جست‌وجوی استاد و پژوهشگر

• Empirical Management Accounting
• Incentives
• Performance Measurement
• +۵ مورد دیگر

Maximilian Margolin is an Assistant Professor at the Rotterdam School of Management (RSM), Department of Accounting & Control. He joined RSM in September 2019 after completing his doctorate at WHU – Otto Beisheim School of Management, an MA in Accounting and Finance from the University of St. Gallen, and a BSc in Business Administration from the University of Mannheim. His research focuses on empirical management accounting , particularly examining incentives , performance measurement , and the role of cognitive flexibility in controller-manager collaboration. Recent work explores the integration of artificial intelligence (e.g., ChatGPT) in accounting education and assessment. Notable publications include studies on real-time feedback systems in performance contexts AI-driven accounting chatbots cognitive dynamics in business partnerships His work bridges traditional accounting principles with modern behavioral and technological challenges.

• Biomanufacturing
• Stem Cell Therapy
• Cell Culture Automation
• +۳ مورد دیگر

Robert Thomas is a Professor of Manufacturing for Cell and Gene Therapies at Loughborough University, holding an RCUK Academic Fellowship in Biomanufacturing. He leads the Healthcare Engineering Research Group and specializes in optimizing therapeutic cell manufacturing processes. Education: MPharm (Nottingham University, 2001), PhD in Tissue Engineering (Nottingham University, 2006) His research focuses on scalable bioprocessing, automation in cell therapy production, and improving manufacturing consistency for regenerative medicines. Key areas include stem cell expansion, cryopreservation systems, and mechanistic modeling for process optimization. Notable contributions include developing automated vial thawers for mesenchymal stem cells and evaluating novel container systems for viral vectors. His work bridges engineering principles with biomedical applications to advance clinical-grade cell therapies. Awards: RCUK Academic Fellowship (2007) Grants and advising details are not explicitly listed in the provided text. He collaborates extensively with industry partners to translate lab-scale processes into clinical manufacturing solutions.

Thierry Eudeمشاهده پروفایل

استاد مهمان

• Image Compression
• Image Quality Assessment
• Medical Imaging
• +۳ مورد دیگر

Thierry Eude is a Visiting Professor at the University of Burgundy, affiliated with the Computer Science Department of the IUT of Dijon. He holds a Doctorate in Physical Sciences (Industrial Computing) and has held academic roles including Director of the IUT's Computer Science Department (1999–2002). His research focuses on image compression, quality assessment, and perceptual metrics, with notable contributions to medical imaging and human vision models. Education includes a DEA in Instrumentation and Control, and a Master's in Advanced Maintenance Techniques. He collaborates with institutions like Laval University and University of Paris 13, and leads projects on digital twin technology, automated evaluation systems, and content-based image retrieval. Key research areas span image compression techniques, subjective/psychovisual quality metrics, and segmentation algorithms. His work integrates human visual system models to enhance compression efficiency and quality evaluation. Over 30 peer-reviewed articles since 1993 reflect his expertise in digital imaging and multimedia systems. Awards include membership in the Order of Engineers of Quebec and academic qualification for lecturer roles. He advises students on projects in image coding, quality metrics, and machine learning applications. Current initiatives include hybrid learning models and biometric authentication for remote evaluation. Laboratory affiliations include LE2I (UMR CNRS 5158) and LVSN, focusing on interdisciplinary projects in signal processing and database systems.

Clemente Ibarra-Castanedoمشاهده پروفایل

پژوهشگر

• Nondestructive Testing and Evaluation
• Infrared Thermography
• Digital Signal Processing
• +۳ مورد دیگر

Clemente Ibarra-Castanedo is a Researcher at Laval University's Electrical and Computing Engineering Department, affiliated with the Computer Vision and Systems Laboratory. He holds a Ph.D. in Electrical Engineering (2005), M.Sc. and B.Sc. in Mechanical Engineering from Laval University and Regiomontana University, respectively. His primary research focuses on Nondestructive Testing (NDT) using Infrared Thermography, Digital Signal Processing, and Heat Transfer modeling. He has extensive experience in academic and industrial projects, including roles as a Research Engineer in France and Canada, and Graduate Assistant at Laval University. Key research interests include quantitative subsurface defect evaluation, thermal modeling of composites, and image analysis techniques. He has authored over 138 publications, including peer-reviewed articles on pulsed phase thermography and composite inspections. Awards include the Quebec Excellence Scholarship (2000-2001). Affiliations include ASME, IEEE, and SPIE memberships. His work integrates advanced imaging systems, drone-based inspections, and machine learning for structural health monitoring. Collaborative projects span aerospace composites, civil infrastructure, and cultural heritage preservation. His lab develops innovative non-invasive inspection tools, including drone-enabled thermography and automated defect detection algorithms. Publications highlight contributions to thermal data enhancement, fusion techniques, and deep learning applications in NDT.

Oscar José Pellicer Valeroمشاهده پروفایل

استادیار

• Climate Remote Sensing
• Medical Image Analysis
• Artificial Intelligence
• +۳ مورد دیگر

Assistant Professor at University of Valencia, Spain with evolving research focus from medical image analysis to climate remote sensing applications. Current work emphasizes AI-driven solutions for environmental monitoring while maintaining expertise in medical imaging developed through previous research. Research interests span both medical and environmental domains with strong emphasis on AI applications. Primary expertise includes deep learning architectures for image analysis, with demonstrated capability in both medical diagnostics (particularly prostate cancer detection from MRI) and climate-related remote sensing. Current trajectory shows strategic pivot toward environmental applications of computer vision techniques. Publications demonstrate significant contribution to medical imaging literature, particularly in developing fully automated systems for prostate cancer detection. The 2022 Scientific Reports paper established technical approach using Retina U-Net for lesion detection, segmentation and Gleason grading from multiparametric MRI data. Professional activities include active software development with multiple GitHub repositories showing technical proficiency in Python, medical imaging libraries, and deep learning frameworks. Current repository activity indicates ongoing development in climate and remote sensing applications.

Ann E. Elsnerمشاهده پروفایل

استاد

• Retinal Imaging
• Ophthalmology
• Optometry
• +۳ مورد دیگر

Ann E. Elsner is a Distinguished Professor at the Indiana University School of Optometry, serving as Graduate Faculty with endorsement to chair PhD committees. Her research laboratory focuses on advanced retinal imaging techniques for diagnosing and monitoring ocular diseases, with particular emphasis on diabetic retinopathy and age-related macular degeneration (AMD). Education: Ph.D., University of Oregon (1977) Dr. Elsner's research integrates optical engineering with clinical ophthalmology to develop novel imaging methodologies. Her work centers on scanning laser ophthalmoscopy, polarimetry, and spectral imaging to visualize subretinal structures and quantify pathological changes. Key innovations include low-cost retinal imaging devices and techniques for detecting early photoreceptor damage in diabetic patients. She maintains active collaborations with ophthalmology departments globally to validate imaging biomarkers for disease progression. Analysis of her 15 most recent publications (2002-2005) reveals consistent focus on improving contrast in retinal imaging through polarization analysis, spectral techniques, and motion correction. These works establish methodological frameworks for detecting AMD progression, quantifying vascular changes, and visualizing subretinal pathology. Her research bridges engineering innovation with clinical diagnostics, emphasizing practical applications for early disease detection. Scientific Awards: No specific awards documented in provided materials As Graduate Faculty with PhD committee chairing privileges, Dr. Elsner mentors doctoral candidates in vision science and optical engineering. She currently leads two NIH-funded research projects: "Spatial Extent of Retinal Damage" investigating diabetic retinopathy biomarkers, and "Low-Cost Device for Digital Retinal Imaging" developing accessible diagnostic technology for underserved populations. Her grants emphasize translational research with immediate clinical applications. Her laboratory operates within the Indiana University School of Optometry's research infrastructure, utilizing custom-built scanning laser ophthalmoscopes and polarization imaging systems. The team collaborates with clinical partners at IU Health for patient studies and device validation, maintaining strong ties with international researchers in retinal imaging through publications and conference presentations.

• Computer Science Education
• Educational Technology
• Mastery Learning
• +۳ مورد دیگر

Daniel D. Garcia is a Professor in the Department of Computer Science at the University of California, Berkeley. He specializes in computer science education, focusing on innovative teaching methods, mastery learning, and the development of educational technology tools. His work includes contributions to platforms like Snap!, Prairielearn, and GradeSync, which aim to enhance student engagement and learning outcomes through adaptive and automated systems. Research Interests Computer Science Education: Developing curricula and tools for K-12 and university-level instruction. Educational Technology: Designing interactive tools like Snap! and automated assessment systems. Mastery Learning: Implementing policies and systems to improve student success in computing courses. Cybersecurity Education: Integrating security concepts into introductory computing courses. Articles Trends Recent work emphasizes tools for automated assessment (e.g., Checkpoint, GradeSync), mastery learning systems, and interactive programming environments. He also explores the impact of course policies on student performance and sentiment. Awards No specific awards listed in the provided texts. Advising & Grants Collaborates with teams on grants related to educational technology and curriculum development, though specific grants are not detailed here. Advises students on projects related to the Beauty and Joy of Computing (BJC) curriculum and Snap! development. Labs/Teams Part of the BJC curriculum development team and leads initiatives at UC Berkeley for improving computing education through technology and pedagogy innovation.

• AI/ML
• Cloud Computing
• Manufacturing Engineering
• +۳ مورد دیگر

Jeanetta Zotter is a part-time PhD Candidate at Loughborough University, researching IoT, AI, and cloud-assisted smart manufacturing in aerospace contexts. Her academic background includes an MBA in Engineering Management from Wilhelm Büchner Hochschule and a B.Sc. in Mechatronics, Robotics, and Automation from Fachhochschule Wiener Neustadt. She specializes in applying AI and IoT to optimize manufacturing processes, particularly for aerospace applications like Airbus systems. Education: PhD Candidate (Part-Time): Computer Science & Manufacturing Engineering, Loughborough University MBA (A Grade): Engineering Management International, Wilhelm Büchner Hochschule B.Sc.: Mechatronics, Robotics & Automation, Fachhochschule Wiener Neustadt Research Focus: Combines AI/ML, cloud computing, and IoT to enhance smart factory operations. Her thesis explores 'IoT Delivered Data Powered by AI for Cloud-Assisted Smart Factory' under supervisors Prof. Roy Kalawsky (Airbus Research Chair) and Dr. Konstantinos Kyriakopoulos. Additional interests include nanotechnology and AI in retail. Career Highlights: 13+ years in tech startups and multinational corporations as a sales leader/entrepreneur, with expertise in international strategy and technology adoption. Lifestyle & Culture: Passionate about cross-cultural collaboration, having lived in 7 countries. Engages in salsa/bachata dancing, running, and global travel.

Bob Edmisonمشاهده پروفایل

دانشیار

• Computer Science Education
• Software Engineering
• Feedback Mechanisms
• +۴ مورد دیگر

Bob Edmison is a Collegiate Associate Professor in the Department of Computer Science at Virginia Tech, affiliated with the College of Engineering. He serves as the Online Teaching and Learning Coordinator. His research focuses on enhancing computer science education through software engineering tools, particularly developing feedback mechanisms for students. He holds a Ph.D. in Computer Science and Applications (2019), M.IT. in Information Technology (2006), M.A.Ed. in Curriculum and Instruction (1995), and a B.A. in Economics (1992), all from Virginia Tech. Edmison's work bridges software engineering and education, emphasizing automated feedback systems, learning analytics, and accessibility. He previously led the Software Development team at Virginia Tech’s Technology-enhanced Learning and Online Strategies (TLOS) division, managing enterprise learning systems like Canvas. His earlier roles include Senior Research Associate at the Software Technologies Laboratory and industry experience in web development. His research has explored heatmaps for debugging assistance, learning management system utilization frameworks, and grading innovations. Notable contributions include 'Depth of Use' (2020) and 'Turn up the Heat!' (2020), advancing educational technology practices. Edmison teaches courses like CS 5040 (Data Structures), CS 5744 (Software Design), and CS 3114 (Algorithms), emphasizing practical software engineering skills. He actively engages in professional development, presenting at conferences like InstructureCon and ITiCSE.

Margaret Ellisمشاهده پروفایل

استاد

• Computer Science Education
• Undergraduate Teaching
• Curriculum Design
• +۵ مورد دیگر

Margaret Ellis is a Professor in the Department of Computer Science at Virginia Tech's College of Engineering. She holds a B.S. in Mathematics and an M.S. in Computer Science from Virginia Tech. Her academic roles include teaching CS2104 (Problem Solving in Computer Science) and CS2114 (Software Design and Data Structures), as well as leading initiatives like the Broadening Undergraduate Research Groups in Systems (BURGS) and the Computer Systems Genome Project. Ellis is recognized for her contributions to undergraduate teaching and diversity initiatives, highlighted by the 2024 IEEE Mary Kenneth Keller Award. Education: B.S. Mathematics (Virginia Tech), M.S. Computer Science (Virginia Tech) Research Interests: Computer Science Education, Student Motivation, Curriculum Design, and Diversity in STEM Service: Serves on committees like the College of Engineering Diversity Committee and the SIGCSE Organizing Committee Her research emphasizes practical computing skills integration, motivational climate in courses, and broadening participation in computer systems research. Ellis has led projects such as the 'Hidden Figures' initiative showcased at SC23 and co-authored numerous papers on student performance and educational strategies. Awards: 2024 IEEE Teaching Award, 2023 Faculty Service Award, 2020 Dean's Excellence in Teaching Award Grants/Projects: BURGS, Computer Systems Genome Project, Edamame Supply Chain Case Study Ellis's outreach efforts include Hidden Figures Day, Women in Computing events, and K-12 educational app development for special needs students.

Mohammed Seyamمشاهده پروفایل

دانشیار

• Computer Science Education
• Agile Development
• Software Engineering
• +۳ مورد دیگر

Mohammed Seyam is a Collegiate Associate Professor in the Department of Computer Science at Virginia Tech, where he also serves as the Experiential Learning coordinator. He holds a Ph.D. and M.S. in Computer Science from Virginia Tech, along with an M.Sc. in Information Systems from Cairo University and a B.Sc. in Information Systems from Mansoura University. His research focuses on software engineering, agile development, computer science education, usability engineering, and integrating ethics into technical curricula. His educational background spans multiple institutions, with a strong emphasis on both theoretical and applied computer science. Dr. Seyam is particularly known for advancing experiential learning methodologies and addressing ethical dimensions in computing education. His work often bridges pedagogical innovation with practical software development practices. In research, Seyam explores topics such as AI-driven educational tools, usability evaluation frameworks, and the design of inclusive computing curricula. Recent studies highlight his contributions to capstone course design, automated assessment systems, and the ethical integration of AI in learning environments. His publications reflect a commitment to improving both technical and educational practices, with a focus on machine learning applications in education, ethics in CS courses, and student performance prediction. Current projects emphasize training future teaching-focused faculty and enhancing global perspectives in higher education.

• Precision Agriculture
• Biomass Processing
• Soil Management
• +۱ مورد دیگر

Tony E Grift serves as Professor in Agricultural and Biological Engineering at the University of Illinois, with joint appointment at the National Center for Supercomputing Applications. His research advances precision agriculture technologies, biomass processing systems, and sustainable soil management practices. Grift's work integrates engineering principles with agricultural applications to optimize production systems. Research domains include: Machine vision systems for crop monitoring Soil compaction dynamics under machinery systems Biomass densification processes Robotics for agricultural operations Publication analysis reveals consistent focus on machinery-soil interactions, precision measurement techniques, and economic sustainability of agricultural innovations. Recent work emphasizes computer vision applications for yield prediction and quality assessment. Honors include the NACTA Educator Award (2017) recognizing teaching excellence. His research laboratory develops practical solutions for biomass logistics, soil conservation, and automation in field operations, with projects spanning sugarcane lodging detection to tire pressure optimization.

• Formal Methods
• Model Checking
• Automata Theory
• +۵ مورد دیگر

Mahesh Viswanathan is a Professor and Associate Head at the Siebel School of Computing and Data Science at the University of Illinois. His primary research focuses on formal methods, automata theory, and model checking, with applications in computer security, runtime verification, and cyber-physical systems. He received the NSF CAREER Award in 2005 for his contributions to these fields. His research explores: Foundations of automata theory and formal verification Runtime assurance mechanisms for safety-critical systems Concurrency analysis and race detection algorithms Differential privacy and security protocol verification Theoretical aspects of real-time and hybrid systems Viswanathan's recent publications demonstrate a strong focus on developing theoretically-grounded verification techniques for practical applications. His work frequently combines formal methods with machine learning approaches to solve challenging problems in program verification and system security. Awards and Honors: NSF CAREER Award (2005)

Boran Zhouمشاهده پروفایل

استادیار

• Medical Imaging
• Ultrasound Elastography
• Radiation Oncology
• +۳ مورد دیگر

Boran Zhou is an Assistant Professor in the Department of Radiation Oncology at Baylor College of Medicine. His research focuses on medical imaging technologies, particularly ultrasound elastography and AI-driven image analysis, with applications in radiation oncology, pulmonary disease assessment, and vascular mechanics. Zhou holds a BE from Harbin Institute of Technology (2009), a PhD from the University of South Carolina (2014), and completed a residency at Medstar Georgetown University Hospital (2023). His work spans advancements in ultrasound-based diagnostic techniques, including lung surface wave elastography for interstitial lung disease staging, AI-driven quantitative imaging for radiation toxicity monitoring, and vascular biomechanics of arterial tissues. He has pioneered non-invasive methods for assessing carpal tunnel pressure, penile tissue viscoelasticity, and papilledema via ultrasound vibro-elastography. Zhou’s research also addresses clinical challenges such as radiation-induced breast toxicity and erectile dysfunction through longitudinal ultrasound studies. His interdisciplinary approach integrates machine learning, biomechanical modeling, and clinical validation across oncology, pulmonology, and ophthalmology.

Amjad Hossainمشاهده پروفایل

مدرس

• Structural Engineering
• Earthquake Engineering
• Structural Dynamics
• +۴ مورد دیگر

Amjad Hossain is a full-time Lecturer in the Department of Construction Management at the University of Texas at Tyler, part of the College of Engineering. He holds an M.A.Sc in Civil Engineering (Concordia University, 2006) and is a Ph.D. Candidate in Structural Engineering. A licensed Professional Engineer in Texas and Washington (USA) and former P.Eng in Alberta (Canada), he brings over 15 years of structural engineering design experience in North America. Prior roles include adjunct Professor at the University of Houston and teaching/research assistant at Concordia University. His research focuses on Structural Dynamics, Earthquake Engineering, Structural Health Monitoring, Reinforced Concrete Design, and Finite Element Method applications . He has published widely in structural engineering conferences, including works on seismic performance of concrete shear walls and vibration analysis. Courses taught include Construction Structural Systems, Advanced Estimating, and Steel/Concrete Applications. Notable technical expertise includes matrix analysis methods, earthquake-resistant building design, and professional licensure across multiple jurisdictions. While no explicit awards are listed, his publications reflect sustained engagement with structural safety and innovation.