Human-Machine Interaction in Writing Professors and Supervisors

Bennett Kleinbergمشاهده پروفایل

دانشیار

Tilburg UniversityNetherlands

Bennett Kleinberg is an Associate Professor in Behavioural Data Science at the Department of Methodology and Statistics at Tilburg University (The Netherlands) and the Department of Security and Crime Science at University College London (UK). His academic journey includes a PhD from the Department of Psychology at the University of Amsterdam and a previous position at the UCL Dawes Centre for Future Crime. Professor Kleinberg's research revolves around the interplay between psychological research and computational methods to study human behaviour. His work addresses two key questions: How can computational methods enhance our understanding of the human mind and behaviour? And how can psychological research methods inform our understanding of computational model behaviour? His substantive research interests include deception detection and legal psychology, human resilience, and machine behaviour. In the Computational Psychology and Computational Methods (CPCM) Lab, his team collects data through psychological experiments and applies techniques from natural language processing, adversarial machine learning, and statistical modeling to better understand human behavior. His recent publications (2023-2025) demonstrate a strong interdisciplinary focus, spanning psychology, computer science, criminology, and AI research. Key trends include the application of computational methods to deception detection, analysis of large language models, and examination of human-AI interactions. His work often bridges theoretical psychological concepts with practical computational approaches, resulting in publications in high-impact journals across multiple disciplines. Scientific publications that use promotional language receive more citations Verbal deception detection enhanced through adversarial attacks Computational text analysis for identifying embedded lies Analysis of cognitive phenomena in large language models Applications of NLP to legal and security contexts Professor Kleinberg actively supervises students through limited positions to ensure close mentorship quality. His teaching responsibilities include the joint BSc in Data Science and the innovative MSc programme 'AI for Psychological Research.' The Computational Psychology and Computational Methods Lab offers structured pathways for PhD students, thesis projects, and research internships (minimum 6 months), with all projects required to align with the lab's core focus on computational methods to study human behavior and psychology.

پروفایل رسمی دانشگاه

Line Henriksenمشاهده پروفایل

مدرس

Örebro UniversitySweden

Line Henriksen is a Lecturer in Literature and Creative Writing at Malmö University's Faculty of Culture and Society, Department of Art, Culture and Communication. She holds a PhD in Gender Research from Linköping University and is affiliated with the MEDEA Lab and The Monster Lab research groups. Her research explores: Monster theory and cultural representations of horror Hauntology and temporal studies Creative writing as methodological practice Digital ethics and bot communication Feminist posthumanism and speculative fiction Through artistic research approaches, she examines intersections of gender, technology, and cultural narratives. Recent publications demonstrate interdisciplinary engagement across gender studies, digital humanities, and literary theory, with consistent focus on ethical dimensions of human/non-human relationships. Her 2024 co-authored book examines feminist reconceptualizations of alien encounters. At MEDEA Lab, she contributes to multidisciplinary projects addressing societal challenges through experimental media approaches. Her work with The Monster Lab investigates cultural manifestations of monstrosity in contemporary media landscapes.

پروفایل رسمی دانشگاه

Tiong-Thye Gohمشاهده پروفایل

مدرس ارشد

Victoria University of WellingtonNew Zealand

Dr. Tiong-Thye Goh serves as a Senior Lecturer at the School of Information Management, Victoria University of Wellington, with significant scholarly impact reflected in over 2,497+ Google Scholar citations, an h-index of 25, and an i10-index of 35. His research focuses on the utilization and impact of advanced technology across diverse settings, particularly in educational contexts and healthcare systems. Dr. Goh's academic service includes membership on the Advisory Board of the Journal of Educational Technology & Society and editorial roles for multiple international journals including the International Journal of Mobile and Blended Learning, International Journal of Mobile Human Interaction, and Journal of Information Technology Education. His expertise spans educational technology, artificial intelligence, learning analytics, and health informatics. His research interests center on AI applications for better living, including combating AI-driven threats, enhancing health and well-being through technology, improving AI-human interaction, and developing personalized learning systems. Recent publications demonstrate strong methodological rigor with applications in educational chatbots, knowledge tracing systems, and clinical decision support architectures. Dr. Goh's work shows a clear trajectory toward increasingly sophisticated applications of AI in real-world contexts, with recent publications emphasizing metacognitive aspects of learning, emotion computing, and system integration challenges in healthcare settings. His research bridges theoretical frameworks with practical implementations, particularly in educational technology and clinical decision support. Over 2,497+ citations on Google Scholar h-index of 25 i10-index of 35 Advisory Board member, Journal of Educational Technology & Society Editorial board member for multiple international journals Though Dr. Goh states he is currently not accepting new Master's and PhD theses, he maintains active doctoral supervision in AI applications for fraud detection. His teaching portfolio spans foundational courses in databases and data science to advanced topics in information systems theory, reflecting his commitment to developing both technical and conceptual understanding among students.

پروفایل رسمی دانشگاه

Andy D. Dighمشاهده پروفایل

استاد

Mercer UniversityUnited States

Dr. Andy D. Digh serves as Professor of Computer Science and Co-Chair of the Computer Science Department at Mercer University's College of Liberal Arts and Sciences. He has taught and mentored students since 1998 while coaching the Binary Bears programming team and previously directing the first-year integrative seminar (INT 101) from 2015-2019. His educational credentials include: Ph.D. in Education from University of Tennessee, Knoxville M.S. in Computer Science from University of Tennessee, Knoxville B.A. in Mathematics (with Honors) from University of North Carolina at Asheville Dr. Digh's research bridges theoretical and applied computer science with educational innovation. His primary focus spans artificial intelligence, algorithms, and human-computer interaction, with specialized expertise in genetic algorithms and theoretical mathematics. He actively develops instructional technology frameworks to transform computer science pedagogy, emphasizing authentic learning experiences that connect abstract concepts to real-world applications through writing, speech, and competitive programming. His publication portfolio reveals a consistent trajectory toward enhancing computer science education through AI integration. Recent works examine machine writing's impact on learning, CNN optimization techniques, and evidence-based teaching strategies for AI courses. A recurring theme involves developing multimodal communication skills within technical curricula while maintaining rigorous algorithmic foundations. His scientific recognition includes: Joe and Jean Hendricks Award for Excellence in Teaching (2019) As an academic advisor and coach, Dr. Digh has shaped competitive programming teams and mentored students through the Binary Bears initiative. His leadership extended to designing the INT 101 seminar framework, demonstrating commitment to holistic undergraduate development beyond technical instruction. He maintains active involvement with the Binary Bears programming competition team, providing strategic guidance for national contests while fostering collaborative problem-solving skills.

پروفایل رسمی دانشگاه

I. Aulikaمشاهده پروفایل

پژوهشگر

Daugavpils UniversityLatvia

Dr. I. Aulika is a Senior Researcher at the Institute of Solid State Physics, University of Latvia, where she leads research in the Thin Films Laboratory. Her work focuses on optical tactile sensing (particularly the OptoSkin technology), OLED materials, and smart window materials. Dr. Aulika has over 64 publications with more than 8,000 reads and 346 citations, demonstrating significant impact in her field. She actively participates in major European research projects including Sestosenso and SWEB, and serves as a representative for ISSP UL's industry collaboration platform Materize across several European countries. Dr. Aulika's research interests span multiple cutting-edge areas in materials science and optical engineering. She specializes in spectroscopic ellipsometry for material characterization, optical modeling , and the development of innovative materials including rare-earth metal oxy-hydrides (Y, Gd, Dy and Er), YO, Y2O3, Ga2O3, and ZnO2. Her work on Direct ToF tactile sensing aims to revolutionize touch perception in robotics, while her research on OLED materials contributes to advancements in display technology. Additionally, she investigates photochromic materials and transparent conducting oxides for smart window applications, demonstrating a versatile research portfolio that bridges fundamental science with practical applications. Dr. Aulika's publication record shows a consistent focus on thin film characterization and optical properties, with recent work increasingly centered on optical tactile sensors and OLED materials. Her most recent articles (2024-2025) demonstrate expertise in spectroscopic ellipsometry applied to organic thin films, phase transitions in OLED stacks, and material effects in direct Time-of-Flight sensing systems. She has made significant contributions to understanding yttrium-based photochromic materials and transparent conducting coatings, with applications ranging from robotics to energy-efficient windows. Dr. Aulika has received notable recognition for her work, including: UNESCO L'ORÉAL Latvian National Fellowship for Women in Science (2008) Multiple European Social Funds Scholarships (2006-2008) As a Project Manager at the Institute of Solid State Physics, Dr. Aulika is involved in new R&D idea development, project writing and evaluation, and establishing industrial and academic partnerships. She serves as a local contact point for proposal writing and execution, and represents ISSP UL's industry collaboration platform Materize in Italy, France, Spain, and Switzerland. Her leadership extends to developing lecture materials for MSc physics students on applications of piezoelectric materials, demonstrating her commitment to education alongside research. Dr. Aulika leads the Thin Films Laboratory at the Institute of Solid State Physics, University of Latvia, where her team focuses on point of darkness modeling for biomedical sensor applications, spectroscopic ellipsometry, optical modeling, and thin film technologies. The laboratory's work on innovative materials, particularly rare-earth metal oxy-hydrides, supports cutting-edge research in optical tactile sensing, OLEDs, and smart windows. Through projects like Sestosenso and SWEB, her lab bridges fundamental research with practical applications in robotics, display technology, and energy-efficient building materials.

پروفایل رسمی دانشگاه

Miyuki Sasakiمشاهده پروفایل

استاد

Waseda UniversityJapan

Miyuki Sasaki is a Professor at Nagoya City University's Faculty of Education and Integrated Arts and Sciences, School of Education, specializing in second language writing, language assessment, and the effects of study abroad experiences. With a PhD in Applied Linguistics from UCLA and extensive research experience, she has made significant contributions to understanding L2 writing development and assessment. Educational Background: PhD in Applied Linguistics, University of California, Los Angeles MA in English Education, Hiroshima University BA in English Education, Hiroshima University Additional studies at Georgetown University in Teaching English as a Second Language Professor Sasaki's research focuses on the longitudinal development of second-language writing ability, the effects of raters' values and belief systems on composition evaluations, and sociocultural factors affecting L2 writers' motivation. Her work takes an ecological-historical approach to understanding multilingual writing development, examining how learners' experiences across different languages and contexts interact to shape their writing abilities. Recent research has increasingly incorporated technology, exploring AI tools like ChatGPT in writing assessment and the impact of machine translation on writing instruction. Her publication trends show a consistent focus on longitudinal studies of writing development, with increasing attention to technology-mediated language learning and assessment. The research demonstrates a progression from examining individual writing processes to investigating broader sociocultural and technological influences on L2 writing. Recent work has particularly emphasized the ecological context of writing development and the intersection of writing with other language skills. Scientific Awards: Special Grant for the Promotion of Research (2019) Nagoya City University Highest Ranked Paper Award (2018) Abe Fellowship for international research (2016) UCLA Nida Award for best qualifying paper (1990) Rotary International Foundation scholarship (1984) Ministry of Education scholarship for University of Michigan (1980) Professor Sasaki has served on numerous editorial boards including the Journal of Second Language Writing, Language Testing, and TESOL Quarterly. She has coordinated AAAL conference strands and served on TOEFL and TOEIC technical panels. Her research projects have been consistently funded by Japanese academic institutions, with current work examining third-language study abroad effects and multilingual writing development. She teaches courses in second language writing, applied linguistics, and English communication, mentoring the next generation of language education researchers.

پروفایل رسمی دانشگاه

Zhou Yangمشاهده پروفایل

استادیار

Max Planck Institute for Security and PrivacyGermany

Zhou Yang is an Assistant Professor at the University of Alberta and Fellow at the Alberta Machine Intelligence Institute (Amii), with research focusing on the intersection of software engineering and artificial intelligence. His academic journey includes a Ph.D. from Singapore Management University, an M.Sc. in Software System Engineering from University College London, and undergraduate studies at Yangzhou University. His research interests span Software Engineering, Artificial Intelligence, AI for Software Engineering (AI4SE), Software Engineering for AI (SE4AI), Large Language Models, and Cybersecurity. Yang's work explores how human and AI collaboration can improve code writing, how AI impacts open-source communities, and how developers build software in emerging environments like VR/AR. His recent publications demonstrate strong trends in code language models, with significant contributions to ASE, ICSE, ISSTA, and top journals like TOSEM and TSE. His research addresses critical challenges including token efficiency in code generation, user perception of AI coding assistants, privacy preservation in code models, and fairness in AI systems. 2024 IEEE Computer Society Best Paper Award (1 out of 183 submissions) ACM Distinguished Paper Award from ISSTA 2024 Distinguished Reviewer Award from Internetware 2024 SMU Research Staff Excellence Award (1 of 4 university-wide) SMU Presidential Fellowship Award SMU Dean's List Award 1st Place in ACM Student Research Competition at ICSE 2024 Yang actively mentors graduate students with regular one-on-one meetings, constructive feedback, and support for top-venue publications. He provides full funding through teaching assistantships and research grants, including travel support for conferences. His lab focuses on responsible research conduct and societal implications of AI work. Though early-career, he actively builds professional networks for students through collaborations and supports diverse career paths in academia and industry. He leads research in the Alberta Machine Intelligence Institute, focusing on practical applications where software engineering principles enhance AI systems and where AI techniques solve real-world software engineering challenges.

پروفایل رسمی دانشگاه

Lubomir Ivanovمشاهده پروفایل

استاد

Iona UniversityUnited States

Lubomir Ivanov is a Professor of Computer Science and current Chair of the Computer Science Department at Iona University, where he also serves as Game Development Coordinator and primary contact for all undergraduate programs. He joined Iona in 1999 after completing his academic training at Stevens Institute of Technology and has established himself as a versatile educator teaching courses ranging from computer architecture to virtual reality development. Education: Ph.D. in Computer Science, Stevens Institute of Technology M.S. in Computer Science, Stevens Institute of Technology B.S. in Computer Engineering, Stevens Institute of Technology Dr. Ivanov's research demonstrates exceptional interdisciplinary breadth, with dual pillars in Natural Language Processing and Applied Virtual Reality . His NLP work pioneers authorship attribution techniques using linguistic features from phonetic patterns (alliteration, assonance) to semantic dimensions (abstractness/concreteness), particularly for historical texts like Thomas Paine's writings. Simultaneously, his VR research creates impactful educational tools, including anti-bullying simulators with facial-expression recognition and mental health applications for non-suicidal self-injury assistance, reflecting strong collaborations with psychology departments. Analysis of his 15 most recent publications (2016-2024) reveals an evolving trajectory: early work focused on phonetic features for authorship analysis, progressively incorporating semantic and sentiment features, while his VR research matured from basic environments to sophisticated systems integrating real-time facial recognition and user experience optimization. Both strands consistently address real-world problems through computational methods. Scientific Awards: None mentioned in source material. Dr. Ivanov actively mentors students on research projects including the 'Bully' virtual environment and NSSI assistance software, securing collaborative grants with psychology departments. His leadership extends to university governance through the Faculty Senate and previous department chairmanship (2006-2009), alongside curriculum development for game development courses targeting non-CS majors. He directs a cross-disciplinary research ecosystem centered on the Game Development concentration, integrating computer science with education and psychology to create socially impactful technologies through ongoing VR and NLP innovation.

پروفایل رسمی دانشگاه

Shane McIntoshمشاهده پروفایل

دانشیار

Max Planck Institute for Security and PrivacyGermany

Shane McIntosh is an Associate Professor at the David R. Cheriton School of Computer Science, University of Waterloo, where he leads the Software Repository Excavation and Build Engineering Labs (Software REBELs). His academic career focuses on empirical studies of software development processes with particular emphasis on release engineering and software quality. Dr. McIntosh's research centers on mining historical data generated during software development to derive practical insights for building more reliable systems. His work spans release engineering (assembling, verifying, and delivering software releases) and software quality (developing guidelines for reliable software). This research manifests in studies of continuous integration systems, build outcome prediction, defect prediction models, and code review practices. His publication record reveals a consistent focus on empirical software engineering with recent papers examining build system reliability, continuous integration practices, and defect prediction. The research demonstrates strong methodological rigor through replication studies, longitudinal analyses, and large-scale data mining of software repositories. His work bridges theoretical insights with practical applications for software development teams. Dr. McIntosh actively contributes to the software engineering community through substantial service roles including Proceedings Co-chair for ICSE 2022, General Chair for PROMISE 2021-2022, and committee positions across major conferences like ASE, ESEC/FSE, and MSR. His teaching portfolio includes foundational courses such as Introduction to Software Engineering, Software Analytics, and Software Delivery. He directs the Software REBELs lab, which provides a collaborative environment for investigating software development data. The lab's work focuses on extracting meaningful patterns from version control systems, issue trackers, and continuous integration pipelines to improve software engineering practices.

پروفایل رسمی دانشگاه

Jose Badillo Carlosمشاهده پروفایل

استادیار

Queens University of CharlotteUnited States

Dr. Jose Badillo Carlos serves as an Assistant Professor in the Department of World Languages within the College of Arts & Sciences at Queens University of Charlotte. His academic journey includes a Ph.D. in Hispanic and Cultural Studies from Michigan State University, complemented by advanced degrees in Spanish Language and Literature from Northern Illinois University. Ph.D., Hispanic and Cultural Studies, Michigan State University M.S., Spanish Language and Literature, Northern Illinois University B.A., Spanish Language and Literature, Northern Illinois University Dr. Badillo Carlos specializes in the analysis of Mexican cultural productions examining state violence and corruption through contemporary literature, music, and film. His research particularly focuses on narcocorridos (drug ballads), cinematic satires like Luis Estrada's works, and representations of Chicanx/Latinx communities in media and higher education. He actively investigates how violence manifests in cultural narratives through mediums ranging from Narcos to Breaking Bad , while connecting these analyses to broader societal structures. His recent work has expanded into digital humanities, exploring AI integration in language pedagogy and technological tools for translation learning. His scholarly output demonstrates consistent engagement with Mexican political representation across multiple platforms—peer-reviewed publications in MIFLC Review and Aula lírica , book reviews, and frequent conference presentations at venues like SAMLA and MIFLC. These works collectively trace evolving methodologies from traditional literary analysis toward digital scholarship. Summer Support Fellowship (Michigan State University, $4,500.00, 2021) Dissertation Completion Fellowship (Michigan State University, $8,000.00, 2019) Dr. Johannes Sachse Memorial Award (Michigan State University, $1,128.00, 2018) Outstanding Graduate Student Award (Northern Illinois University, 2014) As an active academic citizen, Dr. Badillo Carlos serves as Faculty Advisor for the Latin American Student Organization (LASO), sits on Queens' Student Experience Committee, and contributes to editorial boards including Revista Letral and Label Me Latina/o Journal . He produces the student-centered podcast Descubriendo Momentos , which highlights student narratives both on and off campus. His community engagement extends to keynote speeches for organizations like ORGULLO at JELD-WEN and Somos Uno for Tepper Sports & Entertainment, where he addresses Latino representation in Hollywood and immigration policy impacts.

پروفایل رسمی دانشگاه

Dora Demszkyمشاهده پروفایل

استادیار

Stanford UniversityUnited States

Dora Demszky is an Assistant Professor in Education Data Science at Stanford University's Graduate School of Education, with a courtesy appointment in Computer Science. She leads the EduNLP Lab, where she develops natural language processing tools to support equitable, student-centered instruction through analyzing educational discourse including student-teacher interactions, student group work, and textbooks. PhD in Linguistics from Stanford University (advised by Dan Jurafsky) BA summa cum laude in Linguistics with a minor in Computer Science from Princeton University Co-founder of Tarisznya Alapítvány (Knapsack Foundation), a nonprofit supporting underprivileged children in Hungary Dr. Demszky's research combines natural language processing, linguistics, and practitioner input to develop interpretable and scalable education measures. Her work focuses on creating tools that analyze classroom discourse to identify features of high-quality instruction and provide actionable feedback to educators. She has particular expertise in developing AI-powered systems that help teachers improve questioning quality, analyze textbook representation, measure dialect features, and scaffold curricula to meet diverse student needs. Her approach emphasizes the importance of human connections in teaching and learning, using technology to enhance rather than replace these critical interactions. Analysis of Dr. Demszky's recent publications reveals a strong trend toward practical applications of NLP in real educational settings, with increasing emphasis on randomized controlled trials to validate effectiveness. Her work spans multiple educational contexts from K-12 classrooms to higher education, with growing attention to equity considerations in AI-powered educational tools. Recent publications show expansion into mathematical education, speaker diarization for noisy classrooms, and open-source tools for the broader research community. MathemaTikZ dataset received the inaugural best dataset prize at Learning at Scale NCTE classroom transcript dataset received the best IEDMS Publicly Available Educational Dataset Prize Selected as a Leading Woman in AI at the ASU GSV AIR Show Dr. Demszky has secured significant research funding including grants from the Gates Foundation, NSF RAPID program, and Stanford HAI. Her work with teachers extends beyond research through initiatives like the Practitioner Voices Summit, which brought together 60 teachers from 22 states to inform AI research related to classrooms. She actively collaborates with educators to ensure her tools address real classroom needs while maintaining a focus on socially responsible edtech development. At Stanford, Dr. Demszky leads the EduNLP Lab, which operates at the intersection of education, computer science, and linguistics. The lab follows a three-pronged approach: gathering evidence through data science using NLP models, developing algorithms through co-design with domain experts, and piloting solutions that practitioners can use in real educational settings. Current projects include M-Powering Teachers, which provides automated feedback to educators, and tools for adapting mathematics curricula to support students with diverse learning needs.

پروفایل رسمی دانشگاه

Fiona Delahaieمشاهده پروفایل

پژوهشگر

University of Toulouse-Jean JaurèsFrance

Fiona Delahaie is a Teacher-researcher in Human Sciences & Arts at the Purpan School of Engineering (INP - PURPAN), part of the Institut National Polytechnique de Toulouse. She is affiliated with the Interdisciplinary Laboratory for Solidarity, Societies, Territories (LISST) and Human Spaces and Cultural Interactions (EHIC). Her doctoral research completed at the University of Limoges in 2022 examined how contemporary artistic practices engage with living systems through 'co-enunciation.' Dr. Delahaie's work bridges humanities, artistic practice, and ecological understanding, focusing on how creative processes can foster meaningful relationships between humans and the environment. Dr. Delahaie's research centers on ecosemiotics - the study of signs in ecological contexts - and explores how artistic practices create connections between humans and living systems. She investigates ephemeral and participatory art forms that emphasize sensory experience, territory, and the interconnectedness of all living beings. Her work often references Nicole Pignier's approach to ecosemiotics and examines artists like Thierry Boutonnier, Liliana Motta, Boris Nordmann, and Liliana Sánchez who create community-engaged works. Analysis of her publications reveals consistent exploration of how artistic practices can transform our relationship with the Earth. Her work spans contemporary art, urban spaces, digital technology, and ecological perspectives, demonstrating how creative practices can challenge conventional understandings of innovation, territory, and human-environment relationships. She particularly examines how artistic 'gestures of know-how and sharing' can help 'spare the territory' and 'anchor multiple esthesias' in place. Dr. Delahaie is actively involved with LISST, contributing to interdisciplinary projects that examine the social and cultural dimensions of art and ecology. Her research demonstrates how artistic practices can serve as vital mediums for ecological understanding and sustainable relationships with the Earth, emphasizing sensory experience and embodied knowledge over purely technical approaches to environmental issues.

پروفایل رسمی دانشگاه