جست‌وجوی استاد و پژوهشگر

Alexandre de Spindlerمشاهده پروفایل

استاد

• Conversational Agents
• Generative AI
• Information Systems
• +۸ مورد دیگر

Prof. Dr. Alexandre de Spindler is a Professor of Information Systems at the Zurich University of Applied Sciences (ZHAW) within the School of Management and Law . He co-leads the Center for Information Systems and Technologies and focuses on application development frameworks for conversational interactions with information systems, leveraging multimodal foundation models while enhancing their controllability and reliability. His work extends to improving social skills in digital interactions and teaching agile requirements engineering. University: Zurich University of Applied Sciences School: School of Management and Law Department: Institute of Business Information Technology Academic Rank: Professor His research explores conversational systems , generative AI , and stateful prompt orchestration for complex interactions, particularly in healthcare and financial sectors. Recent work includes frameworks like PROMISE for model-driven prompt management and Science Fiction Prototyping for responsible AI innovation. Teaching contributions span data science programs (BSc, MSc, CAS) covering machine learning, generative AI, and full-stack application validation. He collaborates across disciplines including gerontology and forensic phonetics, with a focus on applying AI to societal challenges.

Andreas Forstmaierمشاهده پروفایل

مربی

• Environmental Monitoring
• Remote Sensing
• Climate Science
• +۳ مورد دیگر

Andreas Forstmaier, M.Sc., is a staff member at the Technical University of Munich (TUM), affiliated with the Department of Environmental Sensing and Modelling under Prof. Jia Chen. His role includes tutoring in the Advanced Seminar on Environmental Sensing and Modeling. His research focuses on remote sensing applications for environmental monitoring, specifically using multispectral satellite imagery and artificial neural networks to map invasive species like Eucalyptus in protected Natura 2000 areas. He also specializes in improving greenhouse gas emission inventories through column measurements and inverse modeling techniques. His work spans urban methane emissions, coal mine methane quantification, and sensor network development for environmental observations. He collaborates on projects such as the MUCCnet (Munich Urban Carbon Column network) and has contributed to international studies in cities across Europe and Poland. Key research areas include atmospheric chemistry, environmental sensing technologies, and inverse modeling approaches for emission estimation. His publications highlight investigations into methane emissions from cities like Hamburg, the Munich Oktoberfest, and coal mines in Poland. He actively participates in conferences such as EGU General Assembly and ICOS Science Conferences, presenting findings on sensor networks, urban GHG monitoring, and emission modeling. Forstmaier’s technical contributions include developing automated FTIR measurement software (Pyra) and integrating tall-tower flux measurements for refining emission estimates. His work bridges environmental science with technological innovation, emphasizing practical applications for urban and industrial emission management.

Lim Mei Kuanمشاهده پروفایل

مدرس ارشد

• Computer Vision
• Machine Learning
• Smart Manufacturing
• +۴ مورد دیگر

Lim Mei Kuan is a Senior Lecturer at the School of Information Technology, Monash University Malaysia. She holds a PhD in Computer Vision from Universiti Malaya and has conducted post-doctoral research in Artificial Intelligence. Her career includes roles as a researcher at MIMOS Berhad (2004-2007) and visiting researcher at Kingston University (2012-2013). Education: BSc (First Class Honours) in Computer Science, Universiti Malaysia Sarawak (2007) PhD in Computer Vision, Universiti Malaya (2015) Research Interests: Her work spans computer vision, machine learning, and their applications in smart manufacturing and digital health. Current projects include social media analytics for mental health monitoring, anomaly detection in manufacturing, and collaboration on clinical teletherapy systems. She actively explores swarm intelligence and deepfake detection technologies. Grants & Collaborations: DELTA: Inclusive Teletherapy (2022-2024) ADSM: Anomaly Detection for Smart Manufacturing (2022-2023) Sense-ED: Eating Disorder Relapse Detection (2021-2022) Awards: ITEX 2022 Silver Award for Self-Mind mental health app Labs & Teams: Active contributor to interdisciplinary projects with industry partners, focusing on AI-driven solutions for healthcare and manufacturing sectors.

Quentin Cappartمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Combinatorial Optimization
• Constraint Programming
• +۵ مورد دیگر

Quentin Cappart is an Associate Professor at Polytechnique Montréal since 2020, specializing in artificial intelligence , combinatorial optimization , and constraint programming . His work integrates machine learning and operations research to solve complex industrial problems, particularly in transportation , logistics , and healthcare . Affiliations: Co-founder and Head of the Combinatorial Optimization and Reasoning in Artificial Intelligence Laboratory (CORAIL) Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT) IVADO researcher Affiliate member of MILA Researcher at IMC2 institute Research focus: Hybrid algorithms combining logical reasoning , machine learning , and operations research to enhance decision-making tools. His group emphasizes accessibility for non-experts and small companies. Scientific Awards: 2025: Early Career Engineer Award (Ordre des ingénieurs du Québec) 2025: Early Career Professor Award (Polytechnique Montréal) 2025: Prix Méritas (Polytechnique Montréal) 2024: Early Career Researcher Award (ACP) 2024: Best Paper Award (ACP Machine Learning track) 2023: Winning approach for Citylearn challenge (NeurIPS) Teaching: Courses include INF8175: Artificial intelligence - methods and algorithms and INF6102: Local search and metaheuristics . He also teaches at ACP Summer/Winter Schools.

Mahsa Yarmohammadiمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Deep Learning
• Automatic Speech Recognition
• +۴ مورد دیگر

Mahsa Yarmohammadi is an Assistant Research Scientist at the Center for Language and Speech Processing (CLSP), where she leads research in cross-lingual language and speech applications. Her work focuses on deep learning techniques for multilingual data representation, automatic speech recognition (ASR), and speech translation. She develops novel algorithms for ASR decoders and explores interfaces between ASR and machine translation systems. Education: PhD in Computer Science and Engineering, Oregon Health & Science University (2016) Master’s in Computer (Software) Engineering, Shahid Beheshti University, Iran (2007) Undergraduate degree in Computer (Software) Engineering, Amirkabir University of Technology (Tehran Polytechnic) (2004) Research Interests: Her expertise spans Natural Language Processing (syntactic/semantic parsing, information extraction), multilingual systems, deep learning, and ASR. She specializes in resource transfer across languages, neural lattice embeddings, and end-to-end system integration for speech and language technologies. Publication Trends: Recent articles (2019–2025) emphasize multilingual challenges: cross-lingual retrieval, contextual ASR, coreference resolution in dialogue, and zero-shot information extraction. Her work frequently addresses low-resource settings, neural algorithm design, and real-world dataset creation (e.g., earnings call analysis, COVID-19 QA pairs). Grants & Teams: As a prime researcher in multi-site programs, she collaborates on large-scale multilingual projects. She was mentored by Benjamin Van Durme (Johns Hopkins CS) and Sanjeev Khudanpur (Johns Hopkins ECE) during her CLSP post-doctoral fellowship (2021).

• Database Systems
• Data Mining
• Social Network Analysis
• +۳ مورد دیگر

Eric Leclercq is a researcher at the University of Burgundy, affiliated with the LE2I Lab in Dijon, France. His work spans database systems, social network analysis, and biomedical data integration. He has contributed extensively to polystore systems, tensor decompositions, and category theory applications in data modeling. Fields of Interest : Database Systems, Data Mining, Social Network Analysis, Big Data Analytics, Semantic Web Leclercq's recent research focuses on formal frameworks for data lakes using category theory, multi-level tensor decomposition for social network stratification, and schema migration in multi-model systems. He has published in venues like CAiSE, IDEAS, and RCIS. His collaborations include Annabelle Gillet, Marinette Savonnet, and Nadine Cullot. Notable works include Lambda+ architecture for data processing, polarization analysis in social networks, and tools for tweet collection and biomedical data integration.

Sebastian Kempfمشاهده پروفایل

پژوهشگر

• Information Extraction
• Table Extraction
• Ontology Generation
• +۴ مورد دیگر

Sebastian Kempf is a researcher at the Chair of Computer Science VI (Artificial Intelligence and Knowledge Systems) within the Institute of Computer Science at the University of Würzburg's Faculty of Mathematics and Computer Science. He has been working at the chair since October 2021, focusing on information extraction, particularly table extraction and analysis, as well as ontology-based knowledge extraction. His research spans Information Extraction , Table Extraction , Ontology Generation , Document Analysis , Data Mining , and Knowledge Modeling . These areas drive his development of systems for transforming unstructured and semi-structured data into actionable knowledge, with applications across scientific, industrial, and humanities domains. Publications reveal a consistent trajectory in applying AI to interdisciplinary challenges—from materials science (glass development) to digital humanities (literary analysis) and scientific document processing. His work emphasizes practical AI solutions that bridge theoretical frameworks with real-world data complexities. Kempf actively contributes to teaching through Software Engineering courses (Summer Semesters 2022-2024), Medical Image Processing (Winter Semester 2024/25), and regular supervision of seminar topics and software internships. His project portfolio includes current work on PlastiKG and past involvement in ESF-BuDanu. As a core member of the Center for Artificial Intelligence and Data Science (CAIDAS), he collaborates across Würzburg's AI research ecosystem, leveraging university-wide resources for ontology-driven data infrastructure and knowledge systems development.

Len Dawsمشاهده پروفایل

استاد مدعو

• Machine Learning
• Adversarial Machine Learning
• Noisy Label Learning
• +۳ مورد دیگر

Len Daws serves as an Adjunct Professor in the Department of Computer Science at Rowan University's College of Science & Mathematics while concurrently holding a Sr. Engineering Manager position at Lockheed Martin in Moorestown, NJ. With over 12 years of teaching experience across New Jersey state and community colleges, he is currently in his sixth year instructing the Computers & Society course at Rowan University, focusing on large-scale software system development and integration. His research specializes in machine learning robustness under adversarial conditions, particularly addressing noisy label learning challenges and cybersecurity threats in AI systems. Key contributions include modeling label noise dependencies across multiple annotators, developing contributor-aware defenses against backdoor attacks, and analyzing fundamental trade-offs between attack strength and detectability in adversarial settings. Analysis of his publication history reveals a consistent trajectory toward securing machine learning pipelines against sophisticated threats, with recent work emphasizing labeler-dependent noise modeling and spectral ranking techniques for truth extraction from unreliable sources. His scholarship bridges theoretical machine learning with practical defense mechanisms for real-world AI deployment.

Amy J. Koمشاهده پروفایل

استاد

• Computing Education
• Human-Computer Interaction (HCI)
• Equity & Justice in Computing
• +۶ مورد دیگر

Amy J. Ko is a Professor and Associate Dean for Academics at the Paul G. Allen School of Computer Science & Engineering and The Information School at the University of Washington, Seattle . She serves as Editor-in-Chief of ACM TOCE , co-directs Reciprocal Reviews and CS for All Washington , and leads the CENSOR Research Lab . Her work prioritizes equitable, liberatory computing education , bridging human-computer interaction and social justice . Research Focus: Equity in CS education, AI literacy, inclusive design, developer productivity, and ethical technology use Awards: Best Paper Award (2024, 2022) Diversity + Inclusion Award (2024) Most Influential Paper Honorable Mention (2014) Honorable Mention (2024, 2023) Publications: Over 184 works spanning program comprehension, assessment design, ethical pedagogy, and democratizing computing education Books: Foundations of Information , Critically Conscious Computing , and Teaching Accessible Computing Her Google Scholar profile reflects citations under her deadname, which she advocates to correct. She emphasizes student agency and community collaboration , particularly with marginalized groups in computing spaces.

• Declarative Process Modeling
• Process Mining
• Formal Verification
• +۴ مورد دیگر

Paul Cosma is a Postdoctoral Researcher at the Department of Computer Science (DIKU), University of Copenhagen, specializing in the Software, Data, People & Society (SDPS) section. His work focuses on declarative process modeling, formal verification, and explainable AI systems, with strong connections to process mining and Petri net theory. He completed his PhD at the University of Copenhagen's Faculty of Science in 2024 with a thesis on declarative process models as verifiable AI. His research interests center on declarative process modeling and formal verification of complex systems. Cosma develops techniques for improving model simplicity through nested group discovery and creates frameworks like BERMUDA for participatory mapping of domain activities to event data. His work bridges theoretical computer science with practical applications in business process management and AI explainability, emphasizing human-centered design principles where software systems are developed with societal impact in mind. Cosma's publication record shows a clear trajectory in process modeling research, with recent work focusing on transforming Dynamic Condition Response Graphs to Safe Petri Nets (2023) and improving declarative model simplicity (2024). His research demonstrates strong interdisciplinary connections between formal methods, AI verification, and human-computer interaction, particularly in making complex process models accessible and verifiable. Cosma actively collaborates with researchers including Thomas Hildebrandt, Tijs Slaats, and Axel Christfort, primarily within the SDPS section at DIKU. His work receives consistent citations in process mining literature, with his 2023 PETRI NETS paper accumulating 1 citation and his CAiSE 2024 paper gaining 2 Scopus citations. He maintains an ORCID profile (0000-0001-8022-6402) and contributes to open-access research through the university's Pure repository. Based in Sigurdsgade 41, Copenhagen N, Cosma operates within DIKU's collaborative research environment that emphasizes industry partnerships and interdisciplinary work. His recent PhD defense (June 13, 2024) marks his transition from doctoral candidate to postdoctoral researcher, positioning him to expand his contributions to process-aware information systems and verifiable AI.

Kai Rannenbergمشاهده پروفایل

استاد

• Mobile and embedded systems
• Multilateral Security
• Privacy and identity management
• +۷ مورد دیگر

Professor Kai Rannenberg is the Chair of Mobile Business & Multilateral Security at Goethe University Frankfurt since 2002 and holds a Visiting Professorship at the National Institute for Informatics in Tokyo since 2012. He previously worked with the System Security Group at Microsoft Research Cambridge on Personal Security Devices & Privacy Technologies. His extensive academic career spans over three decades with significant contributions to security and privacy research. His research interests focus on mobile and embedded systems, multilateral security in mobile business, location-based services, transport systems, and industrial applications. He has made significant contributions to privacy and identity management, particularly in attribute-based authorization, communication infrastructures and devices, and security/privacy standardization. His work emphasizes balanced security approaches that protect all stakeholders' interests. Professor Rannenberg's publications reveal a strong focus on practical privacy solutions for mobile and IoT environments, with recent work examining privacy-enhancing technologies adoption, mobile augmented reality security, and enterprise smartphone app risk assessment. His research consistently bridges theoretical security concepts with practical implementation challenges across various domains including e-commerce, social media, and critical infrastructure protection. IFIP Honorary Treasurer (2021-2024) and President-elect (2024-present) IFIP Vice President (2015-2021) and Councillor (2009-2015) Chair of IFIP TC-11 'Security and Privacy Protection in Information Processing Systems' (2007-2013) Academic expert in ENISA Management Board (2004-2013) and Advisory Group (2013-2022) Chair of CEPIS Legal & Security Issues Special Interest Network (since 2003) Editor-in-chief of IFIP Advances in Information and Communication Technology (since 2014) Professor Rannenberg has coordinated several leading EU research projects including the Network of Excellence 'Future of Identity in the Information Society' and the Integrated Project 'Attribute based Credentials for Trust' (ABC4Trust). He currently coordinates CyberSec4Europe, a pilot for the European Cybersecurity Competence Network. His leadership extends to ISO/IEC standardization work, where he served as Convenor of SC 27/WG 5 'Identity management and privacy technologies' and previously coordinated the 'Kolleg Security in Communication Technology' sponsored by Gottlieb Daimler & Karl Benz Foundation. His research group at Goethe University Frankfurt maintains active collaborations with industry and government agencies, particularly in the areas of mobile security, privacy-enhancing technologies, and standardization efforts. The group has recently received funding from the Goethe-Corona-Fonds for research on the German Corona Warning App adoption factors.

Massimo Mecellaمشاهده پروفایل

استاد

• Service-Oriented Computing
• Business Process Management
• Process Mining
• +۱۲ مورد دیگر

Massimo Mecella serves as Full Professor at Sapienza University of Rome's Faculty of Information Engineering, Computer Science and Statistics, where he leads the Processes, Services and Software Management research group and participates in the CINI National Cyber Security Lab. His academic foundation stems from a PhD in Computer Engineering earned at Sapienza in 2002. His research expertise spans service-oriented computing, business process management, and cyber-physical systems with emphasis on service composition, process mining, and adaptive distributed architectures. Key technical domains include IoT integration, digital twin development, and security frameworks for complex software ecosystems. Recent publications (2024-2025) demonstrate a pronounced shift toward Large Language Model (LLM) integration in business processes and smart manufacturing. Dominant themes include LLM-driven process modeling, multimodal quality control systems, and digital twin implementations for energy management and production optimization. Methodological innovations focus on retrieval-augmented generation (RAG) for service discovery and fuzzy cognitive maturity assessments. His distinguished recognition includes: ICSOC 2013 Most Influential Paper Award (2003-2012 decade) 2017 Best Paper Award As research group leader, Mecella directs projects in smart manufacturing, process mining, and cyber-physical security, with funding typically sourced from EU initiatives and industry partnerships in aerospace, healthcare, and energy sectors. His team maintains active collaborations with aerospace manufacturers through the MICS SPOKE8 project and develops frameworks like SAMBA for human-in-the-loop manufacturing systems. The Processes, Services and Software Management group operates within Sapienza's engineering faculty infrastructure, utilizing specialized labs for CPS/IoT testing and digital twin simulation, with strong ties to the CINI Cyber Security Lab for security validation.

Mostafa Mostafaمشاهده پروفایل

دانشیار

• Cybersecurity
• Computer Networks
• Database Systems
• +۳ مورد دیگر

Mostafa Mostafa, Ph.D., serves as Associate Professor and Chair of the Division of Computing at McKendree University. His academic leadership spans cybersecurity, network systems, and database technologies with significant contributions to critical infrastructure protection and educational innovation. His educational background includes: Ph.D., Computer Science and Engineering, University of Louisville, December 2003 M.S., Computer Science, University of Louisville, May 1999 Advanced Professional Certificate in Computer Systems and Applications, American University in Cairo, May 1992 Bachelor of Accounting, Cairo University, May 1989 Dr. Mostafa's research focuses on SCADA security for critical infrastructure, bandwidth pricing economics , and spatial database quality . His work bridges theoretical models with practical applications in industrial control systems and network resource management, demonstrating expertise in both cybersecurity protocols and educational methodologies including game-based software engineering instruction. His publication record (2002-2012) reveals consistent contributions to securing industrial networks and optimizing resource allocation, with increasing emphasis on applied frameworks for spatial data quality and security threat mitigation in critical infrastructure systems. Recognition includes: Dean Citation, 2003, University of Louisville Who is Who among American Ph.D. Students, 2003 As Principal Investigator, he secured $117,000 in competitive funding including a $100,000 Department of Homeland Security grant (2006-2007) for SCADA security in chemical plants and a $17,000 Kentucky Real Estate Commission grant (2008-2009) for website infrastructure. He mentored two master's students to completion on spatial database frameworks and SCADA intrusion detection systems, demonstrating commitment to both research and student development.

Xavier Devroeyمشاهده پروفایل

استادیار

• Software Testing
• Search-Based Software Engineering
• Software Variability
• +۵ مورد دیگر

Xavier Devroey is an Assistant Professor of Software Engineering at the University of Namur in Belgium. He co-leads the SNAIL Team with Benoît Vanderose, focusing on innovative approaches to software testing and automation. His work bridges academic research with practical applications in the software engineering community. His educational background includes a Ph.D. and Master's in Computer Science from the University of Namur, plus a Bachelor's in Analyst Programming from Haute Ecole de Bruxelles, Belgium. This comprehensive academic training informs his research and teaching approach. Devroey's research interests center on Software Testing , with particular emphasis on Search-Based Software Engineering and Software Variability . His specific focus areas include: Search-Based Testing and Fuzzing Model-Based Testing Mutation Testing Variability Modeling Software Product Line Testing Test suite augmentation DevOps integration These interests reflect his commitment to advancing automated approaches for test case design, generation, selection, and prioritization. His recent publication portfolio (2019-2025) demonstrates consistent contributions to software testing research, with particular focus on crash reproduction, API testing, and innovative approaches to test automation. The articles reveal a strong emphasis on practical applications of search-based techniques across various testing domains. Devroey maintains active engagement with the academic community through conference participation, having served on program committees for major software engineering conferences including ASE, ICSE, ISSTA, and ICST across multiple years (2019-2025). He also contributes to educational aspects of software engineering, with publications examining testing education approaches and tools for programming exercise assessment. His personal website (xdevroey.be) and GitHub profile demonstrate his commitment to open academic practices and community engagement.

Shounak Roychowdhuryمشاهده پروفایل

دانشیار

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۴ مورد دیگر

Shounak Roychowdhury is an Associate Professor of Practice at the School of Information, University of Texas at Austin. He holds a PhD in Computer Engineering from the University of Texas at Austin (2013) and an MS in Computer Science from the University of Tulsa (1997). His teaching focuses on foundational and advanced topics such as Computer Vision, Database Management, Programming, and Data Science. Recent courses include INF 385T: Special Topics in Information Science: Computer Vision (2025) and I 320D: Topics in Human-Centered Data Science: Database Design (2024). Roychowdhury's research spans Computer Science , Machine Learning , and Software Engineering , with a focus on probabilistic methods, fuzzy systems, and medical informatics. His work explores areas like fault localization in software, data clustering optimization, and applying generative models to healthcare analytics. He has also contributed to fuzzy logic applications in decision-making and pattern recognition. His publications highlight interdisciplinary approaches, including Alzheimer’s disease modeling with GANs and color space analysis in art through probabilistic divergences. While no scientific awards are listed, his work reflects sustained contributions to theoretical and applied computing. Roychowdhury advises no listed students but maintains an active teaching role. No specific grants or labs are mentioned, though his research aligns with computational and data-driven methodologies.