced analytical methods, including natural language processing and quasi-experimental designs, to derive actionable marketing insights. The recent publications reflect a consistent trend in leveraging large-scale digital data—especially social media and sales interactions—to understand consumer behavior, brand dynamics, and marketing effectiveness. His work bridges theoretical rigor with practical relevance in digital and data-driven marketing. Scientific Awards: MSI Scholar (2022) O'Dell Award (2019) Lehmann Award (2015) John A. Howard/AMA Doctoral Dissertation Award (2012) Best Paper, European Marketing Conference (2009) Best Reviewer, International Journal of Research in Marketing Best Reviewer, Journal of Interactive Marketing Finalist, Bass Dissertation Award (2014) Shankar-Spiegel Award Honorable Mention (2008) Seshadri Tirunillai has made significant contributions to marketing theory and practice through his research, editorial service, and teaching. He serves on the editorial boards of top journals including Marketing Science , Journal of Marketing Research , and Journal of Interactive Marketing . He teaches Digital Marketing Analytics (MARK 7366) at the graduate level and Introduction to Internet Marketing (MARK 3365) at the undergraduate level. His work has been supported by recognition from major marketing institutions, though specific grants are not detailed in the text. He is actively involved in academic leadership through editorial roles and professional associations, contributing to the advancement of marketing science and digital strategy research.

• Distributed Computing
• High-Performance Computing
• Distributed Shared Memory
• +7 more

Tore Brox-Larsen is an Associate Professor in the Department of Informatics at UiT The Arctic University of Norway. His work centers on distributed computing, high-performance systems, and large-scale visualization technologies. He is actively engaged in research involving sensor networks, Arctic observatories, and remote visualization of scientific data. His research interests span distributed shared memory systems, MPI performance, tiled display walls, and networked visualization. He has made significant contributions to improving communication efficiency in cluster computing and enabling scalable interactive visualization environments. His work bridges computer systems engineering with applications in genomics and environmental monitoring. The most recent publications reflect a strong trend toward real-world deployment of large-scale systems, particularly in Arctic observation and healthcare informatics. His work emphasizes practical system design, latency optimization, and cross-platform interoperability in distributed environments. Tore Brox-Larsen has collaborated extensively with researchers such as Otto Anshus, John Markus Bjørndalen, and Brian Vinter. While no formal advising or grant history is listed, his sustained publication record indicates active research leadership and team-based scientific inquiry. He has contributed to major projects including the development of a large-scale Arctic observatory sensor system and interactive tiled display walls. His work supports both academic research and societal applications in health and environmental science.

• Electronics Engineering
• Digital Systems Design
• Embedded Systems
• +12 more

Julio Martos Torres is an Associate Professor in the Department of Electronic Engineering at the School of Engineering, Universitat de València (UV). His work is centered in the DSDC Communications and Digital Systems Design Group, where he conducts research in embedded systems, condition monitoring, and educational technologies. He earned his PhD from UV in 2004 with a thesis on biomechanical measurement systems for wheelchair users. His research interests span electronics engineering , industrial monitoring , visible light communication , electromagnetic compatibility , geothermal energy systems , and engineering education . He has developed real-time systems for welding processes, sensor networks for thermal monitoring, and FPGA-based medical instrumentation. His recent work extends into interdisciplinary medical applications, particularly in gastroenterology, suggesting strong collaboration with clinical researchers. The most recent publications show a consistent trend in real-time monitoring systems , sensor design , and educational innovation in engineering. His work bridges theoretical electronics with practical industrial and medical applications, and he actively contributes to pedagogical advancements in STEM education through robotics and remote laboratories. Scientific awards are not mentioned in the provided text. Julio Martos Torres advises students and leads research within the DSDC group, focusing on applied electronics and digital systems. While specific grants are not listed, his involvement in high-profile projects like the ATLAS Tile Calorimeter suggests participation in large-scale collaborative funding initiatives. His work integrates industry collaboration and educational innovation, particularly in resistance welding monitoring and teaching methodologies. He is an active member of the DSDC Communications and Digital Systems Design Group , where his team develops advanced digital systems, wireless sensors, and educational platforms. The group emphasizes practical, industry-aligned research and innovative teaching tools, including robotic platforms and remote laboratories for STEM disciplines.

Marcelo CoelhoView profile

Academic

• Artificial Intelligence
• Industrial Design
• User Experience
• +3 more

Marcelo Coelho is an Associate Professor of the Practice in the Department of Architecture at MIT, where he teaches graduate and undergraduate design studios and directs the Design Intelligence Lab. His work integrates artificial intelligence, industrial design, and user experience to create innovative physical interfaces and systems. He holds a doctorate from MIT’s Media Lab and focuses on projects like Large Language Objects (LLO), Geolectric (sustainable materials for electronics), and Light Craft (AI-driven film lighting). His research interests span generative AI applications, sustainable materials, interactive technologies, and human-machine collaboration. Notable projects include the Paralympic Ceremony’s 'Beyond Vision' lighting performance and the 'Six-Forty by Four-Eighty' interactive lighting installation. He has been recognized with awards including the Prix Ars Electronica, Design Miami/ Designer of the Future, and Fast Company’s Innovation by Design. Marcelo teaches courses such as 4.031 (Objects and Interaction) and 4.043 (Interaction Intelligence). His work bridges academia and industry, emphasizing sustainable design and accessible creative tools. The Design Intelligence Lab explores AI’s role in fabrication, interaction, and material innovation.

Andreas Buttinger-KreuzhuberView profile

Researcher

• Hydrology
• Computational Fluid Dynamics
• Environmental Engineering
• +3 more

Andreas Buttinger-Kreuzhuber is affiliated with the Department of Engineering Hydrology at TU Wien. His research focuses on advanced hydrodynamic modeling, GPU-accelerated flood simulations, and integrating geospatial data for flood risk assessment. He contributed to projects like HORA 3.0, a national flood risk mapping initiative, and developed frameworks for high-resolution simulations of urban and rural flash floods. His work bridges computational science and environmental engineering, emphasizing real-world applications in disaster management and urban planning. Education: Dipl.-Ing. (FH) in Civil Engineering, Dr.techn. (PhD) in Technical Sciences, and BSc in a related field. Notable research themes include shallow-water schemes optimization, interactive visualization tools for flood management, and nanopore fluid dynamics. His interdisciplinary approach combines hydraulic modeling with geomatics and computational fluid dynamics. Collaborations include work with Prof. Günter Blöschl and the Network Lab at TU Wien. Recent efforts focus on accelerating hydrodynamic simulations using GPU technology and improving regional-scale flood modeling accuracy.

Shannon DriskellView profile

Professor

• Mathematics Education
• Technology Integration in Education
• Pedagogy of Mathematics
• +7 more

Shannon Driskell is a Professor in the Department of Mathematics at the University of Dayton, within the College of Arts and Sciences. She is a full-time faculty member with extensive contributions to mathematics education and technology integration in teaching. Education: Ph.D. in Mathematics Education, University of Virginia, 2004 M.A. in Instructional Technology, East Carolina University, 1997 B.S. in Mathematics, Edinboro University, 1992 Her research focuses on mathematics education, particularly the integration of technology in teaching and learning. She explores how dynamic software enhances understanding of geometry and statistics among middle and secondary school teachers. Her work emphasizes pedagogical content knowledge, especially through the TPACK framework, and investigates effective professional development models for pre-service and in-service teachers. She has also contributed to curriculum development and instructional strategies for geometric reasoning and statistical problem solving. The recent publications reflect a strong trend in educational technology, teacher training, and research methodology in mathematics education. Her work consistently addresses how digital tools transform pedagogy and improve student outcomes, with a focus on teacher cognition and classroom application. Scientific Awards: Manuscript awarded the National Technology Leadership Initiative Award Driskell has been actively involved in advising and collaborative research, contributing to national position statements and handbooks in mathematics teacher education. She has participated in numerous funded research projects related to technology in education, though specific grants are not listed. She has presented widely at national conferences such as AMTE and PME-NA, demonstrating sustained scholarly engagement. She is associated with research teams focused on technology integration in mathematics education, particularly through collaborative projects on TPACK and dynamic software use. Her work often involves interdisciplinary teams across institutions, contributing to large-scale research initiatives in teacher development and educational innovation.

Zihan WuView profile

Assistant Professor

• Human-Computer Interaction
• Computing Education Research
• Educational Technology
• +3 more

Zihan Wu is an Assistant Professor at the University of Maine's School of Computing and Information Science (SCIS), where he leads the Puffin Lab (Participation, Understanding, Feedback, and Interaction for Novices). His academic journey includes a Ph.D. from the University of Michigan School of Information under Dr. Barbara Ericson and a Bachelor's in Computer Science from Tsinghua University. Education: Ph.D., University of Michigan, School of Information Bachelor's in Computer Science and Technology, Tsinghua University Dr. Wu's research bridges Human-Computer Interaction (HCI) and Computing Education Research (CER) , focusing on creating scalable educational tools through human-centered design and learning theory integration. His work employs mixed-methods evaluation including large-scale classroom studies and lab experiments, with emphasis on AI-supported programming tools, accessibility solutions, and novice learning experiences. His 2020-2025 publications reveal a strong trajectory in programming education tools (particularly Parsons Problems variants), AI-human co-creation systems, and accessibility technologies. Key venues include CHI, ICER, and AIED, demonstrating cross-disciplinary impact in both HCI and computing education communities. Scientific Recognition: Best Paper Nomination at CHI 2024 Best Paper Nomination at L@S 2024 Honorable Mention at CHI 2020 Dr. Wu actively mentors through the Puffin Lab, recruiting PhD students for Fall 2026 and research assistants for educational technology projects. His teaching portfolio includes Human-Centered Design courses at University of Maine and prior instruction in Web Development, Data Manipulation, and Data Mining at University of Michigan. The Puffin Lab drives innovation in novice computing education through tools that enhance participation, understanding, and feedback mechanisms, with current projects exploring LLM-powered personalized learning and context-aware creative systems.

Masashi ToyodaView profile

Associate Professor

• Web Mining
• User Interfaces
• Information Visualization
• +4 more

Masashi Toyoda is an Associate Professor at the Institute of Industrial Science, University of Tokyo. He leads the Kitsuregawa and Toyoda Laboratory and is affiliated with the International Research Center for Strategic Information Fusion. His research focuses on web mining, user interfaces, and information visualization. Education: Ph.D. in Computer Science, Tokyo Institute of Technology (1999) M.S. in Computer Science, Tokyo Institute of Technology (1996) B.S. in Computer Science, Tokyo Institute of Technology (1994) His research interests span web mining, user interfaces, information visualization, and visual programming. He has conducted significant work in spatiotemporal web analysis, web spam detection, evolution of web communities, and visualization techniques including zooming interfaces and 3D web graph visualization. Recent publications (2008-2011) demonstrate strong focus on web mining, information visualization, and web security. Research trends include 3D visualization of time-series web data, analysis of blog archives and CGM images, and novel methods for detecting and classifying web spam. The work consistently emphasizes large-scale web data analysis and interactive systems. Scientific Awards: 1st DBSJ Paper Award Winner (2003) FIT Paper Award and Funai Best Paper Award (2002) Best Presentation Award at DEWS2002 Presentation Award at DEWS2000 Best Paper Award at DEIM2011 Conference Excellence Award at IPSJ 72nd National Convention As head of the Toyoda Laboratory at the University of Tokyo, he leads research in web mining, information fusion, and visualization. The lab has developed notable projects including WebRelievo for web structure evolution analysis and KLIEG visual programming environment.

Eva Cernadas GarcíaView profile

Associate Professor

• Machine Learning
• Computer Vision
• Image Segmentation
• +6 more

Eva Cernadas García is an Associate Professor at the Escola Técnica Superior de Enxeñaría of the University of Santiago de Compostela (USC), where she conducts research at the intersection of machine learning, computer vision, and practical applications in medicine, food technology, and marine resource management. Her academic position is firmly established within the Computer Science department, where she has developed significant expertise in image segmentation, texture analysis, and shape recognition. Dr. Cernadas' research interests span multiple domains of artificial intelligence with a strong emphasis on practical implementations. She specializes in developing computer vision algorithms for medical diagnostics, including software tools like CystAnalyser for polycystic kidney disease detection, STERapp for stereological analysis, and PDApp for dental eruption prediction. Her work extends to food technology applications such as MarblingPredictor for ham quality assessment and Govocitos for fish fecundity estimation. Notably, she integrates gender perspective into her technical work, having been awarded by USC in 2021 for introducing gender perspective in machine learning teaching. Analysis of her recent publications reveals a strong focus on applying machine learning techniques to solve real-world problems across diverse fields. Her work demonstrates consistent innovation in developing efficient algorithms for classification and regression tasks, with increasing attention to gender issues in STEM education. The publications show progression from fundamental algorithm development to practical implementations in medical diagnostics, mental health assessment, and sustainable resource management. Awarded by the University of Santiago de Compostela for the introduction of the gender perspective in machine learning teaching in 2021 Dr. Cernadas actively promotes gender equality in STEM through various initiatives including designing workshops for primary education in the program 'Unha enxeñeira ou cientifica en cada cole', early childhood education programs, and promoting the 'INFORMATIZATE' video contest for non-university students. Her research includes significant grant-funded projects related to service robots, intelligent control scenarios, and development of new technologies for studying reproductive ecology in fishery. She collaborates extensively with researchers across multiple disciplines, particularly with Manuel Fernández-Delgado, with whom she has co-authored numerous publications. Her laboratory work focuses on developing practical software tools that bridge the gap between theoretical machine learning algorithms and real-world applications. The CITIUS research center at USC appears to be her primary research base, where she contributes to projects involving image analysis, pattern recognition, and development of user-friendly interfaces for domain experts in medicine and biology.