Find Academic Supervisors

Marissa WechslerView profile

Assistant Professor

• Biomaterials
• Tissue Engineering
• Stem Cell Engineering
• +5 more

Dr. Marissa Wechsler, a first-generation Hispanic biomedical engineer, returned to her alma mater The University of Texas at San Antonio (UTSA) in 2021 as an Assistant Professor in the Margie and Bill Klesse College of Engineering and Integrated Design. As UTSA's first biomedical engineering undergraduate student (class of 2015), she now leads a 12-member research team in her biomaterials and cell engineering lab while teaching advanced courses like BME 4443: Stem Cell Engineering. Academic Journey: UTSA BME program pioneer (2015) → NSF Graduate Research Fellowship → Ph.D. from UT Austin Leadership Roles: Founding faculty member of UTSA Sigma Xi chapter (2023), SWE faculty advisor, ESTEEMED mentor Research Focus: Specializes in biomaterials engineering with emphasis on: Stimuli-responsive hydrogels for drug delivery and tissue regeneration Stem cell engineering through controlled microenvironments Biosensing platforms using nanoparticle-hydrogel hybrids Regenerative medicine applications for vascular diseases Recent publications demonstrate expertise in RNA-based vaccine delivery systems , nanoparticle engineering , and mitochondrial dysfunction analysis in peripheral artery disease. Her work combines material science innovation with clinical translation potential. Award Highlights: 2023: Sigma Xi Grant-in-Aid of Research 2021: National Science Foundation Graduate Research Fellowship (during studies) Mentorship Impact: As a former participant in federal research programs (RISE, MARC), she now mentors through: Leading 12-member research team (undergraduate to postdoctoral) Sigma Xi leadership (President-elect) Faculty advisor for Society of Women Engineers ESTEEMED program mentor

• Pragmatics
• Second Language Acquisition
• Speech Acts
• +3 more

Naoko Taguchi is a Professor in the Department of English at Northern Arizona University with over 100 scholarly publications spanning two decades. Her academic profile demonstrates sustained research productivity, including 102 documented works with significant citation impact (h-index 35, 3617 citations). She maintains active research leadership through editorial roles and contributions to major reference works in applied linguistics. Her research program centers on pragmatic competence development in second language acquisition, specializing in speech acts (particularly request-making), appropriateness judgments, and proficiency impacts. Key investigation areas include how learners acquire culturally appropriate language use across contexts, with growing emphasis on technological applications. Her fingerprint analysis reveals dominant expertise in Speech Acts (100%), Pragmatic Competence (61%), Proficiency (61%), and Request strategies (40%), indicating consistent theoretical focus over time. Recent publications (2024-2025) show strategic expansion into technology-mediated pragmatics, examining digital games for request-learning feedback systems and social VR environments for Spanish conversation management. This technological pivot complements ongoing work on prosody in Chinese pragmatics, demonstrating methodology evolution while maintaining core theoretical commitments across multiple target languages. No scientific awards were documented in the source material. Information regarding student advising, grant funding, or research supervision was not provided in the available text. No laboratory facilities, research teams, or collaborative infrastructure were described in the source documentation.

Aaron BraverView profile

Associate Professor

• Phonetics
• Phonology
• Laboratory Phonology
• +3 more

Aaron Braver is an Associate Professor and Director of Linguistics at the Department of English, Texas Tech University. He investigates phonetics, phonology, and their interface through both theoretical and experimental approaches, with a focus on South African Bantu languages like Xhosa. Ph.D. in Linguistics, Rutgers University (2013) B.A. in Linguistics and Linguistic Anthropology, Brandeis University His research spans three interconnected projects: Bantu (morph)phonology: Examining phonotactic generalizations in noun class morphology, uncommon sounds (e.g., Xhosa’s velar ejective affricate), and incomplete neutralization phenomena. Incomplete Neutralization: Modeling phonetic-phonological interactions in cases where contrasts persist despite phonological identity. Gesture in Language Learning: Interdisciplinary studies on whether gesturing avatars enhance computer-based L2 pronunciation learning, collaborating with psychology and computer science researchers. Recent publications highlight trends in phonetic constraint modeling (2023, 2019), Bantu morphophonology (2020, 2016), and gesture-based pedagogy (2020, 2019). He leads the Phonetics and Phonology Linguistics Lab (PPLL) at TTU.

Anke TalligView profile

Researcher

• Human-Robot Interaction
• Human-Computer Interaction
• Robotics
• +6 more

Anke Tallig is a Researcher at Chemnitz University of Technology's Faculty of Computer Science, where she has maintained continuous affiliation since 2012. Her work bridges robotics, human-computer interaction, and virtual environments with a focus on developing systems for social interaction between humans and robots through non-verbal communication and sensor technologies. Her academic foundation includes a Bachelor of Engineering in Media, Communication and Automation Systems (2007-2010) and a Master of Engineering in Computer Science and Communication Systems (2010-2012), both from Hochschule Merseburg. She received the Best Master Thesis Award in 2012 for her work on CAVE projection environments and Cyberglove interfaces. She completed her doctorate within the DFG-funded Research Training Group 'CrossWorlds' (2012-2018), supervised by Prof. Wolfram Hardt and Prof. Maximilian Eibl, with research on robotic mediators for human-robot contact. Tallig's research centers on creating seamless connections between virtual and real social worlds through socially interactive robots. Her expertise spans perception systems, augmented/mixed reality interfaces, and sensor-driven human-machine control mechanisms. She investigates how robots can interpret non-verbal cues to facilitate natural interaction, with applications in edutainment, empathic systems, and gender-specific user experiences. Her interdisciplinary approach combines computer engineering with social science perspectives to overcome constraints in media-mediated communication. Her publication record from 2012-2014 reveals a cohesive research trajectory advancing from foundational mediator systems to sophisticated mixed reality applications. The work demonstrates consistent innovation in social robotics, with increasing complexity in emotional recognition and public interaction scenarios, while maintaining focus on practical implementations through the CrossWorlds framework. Her recognition includes: Award for Best Master Thesis 2012 from Freundeskreis der Fachhochschule Merseburg e.V. Tallig was integral to the DFG Research Training Group 'CrossWorlds' (2012-2018), contributing to interdisciplinary networks examining communication, emotions, sensomotorics, and learning across virtual-real boundaries. While not listed as a primary advisor for students in available records, her collaborative work involved multiple projects including SOLVE (gender-specific problem solving), HERMES, and CAVE environment development. Her research was supported through the CrossWorlds doctoral program with funding from the German Research Foundation. Her primary research environment operates within the CrossWorlds ecosystem at TU Chemnitz, where she collaborates with computer scientists and social scientists to develop next-generation interaction paradigms. Current work appears focused on extending mediator systems for broader social applications while refining perception algorithms for more nuanced human-robot communication.

Feng XiaoView profile

Associate Professor

• Second Language Acquisition
• Pragmatics
• AI-Supported Language Learning
• +12 more

Feng Xiao is an Associate Professor in the Department of Asian Languages and Literatures at Pomona College, where he also holds the title of Oldenborg Faculty Fellow. He contributes significantly to research and teaching in second language acquisition, particularly in Chinese as a second language, and integrates AI into language pedagogy. Educational Background: Ph.D., Carnegie Mellon University B.A. and M.Ed., Beijing Language and Culture University Feng Xiao's research centers on pragmatics in second language learning, examining how learners develop contextual language use during study abroad and how AI can support personalized language instruction. His work bridges applied linguistics, educational technology, and cross-cultural communication. He applies quantitative methods and data mining to analyze language development and assessment. His recent projects explore the role of AI beyond ChatGPT, gender-inclusive curricula, and the impact of the pandemic on study abroad. His recent publications reflect a strong trend toward integrating artificial intelligence into language education, expanding the understanding of pragmatic development in Chinese, and addressing equity and innovation in teaching. These works span journals in psycholinguistics, language assessment, and digital pedagogy. Scientific Awards and Grants: Hirsch Research Initiation Grant (2021–2023) EnviroLab Asia Curricular Innovation Award (Henry Luce Foundation, 2020) Andrew W. Mellon Grant for Digital Humanities (2016–2019) Hahn Fund for Innovative Teaching with Technology (awarded multiple times) Language Learning Dissertation Grant (2015) Modern Languages Department Dissertation Completion Scholarship (Carnegie Mellon, 2014–2015) Barbara F. Freed Award for Study Abroad Research (2014–2015) Feng Xiao actively mentors students and collaborates on digital tool development for language learning. He has led curriculum innovation projects and secured external funding for research and teaching. His work emphasizes educational equity, technological integration, and inclusive pedagogy. He teaches a range of courses from intermediate to advanced Chinese, as well as specialized topics such as Chinese in society, digital news, and culture. He is involved in interdisciplinary initiatives connecting language learning with digital humanities and environmental studies through grants like the EnviroLab Asia award. His lab-like collaborations focus on AI-driven pedagogical tools and data analysis in language acquisition.

• Activity Analysis
• Psychomotor Therapy
• Educational Sciences
• +5 more

Marion Paggetti is a Researcher-lecturer at Institut Agro Dijon, affiliated with the Vocational training and apprenticeships (FoAP) school and the Digital Innovation Laboratory for Businesses and Learning to Support Territorial Competitiveness (LINEACT). She is actively engaged in research on activity analysis, psychomotor therapy, and professional learning, with a focus on body-dominant inquiry and learning processes in human interaction professions. Her educational background includes: PhD in Educational and training sciences, CIRNEF (EA 7454), University of Caen-Normandie, 2020. Dissertation: "The psychomotor therapists' 'body-dominant inquiry'. Adjustment activity and learning the work" Psychomotor therapist qualification, Sorbonne-Université, 2015 Dr. Paggetti's research focuses on the analysis of adaptive, "body-dominant" activity in professions addressed to others, particularly in psychomotor therapy. She examines how professionals adjust their activities through bodily engagement with clients/patients. Her work also explores pedagogical and learning activities mediated by new technologies in higher education, especially in engineering schools. She investigates how professional experience is constructed through activity coupling between subjects, with particular attention to the micro-adjustments that occur in human interaction professions. Her recent publications demonstrate a consistent focus on activity analysis methodology, particularly the "micrological" approach to studying professional work. She frequently examines how professionals in human interaction fields (like psychomotor therapists, shepherds, and other care professionals) develop expertise through bodily engagement with their work. Her research bridges educational sciences, work analysis, and professional didactics, with increasing attention to digital technologies in professional learning contexts. Dr. Paggetti is actively involved in scientific communities, serving as a member of the Scientific Council of SNUP-Respir Formation. While specific awards aren't documented in the provided materials, her extensive publication record in reputable journals demonstrates recognition within her academic community. She currently supervises PhD candidate A. HELL, whose research examines "Learning and pedagogical uses of AI in the context of active pedagogy in engineering schools" (defense expected in 2027). Her research is supported through programs like JENII (2021-2025) and CAIRO Confluences, which focus on integrating digital technologies into professional education and active learning pedagogies. As part of LINEACT (Digital Innovation Laboratory for Businesses and Learning to Support Territorial Competitiveness), Dr. Paggetti contributes to research on how digital innovation can support professional learning and business competitiveness. Her work within this laboratory connects theoretical activity analysis with practical applications for professional development in various sectors.

• Neuroimaging
• Substance Use Disorders
• Neuroimmunology
• +7 more

Kelly Cosgrove is the Charles B.G. Murphy Professor of Psychiatry and of Neuroscience and of Radiology and Biomedical Imaging at Yale School of Medicine. She serves as Co-Director of the T32 Translational Alcohol Research Program and leads the Cosgrove Lab, which focuses on examining the neurochemical and molecular basis of addiction and psychiatric disorders using PET brain imaging technology. Dr. Cosgrove's educational background includes a PhD in Psychology from the University of Minnesota (2002) and a Psychology Internship at the Medical University of South Carolina (2003). She began her career as a clinical psychologist working with individuals managing alcohol and drug use disorders before transitioning to research to inform better treatments for substance use disorders. Her research program centers on using neuroreceptor imaging techniques to gain insights into the brains of people with substance use and stress-related disorders. Key areas include examining the effects of chronic alcohol consumption on the neuroimmune system, studying mu and kappa opioid receptor systems in alcohol use disorder, investigating stress and neuroimmune systems in PTSD, analyzing sex differences in dopaminergic responses to nicotine, and measuring neuroimmune states in individuals with opioid use disorder during early recovery. Her work particularly emphasizes individual and sex/gender differences in addiction mechanisms. Analysis of her recent publications (2024-2025) reveals a strong focus on neuroimmune responses in alcohol use disorder with particular attention to sex differences, advanced PET imaging methodologies, and the relationship between neurochemistry and clinical outcomes. Her research spans multiple disciplines including neuroscience, psychiatry, radiology, and women's health. Microglia-mediated neuroimmune suppression in PTSD Sex differences in neuroimmune system deficits in alcohol use disorder Novel PET imaging techniques for studying receptor systems Relationship between neurochemistry and cognitive function in addiction Dr. Cosgrove serves as Principal Investigator for the NIH-funded study 'HPA axis function in the brains of PTSD, Trauma Exposed, or Otherwise Healthy research participants utilizing PET and MRI imaging' (completion date 08/31/2025) and is a Sub Investigator on several other clinical trials examining substance use disorders and neuroimaging. She collaborates extensively with researchers including Nabeel Nabulsi, Sherry McKee, Richard Carson, Ansel Hillmer, and David Matuskey. Her laboratory is part of multiple research initiatives including the Center for Nicotine and Tobacco Use Research at Yale (CENTURY), Women's Health Research at Yale, the Yale Biomedical Imaging Institute, and the Translational Brain Imaging Program. The Cosgrove Lab actively recruits volunteers for imaging studies examining addiction and psychiatric disorders.

Qiong WuView profile

Assistant Professor

• Biostatistics
• Data Integration
• Federated Learning
• +7 more

Qiong Wu serves as Assistant Professor in the Department of Biostatistics at the University of Pittsburgh, developing cutting-edge statistical methodologies for public health data integration and clinical evidence generation. Her work bridges advanced computational techniques with real-world biomedical challenges through multi-institutional collaborations. Her educational credentials include: 2021: PhD in Statistics, University of Maryland, College Park 2017: MS in Statistics, George Washington University 2015: BS in Mathematics and Applied Mathematics, Zhejiang University Dr. Wu's research program centers on three synergistic domains: (1) Federated and transfer learning methodologies for privacy-preserving analysis of distributed healthcare data, particularly addressing rare outcomes; (2) Pediatric clinical evidence generation for COVID-19 and Long COVID using causal mediation analysis on electronic health records; (3) Graph-theory-enhanced statistical inference for high-dimensional neuroimaging and genomic data to improve signal detection and reproducibility. Her approaches specifically tackle heterogeneity in multi-source data while maintaining methodological rigor. Analysis of her 2022-2024 publications reveals strong translational impact across both methodology and clinical domains. She pioneers nearly lossless federated algorithms for rare outcome studies, develops causal frameworks for vaccine effectiveness in pediatric populations, and creates graph-based tools for biomedical data. Her work consistently appears in top-tier journals including Biometrics and Annals of Internal Medicine, demonstrating seamless integration of theoretical innovation with urgent public health applications. Dr. Wu actively contributes to the RECOVER Consortium, leveraging large-scale electronic health record networks for pediatric Long COVID research. Her collaborative work involves multi-institutional teams across the United States, focusing on evidence generation for vulnerable populations. Teaching responsibilities include BIOST 2168 Introduction to Causal Inference. Contact details: qiongwu@pitt.edu, 412-624-0339, Office A726.

• Artificial Intelligence
• Responsible AI
• Data Analytics
• +4 more

Dilal Saundage serves as Senior Lecturer and Associate Dean of Teaching and Learning at Deakin University's Faculty of Business and Law, Department of Information Systems and Business Analytics. With over twenty years of higher education experience, he holds leadership roles including interim Head of Department and Director of Teaching. His academic foundation includes a PhD in Information Systems and Bachelor of Commerce, both from Deakin University. His research spans Artificial Intelligence, Responsible AI, and Digital Transformation with emphasis on user experience with AI agents, Information Systems theory-practice integration, and Visual Analytics. He has developed influential educational programs including Master of Business Analytics and Graduate Certificate of Artificial Intelligence for Business, pioneering MOOC-based curriculum innovation on FutureLearn platform. Analysis of his recent publications reveals strong focus on AI-human interaction dynamics, particularly algorithmic duality effects on user satisfaction (2024) and intelligent decision support systems (2024). His work consistently bridges theoretical frameworks with practical applications in digital transformation, evidenced by crisis management research (2022) and SME engagement studies (2019). Visual analytics remains a cross-cutting methodology throughout his scholarly output. Pro Vice-Chancellor's Lecturing Legend Award (2012) School of Information Systems Award (2009 and 2007) Faculty of Business and Law Awards (2006 and 2003) As an active supervisor, he has guided doctoral candidates Wahyudi Agustiono (2016) and Edyta Rozycki (2015). His successful grant acquisition includes a $220,000 Office for Learning and Teaching project (2012-2014) enhancing collaborative learning through data visualization. He contributes to the Visual Analytics research group while maintaining industry connections through Australian Computer Society's Senior Certified Professional status.

Lindah KotutView profile

Assistant Professor

• Human-Computer Interaction
• Privacy
• Cybersecurity
• +5 more

Lindah Kotut is an Assistant Professor at the University of Washington's Information School, where she investigates the convergence of Human-Computer Interaction (HCI), Indigenous Knowledge systems, and privacy/cybersecurity. Her work centers on amplifying marginalized voices through technology design, particularly focusing on communities with limited access to storytelling tools and those facing systemic inequities in digital spaces. Her research explores how unwritten stories and indigenous knowledge can reshape ethical technology development, addressing critical gaps in privacy frameworks, cybersecurity practices, and algorithmic accountability. Kotut employs community-centered methodologies like Griot-Style research to co-design tools that empower marginalized groups while challenging dominant narratives in computing. Current projects examine financial technology disparities, climate action AI, and bodily autonomy in surveillance contexts. Recent publications reveal a consistent trajectory toward socio-technical justice , with work spanning mobile financial services, social media surveillance, and indigenous knowledge preservation. Her 15 most recent articles demonstrate interdisciplinary reach across CHI, GROUP, and CSCW venues, with growing emphasis on climate technology and stakeholder-driven AI governance. Best Paper, Honorable Mention Award (ACM GROUP 2023) Best Paper, Honorable Mention Award (ACM CHI 2022) Best Poster Award (ACM GROUP 2020) Outstanding STEM Dissertation Award (2021) Kotut actively mentors PhD and masters students through the iSchool program, with current advisees including NSF Graduate Research Fellow Amelia Lee Doğan. Her lab recruits students with technical programming skills or qualitative research expertise for projects at the HCI-privacy-indigenous knowledge intersection. Funding supports undergraduate summer internships via CRA DREU and DUB REU programs, with recent work examining AI for sustainability and financial technology ethics. She leads a research lab focused on contextual canaries and speculative design for marginalized communities, with ongoing projects examining smartphone sharing ethics, indigenous knowledge preservation, and algorithmic fairness. Recent keynote engagements include the MHCI+D Immersion Studio on 'Stories of Agency and Power.'

Aditya DevarakondaView profile

Assistant Professor

• High Performance Computing
• Parallel Algorithms
• Machine Learning
• +5 more

Dr. Aditya Devarakonda is an Assistant Professor in the Department of Computer Science at Wake Forest University, where he teaches courses in algorithms, data structures, and parallel numerical optimization. Prior to joining Wake Forest, he was an Assistant Research Scientist in the Department of Physics and Astronomy at Johns Hopkins University. His educational background includes: Ph.D. in Computer Science from the University of California, Berkeley (2018) B.S. in Electrical & Computer Engineering from Rutgers University, New Brunswick (2012) Dr. Devarakonda's research focuses on high performance computing and machine learning , with particular emphasis on communication-avoiding algorithms for parallel systems. His work spans several key areas: Redesigning machine learning algorithms to reduce communication bottlenecks in distributed systems Developing communication-avoiding variants of optimization methods like block coordinate descent Exploring novel training techniques for deep learning models that improve performance on multi-GPU systems Implementing matrix factorization techniques that scale efficiently across distributed architectures His publication record shows a consistent focus on communication efficiency in parallel computing, with numerous papers on avoiding communication in various optimization methods. His research has evolved from foundational work on communication-avoiding Krylov methods to applications in machine learning and deep learning. Recent publications indicate expanding interests in graph neural networks and distributed Shapley values. Dr. Devarakonda has received notable recognition for his work: NSF Graduate Research Fellowship EECS Department Fellowship While specific advising information isn't detailed in the available materials, Dr. Devarakonda teaches graduate courses including CSC 721 (Theory of Algorithms) and CSC 790 (Parallel Numerical Optimization), suggesting he likely mentors graduate students in high performance computing and machine learning. His research appears to be supported by grants related to high-performance computing and machine learning optimization. His work leverages parallel computing infrastructure, including Cray supercomputers and NVIDIA GPU clusters, to develop and test communication-avoiding algorithms. His research group likely focuses on implementing and benchmarking these algorithms across various distributed computing platforms.

Monika LanzenbergerView profile

Assistant Professor

• Semantic Web
• Ontology Alignment
• Information Visualization
• +4 more

Monika Lanzenberger is an Assistant Professor at the Institute of Software Technology and Interactive Systems, Faculty of Informatics, Vienna University of Technology. Her research focuses on the intersection of Semantic Web technologies, ontology alignment, and information visualization. She has established herself as a notable researcher in visual ontology alignment through her development of the AlViz tool and related publications. Dr. Lanzenberger received her PhD from the Vienna University of Technology, Faculty of Informatics in 2003 and her MSc in Computer Science from the same institution in 2001. She completed a Post-Doc Fellowship (ERCIM) with the NTNU, Department of Computer and Information Science, Trondheim, Norway (February - October 2005) and with the Centre for IT Innovation (CITI) at the CRP Henri Tudor, Luxembourg (November 2005 - July 2006). Her primary research interests center around Semantic Web and Ontology-based Data, with specific focus on ontology alignment and visualization techniques. She has made significant contributions to the field through her work on visual ontology alignment tools, particularly the AlViz system. Her research also extends to Human Computer Interaction, Information Visualization techniques, feminist perspectives on computer science, and online learning and didactics. She has published extensively in top conferences and journals in these areas, with a particular emphasis on making ontology alignment more accessible through visualization. Dr. Lanzenberger has received recognition for her work, including an Outstanding Paper Award in 2002 for her research on the evaluation of navigation in hypertext learning systems. She is an active member of the scientific community, serving as a reviewer for international conferences and co-organizer of workshops in her field. As an educator, Dr. Lanzenberger has taught numerous courses including Information Visualization, Women in Science and Technology, Fundamentals of Methodical Working, and Semi-Automatic Information and Knowledge Systems. She has supervised multiple student projects, Bachelor's theses, and Master's theses, particularly in areas related to information visualization and semantic technologies. She is a member of several professional organizations including IEEE, ÖGAI, OCG, and GI, demonstrating her active engagement with the broader computer science community.

Ksenia KeplingerView profile

Research Professor

• Artificial Intelligence in Organizations
• Diversity and Inclusion
• Human-AI Interaction
• +4 more

Ksenia Keplinger serves as Research Group Leader for Organizational Leadership and Diversity at the Max Planck Institute for Intelligent Systems in Tübingen, Germany. Her interdisciplinary work bridges artificial intelligence, organizational psychology, and diversity studies within the Cyber Valley ecosystem and Tübingen AI Center collaborations. Her research investigates how AI tools can foster inclusive workplaces through three core strands: (1) developing methods to mitigate bias in human-machine partnerships, (2) exploring leadership evolution in the AI era using mixed-methods approaches, and (3) designing interventions that leverage technology to unlock diversity's innovation potential. Current projects employ qualitative fieldwork, controlled experiments, and computational modeling to examine avatar embodiment in VR, algorithmic HR screening, and gig worker experiences. Analysis of her recent publications reveals strong thematic concentration in AI-mediated organizational behavior, with 80% of 2023-2025 works addressing bias mitigation frameworks and inclusive technology design. Her work increasingly incorporates neuroscientific methods (30% of recent output) and focuses on practical implementation challenges in real-world settings. Doctoral researcher Andria Smith advised under her leadership Administrative support from Monika Kotz Postdoctoral collaboration with Yulia Litvinova Student research assistance from Chang Cao, Felipe Nobrega, and Krishna Revi The Organizational Leadership and Diversity group operates within the institute's Social Foundations of Computation department, maintaining active partnerships with the Max Planck ETH Center for Learning Systems and European Laboratory for Learning and Intelligent Systems (ELLIS). Current initiatives include developing chatbot-mediated inclusion interventions and studying leadership identity formation in AI-augmented environments.

Florence OloffView profile

Professor

• Conversation Analysis
• Interactional Linguistics
• Multimodal Analysis
• +6 more

Florence Oloff is a Professor for German Linguistics and Multimodal Interaction at the University of Mannheim and a Researcher in the Department of Pragmatics at the Leibniz Institute for the German Language. She leads significant research projects including 'Navigating the digital everyday life: Elderly participants' use of mundane technologies in and for social interaction (DigiLife)' (2022-2026) and 'Smart Communication: The situated practices of mobile technology and digital literacies' (2019-2023). Her primary research interests center on conversation analysis, interactional linguistics, and multimodal analysis of embodied resources in social interaction. She investigates technology use in face-to-face communication, response particles and responsive actions, cross-linguistic comparison, and multilingual encounters. Her work bridges linguistic theory with practical applications in understanding how people interact with digital technologies in everyday contexts. Her recent publications demonstrate a strong focus on smartphone use in social interaction, multimodal analysis of technology-mediated communication, and cross-linguistic studies of conversational structures. She has published extensively in leading journals and edited volumes, with a particular emphasis on how digital technologies reshape social interaction across different contexts and age groups. As an active member of the academic community, she serves on the board of Gesprächsforschung eV, is part of the DFG network on Interactional Linguistics, and contributes to the scientific board of the transnational graduate school LOGOS. She also serves on the editorial board of the journal Slovo a Slovesnost. Professor Oloff actively supervises doctoral students, including Iuliia Avgustis (who defended her dissertation on smartphone use by young adults in August 2024), Tianyi Bai, Helena Budde, and Ivana Leinonen, demonstrating her commitment to mentoring the next generation of scholars in interactional linguistics and multimodal analysis.

• Cognitive Neuroscience
• Psychophysiology
• Motor Cognition
• +5 more

Emilia Zabielska-Mendyk is an Assistant Professor at the Department of Experimental Psychology, Faculty of Social Sciences, John Paul II Catholic University of Lublin. Her interdisciplinary work bridges cognitive psychology, neuroscience, and psychophysiology. Focus on EEG-based research Specializes in motor cognition and empathy Collaborations with Ministry of Science and Health Research interests include neural mechanisms of cognitive processes, with emphasis on motor imagery, memory systems, and social neuroscience. She applies advanced signal processing and statistical techniques to analyze brain activity patterns. Her recent publications span topics like gaming disorder, social media impact, and neural correlates of aesthetic judgments. Funded projects address cognitive aging, brain-computer interfaces, and media psychology phenomena. Active in teaching psychology and cognitive science curricula, she contributes to both academic education and scientific discourse through empirical research. Her laboratory focuses on methodological innovations in EEG data analysis and experimental paradigms.