جست‌وجوی استاد و پژوهشگر

Mark Stehlikمشاهده پروفایل

استاد آموزشی

• Computer Science Education
• K-12 Outreach
• Programming Pedagogy
• +۳ مورد دیگر

Mark Stehlik is a University Teaching Professor, Assistant Dean for Outreach, and Director of the CSD Undergraduate Program at Carnegie Mellon University's School of Computer Science (SCS). He holds dual affiliations with the Computer Science Department and the SCS Dean's Office. His administrative support is provided by Amy Weis. Stehlik's research focuses on computer science education, K-12 outreach, and curriculum design. Notable projects include the CMU CS Academy, a browser-based programming platform for high school education, and initiatives to address the lack of K-12 CS education in the digital age. He has published extensively on topics like text-based programming, cognitive load in education, and international outreach in Qatar. Recent publications emphasize bridging early college success through programming education and addressing cognitive challenges in curriculum design. His work spans over four decades, with foundational contributions to introductory programming pedagogy via tools like Karel J Robot. Stehlik's teaching roles include courses such as 15-090, 15-111, and 15-594, reflecting his commitment to undergraduate education. His outreach efforts aim to broaden participation in computing through innovative programs and policy advocacy.

Larry Rudolphمشاهده پروفایل

استاد پژوهشی

• Mobile Computing
• Pervasive Computing
• Computer Networks
• +۷ مورد دیگر

Larry Rudolph is a Research Professor at the Massachusetts Institute of Technology (MIT), affiliated with the Computer Science and Artificial Intelligence Laboratory (CSAIL). He holds the role of Principal Research Scientist and has been a key contributor to projects like the Oxygen Research Group and the Computational Structures Group (CSG). His academic journey includes roles as a Full Professor at the Hebrew University of Jerusalem and postdoctoral research at the University of Toronto. Rudolph specializes in pervasive computing, mobile systems, and virtualization, with notable contributions to Bluetooth technology and location-aware computing. He has advised numerous students and pioneered courses such as MIT's 6.883 Pervasive Human-Centric & Mobile Computing. Education: PhD in Mathematics, Courant Institute, NYU (1977-1981) Postdoc in Computer Science, University of Toronto (1981-1982) Research Faculty, Carnegie-Mellon University (1982-1986) Full Professor, Hebrew University (1986-1997) Research Interests include mobile device virtualization, privacy in pervasive systems, and adaptive algorithms for personal data management. He co-founded Redigi, a marketplace for digital music resale, and led VMware's Mobile Virtualization Project. His work emphasizes experimental approaches to computer science, integrating hardware and software innovations. Notable Projects: Bluetooth Essentials for Programmers (book, 2007) Oxygen Research Group (2000-2005) Virtualization and pervasive computing systems Advising and Collaborations: Guided over 15 students to completion of Master’s and PhD theses Co-organizer of DOE Supercomputer Valuation and Workshop on Job Scheduling Contributions to CSAIL and NECSI (New England Complex Systems Institute) Labs/Teams: Active in CSAIL's Pervasive Computing initiatives and Oxygen sub-projects. Current focus includes mobile phone security, privacy-aware systems, and adaptive learning frameworks for personal data tagging.

Graeme Jenkinsonمشاهده پروفایل

پژوهشگر ارشد

• Computer Architecture
• Programming Languages
• Security
• +۳ مورد دیگر

Dr Graeme Jenkinson is a Senior Research Associate in the Department of Computer Science and Technology at the University of Cambridge. His research focuses on computer architecture, programming languages, security, systems, and networking. He contributes to projects such as the Pico password replacement system and OpenDTrace , exploring topics like memory safety standards, usable security designs, and authentication systems. His work bridges theoretical computer science with practical system implementations, emphasizing secure software development and user-centric security solutions. Key research interests include: Cybersecurity frameworks for authentication systems Memory safety in programming languages Provenance tracking for network security Usability of security interfaces Secure system design principles Recent publications highlight his contributions to authentication usability studies, APT monitoring techniques, and secure delegation protocols. His research often addresses real-world challenges in deploying secure systems while maintaining user accessibility.

Jane Waiteمشاهده پروفایل

پژوهشگر ارشد

• Computing Education
• Artificial Intelligence in Education
• Primary Education Pedagogy
• +۳ مورد دیگر

Jane Waite is a Senior Research Scientist at the Raspberry Pi Computing Education Research Centre, part of the University of Cambridge's Department of Computer Science and Technology. She holds a PhD from Queen Mary University of London and has extensive experience as a primary school teacher, IT industry developer, and teacher trainer. Her work focuses on K-12 computing education, AI literacy for young learners, and culturally responsive teaching practices. Education background includes a PhD in computing education from QMUL, complementing her prior career in education and industry. Her research explores programming pedagogy (e.g., PRIMM framework), design-based learning, and application of Legitimation Code Theory (LCT) in classroom settings. She leads initiatives like the Barefoot Computing project and TechPathways, funded by DfE and Mayor of London grants. Key areas of expertise include broadening participation in computing, teacher professional development, and integrating AI education into K-12 curricula. She actively collaborates with educators and industry professionals, presenting at conferences and publishing widely in journals like Computers & Education and Computer Science Education.

Claudio Silvaمشاهده پروفایل

استاد

• Visualization and Graphics
• Geometric Computing
• Data Science
• +۲ مورد دیگر

Claudio Silva is an Institute Professor of Computer Science and Engineering at NYU Tandon School of Engineering and Professor of Data Science at NYU Center for Data Science. He co-founded the Center for Urban Science and Progress (CUSP) and the Visualization, Imaging and Data Analysis (VIDA) Center. His academic journey includes a BS in mathematics from Universidade Federal do Ceará (1990) and PhD in computer science from SUNY Stony Brook (1996). Co-Director, VIDA Center Former Professor, University of Utah (2003-2011) Technology Consultant, MLB Advanced Media (2012-2017) Research Interests : At the intersection of visualization, geometric computing, and urban/sports analytics, his work includes: AR task guidance systems (ARGUS, HuBar) Urban data analysis (3D visualization, sidewalk mapping) LLM multimodal reasoning (POEM, BDIViz) Biomedical data tools (TopoMap++, T-Explainer) 2023-2025 Research Trends : Recent publications focus on neuroadaptive AR systems (AdaptiveCoPilot), LLM prompt optimization (POEM), explainable AI frameworks (T-Explainer), and urban data visualization (Urban Rhapsody). Collaborations span NYU, Northrop Grumman, and NSF/DARPA grants for projects like OSCUR and PTG. Scientific Honors : ACM Fellow (2024) IEEE Visualization Academy (2019) IEEE Technical Achievement Award (2014) Technology Emmy for Statcast (2018) His lab has developed open-source tools like ARGUS on GitHub and pioneered methods in fNIRS-based cognitive workload analysis for pilot training systems. Current projects include NASA-funded OpenSpace and NSF-backed OSCUR.

Abdullah Al-Mamunمشاهده پروفایل

استادیار

• High-Performance Computing
• Distributed Systems
• Blockchain Technology
• +۵ مورد دیگر

Abdullah Al-Mamun is an Assistant Professor and Director of the High Performance & Secure Data Computing (HPSDC) Lab at Augusta University's School of Computer and Cyber Sciences. His research focuses on resource-efficient distributed systems, high-performance computing, and blockchain-based solutions for secure data management. He holds a Ph.D. from the University of Nevada, Reno, and a double M.Sc. from RWTH Aachen University and the University of Trento under the Erasmus Mundus program. His work has been supported by grants including an NSF CRII award ($165,000) and a Google Cloud Research Grant ($10,000). Education: Ph.D., Computer Science & Engineering (2022), University of Nevada, Reno M.Sc., Computer Science (2013), RWTH Aachen University / University of Trento (Double Degree) B.Sc., Computer Science & Engineering (Summa Cum Laude, 2009), American International University-Bangladesh Research Interests: High-Performance Blockchain Resource-Efficient HPC Extreme-Scale Data Management Secure Data Provenance Edge Computing Selected Awards: NSF CRII Award (2024–2026) Best Paper Award (Cloud'19) Outstanding Graduate Student Scholarship (UNR, 2020–2021) Service & Teaching: ACM Programming SIG Club Advisor (2023–present) Reviewer for IEEE IoT Journal, IEEE Transactions on Consumer Electronics, and others Teaches courses in Low-Level Programming, Computer Architecture, and High-Performance Computing Labs & Teams: Directs the HPSDC Lab, publishing in top-tier venues like SC, ICDE, and IPDPS.

Gerrit Meixnerمشاهده پروفایل

استاد پژوهشی

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +۳ مورد دیگر

Prof. Dr.-Ing. Gerrit Meixner is a Research Professor for Human-Computer Interaction at Heilbronn University's Faculty of Computer Science. He serves as Managing Director of the UniTyLab and Program Dean for the SEM Faculty. His research focuses on Virtual Reality (VR), Augmented Reality (AR), Mixed Reality (MR), and innovative interaction technologies, with applications in health, industrial training, and software development. He leads projects addressing usability engineering, rehabilitation systems, and AR/VR integration in industry 4.0 environments. Prof. Meixner's work emphasizes practical applications, including VR-based therapy for cerebral palsy, gamified alcohol disorder treatments, and ergonomic training solutions using HoloLens 2. He actively contributes to advancing AR/VR tools for CAD design, automotive interfaces, and smart factory systems. His research also explores human factors in virtual environments, including motion sickness mitigation in automated driving simulations and user experience optimization for industrial workflows. As a program dean, he oversees academic programs while advancing interdisciplinary research through the UniTyLab. Notable collaborations include projects with Audi AG for smartglass applications in manufacturing and AR systems for medical training. His contributions bridge academic research with real-world implementations, focusing on usability, accessibility, and technological innovation.

Michael Uelschenمشاهده پروفایل

استاد

• Software Engineering
• Embedded Systems
• Multicore/Manycore Computing
• +۵ مورد دیگر

Prof. Dr.-Ing. Michael Uelschen is a Professor of Software Engineering for Technical Systems at Osnabrück University of Applied Sciences, part of the Faculty of Engineering and Computer Science. He holds a PhD in Mechanical Engineering and has over a decade of industry experience in automotive software development. His research focuses on energy-efficient embedded systems, model-driven software engineering, multicore systems, and medical technology applications such as motion analysis for rehabilitation. He teaches courses in software engineering, embedded systems, and parallel algorithms at both bachelor's and master's levels. Research Interests : Software Engineering for Automotive Embedded Systems, Power Optimization, Energy-Aware Design Patterns, Medical Motion Analysis (gait stability), IoT Sustainability, and Process Improvement (CMMI). His work often bridges theoretical models with practical implementation in real-time systems. Key Projects : Developed a contactless monitoring system for elderly/patient care using commodity electronics, supported by Bayer Healthcare Grants4Apps. Also contributed to frameworks for energy-efficient embedded systems design patterns and algorithms for kinematic analysis in clinical settings. Teaching : Leads courses like 'Software Engineering for Parallel Systems', 'Embedded Systems', and 'Object-Oriented Design'. Supervises student projects and theses in automotive and medical software domains.

Ingrid Buckleyمشاهده پروفایل

استادیار

• Software Engineering Education
• Fault-Tolerant System Design
• Cybersecurity
• +۵ مورد دیگر

Ingrid Buckley is an Assistant Professor in the Department of Computing & Software Engineering at Florida Gulf Coast University (FGCU). She holds a Ph.D. in Computer Science from Florida Atlantic University. Her research focuses on software engineering education, fault-tolerant system design, and cybersecurity, with an emphasis on integrating cybersecurity principles into software development curricula. She is affiliated with the U.A. Whitaker College of Engineering and is a member of professional organizations such as IEEE and ASEE. Dr. Buckley’s educational background includes a Ph.D. in Computer Science, an M.S. in Computer Science, and a B.S. in Computing and Information Technology. Her teaching interests span software testing methodologies, operating systems education, and cybersecurity curriculum design. She has contributed to course development in cybersecurity and has explored innovative approaches to enhance student engagement and learning outcomes in software courses. Her research publications highlight trends in combining pedagogical strategies with technical challenges, such as integrating learning engagement strategies into classroom activities and evaluating teaching modalities for operating systems. She has also investigated fault tolerance and reliability patterns in distributed systems, emphasizing practical applications in secure software development. Dr. Buckley’s work reflects her dedication to advancing both technical and educational aspects of software engineering, particularly in fostering a cybersecurity mindset among undergraduate students through curriculum integration and project-based learning.

Babak Salimiمشاهده پروفایل

استادیار

• Data Management
• Causal Inference
• Algorithmic Fairness
• +۵ مورد دیگر

Babak Salimi is an Assistant Professor at the Halıcıoğlu Data Science Institute (HDSI) at the University of California, San Diego (UCSD), with an affiliation to the Department of Computer Science and Engineering. His research focuses on trustworthy data analysis, algorithmic fairness, and causal inference, aiming to enhance transparency, fairness, and reliability in data-driven decision-making. Salimi completed his Ph.D. in 2016 at Carleton University under Prof. Leopoldo Bertossi and was a postdoctoral researcher at the University of Washington under Prof. Dan Suciu. Salimi has been honored with prestigious awards including the NSF CAREER Award (2024), the SIGMOD Best Paper Award (2019), and the VLDB Best Demonstration Paper Award (2018). His work emphasizes causal modeling for data quality and bias mitigation, addressing systemic biases through data-centric approaches. He actively engages in academic service roles, including General Chair of Guide-AI 2025 and Area Chair for FAccT 2023/2024. His research group develops tools to bridge the gap between complex data and human understanding, with a focus on data management for machine learning and responsible AI practices. Salimi teaches courses like DSC 261 (Responsible Data Science) and DSC 100 (Introduction to Data Management), emphasizing education in ethical data science principles. Key research thrusts include causal modeling for bias mitigation, data cleaning techniques, and holistic debiasing frameworks. His NSF CAREER project redefines algorithmic bias as a data quality issue, integrating causal modeling with traditional data management strategies to enhance decision-making trustworthiness. Salimi’s work impacts diverse sectors, including healthcare and criminal justice, by improving data quality and fairness. His educational initiatives aim to broaden participation in data science through enhanced data literacy programs.

Jonas Kucklingمشاهده پروفایل

پژوهشگر ارشد

• Artificial Life
• Swarm Robotics
• Artificial Intelligence
• +۳ مورد دیگر

Jonas Kuckling is a postdoctoral researcher at the Department of Computer and Information Science, University of Konstanz, and a fellow at the Zukunftskolleg. His research focuses on artificial life and swarm robotics, particularly open-endedness in embodied collectives, integrating disciplines including biology, chemistry, physics, computer science, philosophy, and art. Dr. Kuckling obtained his doctoral degree in April 2023 from the Artificial Intelligence research laboratory (IRIDIA) at the Université Libre de Bruxelles, Belgium. His doctoral work established foundations for his current investigations into emergent collective behaviors in robotic systems. His primary research interests center on artificial life and swarm robotics, with emphasis on open-ended evolution in embodied collectives. He explores how interdisciplinary approaches can generate autonomous systems capable of continuous novelty without external direction, bridging computational models with biological principles of self-organization and adaptation. This work addresses fundamental challenges in scalability, robustness, and emergent complexity in multi-robot systems. Analysis of his recent publications reveals a concentrated focus on automatic modular design of robot swarm control software, particularly through behavior trees and optimization techniques like simulated annealing. His work progresses from theoretical frameworks (e.g., manifestos on off-line design) to practical implementations (AutoMoDe tools), with increasing integration of learning, communication, and edge computing in large-scale swarm deployments. No scientific awards are documented in available sources. Dr. Kuckling currently leads an interdisciplinary research project at the Zukunftskolleg, collaborating with experts in complex systems, artificial life, AI, and robotics to advance open-endedness in embodied collectives. No information is available regarding student advising or specific grant funding beyond his fellowship appointment.

José Orlando Pereiraمشاهده پروفایل

دانشیار

• Dependable Distributed Systems
• Data Management
• Database Replication
• +۷ مورد دیگر

José Orlando Pereira is an Associate Professor at the Department of Informatics, University of Minho, and Research Coordinator at INESC TEC (INESC Technology and Science). His primary research interests lie in dependable distributed systems, with a focus on data management, group communication protocols, and tools for distributed system evaluation. He leads the High-Assurance Software Laboratory (HASLab) , part of INESC TEC and the University of Minho. Roles: Academic supervisor, conference committee member (e.g., SRDS 2025 General Co-Chair), and grant recipient (e.g., ADAPQO funding from CMU Portugal 2024). Key Projects: Includes CYBERACTIONING (cybersecurity education), EUMaster4HPC (European HPC master's program), and AIDA (adaptive assurance platform). Research Themes: Database replication, georeplicated systems, consensus protocols, edge computing, and fault injection tools like LAZYFS. His work emphasizes practical applications, such as improving transactional performance in hybrid workloads (TiQuE) and designing scalable NoSQL middleware (CloudMdsQL). He has authored over 200 publications, including seminal contributions to gossip protocols (HyParView) and consensus algorithms. Awards: Honorable Mention at ACM SIGMOD 2025 for CRDV research. Active in organizing conferences such as SRDS, DSN, and EuroSys. Teaching: Offers advanced courses on distributed systems, database administration, and large-scale data replication at both undergraduate and graduate levels.

Sangeeta Sangeetaمشاهده پروفایل

مدرس

• Software Engineering
• Data Mining
• Machine Learning
• +۲ مورد دیگر

Dr. Sangeeta Sangeeta is Lecturer in Data Science at Keele University, directing the MSc AI and Data Science program. Her research combines software engineering with data science methods to analyze developer communities. Key research areas include mining software repositories, log analysis, and social computing in developer forums. She leads the SEADS research group investigating patterns in Q&A platforms like Stack Overflow.

• Mathematics Education
• STEM Education
• Mathematics Identity
• +۳ مورد دیگر

Jennifer Cribbs is a Professor in the School of Teaching, Learning & Educational Sciences at Oklahoma State University, where she has served since 2016, first as an Associate Professor (2016-2022) and then as a Professor (2022-present). Her academic work focuses on mathematics education, particularly examining how students develop mathematics identity and persist in STEM fields. Dr. Cribbs earned her educational credentials from prestigious institutions: Ph.D. in Curriculum and Instruction with a focus on Mathematics Education from Clemson University (2012) Master of Arts in Teaching, Secondary Mathematics Education from Converse College (2005) Bachelor of Science, Chemical Engineering from Florida Institute of Technology (1999) Before entering higher education, Dr. Cribbs taught secondary mathematics in the South Carolina public school system, giving her valuable practical experience that informs her research. Her certification as a Secondary Mathematics teacher from the South Carolina Department of Education (2005-2017) further demonstrates her commitment to quality mathematics instruction. Dr. Cribbs' research primarily investigates mathematics identity and student persistence in STEM , exploring how students develop their sense of self in relation to mathematics. She also examines teachers' beliefs and practices and how these connect to student affect and learning outcomes. Her work often employs mixed-methods approaches, combining quantitative scale development with qualitative exploration of student and teacher experiences. Her recent scholarly output demonstrates a clear trajectory toward developing robust instruments for measuring mathematics identity and related constructs, with several 2024-2025 publications focused on scale validation. She has also expanded her research to include semiconductor education and circuit debugging skills, indicating a broadening scope of her STEM education research. Her work consistently addresses practical applications for classroom teachers while contributing to theoretical understandings of mathematics identity development across K-12 and undergraduate contexts. Dr. Cribbs has secured significant research funding from multiple sources, including the National Science Foundation, National Security Agency, and the Oklahoma State Department of Education. Her grants portfolio demonstrates her ability to lead substantial research projects focused on STEM education, teacher development, and student engagement in mathematics. Through her work with preservice teachers and in-service educators, Dr. Cribbs has made substantial contributions to understanding how professional development influences teacher beliefs and classroom practices. Her research on the transition to online instruction during the pandemic provides valuable insights for teacher education programs navigating technological changes in education delivery.

• Entity Resolution
• Knowledge Graphs
• Anomaly Detection
• +۴ مورد دیگر

Vassilis Christophides is a Researcher at INRIA Paris, France, specializing in data management and knowledge systems. His research spans entity resolution, knowledge graphs, anomaly detection, and IoT analytics, with recent focus on fairness-aware algorithms and explainable AI. He maintains active collaborations with institutions across Europe and has published extensively in top-tier venues including VLDB, ICDE, and KDD. His core research investigates: Scalable entity resolution techniques for web-scale data Knowledge graph construction and alignment methodologies Real-time anomaly detection in streaming environments Fairness and bias mitigation in data integration pipelines Edge computing optimizations for IoT analytics Recent publications demonstrate a strong trend toward responsible data science, combining foundational data management with emerging concerns in AI ethics. His work frequently develops novel methods for: (1) improving transparency in automated systems through explainable anomaly detection, (2) ensuring fairness in entity resolution workflows, and (3) optimizing resource-constrained edge environments for continuous analytics. Dr. Christophides leads research initiatives at INRIA and collaborates on European projects involving streaming data processing, knowledge representation, and distributed computing infrastructures. His team focuses on bridging theoretical frameworks with practical implementations for web-scale data challenges.