جست‌وجوی استاد و پژوهشگر

• Cyber-physical system security
• Threat modelling
• Critical infrastructure resilience
• +۳ مورد دیگر

Dr. Carmen Cheh is a Research Scientist in the Department of Computer Science at the University of Illinois at Urbana-Champaign. She holds a Ph.D. in Computer Science from UIUC and a Bachelor of Computing (Hons) from the National University of Singapore. Her research focuses on cyber-physical system security, threat modeling, and critical infrastructure resilience. She has served as Co-Principal Investigator on two major grants: the 2023-2024 project on threat modeling for government systems and the 2022-2025 initiative on real-time fraud detection in e-commerce platforms. Her work bridges theoretical computer security with practical applications in critical infrastructure protection. Dr. Cheh has contributed to tools like CyberSAGE, which aids in automated security argument evaluation, and frameworks for detecting business logic flaws in software systems. She collaborates extensively with industry and government entities to advance cybersecurity practices in both digital and physical domains. Education: Ph.D., Computer Science, University of Illinois at Urbana-Champaign Bachelor of Computing (Hons), National University of Singapore Her research interests emphasize real-world security challenges in interconnected systems, including automated threat modeling, vulnerability discovery in business logic, and compliance frameworks for financial services. She has pioneered constraint-based methodologies for identifying security flaws in complex systems and developed novel approaches to insider threat detection using physical access data. Recent work explores the intersection of machine learning and cybersecurity in fraud detection systems. Her publications span top venues like ACM Transactions on Modeling and Computer Simulation, IEEE Secure Development Conference, and the IEEE International Conference on Computer Communications. Collaborations include projects with institutions like Argonne National Laboratory and the National Science Foundation.

Olufisayo Omojokunمشاهده پروفایل

مدرس ارشد

• Mobile Computing
• Networking
• User Interfaces
• +۶ مورد دیگر

Olufisayo Omojokun is the Associate Dean for Undergraduate Education and Principal Lecturer at Georgia Tech's College of Computing. He also serves as the inaugural chair of the School of Computing Instruction and is affiliated with the Online Master of Science in Computer Science (OMSCS) program. His roles include curriculum innovation and teaching across diverse areas like computer law, entrepreneurship, and software development. Education: B.S. in Computer Science, Virginia Commonwealth University (1999) M.S. in Computer Science, University of North Carolina at Chapel Hill (2001) Ph.D. in Computer Science, University of North Carolina at Chapel Hill (2006) Research interests span mobile computing, networking, ethical/legal issues in technology, recommendation systems, and educational technology. He emphasizes practical applications of computing in entrepreneurship and online learning, as seen in his development of video-based content for CS 1331's online section. Awards: Institute's Co-Curricular Innovation Award (2022) College's William D. 'Bill' Leahy Jr. Outstanding Instructor Award (2021) Institute's Curriculum Innovation Award (2019) Jim Pope CREATE-X Faculty Fellow (2020) Teaching highlights include courses such as CS 4010 (Introduction to Computer Law), CS 4853-X (CREATE-X Capstone), and online variants of CS 1331. He also trains graduate TAs through CETL 8000/8801 courses. His work with the Laboratory for Interactive Artificial Intelligence (postdoc, 2006) contributed to research in user interfaces and device interaction.

Erik Demaineمشاهده پروفایل

استاد

• Algorithms
• Computational Geometry
• Complexity Theory
• +۵ مورد دیگر

Erik Demaine is a Professor in the Department of Electrical Engineering and Computer Science at MIT, affiliated with the Computer Science and Artificial Intelligence Laboratory (CSAIL), the Theory of Computation group, and the Algorithms Group. His research spans algorithms, computational geometry, folding, robotics, complexity theory, and interdisciplinary connections between mathematics and art. He received the MacArthur Fellowship ("genius grant") for his work on folding and computation. Demaine's work includes co-authoring books such as Geometric Folding Algorithms and Games, Puzzles, and Computation . His art collaborations with his father Martin Demaine, including curved-crease sculptures, are in the permanent collections of the Museum of Modern Art (MoMA) and the Renwick Gallery. He is also involved in software projects like Coauthor and Cocreate, supporting collaborative research and education. His research interests include folding and unfolding of geometric structures, computational complexity of games, protein folding, and algorithm design. He has contributed to areas like data structures, robotics, and network computing, with a focus on bridging theoretical computer science and tangible applications. Demaine holds patents and has been recognized with numerous awards, including the NSERC Doctoral Prize and the Gödel Prize. His work often involves supercollaboration, emphasizing open problem-solving and interdisciplinary approaches.

Shufang Zhuمشاهده پروفایل

مدرس

• Artificial Intelligence
• Formal Methods
• Automated Reasoning
• +۳ مورد دیگر

Dr. Shufang Zhu is a Lecturer (Assistant Professor equivalent) at the Department of Computer Science, University of Liverpool , and an Associate Member at the University of Oxford’s Department of Computer Science . Previously, she held roles including Senior Research Associate at Oxford (2023–2024) and Postdoctoral Researcher at Sapienza Università di Roma (2020–2022). She earned her Ph.D. in Software Engineering from East China Normal University (ECNU, 2020) under Prof. Geguang Pu, with a visiting Ph.D. at Rice University (2016–2018) under Prof. Moshe Y. Vardi. Education: B.Sc./Ph.D. in Software Engineering from ECNU (2010–2020). Scholarships include the Chinese Scholarship Council (CSC) and UT Austin EECS Rising Star (2022). Her research focuses on interdisciplinary areas of Formal Methods and Artificial Intelligence , emphasizing automated reasoning, planning, and synthesis. Key topics include temporal logics (LTL/LTLf), symbolic synthesis frameworks, and applications in reactive systems. Notable work addresses finite-trace specifications, best-effort strategies, and coordination in multi-agent systems. Teaching: Lecturer for Game-Theoretic Approach to Planning and Synthesis (European Summer School) and Foundations of Self-Programming Agents (Oxford). She also supervises funded Ph.D. positions, including a 2025 deadline for CSC-Liverpool scholarships. Awards: Future Digileader (Digital Futures, 2023), UT Austin EECS Rising Star (2022). Erdős number ≤3 via Moshe Y. Vardi. Collaborations: Co-chair of AAAI 2023 symposium on temporal logics in AI. Active in open-source tools like LydiaSyft for LTLf synthesis. Engages with academic networks through Google Scholar, DBLP, and GitHub.

Kourosh Davoudiمشاهده پروفایل

دانشیار

• Natural Language Processing
• Machine Learning
• Deep Learning
• +۳ مورد دیگر

Kourosh Davoudi is an Associate Professor of Computer Science at Ontario Tech University's Faculty of Science. He holds a PhD in Computer Science from York University with a focus on Machine Learning and Data Mining. Prior to joining Ontario Tech in 2019, he was a postdoctoral research fellow at the University of Waterloo's Department of Management Sciences. His research interests span Natural Language Processing, Deep Learning, Reinforcement Learning, Graph Mining, and Machine Learning. He actively supervises graduate students in these areas and teaches courses such as Data Mining and Artificial Intelligence. His research emphasizes practical applications of AI techniques in areas like outbreak detection, sentiment analysis, and automated grading systems. Recent work includes innovations in neural document segmentation, vision-language models, and hybrid outbreak detection using social media data. His publications consistently address challenges in algorithm design, explainable AI, and domain-specific NLP applications. Dr. Davoudi has contributed to conferences such as COLING, EMNLP, and IEEE transactions, focusing on interdisciplinary applications of machine learning. His work bridges theoretical advancements with real-world problems in healthcare, education, and social media analysis.

Jack Mostowمشاهده پروفایل

استاد پژوهشی

• Educational Technology
• Artificial Intelligence
• Natural Language Processing
• +۳ مورد دیگر

Jack Mostow is a Research Professor affiliated with the Human-Computer Interaction Institute at Carnegie Mellon University. His work focuses on educational technology, artificial intelligence, and natural language processing. He is renowned for developing Project LISTEN's automated reading tutor that listens to children's oral reading, integrating speech recognition and machine learning to improve literacy. His research addresses challenges in child literacy, automated assessment, and the application of AI in education. Key contributions include advancing speech recognition accuracy for children’s voices, designing adaptive tutoring systems, and exploring EEG and visual features to gauge learning states. He has contributed to global education initiatives, such as the XPRIZE field study, and developed tools for iterative improvement of intelligent tutoring systems. His work emphasizes scalable educational technologies for under-resourced regions and data-driven approaches to enhance learning outcomes. Mostow’s publications span over two decades, addressing topics like reinforcement learning for instructional policies, semi-supervised affect perception, and difficulty-controllable question generation. His research bridges AI, education, and human-computer interaction, aiming to create systems that adapt to learners’ needs while advancing computational methods for educational analytics.

• Software Engineering
• Cyber-Physical Systems
• Digital Ecosystems
• +۳ مورد دیگر

Tero Päivärinta is a Professor at the University of Oulu, Faculty of Information Technology and Electrical Engineering. His work focuses on software engineering, digital ecosystems, and cybersecurity. He specializes in empirical studies of software systems, digital twins, and autonomous driving technologies. His research explores hybrid intelligence systems, data-centric decision-making, and governance of collective ambidexterity in digital initiatives. Education: PhD holder with extensive experience in academic and industry collaborations. Key research domains include cyber-physical systems, DevSecOps automation, and IT governance in public sectors. He co-leads projects such as the NUVE Lab’s vehicle testing frameworks and contributes to initiatives like the Software-Defined Vehicle project. Research highlights include advancing knowledge graphs for manufacturing, cybersecurity compliance in DevOps pipelines, and evaluating data-driven decisions. His articles emphasize interoperability challenges, adaptive systems design, and sustainable digital transformation in public utilities. Professional contributions include organizing the TKTP Annual Symposium and co-editing volumes celebrating academic peers like Markku Oivo. His work bridges theoretical software engineering with practical applications in mobility, governance, and industrial systems.

Tanel Alumäeمشاهده پروفایل

دانشیار

• Speech Processing
• Natural Language Processing
• Machine Learning
• +۵ مورد دیگر

Tanel Alumäe is a Tenured Associate Professor of Speech Processing and Head of the Laboratory of Language Technology at Tallinn University of Technology (TalTech). He holds a PhD in Information and Communication Technology from TalTech (2006) and has conducted research at institutions like LIMSI/CNRS, Aalto University, and Raytheon BBN Technologies. His research focuses on speech processing, speaker and language recognition, and low-resource language technologies. Affiliations: Department of Software Science, School of Information Technologies, TalTech. Education: PhD in ICT (2006), MSc in Informatics (2002), Diploma in Computer & Systems Engineering (1999). Research interests include speech recognition, speaker diarization, spoken language translation, and combating DeepFake voices. He leads teams achieving top results in competitions like IARPA BABEL, NIST LRE, and Interspeech challenges. His work emphasizes open-source tools and equitable AI solutions. Key Awards: Best Student Paper at Odyssey 2024 and TSD 2018. Keeletegu Awards (2019, 2011) for contributions to Estonian language technology. Grants & Leadership: Managed the National Programme for Estonian Language Technology (2011–2017). Serves as Secretary of the Northern European Association for Language Technology (NEALT) and Area Chair for ICME, EACL, and Interspeech conferences. Labs & Teams: Directs the Laboratory of Language Technology, focusing on practical applications of speech and language technologies.

Karim ZKIKمشاهده پروفایل

دانشیار

• Cybersecurity
• Blockchain Technologies
• Artificial Intelligence
• +۳ مورد دیگر

Karim ZKIK is an Associate Professor of Cyber Security and Information Systems at ESAIP Graduate School of Engineering, Angers, France. Previously, he served as an Assistant Professor at the International University of Rabat (UIR), Morocco. His roles include Educational Manager of the Cyber Security track, Head of the Cybersecurity Innovation Hub, and committee member for ABET certification and curriculum design. He actively contributes to academic service, organizing conferences such as the International Conference on Cryptology, Coding Theory, and Cyber Security (I4CS 2022), and serves as a Guest Editor for Computers and Industrial Engineering . His research focuses on cybersecurity for connected systems, blockchain technologies, AI-driven security solutions, and cyber resilience in industrial control systems. Recent work explores integrating blockchain and machine learning for threat detection, secure IoT networks, and supply chain resilience. Key contributions include frameworks for cyber resilience in retail and airlines, blockchain-based crowdfunding security, and SDN-based attack mitigation. ZKIK holds a Habilitation (2024) and PhD in Cyber Security from Université d’Angers and Mohamed V University, Rabat. He holds over 20 certifications from EC-Council, IBM, and Cisco. His work bridges theoretical research and industry applications, addressing challenges in smart environments, industrial systems, and sustainable supply chains.

Theocharis Kyriacouمشاهده پروفایل

دانشیار

• Data Science
• Machine Learning
• Robotics
• +۴ مورد دیگر

Theocharis Kyriacou is a Reader in Computer Science at Keele University, School of Computer Science and Mathematics. He holds roles as Director of Education and Programme Director for undergraduate and postgraduate Computer Science programmes since 2018. Educated at the University of Sheffield (BEng, 2000) and University of Plymouth (PhD in Computer Science, 2004), his research focuses on Data Science and Machine Learning applied to healthcare, robotics, education, and sports science. He has led a 3-year Knowledge Transfer Partnership (KTP) with Bentley Motors and supports local SMEs through consultancy. His work spans academic research collaborations across disciplines and organizational roles in curriculum development. Research interests include machine learning applications in cardiology (predicting cardiovascular risks), wearable electronics for neurological conditions, and educational technology for curriculum design. He has published widely in journals like International Journal of Cardiology and BMJ Open Sport and Exercise Medicine , with a focus on interdisciplinary problem-solving. Awards and recognitions are not explicitly listed, but his contributions include impactful collaborations with medical institutions and industry partners. Advising and grants include guiding students in KTP projects and securing funding for robotics and healthcare-related research. He has developed new academic programmes in computer science apprenticeships and cross-school initiatives. His involvement in labs/teams includes collaborations with Keele’s pharmacy, sports science, and medicine departments, as well as international partners.

Abbas Heydarnooriمشاهده پروفایل

استادیار

• Software Engineering
• Artificial Intelligence for Software Engineering (AI4SE)
• Software Analytics
• +۵ مورد دیگر

Abbas Heydarnoori is an Assistant Professor in the Department of Computer Science at Bowling Green State University (USA) since 2022, and previously held a faculty position at Sharif University of Technology (Iran) from 2012 to 2022. He earned his Ph.D. in Computer Science from the University of Waterloo (Canada, 2009), and M.Sc. and B.Sc. in Software Engineering from Sharif University of Technology (2001 and 1999). His research focuses on AI-driven software engineering (AI4SE/SE4AI), leveraging data science and AI to address challenges like fault localization, bug prediction, and code comprehension. He analyzes software repositories (e.g., GitHub, Stack Overflow) to improve developer productivity and software quality. He has contributed to tools like CrowdSummarizer and ExceptionTracer, and his work spans topics such as microservices architecture, API usage analysis, and code summarization. Teaching includes graduate/undergraduate courses on AI for Software Engineering, Database Systems, and Software Engineering. His service roles include editorial board membership at Science of Computer Programming , and PC membership in conferences like MSR, SANER, and FSE. His research group actively publishes on automated code analysis, documentation generation, and developer productivity tools, with a focus on empirical and data-driven approaches.

Alexandra Kirschمشاهده پروفایل

استادیار

• Artificial Intelligence
• Robotics
• Human-Robot Interaction
• +۳ مورد دیگر

Alexandra Kirsch is an Assistant Professor in the Media Informatics Department at the University of Tübingen's Faculty of Informatics. She held the Carl von Linde Junior Fellowship at the Technical University of Munich (TUM) Institute for Advanced Study (TUM-IAS) from 2010. Previously, she was a senior research scientist at TUM's Intelligent Autonomous Systems Group and led the independent Junior Research Group “Planning for Adaptive Robot Assistance” within the Excellence Cluster CoTeSys (Cognition for Technical Systems). Education: Diploma in Computer Science from TUM, 2003 Doctoral degree from TUM, completed between 2003-2007 Research Interests: Kirsch focuses on developing control mechanisms for autonomous robots using artificial intelligence, aiming to create systems that collaborate closely and transparently with humans. Her work emphasizes models of world dynamics, robot action effects, and human behavior. She created the Robot Learning Language (RoLL) to automate model acquisition and update processes during robot operations. Collaborations with psychologists and neuroscientists explore joint human-robot planning tasks and model development for seamless interaction. Scientific Awards: Member of the Bayerische Akademie der Wissenschaften Förderkolleg (2012) Award by Comet Computer GmbH for excellent graduation results (2003) Advising & Grants: Managed interdisciplinary research projects during her junior fellowship at TUM. Previously worked as a management consultant at Booz & Co., 2007-2008. Her grants include the Carl von Linde Fellowship and support for the Junior Research Group. Labs/Teams: Active in the Planning for Adaptive Robot Assistance group (CoTeSys) and collaborates with the Cognitive Technology focus group at TUM-IAS. Engages in cross-disciplinary teams involving neuroscience and psychology for human-robot interaction studies.

Lea Scharffمشاهده پروفایل

پژوهشگر

• Volcanology
• Geophysics
• Remote Sensing
• +۳ مورد دیگر

Dr. Lea Scharff is a Staff Scientist in Volcanology at the University of Hamburg, affiliated with the Center for Earth System Research and Sustainability (CEN) and the Department of Geophysics. She holds a PhD in Volcanology from the University of Hamburg (2012) and a Diplom in Geophysics (2006). Her research focuses on volcanic ash cloud modeling, volcano monitoring systems, and Doppler radar technology development for eruption dynamics analysis. She leads the development of software for volcano radar data processing and collaborates with Metek GmbH on radar innovations. Education: 2006: Diplom in Geophysics, University of Hamburg 2012: PhD in Volcanology, University of Hamburg Research Interests: Her work emphasizes understanding volcanic systems' physics to improve hazard mitigation. Key areas include Doppler radar analysis of eruption plumes, interdisciplinary data integration, and real-time monitoring tools. She investigates volcanic ash transport, pyroclastic density currents, and eruption mechanisms using radar, thermography, and numerical models. Grants & Projects: Lead developer of volcano radar software under DFG-funded projects Collaborator on Sakurajima volcano electrification studies (Japan) Member of MeMoVolc international workshop on volcanic data integration Labs/Teams: Physical Volcanology Group at the University of Hamburg Institute of Geophysics. Active in field installations of radar networks at volcanoes like Colima (Mexico) and Turrialba (Costa Rica).

• Artificial Intelligence
• Machine Learning
• Software Engineering
• +۶ مورد دیگر

Talal Shaikh is an Associate Professor at Heriot-Watt University's School of Mathematical and Computer Sciences in Dubai. He serves as Director of Undergraduate Studies and Programme Director for BSc Computer Science, BSc CS (AI), and MSc Software Engineering. With a decade of industry experience as a Chief Information Officer and Software Engineer, he bridges practical insights with academic research. Research Interests: Pervasive Computing, IoT/M2M, AI/ML, WiFi Sensing for Healthcare, Financial Machine Learning, Educational Technology Awards: Teaching Excellence Awards (2017/18), Fellow of the Higher Education Academy (FHEA), multiple Learning and Teaching Oscars (2016, 2017, 2018) His work spans Ubiquitous Computing and IoT , focusing on sensor networks and WiFi-based sensing for healthcare. In Artificial Intelligence , he applies ML to robotics, financial analytics, and educational innovation. Recent articles analyze Reinforcement Learning , Emotion Recognition , and WiFi Sensing applications. His teaching emphasizes student-centric learning, with over 100 supervised dissertations achieving distinctions. Collaborations include international conferences and interdisciplinary research in smart environments and adaptive systems.

Mauro Pezzèمشاهده پروفایل

استاد

• Software Engineering
• Software Testing and Analysis
• Self-Adaptive Systems
• +۵ مورد دیگر

Mauro Pezzè is a Full Professor of Software Engineering at the Università della Svizzera italiana (USI) and Università di Milano Bicocca, leading the STAR research group since 2006. He holds a laurea from the University of Pisa and a PhD from Politecnico di Milano. His research focuses on software testing, analysis, self-adaptive systems, and cloud systems. He has held editorial roles, including Editor-in-Chief of ACM Transactions on Software Engineering and Methodologies (TOSEM), and served on numerous program committees. Education: Laurea (Pisa), PhD (Politecnico di Milano). Professional roles include Dean of the Faculty of Informatics at USI (2009-2013), visiting scientist at UC Irvine and Edinburgh, and technical lead for international projects. He co-authored a seminal book on software testing (Wiley, 2007), with over 670 citations. Research Interests: Software Testing, Self-Adaptive Systems, Cloud Computing, AI in SE, Sustainable Software. Projects include work on field-based testing, failure prediction in distributed systems, and neuro-symbolic approaches for test oracles. Grants and Advising: Led STAR Lab projects in self-healing systems, GUI testing, and semantic matching. Advised numerous PhD/postdoc students (e.g., Ciniselli, Di Grazia, Qiu). Collaborations with European tech firms on R&D initiatives. Labs/Teams: STAR Group at USI/Constructor Institute, Bicocca, and Politecnico di Milano. Current members include postdocs and PhD students working on AI-driven testing and cloud reliability.