جستجوی استاد راهنمای دانشگاهی

Wayne Wobckeمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Data Science
• Machine Learning
• +۷ مورد دیگر

Associate Professor Wayne Wobcke is a faculty member in the School of Computer Science and Engineering at the University of New South Wales (UNSW), where he has been employed since 2002. His academic career includes previous positions at the University of Sydney until 1998, British Telecom Labs in the UK for three years, and the University of Melbourne for one year. He holds a PhD in Computer Science from the University of Essex (1989), an MSc from the University of Queensland (1985), and a BSc (Hons) in Mathematics/Computer Science from the University of Queensland (1984). Dr. Wobcke's research spans both theoretical and practical aspects of artificial intelligence and data science. His work encompasses intelligent agents, data mining, agent-based modeling, dialogue management, personal assistants, recommender systems, and computational social science. He has collaborated extensively with industry through three Cooperative Research Centres (Smart Internet Technology CRC, Smart Services CRC, and Data to Decisions CRC), where he served as a Programme Manager and Project Leader for over 10 years. Notable achievements include developing a voice-controlled mobile application for email and calendar interaction (a precursor to Apple's Siri) and deploying a people-to-people recommender system for online dating on one of Australia's largest dating sites. His recent research focuses on data science in humanitarian contexts and machine learning applications in official statistics, conducted in collaboration with BPS (Statistics Indonesia) and STIS (Politeknik Statistika, Indonesia). His publication record shows a consistent trajectory of impactful research, with recent work concentrating on poverty targeting, domain adaptation, natural language processing for recommender systems, and political opinion mining. Scientific Awards: Best Paper Nomination, 11th Workshop on Argument Mining (2024) UNSW Arc Postgraduate Research Supervisor Award (2017, 2018) AAAI Deployed AI Application Award, Twenty-Sixth Annual Conference on Innovative Applications of Artificial Intelligence (2014) Best application paper runner up, 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (2013) Dr. Wobcke has successfully supervised numerous research students, with Irwan Rahadi currently working on 'Causal Modelling and Machine Learning for Official Statistics'. His grant portfolio includes significant funding from the Australian Research Council and various Cooperative Research Centres, totaling over $3.7 million since 2003. He teaches COMP9414 Artificial Intelligence and COMP9727 Recommender Systems at UNSW.

Robert Godwin-Jonesمشاهده پروفایل

استاد

• Computer-Assisted Language Learning
• Second Language Acquisition
• Artificial Intelligence in Language Education
• +۳ مورد دیگر

Robert Godwin-Jones is a Professor in the Department of Foreign Language at Virginia Commonwealth University's College of Humanities and Sciences, where he has served since 1979. He holds the position of Foreign Language Liaison and maintains active scholarly contributions through his "German Stories" digital repository and "Communicating Across Cultures" blog, focusing on technology-enhanced language pedagogy and intercultural communication. His educational background includes: B.A. in French and German from Franklin and Marshall College (1971) M.A. in Comparative Literature (German, French, and English) (1973) Ph.D. in Comparative Literature from the University of Illinois Urbana-Champaign (1977) Dr. Godwin-Jones specializes in Computer-Assisted Language Learning (CALL), with research spanning artificial intelligence applications, virtual reality environments, and digital literacies for language learners. His work examines how emerging technologies transform second language acquisition through ecological semiotics, distributed agency models, and multimodal communication frameworks. He investigates pedagogical translanguaging strategies for less commonly taught languages and analyzes authenticity in AI-mediated language interactions, particularly in pragmatics and writing development. Analysis of his 2021-2025 publications reveals three dominant trajectories: (1) generative AI integration in language instruction with emphasis on ethical implementation and threat mitigation; (2) extended reality applications creating immersive language spaces in the metaverse; and (3) ecological approaches connecting smart devices, ambient intelligence, and situated learning contexts. His scholarship consistently bridges theoretical frameworks with practical classroom applications across 19th-century German literature studies and contemporary language education. He maintains active professional engagement through memberships in: Delta Phi Alpha German Honorary Society Phi Kappa Phi Honorary Society Modern Language Association American Association of Teachers of German American Association of Teachers of French Foreign Language Association of Virginia As director of the "German Stories" project since 1994, he has curated verified editions of 19th-century German narratives with English translations under Creative Commons licensing, creating what has become a foundational resource for literary study and language acquisition. His blog extends this work through contemporary analyses of intercultural communication challenges, while his scholarly leadership in organizations like CALICO shapes national discourse on technology in language education. His laboratory functions as the "German Stories" digital ecosystem, which has evolved into a comprehensive platform hosting annotated texts, pedagogical resources, and research archives. This environment supports both formal classroom instruction and informal learning communities, demonstrating his commitment to porous classroom models that integrate physical and digital learning spaces.

Alexander Pretschnerمشاهده پروفایل

استاد

• Software Engineering
• Information Security
• Testing
• +۵ مورد دیگر

Prof. Dr. Alexander Pretschner is a leading academic in software and systems engineering at the Technical University of Munich, with additional roles as Chair of the bidt Board of Directors, Member of the Executive Committee, and Chair of the Scientific Directorate at fortiss (Bavarian Research Institute for Software-Intensive Systems). His expertise spans software engineering, information security, and ethical deliberation in agile processes. Professor for Software & Systems Engineering, TUM Founding Director and Chairman of bidt Chair of Scientific Directorate at fortiss Research interests focus on software engineering with emphasis on testing and information security , alongside pioneering work in AI ethics , digital sustainability , and data privacy . Key projects include EDAP (Ethical Deliberation for Agile Processes), DetDat (Determinants of Data Disclosure), and AIffectiveness in Education. Publications and lectures address critical issues like "What makes Munich attractive for Open AI?" , "How generative AI transforms creative work" , and "Balancing benefits and risks of AI assistants in workplaces" . Collaborations include prominent researchers like Julian Nida-Rümelin and Niina Zuber.

• Artificial Intelligence
• Machine Learning
• Medical Education Technology
• +۷ مورد دیگر

Andrew R. Jamieson is an Assistant Professor in the Lyda Hill Department of Bioinformatics at UT Southwestern Medical Center, where he leads a research team focused on developing advanced AI systems for medical education and clinical performance assessment. He was appointed in 2019 and serves as Principal Investigator of the Jamieson Group. Institution: UT Southwestern Medical Center School: School of Health Professions Department: Lyda Hill Department of Bioinformatics Academic Rank: Assistant Professor Dr. Jamieson earned his B.A. in Physics with honors (2006) and Ph.D. in Medical Physics (2012) from the University of Chicago. His early work in computer-aided diagnosis laid the foundation for his career in AI and machine learning. Education: University of Chicago (B.A., Ph.D.) Prior Experience: GE Healthcare, Big Data Analytics Startup (First Data Scientist) Dr. Jamieson's research lies at the intersection of artificial intelligence, medical education, and bioinformatics. His team leverages multimodal data—including video, audio, and text—from the UTSW Simulation Center to train frontier AI models for automated assessment of medical student performance. His work in computational image analysis spans label-free live-cell imaging, spatial biology, and highly multiplexed immunofluorescence, with applications in cancer biology and diagnostics. He has also made significant contributions to public health through the development of the UTSW COVID-19 forecast model. The most recent publications reflect a strong trend toward AI-driven medical education tools, particularly using large language models and multimodal AI for OSCE assessment. Earlier works focus on deep learning in medical imaging, dimensionality reduction, and computer-aided diagnosis in mammography. The research consistently emphasizes interpretability, automation, and clinical translation. Scientific recognition includes being featured on the cover of Cell Systems (July 2021) for work on melanoma cell analysis. His team's development of the first automatic AI grading system for medical student OSCE notes in 2023 marks a major innovation in educational assessment. Featured on cover of Cell Systems (2021) Developed UTSW COVID-19 forecast model Pioneered AI grading system for OSCE notes (2023) Dr. Jamieson is actively involved in mentoring and graduate education. He serves as Course Director for the Master’s in Health Informatics program and contributes to nanocourses at the Clinical Informatics Center. His team includes multiple advisees and collaborators working on NLP, LLMs, and AI/ML in healthcare. He is expanding his group and seeking researchers in AI, data science, and software development. His leadership in the Bioinformatics Core Facility (2018–2021) and ongoing collaborations with pathologists and radiation oncologists demonstrate strong interdisciplinary grant and project engagement. Course Director: Master’s in Health Informatics Mentor to multiple graduate students and researchers Collaborations: Pathology, Radiation Oncology, Surgery, Clinical Informatics The Jamieson Group is a dynamic, interdisciplinary research team at the forefront of applying cutting-edge AI to medical education and clinical data analysis. The lab focuses on natural language processing, multimodal learning, and computer vision, with strong ties to the UTSW Simulation Center and Clinical Informatics Center. The team develops custom pipelines for spatial biology and imaging data and is actively expanding to meet growing research demands.

Rrezarta Krasniqiمشاهده پروفایل

استادیار

• Software Engineering
• Requirements Engineering
• Software Quality
• +۳ مورد دیگر

Rrezarta Krasniqi is an Assistant Professor in the Department of Software and Information Systems at the University of North Carolina at Charlotte. She holds a Ph.D. in Computer Science and Engineering from the University of North Texas (2024) and has previously taught at multiple institutions while working as a senior Java developer in industry. Research Focus: Her work centers on improving software quality through automated detection of quality-related bugs, using AI-driven approaches and empirical methodologies to address challenges in code scattering, requirement vagueness, and system-wide reliability issues. She specializes in semantic analysis, classifier development, and 3D visualization tools for codebase monitoring. Key Contributions: Developed RetroRank for bug-fixing comment recommendation (2021-2023) Pioneered SoftQualDetector for semantic quality concern mapping (2023-2024) Co-authored surveys on quality concern management in open-source communities Publications: Her work spans leading venues like EMSE'23, ICSME'23, SANER'23, and SQJ'23, with earlier contributions at ICSE'2017 and FSE'2018 through the TraceLab reproducibility framework.

Collin F. Lynchمشاهده پروفایل

دانشیار

• Intelligent Tutoring Systems
• Adaptive Educational Technologies
• Argument Mining
• +۵ مورد دیگر

Collin F. Lynch is an Associate Professor in the Department of Computer Science at North Carolina State University, specializing in intelligent tutoring systems and adaptive educational technologies. His research addresses complex domains like scientific writing, law, and software development through AI integration. Education Ph.D. in Intelligent Systems (2014), University of Pittsburgh M.S. in Intelligent Systems (2011), University of Pittsburgh B.A. in Cognitive Science and Artificial Intelligence (2000), Hampshire College Research Focus Lynch's work combines artificial intelligence, learning science, and human-computer interaction. Key areas include: Argument mining and natural language processing Real-time classroom support for writing-to-learn Student modeling and hint generation Embodied cognitive agents in collaborative learning Social network impacts on education Grant Leadership Validating Automated Measures of Student Writing (2021-2026, $634,620, IES) RET Site: Socially Relevant Computing (2021-2025, $598,913, NSF) IGE: Learning the Entire Pipeline (2021-2024, $332,184, NSF) FLECKS: Collaborative CS Learning (2017-2023, $1,399,088, NSF) Integrated Teaching Platforms (2018-2022, $597,529, NSF) Evaluation for Actionable Change (2016-2021, $799,837, NSF) His projects often involve interdisciplinary collaboration and address challenges in blended learning environments, data-driven educational interventions, and socially relevant computing.

• Natural Language Processing
• Machine Learning
• Cognitive Science
• +۳ مورد دیگر

Sam Scott is an Associate Professor in the Department of Computing and Software at McMaster University's Faculty of Engineering. He teaches undergraduate computer science and software engineering courses but does not supervise graduate students. His contact information includes phone number 905-525-9140 x22500 and email samscott@mcmaster.ca. Dr. Scott's research spans multiple interdisciplinary domains with primary interests in Natural Language Processing, Machine Learning, Cognitive Science, Philosophy of Language, and Computer Science Education. His scholarly work demonstrates a consistent trajectory from theoretical foundations in cognitive science and philosophy toward practical educational applications. He has made notable contributions to culturally responsive teaching approaches, particularly in incorporating Indigenous Ways of Knowing into computer science curriculum development. Analysis of Dr. Scott's publication history reveals an evolution from foundational work in natural language processing and philosophical inquiry toward innovative educational approaches. His recent publications show increasing focus on inclusive pedagogy, flexible assessment methods, and culturally relevant computing education. The interdisciplinary nature of his work bridges theoretical computer science with practical classroom applications. According to available information, Dr. Scott does not supervise graduate students. The VIVO database indicates no grants are currently listed for him, though the system note suggests this may represent only a small sample of his total professional activities. His teaching portfolio is extensive, covering core computer science and software engineering courses through 2025.

Lei Buمشاهده پروفایل

استاد

• Model Checking
• Bounded Model Checking
• Formal Methods
• +۷ مورد دیگر

Lei Bu is a Professor and Vice Dean at the Software Institute , Nanjing University . He leads research in formal verification, cyber-physical systems, and software engineering, with a focus on bounded model checking and hybrid system analysis. B.Sc. and Ph.D. in Computer Science from Nanjing University (2004, 2010) Visiting student at Carnegie Mellon University and University of Texas at Dallas His research integrates formal methods and machine learning for verifying complex systems like IoT and software with real-time constraints. Key projects include BACH Toolset and BRICK for reachability analysis. Recent publications demonstrate expertise in hybrid system verification , cache side-channel detection , and parallel code analysis frameworks . His work bridges theoretical advancements with practical applications in safety-critical systems. Zhongchuang Software Talent Award (2023) CCF-IEEE CS Young Computer Scientist Award (2022) High-Tech Software Innovation Awards (2019-2023) As Principal Investigator, he leads major projects funded by National Science Foundation of China and Jiangsu Natural Science Foundation (2020-2027). Current tools include BACH for hybrid systems and MLB for Java symbolic execution.

• Artificial Intelligence
• Natural Language Processing
• Computational Linguistics
• +۶ مورد دیگر

Ayşenur Akyüz Birtürk serves as a Lecturer in the Department of Computer Engineering at Middle East Technical University (METU), Ankara, where she has taught since February 1994. Her academic career spans foundational programming courses to advanced graduate seminars in AI and Computational Linguistics, reflecting 30+ years of institutional commitment. She earned all her degrees from METU, culminating in a 1998 Ph.D. focused on Turkish language computational analysis. Her educational journey includes: B.S. in Computer Engineering (1985) M.S. in Computer Engineering (1988) with thesis on “A Model for Representing Concepts: Conceptual Dependency Theory” Ph.D. in Computer Engineering (1998) with thesis on “A Computational Analysis of Turkish using the Government-Binding Approach” Dr. Birtürk’s research centers on Artificial Intelligence and Natural Language Processing , with pioneering work in Turkish language parsing evolving into modern Recommender Systems . She integrates semantic relations and multi-domain data to build hybrid engines for movies, books, and music, emphasizing user modeling through knowledge representation and data mining techniques. Analysis of her 2010-2015 publications reveals two dominant threads: adaptive recommender systems (80% of output) using semantic similarity and dynamic clustering, and renewable energy analytics (20%) applying machine learning to wind/hydrological data. This pivot from NLP to energy forecasting demonstrates methodological versatility while maintaining core AI expertise. Her scientific recognition includes: TUBITAK scholarships throughout education (1977-1988) Multiple national contest awards in high school (1979-1980) Leadership in TUBITAK-funded energy and healthcare projects Dr. Birtürk has supervised 17 Master’s theses in NLP and recommender systems while securing competitive grants including METU-ISTEC #17435 (2006-2008; 504,000 YTL) and HASAT (2010-2013; 601,637 YTL). Her industry consultancy spans medical form design (FormAnalitik), question-answering systems, and retail intelligence platforms, translating academic research into real-world tools.

• Software Engineering
• Software Testing
• Program Analysis
• +۴ مورد دیگر

Alessandro (Alex) Orso is the Dean and Professor at the University of Georgia College of Engineering , starting in 2025. Previously, he spent 25 years at Georgia Institute of Technology , where he served as a Professor in the College of Computing , Director of the Scientific Software Engineering Center , and Associate Dean for Off-Campus and Special Initiatives . Education: Ph.D. in Computer Science – Politecnico di Milano, Italy M.S. in Electrical Engineering – Politecnico di Milano, Italy B.S. in Electrical Engineering – Politecnico di Milano, Italy Research Focus: Alex Orso is a leading expert in software engineering , with a focus on software testing , program analysis , and debugging . His work aims to improve software reliability, security, and trustworthiness , and has been validated on real-world systems. He has led initiatives to integrate AI and large language models into testing workflows, particularly for REST APIs and mobile applications . Scientific Recognition: Distinguished Member of the Association for Computing Machinery (ACM) Fellow of the Institute of Electrical and Electronics Engineers (IEEE) ISSTA Impact Paper Award (2021) Research Funding & Leadership: Orso has secured major funding from Google, IBM, Microsoft , and government agencies. In 2021, he led the acquisition of $11 million from Schmidt Futures to establish the Scientific Software Engineering Center at Georgia Tech, where he served as inaugural director. Teaching & Innovation: He was an early advocate of Georgia Tech’s Online Master of Science in Computer Science (OMSCS) and has taught a virtual software engineering course since its launch in 2014.

Morteza Zihayatمشاهده پروفایل

دانشیار

• Data Analytics
• Human-centered AI
• Decentralized AI
• +۶ مورد دیگر

Morteza Zihayat is an Associate Professor and Canada Research Chair (Tier 2) in Human-Centered Artificial Intelligence at Toronto Metropolitan University. He holds dual appointments in the Faculty of Engineering and Architectural Science (Department of Electrical, Computer, and Biomedical Engineering) and the Ted Rogers School of Management. Additionally, he serves as an Adjunct Professor at the University of Waterloo in Management Sciences and is a Faculty Fellow at IBM's Centre for Advanced Studies. Dr. Zihayat's educational background includes: PhD in Computer Science from York University (2016) MSc in Computer Engineering from University of Tehran (2011) Postdoctoral Research Fellowship at University of Toronto's Faculty of Information (2017) His research lies at the intersection of AI, security, and society with a focus on building fair and transparent AI systems. Dr. Zihayat's expertise spans human-centered AI, fair information retrieval systems, and blockchain-enabled AI infrastructures. His work emphasizes creating AI systems that are accountable and designed to serve the public good, with applications in healthcare, digital media, and social networks. Dr. Zihayat has received numerous accolades including the Canada Research Chair (Tier 2) in Human-Centered AI (2024), Dean's Outstanding Scholarly, Research, and Creative Activity Award (2023), Best Short Paper Award at ECIR (2023), and IBM CAS Faculty Fellowship (2021). His research has attracted over $1.7 million in external funding from agencies such as NSERC, Mitacs, and multiple industry partners including Toronto Transit Commission, The Globe and Mail, AT&T, and IBM. Dr. Zihayat serves as Associate Editor of the Computational Intelligence Journal and is an active reviewer for top-tier venues. He is also Co-director and Co-founder of the Digital Enterprise Analytics and Leadership (DEAL) Research Center.

Jignesh M. Patelمشاهده پروفایل

استاد

• Database Systems
• Query Optimization
• Data Analytics
• +۳ مورد دیگر

Jignesh M. Patel is a Professor in the Computer Science Department at Carnegie Mellon University, where he leads research on efficient data analysis methods. His work focuses on improving both system efficiency (e.g., high-performance data algorithms) and human efficiency (e.g., user productivity with data systems). Research Focus: Patel's group specializes in database systems, query optimization, hardware acceleration, and human-data interaction. Their interdisciplinary work spans: Transactional processing and real-time analytics Query optimization techniques Hardware-algorithm co-design Natural language interfaces for data systems Memory-efficient data processing Professional Activities: Co-founded four technology companies (Paradise, Locomatix, Quickstep, DataChat). Serves on program committees for premier conferences including SIGMOD and CIDR (as co-chair). Teaches database systems courses at CMU. Awards: Received Best Paper Award at DaMoN 2010 for work on cluster efficiency.

• Networking
• Distributed Systems
• Network Security
• +۳ مورد دیگر

Siegmar Sommer is a Researcher at the Humboldt University of Berlin , affiliated with the Institute of Computer Science under the Faculty of Mathematics and Natural Sciences . He has worked at the university since 1986 in various technical and scientific roles. Dipl.-Ing. in Computer Engineering (1982) Dr.-Ing. in Computer Science (1986) Postgraduate studies in Higher Education (1990) His research focuses on networking , distributed systems , and network security , with historical contributions to optical information transmission , LAN protocols , and security-relevant systems . His work bridges hardware-software co-design and educational theory in technical disciplines. The 1980s-1990s articles highlight expertise in LAN architecture, optical communication, and security frameworks. Keywords span Networking , Operating Systems , and Education , with subfields like Fiber Optic Networks , CSMA/CD Protocols , and Higher Education Curriculum . He contributed to the Computer Engineering Group and holds a patent for " Bus Access Method for a Local Computer Network " (1986). His teaching legacy includes courses on programming languages (BASIC, PASCAL, PEARL), computer graphics, and modern topics like Wireless Communication Systems and Reliable Distributed Systems . Contact: Email: sommer@informatik.hu-berlin.de Phone: +49 30 2093-41256 Office: Room IV.303, Rudower Chaussee 25, Berlin-Adlershof

Ebrahim Bagheriمشاهده پروفایل

استاد

• Artificial Intelligence
• Data & Society
• Information Behaviour
• +۳ مورد دیگر

Professor Ebrahim Bagheri is a Tenured Full Professor at the University of Toronto's Faculty of Information and co-founder of Reviewerly, an AI-driven platform for scientific peer review. He holds editorial roles at IEEE Transactions on Network Science and Engineering and ACM Transactions on Intelligent Systems and Technology. His research focuses on ethical AI, information retrieval, and responsible AI development. He has secured over $16M in research funding and led initiatives such as the NSERC CREATE program on Responsible AI and the CFREF Bridging Divides Program. Education: PhD (prior institution not specified) Research Interests: Artificial Intelligence, Data & Society, Information Behavior, Social Media, Software & Systems. He emphasizes balancing technological innovation with societal benefits, addressing issues like algorithmic bias and ethical AI practices. Notable Awards: NSERC Synergy Award for Innovation (2019) recognizing industry-academia collaboration excellence. Grants: Includes projects on warranty design, knowledge graph mining, and robust neural retrieval techniques. Labs: Laboratory for Systems, Software and Semantics (LS3).

Wei Liمشاهده پروفایل

استاد

• Computer Security
• Network Security
• Artificial Intelligence
• +۳ مورد دیگر

Wei Li is a Professor in the Department of Computing at Nova Southeastern University's College of Computing & Engineering. He joined NSU in 2005 after earning his Ph.D. from Mississippi State University. His research focuses on enhancing computer system security through interdisciplinary approaches, including network security, artificial intelligence applications, and software engineering practices. Dr. Li’s research areas encompass computer security, network security, software engineering, artificial intelligence, and database systems. His work bridges theoretical advancements and practical cybersecurity solutions, such as improving intrusion detection systems, analyzing social engineering attack vulnerabilities, and developing machine learning models for IoT security. His recent publications (2020–2025) address topics like password policy effectiveness, remote worker cybersecurity risks, and adaptive deep learning models for anomaly detection. These contributions highlight his focus on mitigating organizational cybersecurity risks through empirical studies and innovative technical solutions. No scientific awards or grants are explicitly listed in the provided information. His advising record remains unspecified, and no active labs or teams are mentioned.