جست‌وجوی استاد و پژوهشگر

• Translation Technologies
• Machine Translation
• Post-editing Evaluation
• +۴ مورد دیگر

Mihaela Vela is a Senior Lecturer at the Department of Language Science and Technology at Saarland University. Her research focuses on machine translation evaluation, post-editing strategies, and translation technologies. Prior to her academic role, she worked as a researcher at the Language Technology Lab of DFKI (2007–2011), contributing to projects like ontology schema extraction from financial news. She holds a PhD in Computational Linguistics (2011) from Saarland University, supervised by Hans Uszkoreit and Thierry Declerck, and a Licentiate degree in Linguistics from West University of Timisoara. Her teaching portfolio includes courses such as Translation and Content Management , Applied Language Technologies , and Machine Translation , reflecting her expertise in integrating computational methods with translation practice. She has developed tools like TeLeMaCo (a collaborative teaching repository) and Catalog (a post-editing interface). Her work emphasizes improving translation workflows through better CAT tool design, metadata preservation, and cognitive load analysis in post-editing tasks. Key contributions include the SubCo corpus of learner translations and studies on post-editing effort in low-resource languages. Her research bridges theoretical linguistics with practical applications, addressing challenges in legal text classification, parliamentary discourse analysis, and neural post-editing systems.

Sudip Subediمشاهده پروفایل

استاد آموزشی

• Construction Safety
• Construction Technology
• Occupational Health
• +۳ مورد دیگر

Sudip Subedi, Ph.D., PE is an Assistant Teaching Professor at Florida International University (FIU), specializing in Construction Safety and Technology. His work focuses on integrating innovative technologies like sensors and virtual reality to enhance occupational health and safety in construction environments. He holds a Ph.D. in Civil Engineering and is licensed as a Professional Engineer (PE). Research Interests: - Construction Safety - Technology in Construction - Virtual Reality Applications - Ergonomics and Biomechanics - Sensor Technology - Sustainable Safety Practices Recent articles emphasize data-driven approaches to workplace safety, including sensor-based injury prevention and virtual reality for training. His work also explores comparative construction techniques in space vs. Earth contexts, reflecting interdisciplinary interests. No scientific awards or major grants are explicitly mentioned in the provided text. Teaching and Advising: - Advises students in FIU’s Construction Management programs (BS, MS, and online formats). - Engages in curriculum development for technology adoption in construction education. Labs/Teams: - Collaborates with FIU’s Industry Advisory Council and Civil Engineering research groups, though specific lab affiliations are not detailed.

Kenneth Jonesمشاهده پروفایل

مدرس

• Information Technology
• Artificial Intelligence
• Applications Development
• +۳ مورد دیگر

Kenneth Jones is an Instructor of Computing and Decision Sciences at Seton Hall University's Department of Computing and Decision Sciences, where he teaches FinTech technology topics and leads the 16th Annual Jim and Judy O’Brien Capital Markets Colloquium. Concurrently, he serves as a legal technology consultant and Chief Operating Officer at Xerdict Group LLC, a cloud-based legal case management platform. Previously, he held senior roles at Bristol-Myers Squibb and a corporate defense law firm, specializing in mass tort resolution and applications development. Education: MBA in Finance (Rutgers University, 1989) and BA in Economics (Rutgers University, 1986). His research focuses on the intersection of legal technology and business operations, emphasizing cybersecurity, process optimization, and AI applications in legal domains. Over 50 published articles since 2018 highlight his contributions to legal tech adoption strategies, litigation tracking systems, and technology ROI analysis. Recent work emphasizes cyber-insurance considerations and change management frameworks for law firms. Recipient of the 2018 National Law Journal’s Elite Boutique Trailblazer award Editorial Review Board Member for Thomson Reuters’ Practice Innovations Newsletter Professional service includes leadership roles at the International Legal Technology Association (ILTA), MIT Media Lab’s Computational Law initiatives, and cybersecurity organizations like ISSA Wisconsin. Active in legal education, he teaches LinkedIn strategies for academics and advises on legal tech budgets through speaking engagements at ILTACON and iManage ConnectLive events.

• Software Engineering
• Software Evolution
• Knowledge Worker Productivity
• +۴ مورد دیگر

Gail Murphy is a Professor in the Department of Computer Science and Vice-President Research & Innovation at the University of British Columbia (UBC). A co-founder of Tasktop Technologies Incorporated, she leads the Software Practices Lab and is affiliated with CAIDA (Centre for Artificial Intelligence Decision-making and Action) and ICICS (UBC Institute for Computing, Information and Cognitive Systems). B.Sc. (Honours), University of Alberta (1987) M.Sc., University of Washington (1994) Ph.D., University of Washington (1996) Her research focuses on software engineering , particularly improving knowledge worker productivity and tools for evolving large-scale systems. She combines lightweight design approaches with industrial evaluations, addressing structural degradation in software systems through: Techniques for understanding/imposing structure in existing systems Design approaches for component reuse and flexible architectures Her recent work includes developer discussion analysis for design recovery (2022), semantic-based task relevance detection (2022), and automated resource-task association (2023). Awards include SIGSOFT Outstanding Research Award (2023), ACM Fellow (2023), and Royal Society of Canada Fellow (2023). She has taught courses like Introduction to Software Engineering (CPSC 310) and Software Construction (CPSC 210).

Alberto Bacchelliمشاهده پروفایل

دانشیار

• Empirical Software Engineering
• Software Quality
• Code Review
• +۳ مورد دیگر

Alberto Bacchelli is an Associate Professor of Empirical Software Engineering at the University of Zurich (UZH), leading the Zurich Empirical Software Engineering Team (ZEST). He joined UZH in 2017, having previously worked as an Assistant Professor at Delft University of Technology (Netherlands), where he earned tenure. His research focuses on improving software quality, developer effectiveness, and code review practices through empirical studies and tool development. Bacchelli holds a PhD from the University of Lugano, with internships at Microsoft Research. He has received prestigious awards, including the MSR Ric Holt Early Career Achievement Award (2020) and the 10-year Most Influential Paper Award from SANER. His work spans code review efficiency, software security, and developer tools. In his personal life, he balances family time with a passion for photography, particularly through his sister Chiara’s wedding photography work. Affiliations: University of Zurich (since 2017), Delft University of Technology (2013–2017), Microsoft Research (internships 2012–2013). Education: PhD in Computer Science (University of Lugano, 2013), Master/BS in Computer Science (University of Bologna), studies at Université Libre de Bruxelles. His research interests center on understanding software engineering challenges and designing tools/methods to enhance practices. Notable projects include studies on code review strategies, developer cognition, and security in collaborative environments. He emphasizes bridging theory and practice, aiming for real-world impact through tools like PyDriller and frameworks for mining software repositories. Awards highlight his contributions to code review and software engineering education. He actively engages in teaching, mentoring, and advancing open-source practices. His team, ZEST, explores topics such as code review dynamics, developer productivity, and empirical methods to improve software processes.

Andrea Galassiمشاهده پروفایل

استادیار

• Natural Language Processing (NLP)
• Machine Learning
• Argument Mining
• +۵ مورد دیگر

Andrea Galassi is a Junior assistant professor (RTD-A) at the University of Bologna's Department of Computer Science and Engineering (DISI), part of the Language Technologies Lab led by Paolo Torroni. He holds a PhD in Computer Science and Engineering from the University of Bologna (2021), with a dissertation on integrating deep neural networks and symbolic knowledge. His postdoctoral research included roles at Stanford, Imperial College London, and the Humane-AI-Net European project on ethical AI. He also served as an Adjunct Professor at the University of Bologna. His research focuses on Machine Learning, Natural Language Processing (NLP), and neuro-symbolic techniques applied to argument mining, legal text analysis, and ethical AI. Notable projects include the FAIR initiative (developing scalable AI techniques), CLAUDETTE, PRIMA, and ADELE legal analytics projects, and StairwAI's horizontal matchmaking services. He is an expert in argument mining for judicial decisions and automated analysis of privacy policies. Galassi has taught over 300 hours of courses, ranging from foundational computer science to advanced NLP topics. He holds National Scientific Qualification for Associate Professor in Computer Engineering (ASN 2023-2025). His recent work emphasizes ethical AI applications, misinformation detection, and AI-driven legal systems, with publications in areas like cross-lingual legal benchmarking (LEXTREME) and subjectivity detection in news media. He leads projects on AI for social impact, including chatbots for asylum seekers and privacy-preserving dialogue systems. His lab participates in CLEF challenges on news credibility and legal argumentation analysis, demonstrating expertise in collaborative AI frameworks and real-world societal applications.

• Legal Technology
• Natural Language Processing (NLP) for Legal Texts
• Computational Law
• +۵ مورد دیگر

Prof. Dr. Matthias Grabmair is a Professor of Legal Tech at the TUM School of Computation, Information and Technology, part of the Technische Universität München (TUM). His research focuses on advancing computational methods for legal analysis, particularly leveraging natural language processing (NLP) to enhance legal document summarization, judgment prediction, and AI-driven legal systems. He leads the JUSMOD organization and has contributed to datasets like ECtHR-PCR for precedent understanding. Key research areas include automated legal reporting (e.g., LexGenie), cross-jurisdictional analysis, and ethical AI applications in privacy policies (PrivaT5). His work emphasizes improving judicial decision-making transparency through models like Hiculr for rhetorical role labeling and Chronoslex for temporal generalization. Prof. Grabmair also explores adversarial robustness in legal AI systems and transfer learning across legal domains. Publications span 2005–2025, with recent emphasis on generative AI for legal texts, explainable AI in judgment prediction, and curriculum learning for legal document analysis. His research bridges computational methods with legal practice, addressing challenges in fairness, reliability, and scalability of AI applications in law.

Davor Runjeمشاهده پروفایل

مدرس

• Artificial Intelligence
• Theoretical Computer Science
• Software Engineering
• +۴ مورد دیگر

Davor Runje is a lecturer at Algebra University with extensive industry experience as a software engineer, computer scientist, and serial entrepreneur. He has co-founded multiple technology ventures including AIRT (an AI startup), DRAP (a digital agency acquired by Imago Ogilvy in 2018), and PlayMedia Systems (1997), which became a global leader in AMP MP3 playback technology. His research interests span artificial intelligence, theoretical computer science, parallel and distributed computing, and cryptography. Runje has made significant contributions to programming for multiprocessor/multicore systems, with work that later became the Task Parallel Library in the .NET framework during his time at Microsoft Research. His publication portfolio shows a clear evolution from theoretical computer science and concurrency research (2003-2009) toward machine learning and AI (2019-2025), with particular focus on neural networks, model interpretability, and security aspects of large language models. His recent work demonstrates expertise in constrained monotonic neural networks, attention mechanisms for tabular time-series, and vulnerabilities in large language models. His notable achievements include: Microsoft Research SSCLI and Phoenix 2005 awards Two US patents 20 publications in theoretical computer science and artificial intelligence Chairing the Croatian Independent Software Exporters board (2020-2024) As an active industry leader, Runje has participated in numerous legal and tax reform initiatives aimed at increasing the competitiveness of the Croatian IT sector in global markets, representing approximately one-third of the Croatian IT industry through his leadership role.

• Artificial Intelligence
• AI & Law
• Computational Argumentation
• +۹ مورد دیگر

Prof. Floris Bex (Utrecht University) is a leading scholar in AI & Law, focusing on explainable AI , computational argumentation , and responsible AI development . He holds a dual appointment at the Molengraaff Institute for Private Law and Department of Information and Computing Sciences , bridging legal theory with technical AI innovation. His work emphasizes transparency in high-risk domains like policing and judicial decision-making. Scientific Director, National Police Lab AI Member, Board of Advisory Scientific Research (WODC), Ministry of Justice Editorial roles in Artificial Intelligence and Law and Argument and Computation His research combines symbolic and subsymbolic AI to create systems that reason with legal arguments, including projects like ALGOPOL and the Formal Explanations with Computational Argumentation framework. He has developed an explainable AI system for crime report assessment that improves citizen trust through transparent rejections. Key publications span 2016–2024 , with recent work on argumentation-based explanations , incomplete evidence handling , and human-AI collaboration in policing . His projects integrate Bayesian networks with argumentation theory to address real-world challenges in digital justice and public safety. Scientific awards include: Editorial board member, Artificial Intelligence and Law Scientific Advisor to Dutch National Police Lead in ICAI network collaborations He teaches Computational Argumentation and Law and Computer Science , and has supervised numerous AI & Law projects involving students like Daphne Odekerken and Anton Borg.

• Natural Language Processing
• Machine Learning
• Computational Linguistics
• +۸ مورد دیگر

Marijn Schraagen is an Assistant Professor in Natural Language Processing at Utrecht University's Faculty of Science, specifically within the Information and Computing Sciences department. His academic work bridges computational linguistics with practical applications across multiple domains including healthcare, law, and cultural heritage. His research interests focus on the application of machine learning methods to large collections of text and speech data. Schraagen has developed expertise in Dutch language processing with specific applications in clinical settings, legal contexts, and historical language analysis. Notably, within the Goallab at the department of Social, Health and Organizational Psychology, he contributes to developing machine learning models for detecting and preventing low literacy among Dutch children. His publication record demonstrates consistent research activity from 2010 through 2025, with recent work showing particular strength in legal text analysis, clinical NLP applications, and historical language processing. His articles reveal a pattern of interdisciplinary collaboration, working with researchers from psychology, public health, law, and social sciences to address real-world problems through NLP solutions. Schraagen has received research funding from diverse sources including Anders AI Lab, NWO Ai-NEDXS, the National Police, and the Royal Library. His projects include developing AI tools for literacy detection, analyzing protest events in social media, and creating systems for processing historical Dutch texts. He teaches courses in computational thinking, knowledge-intensive process analysis, and methods in AI research, contributing to both the theoretical and practical education of students in the field of artificial intelligence and natural language processing.

Paul Luffمشاهده پروفایل

استاد

• Human-Computer Interaction
• Computer-Supported Cooperative Work
• Video-Based Ethnography
• +۶ مورد دیگر

Professor Paul Luff is a leading academic at King's Business School, King's College London , specializing in the intersection of organizational practices and technological innovation . His research employs video-based ethnography to examine technology integration in high-stakes environments like healthcare, finance, and control rooms , with a focus on AI, robotics, and human-computer interaction . Key Research Themes: Designing explainable AI systems through interdisciplinary collaboration Investigating human-robot dynamics in surgical and auction settings Developing methods for analyzing technology in complex workplaces Grants & Collaborations: Holds funding from ESRC, EPSRC, and EU , and contributes to the Trusted Autonomous Systems Hub and King's AI Institute . His work spans Computer Science, Sociology, and Healthcare . Scientific Impact: Over 70 peer-reviewed articles and 35 book chapters Google H-index: 47 (14,500+ citations) 2017 CSCW Lasting Impact Award

• Natural Language Processing
• Computational Linguistics
• Machine Learning
• +۳ مورد دیگر

Dr. Don Tuggener is a Researcher at the ZHAW Zurich University of Applied Sciences' School of Engineering, affiliated with the Centre for Artificial Intelligence. His work focuses on Natural Language Processing (NLP), Computational Linguistics, and Machine Learning applications in professional training and AI evaluation. He leads or collaborates on projects such as Meaning@Work (stress management for healthcare professionals), Virtual Kids (child interrogation training), and Favi-Score (bias detection in AI evaluation). His research emphasizes dialogue systems, generative AI ethics, and legal text analysis. Key projects include developing frameworks for conversational AI evaluation (Spot The Bot), large-scale legal text classification (LEDGAR corpus), and innovative training tools using LLMs. He has contributed to over 30 peer-reviewed publications since 2011, spanning topics like compound splitting in German, coreference resolution, and generative AI applications in professional contexts. As an editor for SwissText conferences and reviewer for ACL/EMNLP, he actively participates in the NLP academic community. Project Leadership: Virtual Kids, Interscriber Deputy Leadership: AutoNews, PRISM, SCAI Core Research Themes: AI ethics, dialogue systems, legal NLP Recent work highlights AI's role in professional education (e.g., investigative interviews with children) and societal challenges (hate speech mitigation via social influencers).

Laura Boeschotenمشاهده پروفایل

استادیار

• Applied Data Science
• Data Donation Methodology
• Privacy-Preserving Techniques
• +۴ مورد دیگر

Dr. Laura Boeschoten is an Assistant Professor in the Methodology and Statistics department at Utrecht University's Faculty of Social and Behavioural Sciences. She specializes in data donation methodologies, privacy-preserving techniques, and applied data science. Her work focuses on developing intuitive workflows for researchers and participants in data donation studies, particularly in social media and digital trace data contexts. She led the PDI-SSH funded 'D3I' project (2022–2025) and currently serves as task lead in the SSHOC-NL initiative. Her research bridges methodological challenges with real-world applications, emphasizing open-source research infrastructures and ethical data practices. Key research areas include measurement error modeling, missing data imputation, and latent class analysis. She has advised on projects such as the Port software tool for digital data donation and contributed to frameworks ensuring privacy in trace data collection. Publications span topics like GDPR compliance, adolescent social media behavior, and deliberative democracy through open data. Her work often intersects policy and technology, addressing data access obligations for platforms and fostering collaboration between researchers and tech companies. She has published in journals like Communication Methods and Measures , Patterns , and Government Information Quarterly , highlighting interdisciplinary approaches to modern data challenges.

• Entrepreneurship
• International Business
• Institutional Economics
• +۳ مورد دیگر

Rangamohan V. Eunni is a Professor at Youngstown State University (YSU), holding degrees including a Doctor of Business Administration from Boston University (2003), Master of Science in Fiscal Studies from the University of Bath, and a B.Tech (Honors) from the Indian Institute of Technology, Kharagpur. Doctor of Business Administration – Boston University (2003) Master of Science in Fiscal Studies – University of Bath B.Tech (Honors) – Indian Institute of Technology, Kharagpur His research focuses on entrepreneurship in emerging markets, institutional frameworks affecting business, and multinational enterprise (MNE) strategies. Publications span comparative analyses of entrepreneurial environments in BRIC countries, transfer pricing mechanisms, and strategic adaptation in regulated industries. Scientific achievements include securing over $1M in consecutive US Department of Education Title VIB grants for YSU's Emerging Markets Initiative (2007-2020). He served as Senior Editor of the International Journal of Emerging Markets and sits on the editorial board of the International Journal of Business Excellence.

Vicent Briva Iglesiasمشاهده پروفایل

استادیار

• Machine Translation
• Natural Language Processing
• Human-Centered Artificial Intelligence
• +۵ مورد دیگر

Dr. Vicent Briva Iglesias is an Assistant Professor in Translation Studies at Dublin City University's School of Applied Languages and Intercultural Studies (SALIS). His roles include adjunct professorships at McGill University and the Universitat Oberta de Catalunya. He holds a PhD in human-centered machine translation and HCI from DCU, an M.Sc. in Translation Technology from Universitat Autònoma de Barcelona, and a BA in Translation/Interpreting from Universitat Jaume I. His research focuses on human-centered AI, machine translation (MT), natural language processing (NLP), and HCI, with applications in legal/medical translation, localization, and healthcare AI collaboration. He is a core member of ADAPT (Ireland's AI-driven digital content research center) and has secured funding from D-REAL and EU COST Action CA19102. Industry experience spans 8+ years in translation/localization, and he runs AWORDZ Language Engineering. His work emphasizes MT user experience (MTUX), ethical AI use, and interdisciplinary applications of language technologies in public services and healthcare. Key research themes include augmented machine translation (HCAMT), user-centric language technology design, and translation ethics. He supervises interdisciplinary PhD projects in HCAMT, MT for non-translators (e.g., doctors, migrants), public service technologies, and localization challenges. Collaborations include the Barcelona Supercomputing Center for AI healthcare research.