جست‌وجوی استاد و پژوهشگر

Dorota Leszczyńska-Jasionمشاهده پروفایل

دانشیار

• Logic
• Proof Theory
• Erotetic Logic
• +۴ مورد دیگر

Dr. Dorota Leszczyńska-Jasion serves as Associate Professor at Adam Mickiewicz University in Poznań, Poland, within the Faculty of Cognitive Science and Department of Logic and Cognitive Science. Her academic profile centers on foundational logic research with significant interdisciplinary applications. Her educational trajectory features: Habilitation (post-doctoral degree) in Social Science (2019) from Adam Mickiewicz University based on From Questions to Proofs. Between the Logic of Questions and Proof Theory Ph.D. in Philosophy (2006) from University of Zielona Góra with dissertation The Method of Socratic Proofs for Normal Modal Propositional Logics M.A. in Philosophy (2003) from University of Zielona Góra Her research pioneers Proof Theory through the Method of Socratic Proofs —a question-based deduction framework enabling loop-free decision procedures for modal logics. She extends this work to Erotetic Logic (logic of questions), developing Erotetic Search Scenarios that model human inquiry processes. Current innovations include Distributive Deductive Systems for classical/non-classical logics and Synthetic Tableaux with unrestricted cut rules, bridging theoretical logic with computational applications. Over the past decade, her publication pattern reveals escalating focus on unifying proof-theoretic and semantic approaches. Recent work integrates correspondence analysis with Socratic proofs and develops distributive frameworks for first-order logic, demonstrating consistent advancement from modal logics toward comprehensive deductive systems with computational relevance. Her scholarly recognition includes: Foundation for Polish Science Scholarship START (2013) Foundation for Polish Science Scholarship under Prof. Wiśniewski's FPS Award (2002-2004) She currently directs the National Science Centre-funded project Distributive Deductive Systems (2017-2023) and previously contributed to major grants including Erotetic Logic in Question Processing (2013-2017) and Inferential Erotetic Logic and Problem-solving (Foundation for Polish Science). Her research program consistently secures competitive funding for exploring the intersection of formal logic, cognitive modeling, and computational methods. As core member of the Reasoning Research Group, she advances theoretical foundations of deductive systems while fostering collaborations across logic, computer science, and cognitive studies. The group's work on erotetic frameworks provides formal tools for modeling scientific inquiry and human reasoning processes.

Jayadhurganandh Jayaramanمشاهده پروفایل

دانشیار

• Educational Data Mining
• Financial Technology
• Machine Learning
• +۳ مورد دیگر

Jayadhurganandh Jayaraman serves as Associate Professor, Dean of the School of Business, and Co-Chair of the Finance Department at New Jersey City University, leveraging over 20 years of prior financial services industry experience in algorithmic trading, risk management, and fintech to bridge academic theory with real-world applications. His educational credentials include: Ph.D. from Oklahoma State University MBA from Bharathidasan Institute of Management B.E. from College of Engineering Guindy, Anna University Professor Jayaraman's research strategically converges finance, education, and artificial intelligence through two primary thrusts: educational data mining for student success prediction and fintech innovation for social impact. His work applies machine learning to analyze advisor communications for dropout prediction while simultaneously developing behavioral science frameworks to enhance financial literacy in underserved populations, demonstrating a commitment to technology-driven solutions for systemic educational and financial challenges. His 2019-2020 publications in the International Conference on Educational Data Mining establish a clear research trajectory focused on machine learning applications for educational equity, with recent media recognition (March 2024) confirming the practical relevance of his work in marginalized community financial literacy initiatives. As an educator, he directs a comprehensive curriculum spanning foundational Financial Literacy (FINC 250) through advanced Financial Technology (FINC 631) and derivative analysis courses, while his administrative leadership as Dean enables institutional implementation of data-driven educational strategies. Prospective students can engage with his research through courses in machine learning, data science, and fintech that incorporate his industry-tested methodologies.

Ivan Polášekمشاهده پروفایل

دانشیار

• Software Engineering
• Virtual and Augmented Reality
• Software Modeling
• +۳ مورد دیگر

Ivan Polášek is a part-time Associate Professor at the Department of Applied Informatics within the Faculty of Mathematics, Physics and Informatics at Comenius University in Bratislava. His institutional affiliations include membership in the Division of Theory and System Design. His research explores: Software modeling and visualization techniques Virtual/augmented reality applications in software engineering AI-driven optimization of software design and refactoring Collaborative development methodologies Design pattern analysis and anti-pattern detection Recent publications (2017-2024) demonstrate strong focus on VR-supported collaborative design, executable software models, and communication methodologies in team-based development environments. He teaches undergraduate courses in agile development and software architectures, while leading research seminars. No awards or supervised students are documented in available sources. Polášek contributes to the INNOVAITE research project and maintains collaborations with European institutions including researchers from the Netherlands, France, and Sweden.

Chao Pengمشاهده پروفایل

مدرس پاره‌وقت

• Software Testing
• Program Analysis
• Programming Languages
• +۵ مورد دیگر

Chao Peng is a Principal Research Scientist at ByteDance where he leads the Trae Research team (ByteDance Software Engineering Lab), conducting cutting-edge research on AI agents for software engineering. He also serves as a Part-time Postgraduate Student Mentor at Fudan University's School of Computer Science, bridging industry research with academic mentorship. PhD in Informatics (2021), University of Edinburgh, UK MSc in High Performance Computing and Data Science (2017), University of Edinburgh, UK BEng in Computer Science and Technology (2016), Xuzhou University of Technology, China Dr. Peng's research focuses on the intersection of software testing, program analysis, and large language models. His work explores how AI agents can revolutionize software engineering practices, with particular emphasis on automated bug detection, code generation, and testing frameworks. He has pioneered approaches for evaluating LLM performance in software engineering contexts and developing agent-based systems that enhance developer productivity while maintaining code quality and security. His recent publications demonstrate a clear trend toward integrating large language models with traditional software engineering practices. The research spans code generation evaluation, security vulnerability detection, automated bug reproduction, and issue localization. These works collectively advance the field of AI-assisted software development by addressing practical challenges in reliability, security, and efficiency of AI-generated code. Distinguished Reviewer for FSE'25 School of Informatics Scholarship (fully-funded PhD scholarship) Outstanding Graduate Scholarship at Xuzhou University of Technology Multiple China National Scholarships Honours Spot Bonus at ByteDance Certificate of Achievement for HPCAC Student Cluster Competition Dr. Peng actively mentors students through his role at Fudan University and previously at the University of Edinburgh, where he served as sub-supervisor for MSc projects and teaching assistant for software testing courses. His research has attracted significant industry attention, leading to multiple collaborations between ByteDance and academic institutions. He frequently serves on program committees for major software engineering conferences including ASE, FSE, and ICSE, demonstrating his leadership in the field. As leader of the Trae Research team at ByteDance Software Engineering Lab, Dr. Peng oversees research on AI agents for software engineering, including the application and evaluation of AI agents and training LLMs for agent-based systems. The lab's work focuses on practical systems that predict, detect, diagnose, and fix bugs across various software systems, with particular emphasis on real-world applications and measurable impact on developer productivity.

Laura Dietzمشاهده پروفایل

دانشیار

• Information Retrieval
• Machine Learning
• Natural Language Processing
• +۶ مورد دیگر

Laura Dietz is a tenured Associate Professor in the Department of Computer Science at the University of New Hampshire, where she leads the TREMA lab. Her academic journey began with a PhD from the Max Planck Institute for Informatics in Saarbruecken, Germany (2011), followed by postdoctoral positions at the University of Massachusetts Amherst (2010-2015) and University of Mannheim (2015-2016). Her educational background includes PhD studies at both the Max Planck Institute for Informatics (2007-2011) under Prof. Gerhard Weikum and Prof. Tobias Scheffer, and earlier research at Humboldt University in Berlin. She has built a distinguished career bridging theoretical computer science with practical applications in information retrieval and machine learning. Dietz's research primarily focuses on the intersection of information retrieval, natural language processing, and knowledge graphs, with a parallel research initiative in watershed data science. She is particularly known for her work on entity-aspect linking, complex answer retrieval, and the vision of automatic Wikipedia construction. Her approach integrates fine-grained knowledge annotations with text understanding to create comprehensive information systems that go beyond traditional 10-blue-links search paradigms. In watershed data science, she applies similar machine learning techniques to environmental data streams, focusing on solute transport analysis during storm events. Her recent publications reveal a strong trend toward fine-grained semantic understanding, particularly in entity-oriented search tasks. She has pioneered methods for entity-aspect linking that significantly improve retrieval accuracy by capturing different contexts in which entities appear. Her work increasingly integrates knowledge graphs with neural architectures, showing sophisticated understanding of how to leverage both structured and unstructured information for better search experiences. Best paper award at JCDL 2018 for work on entity-aspect linking NSF CAREER Award (2019-2023) for "Utilizing Fine-grained Knowledge Annotations in Text Understanding and Retrieval" OSSI Award 2013 from UMass ICB3 for open-source hardware/software Dietz actively mentors PhD and Masters students through the TREMA lab, with current research focusing on entity ranking, topic extraction, conversational search, and watershed forecasting. Her grant portfolio includes the NSF CAREER award and funding from the Northeast Big Data Innovation Hub for forecasting salinity in rivers during storm events. She has also coordinated the TREC Complex Answer Retrieval track (2017-2019), creating important benchmarks for the IR community. The TREMA lab (Text Retrieval, Entity Modeling, and Applications) serves as the hub for Dietz's research activities, bringing together students and collaborators to work on cutting-edge problems in information access. The lab's work spans both theoretical contributions to information retrieval and practical applications in domains ranging from environmental science to scientific publication analysis.

• Neuroscience
• Functional Magnetic Resonance Imaging
• Electroencephalogram
• +۶ مورد دیگر

Janne Kauttonen serves as a Visiting Professor in the Department of Neuroscience and Biomedical Engineering at Aalto University's School of Science. He holds a Doctor of Philosophy (Filosofian tohtori) from the University of Jyväskylä, awarded on October 17, 2012. His research contributes to Sustainable Development Goal 4 (Quality Education) through neuroscience education and research. Dr. Kauttonen's research interests focus on Neuroscience , particularly utilizing Functional Magnetic Resonance Imaging and Electroencephalogram techniques to study brain networks during naturalistic cognitive processes. His work explores how the brain processes social interactions, narrative comprehension, and memory formation during real-world stimuli like movies and audio dramas. Key research areas include angular gyrus functionality, social behavior neuroscience, and cognitive processing differences between holistic and analytical thinkers. His publication record shows consistent output since 2014, with significant impact in cognitive neuroscience. His research demonstrates strong interest in how brain networks respond to natural stimuli, with particular emphasis on social presence, narrative processing, and cue-based memory mechanisms. The 2018 NeuroImage paper on memory formation during movie viewing has garnered 44 citations, indicating substantial influence in the field. Dr. Kauttonen has presented his research at numerous international conferences including Neuroscience 2014 in Washington DC, the 5th Workshop on Computational Models of Narrative in Quebec City, and the APS March Meeting in Boston.

• Cognitive Control
• Selective Attention
• Neuroscience
• +۲ مورد دیگر

Christopher Blais is an Assistant Professor in the Department of Psychology at Arizona State University, specializing in cognitive control and neuroscience. He directs the EEG lab, focusing on implicit mechanisms of self-regulation and attention. PhD in Cognitive Psychology, University of Waterloo (2006) MA in Cognitive Psychology, University of Waterloo (2002) BA in Psychology with minor in Mathematics, University of Waterloo (2001) His research explores cognitive control, selective attention, and neural correlates of behavior regulation. Key areas include understanding how implicit processes influence attentional control and memory, utilizing EEG and computational models. Recent publications highlight trends in cognitive neuroscience, including applications of machine learning to EEG data, social learning mechanisms, and educational technology innovations. Blais has contributed to studies on bilingualism, prospective memory, and emotion regulation. Blais teaches undergraduate courses like BIO 495 (Undergraduate Research) and PSY 499 (Individualized Instruction), emphasizing hands-on learning in psychology and neuroscience.

Yiling Louمشاهده پروفایل

دانشیار

• Software Engineering
• Artificial Intelligence
• Programming Languages
• +۵ مورد دیگر

Yiling Lou is an incoming Assistant Professor at the Siebel School of Computing and Data Science, University of Illinois Urbana-Champaign (starting Spring 2026), currently serving as a Pre-tenure Associate Professor at Fudan University. Previously a Postdoctoral Fellow at Purdue University under Prof. Lin Tan, Dr. Lou holds a Ph.D. and B.S. in Computer Science from Peking University supervised by Prof. Lu Zhang and Prof. Dan Hao. Research interests span Software Engineering synergized with Artificial Intelligence and Programming Languages , specifically focusing on LLM4Code, Agent&SE, Vulnerability Detection, and Software Testing/Debugging. Current projects include AgentIssue-Bench for agent system maintenance and INFERROI for enhancing static analysis with LLMs. Research trends show increasing integration of LLMs with traditional SE techniques, particularly in code generation (ClassEval, CodeGen4Libs), debugging (interactive runtime comparison), and vulnerability detection. Recent work emphasizes practical applications in agent systems and resource leak detection. ACM SIGSOFT Distinguished Paper Award (ESEC/FSE 2023) IEEE TCSE Distinguished Paper Award (ICSME 2021) Advises a large research group including 7 Ph.D. and 8 MS students at Fudan University, actively recruiting for UIUC starting Fall 2026. Leads the LLM4Code workshop series and serves on numerous program committees including ICSE, ASE, and FSE. Currently organizing research on Code Agents, Code LLMs, and AI&Security with strong industry relevance. Coordinates the Siebel School research group at UIUC focusing on the intersection of AI and Software Engineering, with particular emphasis on developing robust agent systems for code maintenance and security applications.

Frans van der Sluisمشاهده پروفایل

دانشیار

• human-information interaction
• human interest and curiosity
• epistemic emotions
• +۴ مورد دیگر

Frans van der Sluis serves as an Associate Professor in the Department of Communication at the University of Copenhagen, where he conducts interdisciplinary research at the intersection of human cognition and information systems. His work focuses on designing search and filtering technologies that align with human learning processes and curiosity-driven exploration. Education: BSc in Psychology (2006) BSc in Business Information Technology (2006) MSc in Psychology (2008) PhD in Interactive Information Retrieval and Filtering (2013) Van der Sluis investigates how information systems can be optimized to transform raw data into meaningful knowledge through understanding epistemic emotions, user uncertainty, and cognitive processing during information interactions. His methodology frequently incorporates eye-tracking and empirical user studies to measure comprehension, interest, and engagement beyond traditional accuracy metrics. Analysis of his recent publications (2023-2025) reveals a consistent trajectory toward conversational approaches in information quality assessment, with growing applications in sustainability domains like wind energy training networks and ethical consumer behavior. His work bridges theoretical HCI frameworks with practical implementations across diverse contexts from social media to specialized research environments. No scientific awards were documented in the source materials. While specific advising details remain unspecified, his collaborative projects—including the EU-funded Train2Wind initiative for offshore wind power researchers—demonstrate active grant management and cross-institutional leadership. His professional network spans major European universities and industry research centers. Van der Sluis maintains active collaborations with University of Twente, Glasgow University, Leiden University, and industrial partners including Philips' Innovation Lab, reflecting his position at the nexus of academic research and real-world information system design.

• Cybersecurity and Privacy
• Artificial Intelligence
• Distributed Computing
• +۶ مورد دیگر

Dr. Keshav Sood is a Senior Lecturer at Deakin University's School of Information Technology, where he leads research in cybersecurity, AI, and next-generation networks. His affiliations include roles as Graduate Research Coordinator and South Asia Country Coordinator. He completed his PhD at Deakin University and a post-doctoral fellowship at the University of Newcastle. Research Interests: Dr. Sood focuses on securing distributed systems, with emphasis on: Federated learning for intrusion detection in IoT/5G networks Biometric privacy in immersive technologies (VR/AR) RF fingerprinting for IoT device authentication Quantum-resistant software-defined networks Adversarial robustness in voice authentication systems His publications consistently explore AI-driven security frameworks, with recent work addressing data sparsity in IoT sensors, cross-domain IIoT authentication, and phishing mitigation using large language models. Awards: Professor of IT Award (2016) IEEE TNSE Excellent Reviewer (2023) Deakin HDR Supervision Award (2023) Course Team Award for Industry Certification Alignment (2021) Supervision & Grants: Dr. Sood currently advises 8 graduate researchers and has secured $655,313 in competitive funding. Key projects include: Smart Farming Cyber Resilience (DFAT Maitri Grant) Secure Access for Critical Infrastructure (Cyber CRC) IoT Data Integrity for Defense Systems (Australian Defence) He leads the Deakin Cyber Research and Innovation Centre, focusing on scalable security solutions for industry partners.

Maximiliano Frías Vázquezمشاهده پروفایل

پژوهشگر

• Migration Studies
• Hate Speech Analysis
• Social Network Analysis
• +۵ مورد دیگر

Maximiliano Frías Vázquez is a Research Staff member at the University of Salamanca's Faculty of Social Sciences, Department of Sociology and Communication. He is affiliated with the Audiovisual Content Observatory (OCA) where he conducts research on migration, hate speech, and big data analysis. His research interests focus on social network analysis , hate speech detection , and political communication in digital environments. Key areas include sentiment analysis toward stigmatized groups, data visualization in journalism, and representation of disability in Spanish cinema. His work combines computational methods with critical social analysis to examine online discourse patterns. His publication record shows strong emphasis on Spanish social media discourse (particularly Twitter), with recurring themes of migration crises (e.g., Aquarius boat incident), political elections, and ideological hate speech. Recent work explores data science communication and educational applications of big data. Frías Vázquez collaborates extensively with researchers including Carlos Arcila Calderón, Patricia Sánchez-Holgado, and David Blanco-Herrero through the OCA research group. His doctoral thesis in the 'Training in the Knowledge Society' program examines hate speech against Central American immigrants in Mexico.

• Visual Analytics
• Artificial Intelligence
• Data Visualization
• +۳ مورد دیگر

Roberto Therón is a Full Professor of Computer Science at the University of Salamanca, Spain, and a leading researcher in the GRIAL Group specializing in visual analytics and its interdisciplinary applications. His educational background includes: PhD in Computer Science BA in Audiovisual Communication BA in Humanities Dr. Therón's research spans visual analytics, artificial intelligence, data visualization, educational technology, human-computer interaction, and sustainability. He develops innovative platforms like LATILL for language learning and DETAILLs for AI-driven sustainable living labs, emphasizing user-centered design and domain-specific knowledge integration. His work bridges technical AI development with practical educational and sustainability applications through interdisciplinary collaboration. Analysis of his 2023-2025 publications reveals a dominant trend toward generative AI integration in educational tools, meta-modeling for reusable open educational resources, and context-aware data visualization techniques. His research consistently focuses on enhancing user experience through heuristic evaluation, domain knowledge incorporation, and sustainable AI frameworks across language learning, poetic analysis, and dashboard design. No scientific awards are mentioned in the available information. While specific advising details are unlisted, his leadership in the GRIAL Group and extensive co-authorship network (including Alicia García-Holgado, Andrea Vázquez-Ingelmo, and Francisco José García-Peñalvo) indicate active research supervision. His editorial roles as Chief Editor for Human-Media Interaction at Frontiers in Computer Science and Review Editor for Data Visualization at Frontiers in Bioinformatics demonstrate scholarly influence beyond direct research. As a core member of the GRIAL Group (Research Group in Applied e-Learning), Dr. Therón contributes to advancing e-learning through projects focused on open educational resources, AI-enhanced language platforms, and sustainability-driven living labs. The group emphasizes practical implementation of theoretical frameworks in real-world educational and environmental contexts.

• Natural Language Processing
• Computational Linguistics
• Formal Concept Analysis
• +۴ مورد دیگر

Dmitry Alekseevich Ilvovsky is an Associate Professor at the Department of Data Analysis and Artificial Intelligence within the Faculty of Computer Science at the National Research University Higher School of Economics (HSE University) in Moscow. He also serves as a Research Fellow at the International Laboratory of Intelligent Systems and Structural Analysis. Having joined HSE in 2011, he has accumulated over 10 years of scientific and teaching experience in the field of computational linguistics and artificial intelligence. Dr. Ilvovsky holds a Candidate of Technical Sciences degree (2017) and a Specialist degree in Applied Mathematics and Computer Science from the Moscow Aviation Institute (2010). His professional interests focus on natural language processing, formal concept analysis, and discourse-based approaches to text analysis. He has made significant contributions to developing methods for detecting disinformation, propaganda, and unreliable information in text data. His recent research demonstrates a clear trend toward integrating discourse structure with deep learning approaches for various NLP tasks. His work spans fact-checking systems, dialogue management, propaganda detection, and text complexity assessment. He has pioneered approaches using discourse trees and structural linguistic information to enhance the performance of language models, particularly in identifying manipulative content and verifying claims against trusted sources like Wikipedia. Gratitude from HSE University (January 2024) Letter of gratitude from the Vice-Rector of HSE (August 2021) Letter of Gratitude from the Faculty of Computer Science at HSE (August 2017) Rector's personal allowance (2016-2017) Academic Work Allowance (2020-2021) Bonus for publication in journal from List A (2023-2026) Bonus for publication in international peer-reviewed journal (2017-2023) Dr. Ilvovsky actively supervises PhD research, notably guiding A. Chernyavskiy's work on models for automatic detection and verification of unreliable information. His teaching portfolio includes courses such as Automatic Text Processing for Bachelor's students and Mentor's Seminar for Master's students. He has also contributed to the development of the International Laboratory of Intelligent Systems and Structural Analysis, where he has worked since 2012, organizing international conferences including the Concept Lattices and Their Applications conference in 2016—the first time it was held in Russia.

Nicolas Garcelonمشاهده پروفایل

پژوهشگر

• Biomedical data science
• Translational research
• Clinical informatics
• +۳ مورد دیگر

Nicolas Garcelon leads the data science platform at the Imagine Institute , specializing in developing biomedical data infrastructure for translational research between hospitals and research institutions. The platform manages 82 phenotypic databases covering 480,000 patients and has developed multiple software tools including eCohorte for database creation, BioPancarte for lab result visualization, and Dr. Warehouse for comprehensive clinical data integration. Director of a platform managing 36 million biological results Developed software registered with Program Protection Agency Open-source contributor with GNU GPL licensed Dr. Warehouse His research focuses on automated phenotypic data processing , clinical text mining , and patient similarity metrics for rare disease diagnosis. The platform enables Google-like search across 4 million clinical documents and provides diagnostic support through patient similarity calculations. Key publication themes include: Biomedical data warehouse architecture Phenotypic similarity algorithms Clinical decision support systems Unstructured clinical data processing Rare disease patient recruitment As part of the Necker-Enfants Malades Hospital collaboration, his team manages a data warehouse containing: 4 million clinical documents 36 million biological results 35 million extracted phenotypes Over 1000 completed studies

• Cognitive Neuroscience
• Language Processing
• Deaf Studies
• +۶ مورد دیگر

Professor Mairead MacSweeney is a leading cognitive neuroscientist at University College London's Institute of Cognitive Neuroscience, where she serves as Deputy Director. She was previously the Director of the UCL Deafness, Cognition and Language Research Centre (DCAL) from 2017-2023 and currently holds a prestigious Wellcome Trust Senior Research Fellowship (2022-2028). Her work bridges the Institute of Cognitive Neuroscience with the DCAL research center, contributing significantly to UCL's reputation in neuroscience and deaf studies. Her educational background includes a Doctor of Philosophy from University College London (1998) and a Bachelor of Science from the University of Northumbria at Newcastle (1993). Her academic career trajectory shows progressive responsibility, starting as a Postdoctoral Research Fellow at UCL in 1998, then advancing through various Wellcome-funded fellowships before reaching her current professorship. MacSweeney's research fundamentally explores how the brain processes language in people born profoundly deaf, examining how altered sensory experiences shape neural organization. Her work demonstrates that 'auditory' brain regions can process visual input when hearing is absent from birth, and that signed and spoken languages engage similar neural networks. This research has significant theoretical implications for understanding brain plasticity and practical applications for deaf education. Her methodology combines functional MRI (fMRI), behavioral analysis, and electroencephalography (EEG) to investigate language, literacy, and cognitive processing in deaf populations. Her recent publications reveal a consistent focus on language processing in deaf individuals, with increasing attention to developmental trajectories from infancy through adulthood. The research shows interdisciplinary connections between cognitive neuroscience, linguistics, developmental psychology, and education, with particular emphasis on bimodal bilingualism (spoken language plus sign language), cross-modal plasticity, and the neural basis of reading in deaf populations. Her work increasingly incorporates longitudinal designs and comparative approaches between deaf and hearing populations. Wellcome Trust Senior Research Fellow (2022-2028) Professor MacSweeney actively supervises undergraduate and MSc research projects and teaches across multiple Masters-level courses in the Faculty of Brain Sciences and Faculty of Population Health Sciences. Her research program is substantially supported by Wellcome Trust funding, indicating major institutional investment in her work on sensory and language experience effects on neural systems. She has secured continuous research funding through multiple competitive Wellcome fellowships since 2001, demonstrating sustained research excellence. MacSweeney leads research within the Visual Communication research group at the UCL Institute of Cognitive Neuroscience and has been central to DCAL's research activities. Her work connects with broader initiatives studying British Sign Language and deaf cognition, contributing to DCAL's mission of conducting world-class research to empower deaf people. She collaborates with researchers across UCL departments including Linguistics, Experimental Psychology, and Language and Cognition, reflecting the interdisciplinary nature of her work.