جستجوی استاد راهنمای دانشگاهی

Chetan Aroraمشاهده پروفایل

مدرس ارشد

• Applied Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۵ مورد دیگر

Dr. Chetan Arora is a Senior Lecturer in Software Engineering at Monash University's Faculty of IT, specializing in applied Artificial Intelligence (AI), including Machine Learning (ML) and Natural Language Processing (NLP). He serves as Director of Education (SSC) at the Faculty of IT and leads research in requirements engineering, software trustworthiness, and satellite communication (SatCom). His work contributes to UN SDGs related to education and innovation. Education : PhD in Computer Science, University of Luxembourg (2016) Masters in Software Engineering, Technische Universität Kaiserslautern (Germany) Bachelor's in Computer Science, Thapar University (India) Research Interests : Focus on AI-driven requirements engineering, generative AI applications in software development, and human-centric cybersecurity. Recent work explores ethical AI, persona-based design, and IoT integration in critical systems. Recent Research Trends : Over 65 publications since 2013, with 2025 highlighting generative AI's role in requirements engineering, ethical AI practices, and persona-driven design. 2024 research emphasizes optimization algorithms for EV networks and LLM-driven modeling. Awards : Best PhD Thesis Award (University of Luxembourg, 2016) ACM SIGSOFT Distinguished Paper Award (2022) Multiple Best Paper Awards at IEEE/ACM Conferences Grants & Collaboration : Secured >$1.1M in grants as Lead CI. Active in projects like RAISE: Responsible AI Software Engineering and GenAI-Powered ICT Education . Collaborates with industry partners like Episoft Pty Ltd and Swordfish Computing. Labs/Teams : Leads initiatives in the Department of Software Systems & Cybersecurity Impact Labs, focusing on AI ethics and human-centric software systems. Member of the International Requirements Engineering Board (IREB).

Wenbo Guoمشاهده پروفایل

استادیار

• Machine Learning
• Cybersecurity
• AI Security
• +۳ مورد دیگر

Wenbo Guo is an Assistant Professor and Zhu Chair in the Department of Computer Science at the University of California, Santa Barbara (UCSB). He holds a PhD from Pennsylvania State University and a Master's from Shanghai Jiao Tong University. His research focuses on the intersection of machine learning and security, particularly in AI agents, LLM code reasoning, and agent security/safety. He actively explores reinforcement learning for security applications, explainable AI, and robustness of large models. Guo's work includes designing foundation models for security problems, developing tools like PatchPilot and Co-PatcheR for software engineering, and defending against adversarial attacks. He leads the Agent Security team at Virtue AI, a startup addressing frontier AI security. His honors include the IBM Fellowship Award, Google ML Junior Faculty Award, and multiple conference recognitions. Education: PhD (Penn State), MS (Shanghai Jiao Tong) Affiliations: UCSB Computer Science, Virtue AI (Head of Agent Security) Labs: BAIR Lab (UC Berkeley), RDI Center Grants include the UCSB Faculty Research Grant (2025), Google ML Award (2025), and Amazon Research Award (2024). He advises on cybersecurity challenges in AI and collaborates with industry partners like DARPA and FAR AI. His CTF engagements include Shellphish and Geekpwn competitions, emphasizing practical security testing.

Yu Zhangمشاهده پروفایل

استادیار

• Data Mining
• Natural Language Processing
• Artificial Intelligence for Science
• +۲ مورد دیگر

Yu Zhang is an Assistant Professor at the Department of Computer Science & Engineering, Texas A&M University since January 2025. He earned his Ph.D. (2024) and M.Sc. (2019) from the University of Illinois at Urbana-Champaign under Prof. Jiawei Han, with a thesis winning the ACM SIGKDD Dissertation Award Runner-Up. Prior to UIUC, he obtained a B.Sc. (2017) at Peking University mentored by Prof. Yan Zhang. Research Focus: NLP & Data Mining for Science (Biology, Medicine, Math); Graph-structured Knowledge Integration; Weakly Supervised Learning Key Contributions: Chain-of-Factors for Paper-Reviewer Matching, Graph Chain-of-Thought for LLM Reasoning, Seed-Guided Topic Discovery Recent Trends: 2025 publications at ACL, WWW, EMNLP Findings on LLMs for Scientific Discovery Scientific Honors: ACM SIGKDD Dissertation Runner-Up (2025), Dissertation Completion Fellowship (2023), Yunni & Maxine Pao Fellowship (2022) He serves as Area Chair for KDD 2025-2026 and Senior Area Chair at WSDM 2025. His lab develops tools like SKnowLLM for structured knowledge in LLMs and MLoG-GenAI for graph learning in general AI era.

Felix T.J. Dietrichمشاهده پروفایل

پژوهشگر

• Educational Technology
• Learning Analytics
• Adaptive Learning
• +۳ مورد دیگر

Felix T.J. Dietrich is a researcher at the Technical University of Munich specializing in educational technology and software engineering. He completed his Master of Science in Informatics at TUM in November 2023 with a focus on machine learning, natural language processing, and computer vision. His educational background includes: Master of Science in Informatics, Technical University of Munich (2019-2023), Grade: 1.7 Student Exchange at The University of Tokyo (2020) Bachelor of Science in Informatics, Technical University of Munich (2016-2019), Grade: 2.0 Dietrich's research centers on Educational Technology, Learning Analytics, and Adaptive Learning systems , with significant contributions to the Artemis educational platform and Hephaestus project for supporting software engineering teams. His work bridges machine learning applications with practical software development, particularly in iOS and web technologies. He has received notable recognition including: Apple's Swift Student Challenge Winner (2024) Dietrich actively advises Master's and Bachelor's theses at TUM, supervising projects on LLM-based educational feedback, code review gamification, and UML integration tools. He coordinates the GenAI Talks series through BayernCollab and teaches iOS development seminars for Winter 2024/25 and Summer 2025. His industry experience includes developing the Finance App MVP for consumer financial health and leading the Hephaestus project for collaborative software engineering environments.

Basem Suleimanمشاهده پروفایل

مدرس ارشد

• AI-driven Software Services
• Applied Artificial Intelligence (GenAI/LLM, Machine Learning)
• Education Technologies (Personalized Learning)
• +۴ مورد دیگر

Dr. Basem Suleiman is an Adjunct Senior Lecturer in Advanced Computing at the University of Sydney and Deputy Director of the Software Engineering Program at UNSW Sydney. He holds a Ph.D. in Computer Science from UNSW (2012) and has over a decade of experience in academia and industry, including roles at SAP, CSIRO’s Data61, and leading universities. Education: Ph.D. in Computer Science, UNSW Sydney (2012) Graduate Certificate in Research Commercialization & Management, UNSW Sydney Master of Computing (Software Engineering), Western Sydney University Research Interests: AI-driven Software Services: Federated Learning, Recommender Systems, Human-Machine Interaction Applied AI: GenAI/LLMs, Machine Learning, Deep Learning for FinTech, Healthcare, and Education Cloud Computing: Elasticity, Workload Management, Privacy-Preserving Techniques Key Contributions: Developed AI models for structural health monitoring, personalized learning systems, and anomaly detection Secured research grants and published 80+ papers in venues like ACM Transactions, IEEE Conferences, and IJCAI Supervised 15+ PhD/MPhil students and led industry partnerships with SAP, CSIRO, and global tech firms Awards & Recognition: Runner-up Best Paper Award (2023) Dean’s Commendation for Teaching Excellence Invited Keynote Speaker (2022 ICoSEIT) Engagement: Leads industry collaborations as UNSW’s Industry Capstone Liaison Officer, fostering partnerships for student projects and curriculum innovation.

• Artificial Intelligence
• Machine Learning
• Software Engineering
• +۴ مورد دیگر

Professor Mohamed Abdelrazek is a Professor of Software Engineering and Research Professor at the Applied Artificial Intelligence Institute (A2I2) within Deakin University. He holds a PhD in Cloud Computing Security from Swinburne University of Technology and a Graduate Certificate in Higher Education Learning & Teaching from Deakin University. His research focuses on robust AI/ML systems, including GenAI and RL approaches, with emphasis on automated software engineering, cybersecurity, distributed systems, and data science. Education: PhD in Cloud Computing Security (Swinburne University of Technology), Graduate Certificate in Higher Ed Learning & Teaching (Deakin University). Research Interests: AI/ML systems, software security, empirical software engineering, data analytics, and human-centered computing. His work spans over 20 years of industry and academic experience, including roles as a senior research fellow and software development manager. He has secured grants totaling millions of AUD from agencies like CSIRO, the Department of Defence, and Telethon Kids Institute, focusing on AI-driven solutions in healthcare, cybersecurity, and robotics. Professor Abdelrazek supervises numerous doctoral and master’s students in topics ranging from robust ML systems to mHealth applications. His recent publications address challenges in AI ethics, cybersecurity, and healthcare technology, emphasizing practical, real-world applications. Key Contributions: Frameworks like 6DVF for mHealth visualization, blockchain service platforms, and reinforcement learning-based cyber-attack simulation tools.

Ramesh Karriمشاهده پروفایل

استاد

• Hardware Cybersecurity
• Trustworthy Integrated Circuits
• Cyber-Physical Systems Security
• +۶ مورد دیگر

Ramesh Karri is a Professor and Chair of the Electrical and Computer Engineering Department at New York University Tandon School of Engineering. He co-founded the NYU Center for Cyber Security (CCS) in 2009 and co-directed it from 2016-2024. He is also a Fellow of the IEEE and has led initiatives such as the Embedded Systems Challenge (ESC), a red-blue team cybersecurity competition. Education: Ph.D. in Computer Science and Engineering, University of California, San Diego (1993) B.E. in Electrical and Computer Engineering, Andhra University (1985) Research Focus: His work centers on hardware cybersecurity, including trustworthy integrated circuits, cyber-physical systems, nano-enabled security, and biochip security. He pioneered security-aware CAD tools and has developed metrics for hardware trojan detection through initiatives like the Trust-Hub. Awards & Leadership: Recipient of the Humboldt Fellowship and NSF CAREER Award Editor-in-Chief of ACM Journal of Emerging Computing Technologies Leadership roles at IEEE conferences (ICCD, HOST, DFTS) Grants & Labs: Directs the Center for Advanced Technology in Telecommunications (CATT) and NYU CCS. His labs focus on additive manufacturing security, digital microfluidic systems, and AI-driven hardware design.

Danny Digمشاهده پروفایل

دانشیار

• Software Engineering
• Gen-AI
• Program Transformations
• +۷ مورد دیگر

Danny Dig is an Associate Professor of Computer Science at the University of Colorado and an Adjunct Professor at the University of Illinois and Ohio State University. He leads the NSF IUCRC Center on Pervasive Personalized Intelligence for IoT Systems. His research focuses on software engineering, particularly automated program transformations and Gen-AI integration to enhance developer productivity and software quality. He earned his Ph.D. from UIUC, where his dissertation won the Best Dissertation Award, and completed a postdoc at MIT. Education: Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign (2007), Postdoc at MIT. Research Interests: Interactive program transformations, LLM-powered refactoring, concurrency, mobile computing, and software evolution. His work has been recognized through numerous awards, including the NSF CAREER Award and Google Faculty Research Awards. He has released tools like RefactoringMiner and LambdaFicator, widely adopted in development environments like Eclipse and IntelliJ. Awards include IoT Innovator of 2021 and Best Reviewer Award at ICSME'19. His grants total over $7.4M, with collaborations from NSF, Boeing, IBM, and others. He advises students and leads industry partnerships through the PPI Center. His courses, such as 'GenAI-powered Software Engineering,' emphasize practical impact and industry engagement.

• Business Communication
• Professional Writing Pedagogy
• Generative AI in Education
• +۳ مورد دیگر

Emily DeJeu is an Assistant Teaching Professor of Business Management Communication at Carnegie Mellon University's Tepper School of Business. Her work focuses on enhancing professional writing pedagogy through mixed-methods research, with a current emphasis on generative AI applications in education. She holds a PhD and MA in Rhetoric from CMU. Affiliations: Tepper School of Business Executive Education (AI for Business Communication, Emerging Business Applications of GenAI programs) Education: PhD and MA in Rhetoric (Carnegie Mellon University, 2018–2022) Her research explores ethical business communication, startup vs. traditional entrepreneurship rhetorics, and civic advocacy curricula. Recent projects include AI's role in data visualization and Olympic athlete analysis. Publications span AI ethics, nonprofit proposal writing, and entrepreneurial storytelling. She received the 2022 Distinguished Publication Award for scholarly contributions. Teaching activities include courses on business communication, presentations, and GenAI integration. She advises the Tepper Undergraduate Consulting Club and CMU's Young Life chapter.

Jeanette Falkمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Artificial Intelligence
• Creativity
• +۴ مورد دیگر

Jeanette Falk is an Assistant Professor in the Department of Computer Science at Aalborg University, affiliated with The Technical Faculty of IT and Design. Her research focuses on temporality in design processes, particularly exploring how time and AI technology influence creativity and design methodologies. She investigates long-term and short-term design processes, fast and slow-paced design thinking, and the impact of generative AI on creative workflows. Her work emphasizes sustainability, including the environmental footprint of AI in HCI research. Her research interests include Human-Computer Interaction, generative AI, participatory design, and temporal aspects of collaborative design. She has published extensively on hackathons, game jams, and the role of pacing in design innovation. Her recent work addresses ethical and environmental considerations in AI-driven design processes. Key contributions include developing tools like the HCI GenAI CO2ST Calculator to assess AI's environmental impact and exploring creative evaluation methods at scale. She actively participates in academic events and contributes to advancing hackathon methodologies and AI literacy initiatives.

Muhammad Hamad Alizaiمشاهده پروفایل

دانشیار

• Internet of Things
• Cyber-Physical Systems
• Embedded AI
• +۷ مورد دیگر

Muhammad Hamad Alizai is an Associate Professor in the Department of Computer Science at the School of Science and Engineering (SBASSE), Lahore University of Management Sciences (LUMS), Pakistan. His research spans the Internet of Things (IoT), Cyber-Physical Systems, Embedded AI, and intermittent computing, with a focus on sustainable and accessible technologies for developing regions. His research interests include energy harvesting, batteryless computing, GenAI for IoT, wireless sensor networks, and distributed systems . He explores how generative AI can democratize IoT access in low- and middle-income countries and addresses societal challenges through computational solutions. His work is supported by grants from HEC, LUMS, DAAD, and NCBC. Recent publications reveal a strong trend in intermittent computing, energy-efficient IoT, and AI-driven system optimization , with high-impact papers in ACM SenSys, IPSN, BuildSys, and CACM. His team develops innovative systems like CheckMate, Glitch in Time, and Guardian Angel, tackling reliability, security, and accessibility in transiently powered devices. Scientific recognitions include: Best Paper Candidate at ACM SenSys 2019 Audience Choice Award at ACM BuildSys 2017 Best Abstract Award at ACM SenSys 2010 He has advised numerous graduate students, including PhDs like Saad Ahmed and Samar Abbas, and leads pedagogical innovation as head of the LUMS Learning Institute , promoting teaching excellence and AI integration in education. He has served on technical committees for ACM CoNEXT, IPSN, MobiSys, and BuildSys, and organized key workshops in transient computing. His lab focuses on building privacy-preserving, energy-neutral, and AI-augmented embedded systems , particularly for applications in water, energy, and transportation in developing regions.

Tanu Mitraمشاهده پروفایل

دانشیار

• Human-Computer Interaction
• Social Computing
• Responsible AI
• +۶ مورد دیگر

Tanu Mitra is an Associate Professor at the Information School of the University of Washington and an affiliate faculty member at the Paul G. Allen School of Computer Science & Engineering. She serves as the Founding Co-Director of RAISE, the Center for Responsibility in AI Systems and Experiences. Her research focuses on Human-Centered Artificial Intelligence and Responsible AI, combining computational techniques, social science principles, and AI methodologies to study human behavior in online systems. Her work spans three interconnected domains: Generative and Responsible AI - examining how to ensure genAI tools produce socio-demographically diverse, value-aligned content while addressing epistemic challenges Algorithmic Auditing - conducting computational audits to reveal how algorithms amplify problematic content across different cultural contexts Designing Defenses Against Problematic Information - developing socio-technical interventions like OtherTube and NudgeCred to counter misinformation Dr. Mitra's publications demonstrate leadership in examining large language models through the lens of social impact, with emphasis on value alignment, demographic biases, and cross-cultural algorithmic behaviors. Her work bridges technical AI research with practical applications for platform design and policy development. Notable projects include: Epistemic Alignment framework for user-LLM knowledge delivery Geolocation audits of YouTube for COVID-19 misinformation across US and South Africa MythTriage system for detecting opioid use disorder myths on video platforms Prior to joining the University of Washington, Dr. Mitra served as Assistant Professor in the Department of Computer Science at Virginia Tech (2017-2020) after earning her PhD in Computer Science from Georgia Tech.

Diarmuid O'Donoghueمشاهده پروفایل

استادیار

• Computational Creativity
• Analogical Reasoning
• Natural Language Processing
• +۴ مورد دیگر

Diarmuid O'Donoghue is an Assistant Professor in the Faculty of Science & Engineering at Maynooth University, specializing in Computational Creativity and Analogical Reasoning . His research explores topological similarities between text and source code to develop cognitively inspired systems for problem-solving and bias detection. Co-PI of the Modelling implicit bias project (€21/FFP-P/10118) Senior Scientific Coordinator for the €2.6M EU-funded Dr Inventor project Key research areas include: Latent homomorphism detection in lexical data Comparative analysis of LLMs and analogical systems Formal specification generation from code/text His work has shaped undergraduate project frameworks with ethical GenAI integration . Publications span ICCC , GECCO , and journals like Artificial Intelligence Review .

Félix do Carmoمشاهده پروفایل

مدرس ارشد

• Translation Technologies
• Machine Translation
• Translation Process Research
• +۳ مورد دیگر

Dr. Félix do Carmo is a Senior Lecturer in Translation and Natural Language Processing at the University of Surrey's Centre for Translation Studies, part of the School of Arts, Humanities and Creative Industries. He holds a PhD from the University of Porto and has over two decades of industry experience as a translator, reviser, and translation company owner. His research focuses on automation of translation processes, post-editing of machine translation, and human-computer interaction in translation workflows. Key projects include the KAITER initiative exploring interactive translation editing systems and the ADAPT Centre post-doctoral work on translation technology. Teaching responsibilities include leading modules on 'Translation as Human-Computer Interaction' and 'Professional Translation Practice II'. He actively collaborates with industry partners and has published extensively on machine translation evaluation, emotion translation challenges, and translation process research. His work bridges theoretical translation studies with practical applications of AI and NLP technologies. Research highlights include studies on MT quality estimation for user-generated content, emotion-loaded text translation challenges, and the ethical implications of translation workflow automation. He co-authored the influential book 'Conducting Research in Translation Technologies' and has contributed to international conferences such as the Machine Translation Summit. Current projects emphasize improving translator-machine collaboration through intelligent tools and exploring GenAI integration in translation education. Dr. do Carmo's academic affiliations extend to the Surrey Institute for People-Centred Artificial Intelligence (PAI) and he maintains strong connections with the translation industry through consultancy and conference organizing. His work consistently emphasizes real-world applicability of research findings, fostering innovation while addressing labor and ethical considerations in an increasingly automated translation landscape.

Duri Longمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Human-Centered AI
• AI Literacy
• +۷ مورد دیگر

Duri Long is an Assistant Professor in the Department of Communication Studies at Northwestern University, with a courtesy appointment in Computer Science. As director of the Creative Interfaces Research + Design Studio , they bridge human-centered AI, design fiction, and co-creativity through interdisciplinary methodologies from learning sciences, cognitive research, and design practice. Their educational background includes a PhD in Human Centered Computing from Georgia Tech (specialization in Learning Sciences and Technology), a minor in Design Research, and BS degrees in Computer Science and Dramatic Art from UNC Chapel Hill. Research focuses broadly on AI literacy , human-AI improvisation , and equitable design for social environments. Recent publications analyze communal GenAI paradigms (ACM DIS 2025), gender bias in college essay AI (FAccT 2025), and hands-on AI education tools (DL.acm.org). They received an Honorable Mention for Best Paper at GROUP 2025. Advises PhD candidates: Richard Zhang, Lauren Lin, Aidan Fitzsimons Collaborates with artists/museums on co-creative AI installations Active in ACM DIS and CHI conferences