Find Academic Supervisors

Henna PaakkiView profile

Visiting Professor

• Computer Science
• Computational Psychology
• Conversation Analysis
• +3 more

Henna Paakki is a Visiting Professor and Doctoral Researcher at the Department of Computer Science, Aalto University. Her research focuses on computational analysis of online discourse, particularly in detecting manipulative behaviors such as trolling and disinformation in social media contexts. She holds a PhD in Computer Science (2024) and a Master's in Humanities from the University of Eastern Finland (2013). Paakki has contributed to projects like the 'Liquid Forms of AI-infused Disinformation' and 'Reconstructing Crisis Narratives,' aiming to enhance information resilience in Finnish media ecosystems. Her work spans crisis communication, migration discourse analysis, and conversational AI applications for cultural adaptation support. Key research interests include natural language processing, computational psychology, and social computing. She has presented at conferences such as ASONAM and CHI, and her findings have been featured in media discussions on disinformation challenges. Awards include travel grants for conferences focusing on disinformation and social computing. Paakki collaborates internationally, analyzing cross-cultural communication dynamics and developing tools to combat online manipulation. Her activities include organizing workshops, delivering academic talks, and participating in public outreach to bridge computational research with societal impact.

Joke DaemsView profile

Assistant Professor

• Human-Computer Interaction
• Machine Translation
• Empirical Translation Studies
• +6 more

Joke Daems serves as Assistant Professor in Human-Computer Interaction within Empirical Translation & Interpreting Studies at Ghent University. Affiliated with both the EQTIS research team (Empirical and Quantitative Translation and Interpreting Studies) and the LT3 Language and Translation Technology team, their academic career spans over a decade at Ghent University. Current roles include co-supervising major research projects including ArisToCAT (FWO), WiLMa (BOF), and DUAL-T (MSCA). Research focuses on the impact of translation technology across multiple domains: Machine translation integration in literary translation workflows Gender-inclusive translation strategies using adaptive technology Cognitive aspects of post-editing through eye-tracking and keystroke logging L2 writing processes enhanced by machine translation ( WiLMa project ) Bias detection in neural machine translation outputs Recent publication trends reveal a strategic shift toward gender-inclusive language applications (2022-2025), with 40% of recent work addressing gender bias in machine translation. Literary translation technology remains a consistent thread since 2016, now intersecting with ethical AI development concerns. Methodologically, Daems combines advanced process-tracing techniques with corpus linguistics approaches. Awarded the CIUTI PhD Award in 2017, Daems has also demonstrated significant editorial leadership: Guest Editor for Informatics Special Issue "Advances in Computer-Aided Translation Technology" (2019) Guest Editor for Journal of European Periodical Studies Special Issue "Digital Approaches Towards Serial Publications" (2019) Co-editor of New Empirical Perspectives on Translation and Interpreting (Routledge, 2020) Guest Editor for Filter Special Issue on literary translation technology (2021) Teaching responsibilities encompass Machine Translation & Post-Editing, Terminology and Translation Technology, and Empirical Translation Studies across multiple graduate programs. Daems actively supervises bachelor's and master's theses in human-computer interaction within translation studies while serving as external examiner for doctoral candidates.

Jeffrey BighamView profile

Associate Professor

• Accessibility and Assistive Technology
• Human-Centered AI
• AR / VR / XR
• +4 more

Jeffrey P. Bigham is an Associate Professor at the Human-Computer Interaction Institute (HCII) within the School of Computer Science at Carnegie Mellon University. His research focuses on accessibility, human-centered AI, and crowdsourcing. He leads projects like VizWiz, which provides visual assistance to blind users, and has contributed to tools such as Rescribe and Screen Recognition for enhancing accessibility in digital interfaces. His work emphasizes inclusive design, with a strong focus on empowering people with disabilities through technology. Notable projects include SpokeSense (wearable fitness tracking for wheelchair athletes) and Diffscriber (collaborative presentation tools for mixed-ability teams). He has received the NSF CAREER Award and multiple best paper nominations at conferences like CHI and ASSETS. Bigham advises numerous PhD students and collaborates with industry partners like Apple and Google. His lab explores cutting-edge topics such as AI alignment, generative models for UI design, and ethical AI practices.

Zhicheng LiuView profile

Assistant Professor

• Human Computer Interaction
• Machine Learning and Data Science
• Data Visualization
• +3 more

Zhicheng Liu is an Assistant Professor in the Department of Computer Science at the University of Maryland. His research focuses on human-computer interaction, machine learning, and data visualization, emphasizing democratizing visualization design through computational tools and human-centered systems. He received the NSF CAREER Award (2023) for his work on manipulable semantic components in data visualization. Education details are not explicitly stated in the provided texts, but his professional trajectory indicates advanced academic training in computer science. Research interests include interactive visualization authoring, collaborative systems, AI-enhanced design tools, and semantic analysis of visual content. His work bridges computer science with cognitive science, psychology, and graphic design to create impactful interdisciplinary solutions. Liu's recent publications (2023–2025) explore topics like semantic chart decomposition, AI-assisted documentation, and cross-linguistic collaboration tools. His NSF-funded project aims to develop modular visualization components for easier creation of interactive charts. Awards include the NSF CAREER Award, recognizing his potential to advance visualization research. He advises four PhD candidates focusing on visualization and HCI topics. His grants include a $600K NSF award supporting his CAREER project. Collaborative tools developed (e.g., DocDancer, VisAnatomy) demonstrate his focus on practical, user-centric systems. Liu’s lab focuses on responsive documents, AI-driven tutorial systems, and visualization corpus development. He emphasizes real-world impact through tools that simplify data analysis and communication for non-experts.

Gloria WashingtonView profile

Associate Professor

• Human-Centered AI
• Affective Computing
• Bias in AI Systems
• +4 more

Dr. Gloria Washington is an Associate Professor in the Department of Electrical Engineering and Computer Science at Howard University's College of Engineering and Architecture. She directs the Affective Biometrics Lab, researching human-centered AI, affective computing, and equity in technology with emphasis on mitigating algorithmic bias and amplifying marginalized voices. Her work investigates AI fairness in speech recognition, explainable hate speech detection, VR-based empathy tools for psychiatric training, and culturally responsive mentorship models. Notable projects include large-scale AAVE data collection for linguistic equity, analysis of microaggressions in clinical interactions, and retention strategies for underrepresented CS students. Educational initiatives focus on social good applications of affective computing, liberatory mentoring frameworks, and HBCU-PWI knowledge transfer for racial equity. Her research bridges technical innovation with social impact, addressing disparities in healthcare, education, and technology access.

Rashina HodaView profile

Professor

• Software Engineering
• Human and Socio-Technical Aspects
• Responsible AI
• +3 more

Rashina Hoda is a Professor of Software Engineering at Monash University, Australia, and currently serves as Associate Dean for Equity, Diversity, and Inclusion (ED&I). Her research focuses on the human and socio-technical dimensions of software engineering, artificial intelligence, and digital health. She holds a PhD in Computer Science from Victoria University of Wellington and a BSc (Honours) from Louisiana State University. As an Associate Dean ED&I, she introduced intersectional approaches to institutional policy. Her advocacy for women in STEM earned the 2024 Guiding Star Mentorship Award. She has been recognized as a 2021-22 Superstar of STEM by Science & Technology Australia. Her key research contributions include advancing socio-technical grounded theory methodologies, as detailed in her 2024 Springer book. She leads projects like the RAISE initiative (Responsible AI Software Engineering Capability) and the DHCRC Translational DH Research Fellowship. She has authored/co-authored over 116 publications spanning journals like IEEE Software and AI & Society, with a focus on ethics, agile methodologies, and human-centric AI. Hoda serves on editorial boards for IEEE Transactions on Software Engineering and IEEE Software, and has organized major conferences like ICSE and Agile. Her awards include the 2017 ICSE Distinguished Paper Award and the 2020 Distinguished Reviewer Award. Her work intersects with UN Sustainable Development Goals related to quality education and gender equality. She actively engages with industry, media, and public audiences through talks, media features, and workshops such as her 2019 TEDx talk on Agile responses to societal challenges.

Tove Stjern FrønesView profile

Researcher

• Reading Comprehension
• Literacy
• Critical Reading
• +4 more

Tove Stjern Frønes serves as a Researcher at the Department of Teacher Education and School Research within the Faculty of Educational Sciences at the University of Oslo. She functions as the Reading Expert for PISA Norway and the National Assessment of Reading Literacy since 2018, with prior advisory roles in these programs dating back to 2015. Her educational foundation includes a 2017 PhD dissertation from the University of Oslo titled Reading and navigating the web. A study of students' navigation strategies , which established her expertise in digital reading comprehension. Earlier professional milestones include serving on Norway's reading expert group (2007-2009) and conducting doctoral research on online reading strategies (2009-2015). Frønes' research centers on critical reading comprehension across physical and digital environments, with particular emphasis on students' navigation strategies in complex online texts, assessment methodologies for reading literacy, and equity issues in educational outcomes. Her work bridges cognitive psychology and educational practice through innovative methodologies including eye-tracking and logfile analysis to examine metacognitive processes during reading tasks. Her publication trajectory from 2020-2025 reveals evolving focus areas: initial concentration on PISA assessment frameworks has expanded into critical digital literacy, multilingual reading contexts, and Nordic educational equity models. Recent works demonstrate growing attention to practical classroom applications, particularly in developing assessment frameworks for critical reading and analyzing how socioeconomic factors influence reading comprehension trajectories across international contexts. No scientific awards were documented in the source materials. Her professional activities indicate no formal student advising roles but significant contributions to national testing frameworks and international large-scale assessments. Frønes operates within the Large-scale Educational Assessment (LEA) research group, where she contributes to Norway's participation in PISA and TIMSS surveys. Her current projects focus on strengthening reading culture in schools through evidence-based interventions that address both traditional literacy and emerging digital competencies required for critical engagement with online information.

• Cognitive Neuroscience
• Reading Research
• Orthographic Processing
• +2 more

María Fernández López is an Assistant Professor (Ajudant Doctor/A) at Universitat de València's Faculty of Psychology and Speech Therapy, affiliated with the Department of Basic Psychology and the ERI Reading Research institute. Her research focuses on cognitive neuroscience of reading, particularly orthographic processing and visual word recognition mechanisms. She completed her PhD in 2022 at Universitat de València with the thesis "How literacy shapes orthographic processing" , supervised by Dr. Manuel Perea Lara, Dr. Marta Vergara Martínez, and Dr. Ana Marcet. Research Interests: Dr. López investigates how the brain processes written language using experimental methods like masked priming, lexical decision tasks, and ERP measurements. Key themes include: Resilience of reading systems to distortions (rotated/replaced letters, accents, case-mixing) Neural mechanisms of word recognition and priming effects Impact of literacy on orthographic processing Visual similarity and positional coding in lexical access Her recent publications (2020-2025) predominantly explore: Sandwich priming dynamics and temporal processing windows ERP correlates of letter degradation and rotation tolerance Top-down feedback in visual word recognition Specialized processing of logotypes and city names She leads/co-leads the READit Cognitive Neuroscience and Reading research group, focusing on experimental psycholinguistics and neurocognitive approaches to reading.

Joachim SchäferView profile

Researcher

• German as a Second Language
• Writing Processes
• Multilingual Education
• +3 more

Joachim Schäfer , born in 1970, is a dedicated academic staff member at the Institute for German Language and Literature at the University of Education Ludwigsburg . Holding a Diploma in Education (2002) and a PhD in Education (2024), he specializes in German as a Second Language (DaZ), Writing Processes , and Multilingual Education . Co-developer of competency grids for writing assessment Coordinator of writing consultations since 2012 Deputy head of Language Didactics Center since 2015 Former head of German Department (2015-2016) Research Focus : His work investigates text production differences between monolingual and multilingual students, emphasizing text quality indicators , narrative development , and language acquisition in lower secondary education. He employs frameworks from Grießhaber (2017), Augst et al. (2007), and Grünke et al. (2017) to analyze writing competence and multilingual challenges. Scientific Awards : Hans Böckler Foundation Scholarship (1995-1998) Notable Contributions : He pioneered process-oriented writing assessment through the "Reading, evaluating and writing texts" examination task, supported development of peer-tutoring graphic organizing strategies for students with learning disabilities, and created multilingual writing diagnostic tools like the "gezinkte Bildpaarspiel" (2011).

Didar AKARView profile

Associate Professor

• Discourse Analysis
• Genre Analysis
• Language and Gender
• +4 more

Didar AKAR is an Associate Professor in the Department of Linguistics at Boğaziçi University, Istanbul, specializing in discourse analysis, language-gender dynamics, and narrative studies. Her current office is JF 302 with contact email akar@boun.edu.tr. She actively contributes to linguistic research and education within Turkey's leading academic institution. Education: PhD in Linguistics, University of Michigan, USA (1998) MA in Linguistics, Boğaziçi University, Turkey (1990) BA in Western Languages and Literatures, Boğaziçi University, Turkey (1987) Research Focus: AKAR's work centers on discourse strategies in trauma narratives, identity construction through language, and Turkish discourse markers. Her research reveals how linguistic choices shape social identities in contexts like domestic violence, migration, and digital communication. Recent projects examine hate speech detection through discourse analysis and the sociolinguistics of Turkish internet memes. Research Trends: Her 2020-2022 publications show increasing interdisciplinary collaboration, merging computational linguistics with discourse analysis for hate speech detection while maintaining core interests in Turkish pragmatic markers like 'hani'. Key themes include epistemic stance marking, narrative morality frameworks, and language attitudes toward standard Turkish. Advising and Grants: She has supervised 20+ master's theses since 2004 on topics ranging from gender representation in advertising to domestic violence narratives. Funded by Boğaziçi University Research Fund and the European Commission (2021-2024 project on digital technology for social cohesion), her work bridges theoretical linguistics and real-world social issues through rigorous discourse analysis methodologies.

Patricia T. SpanglerView profile

Assistant Professor

• PTSD
• Nightmares
• Sleep Disorders
• +3 more

Patricia T. Spangler is a Research Assistant Professor in the Department of Psychiatry at Uniformed Services University of the Health Sciences (USU) School of Medicine and a Clinical Research Psychologist at the Center for the Study of Traumatic Stress (CSTS). Her work focuses on PTSD interventions, nightmares, sleep disturbances, suicide prevention, and firearm safety for military personnel and veterans. Her educational background includes: Ph.D. in Counseling Psychology (2010), University of Maryland, College Park M.A. in Counseling Psychology (2007), University of Maryland, College Park B.A. in English Language and Literature, magna cum laude (2005), University of Maryland, College Park Dr. Spangler specializes in developing trauma-focused interventions, particularly Nightmare Deconstruction and Reprocessing (NDR), an exposure-based therapy for PTSD-related nightmares. Her research integrates physiological, genetic, and inflammatory biomarkers to understand treatment mechanisms. Current work examines NDR's comparison with non-exposure treatments like the NightWare wristband, emphasizing feasibility and biomarker predictors of response. Her publication record reveals strong trends in military mental health innovation, with emphasis on biomarker-integrated PTSD treatments, suicide prevention strategies, and pandemic-adapted research methodologies. Key themes include treatment augmentation for resistant symptoms, firearm safety communication, and trauma memory reconsolidation. Notable recognitions include: Jeremy Safran Poster Award (2020) NIH Summer Institute Fellowship (2018) APA Division 17 Outstanding Publication Award (2015) Milton Dean Havron Outstanding Graduate Award (2008) As principal investigator and co-investigator, she has secured over $4 million in federal funding, including a $940,000 Defense Health Agency grant for NDR/NightWare comparison and a $1,054,000 US Army grant for NDR pilot trials. Her projects consistently feature multi-site military collaborations, biomarker integration, and practical interventions like the "Let's Talk About Your Guns" firearm safety podcast. Dr. Spangler actively contributes to the CSTS Science Collaborative and Uniformed Services University's military health mission through clinical research and evidence-based program development.

Reagan MozerView profile

Assistant Professor

• Causal inference
• Design of experiments
• Text analysis
• +4 more

Dr. Reagan Mozer is an Assistant Professor in the Department of Mathematical Sciences at Bentley University. He holds a Ph.D. and Master of Arts from Harvard University, and a Bachelor of Science from the University of Southern California. His office is located in Morison Hall 337, and he can be contacted at 781.891.2267. Dr. Mozer's research focuses on: Causal inference methodologies Experimental design optimization Text-as-data analysis techniques Longitudinal data modeling Applied statistics in education and health services research He maintains professional memberships in statistical and computational associations. His recent publications demonstrate strong focus on machine learning applications in text analysis, Bayesian methods for longitudinal studies, and healthcare data science, with consistent attention to causal inference methodologies across diverse domains including education assessment and clinical psychology. No significant awards, student advisements, or laboratory affiliations were documented in the provided materials.

• Artificial Intelligence
• Information Systems
• Human-Centric AI
• +2 more

Dr. Achini Adikari is a Lecturer in Business Information Systems at La Trobe Business School, La Trobe University. She holds a PhD in AI and Analytics from La Trobe University (2022) and a BSc (Hons) in IT from the University of Moratuwa, Sri Lanka. Her research bridges artificial intelligence and information systems, focusing on human-centric AI applications including emotional modeling, natural language processing, and healthcare analytics. Her interdisciplinary work spans computational emotion modeling for patients and customers, NLP applications, and AI-driven solutions for healthcare, tourism, and social media. She has collaborated on over 20 industry projects with the Centre for Data Analytics and Cognition, addressing real-world challenges in healthcare, transport, and tourism. Recent publications demonstrate consistent outputs in AI applications for healthcare, including stroke rehabilitation profiling, speech emotion recognition, and cancer support systems. Her work frequently employs machine learning, unsupervised learning, and NLP techniques across medical and business domains. Honors include the Early Career Researcher Award (IARC 2024), ABC Early Career Grant (2023), and La Trobe Business School Internal Grant (2024). Her research contributes to Sustainable Development Goals 3 (Health), 9 (Industry Innovation), and 11 (Sustainable Cities). Dr. Adikari mentors students through industry projects and maintains collaborations with the Centre for Data Analytics and Cognition. Her work advances ethical AI deployment in socially impactful domains.

Toby Jia-Jun LiView profile

Assistant Professor

• Human-Computer Interaction (HCI)
• End-User Software Engineering
• Machine Learning (ML)
• +5 more

Toby Jia-Jun Li is an Assistant Professor in the Department of Computer Science and Engineering at the University of Notre Dame, leading the SaNDwich Lab and directing the Human-Centered Responsible AI Lab at the Lucy Family Institute for Data & Society. He holds a Ph.D. in Human-Computer Interaction from Carnegie Mellon University (2021) and a B.S. in Computer Science from the University of Minnesota (2015). His research focuses on empowering end-users through human-centered AI systems, particularly in areas like human-AI collaboration, end-user software engineering, and ethical AI integration into work environments. Education: - Ph.D., Human-Computer Interaction, Carnegie Mellon University, 2021 - B.S., Computer Science (Distinction), University of Minnesota, 2015 Research Interests : - Human-AI collaboration in work systems - Ethical AI design - Generative AI co-creation tools - Sociotechnical implications of automation - Privacy-aware interfaces Grants & Awards : - NSF grants for AI in gig work and privacy education - Google Research Scholar Award (2022) - Multiple best paper awards at CHI/UIST/CSCW Lab & Teams : - SaNDwich Lab (Social-AI-Not-Dumb-Computing) - Human-Centered Responsible AI Lab - Collaborations with industry (IBM, Microsoft, J.P. Morgan) and academia

Xinwei MaView profile

Associate Professor

• Econometrics
• Causal Inference
• Machine Learning
• +3 more

Xinwei Ma is an Associate Professor in the Department of Economics at the University of California San Diego . He holds a Ph.D. from the University of Michigan (2019). His research focuses on econometric methodologies, causal inference, and their applications in healthcare and policy analysis. Key areas include machine learning integration in causal analysis, Mendelian randomization, and adaptive experimental designs. Recent work explores HIV care disengagement prediction using language models, principal component analysis for mixed data types, and fair adaptive experimentation frameworks. His methodological contributions include boundary-corrected local polynomial estimators and tools for mediation analysis in genomics. He has developed R packages such as lpcde and lpdensity for statistical estimation. Xinwei's research bridges theoretical econometrics with practical policy evaluation, emphasizing methodological rigor while addressing real-world challenges in healthcare and social sciences. His work has implications for public health interventions, tax policy design, and equitable algorithmic systems.