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Senior Lecturer
Dr. Brigitta Mittmann is a Senior Lecturer at the Department of English and American Studies, Friedrich-Alexander University Erlangen-Nuremberg (FAU), holding the Alexander von Humboldt Professorship for Language and Cognition. Her work focuses on lexicography, phraseology, and comparative analysis of spoken English varieties.
Researcher
Dr. Hongwei Wang is a Senior Researcher at Tencent AI Lab Seattle , specializing in applied machine learning for Natural Language Processing and Interconnected Systems . His work bridges Knowledge Graphs , Recommender Systems , and Graph Neural Networks , with a focus on large language models and retrieval-augmented generation. Ph.D. (2018), B.E. (2014) in Computer Science from Shanghai Jiao Tong University Postdoctoral Researcher : Stanford University (2019-2021), University of Illinois Urbana-Champaign (2021-2022) Dr. Wang’s research explores integrating Knowledge Graphs with Graph Neural Networks to enhance recommendation systems, language models, and information retrieval. His work spans Retrieval-Augmented Generation , Representation Learning , and GAN-based Graph Modeling , with recent papers on State-Space Exploration for LLM agents and Semantic Watermarking . His 15 most recent publications (2022-2024) focus on Retrieval Granularity , Interactive Memory , and Agent Systems , with keywords spanning Computer Science , Machine Learning , and Knowledge Graphs . Trends highlight advancements in Token-Level Semantic Matching , Schema-Guided Event Prediction , and Multi-Document Summarization . Scientific Awards: 2020 CCF Outstanding Doctoral Dissertation Award 2018 Google Ph.D. Fellowship Dr. Wang contributes to open-source projects like DKN and RippleNet , with 11 repositories on GitHub. He actively engages in Knowledge Graph Conferences (KDD, WWW, AAAI) and studies Chinese Classical Poetry and Film Arts .
Senior Lecturer
Magnus Westerlund is a Senior Lecturer in Information Technology and Director of the Laboratory for Trustworthy AI at Arcada University of Applied Sciences in Helsinki, Finland. His industry background spans telecom and information management, and he holds a doctoral degree in Information Systems from Åbo Akademi University. He actively contributes to the Z-Inspection® network, focusing on ethical AI implementation and governance. Westerlund’s research emphasizes trustworthy AI, cybersecurity, and distributed systems. Key areas include AI regulatory compliance (e.g., EU AI Act), healthcare AI applications, blockchain security, and IoT edge solutions. His work bridges academia and industry, such as the Valohai-CSC collaboration for machine learning infrastructure in Finnish academia. His publications highlight practical AI assessment methods, ethical AI integration, and decentralized technologies. Notable contributions include frameworks for sustainable AI development, privacy-preserving autonomous systems, and smart contract-based IoT security protocols. Westerlund also explores educational innovations, such as integrating large language models (LLMs) into coding education. His research consistently addresses real-world challenges like pandemic-era healthcare AI, edge computing for IoT, and cybersecurity in autonomous systems.
Associate Professor
Raju Vatsavai is an Associate Professor in the Department of Computer Science at North Carolina State University, affiliated with the Center for Geospatial Analytics. He joined NC State in 2014 as part of the Chancellor’s Faculty Excellence Program cluster hire in Geospatial Analytics. Education: PhD and MS in Computer Science from University of Minnesota Prior Roles: Lead Data Scientist at Oak Ridge National Lab, roles at University of Minnesota, IBM Research, AT&T Labs, and C-DAC (India) His research in geospatial analytics spans big data management , spatiotemporal data mining , deep learning for remote sensing , and high-performance computing , with applications in national security, climate change, and crop monitoring. Recent work includes deep learning frameworks for cloud imputation , multi-sensor satellite data harmonization , and transfer learning applications in crop classification . He has been a leading investigator on grants from the National Geospatial-Intelligence Agency, Department of Energy, and Department of Homeland Security. Labs: Associate Director of the Center for Geospatial Analytics Expertise: Spatial computing, Earth observation, nuclear proliferation detection via remote sensing
Associate Professor
Richard Futrell is an Associate Professor at the University of California, Irvine (UCI), affiliated with the Department of Language Science. He leads the Language Processing Group, focusing on computational models of human and machine language processing. His work bridges information theory, Bayesian cognitive modeling, and natural language processing (NLP) interpretability. University of California, Irvine Department of Language Science Language Processing Group leader His research examines how linguistic structures emerge from cognitive and communicative pressures. Key areas include dependency locality, surprisal theory in sentence processing, and efficiency-driven language evolution. He investigates how memory constraints, predictability, and information density shape syntactic and morphological patterns across languages. Recent publications analyze code-switching efficiency, syntactic priming, ERP component modeling, and agent-based language contact simulations. His work frequently employs Bayesian modeling, neural network analysis, and cross-linguistic corpora to uncover universal principles in language processing. ACL Best Paper Award (2024) Best Paper Award for Computational Modeling of Language (2023) Marr Prize for Best Student Paper (2017) He has developed datasets like SPACER for error repair analysis and contributed to phonotactic learning frameworks. His collaborations span cognitive scientists, computational linguists, and neuroscientists, advancing understanding of language production, comprehension, and structural optimization.
Assistant Professor
Elena Barbieri is a Research Assistant Professor in the Department of Physical Medicine and Rehabilitation at Northwestern University's Feinberg School of Medicine, with dual affiliation at the Mesulam Center for Cognitive Neurology and Alzheimer's Disease. Her interdisciplinary work bridges cognitive neuroscience, clinical neuropsychology, and rehabilitation medicine. Her educational trajectory includes: BS in Cognitive Science from University of Milano-Bicocca (2005) MS in Cognitive Neuroscience from University of Milano-Bicocca (2007) PhD in Cognitive Neuroscience from University of Milano-Bicocca (2012) Postgraduate Training Fellow in Clinical Neuropsychology at Northwestern University (2014) Postdoctoral Fellow in Communication Sciences and Disorders at Northwestern University (2017) Dr. Barbieri's research centers on language-brain relationships with primary focus on aphasia mechanisms and rehabilitation. She investigates both stroke-induced aphasia and Primary Progressive Aphasia (PPA), employing multimodal neuroimaging (structural/functional MRI, PET), electrophysiology (ERP), and noninvasive brain stimulation. Her work examines neural reorganization during recovery, cross-linguistic language processing patterns, and development of culturally adapted assessment tools like the Northwestern Assessment of Verbs and Sentences (NAVS) across Italian, Persian, and German populations. Current projects address TDP-43 pathology progression, virtual reality interventions, and neural mechanisms of syntactic processing in neurodegenerative conditions. Analysis of her 2021-2025 publications reveals strong emphasis on PPA neurobiology, cross-linguistic aphasia rehabilitation, and neural plasticity. Key trends include development of international consensus outcome measures (COS-PPA), investigation of disease-specific progression patterns (TDP-43 pathology), and innovative virtual interventions for dementia-related communication disorders. Her work consistently integrates clinical assessment with advanced neuroimaging to map language network reorganization. Her research excellence is recognized through: Karen Toffler Scholarship for neurodegenerative disease research (2023) Cognitive Neuroscience Society Postdoctoral Fellow Award (2018) Society for Neurobiology of Language Travel Award (2016) Dr. Barbieri serves as Associate Editor for Frontiers in Language Science and maintains active roles in ISTAART and the Academy of Aphasia. Her Mesulam Center affiliation enables collaborative research on cognitive-linguistic deficits in Alzheimer's disease and frontotemporal dementia, with particular focus on developing targeted language interventions for progressive neurodegenerative conditions.
Professor
Prof. Dr. Axel Mecklinger is a leading cognitive neuroscientist at Saarland University , specializing in the neurocognition of memory and language through spatiotemporal brain imaging (EEG/MEG/fMRI). His career spans over three decades, with significant contributions to understanding visual working memory , associative recognition , and memory development . Key research areas: Memory binding, ERP subsequent memory effects, novelty detection, and cognitive aging Major grants: DFG Research Groups, Collaborative Research Centers, and international collaborations with the Chinese Academy of Sciences Scientific leadership: Organized conferences, edited journals, and served as speaker for research training groups His recent work explores unitization in memory formation , cross-cultural differences in memory processing , and theta neurofeedback interventions . Awards include the Early Career Award of the German Psychophysiology Society (1992) and the European Federation of Psychophysiology Societies' Federation Prize (1994). Current projects investigate the neural mechanisms of semantic surprisal and memory plasticity in aging populations.
Associate Professor
Christian Smith is an Associate Professor and Lecturer at the Department of Robotics, Perception and Learning at Kungliga Tekniska Högskolan (KTH Royal Institute of Technology). His research focuses on robotics and applications in human-centered environments like home environments, small workshops, and healthcare facilities, including the development of new robotic systems for research. Teaching Roles: Course Coordinator/Teacher/Examiner for courses such as Introduction to Robotics (DD2410), Research Project in Robotics (DD2411), and Java Programming for Python Programmers (DD1380) Research Themes: Human-Robot Interaction, Behavior Trees, Exoskeletons, Intent Recognition, and Multimodal Perception Awards: No specific scientific awards mentioned in the provided text His KTH profile highlights work on adaptive robotics systems and formalized control strategies. The research portfolio spans from theoretical studies on behavior tree programming to applied work in assistive technologies and teleoperation systems.
Professor
Yongyi Mao is a Professor at the School of Electrical Engineering and Computer Science, University of Ottawa. He holds a Ph.D. in Electrical Engineering from the University of Toronto and has a multidisciplinary background in medical biophysics and engineering. His research focuses on communications and machine learning, with notable contributions to federated learning, information theory, and adversarial robustness. Professor Mao has held academic roles since 2003, advancing from Assistant to Full Professor by 2012. Education: B.Eng., Southeast University, 1992 M.D., Nanjing Medical University, 1995 M.S., University of Toronto (Medical Biophysics), 1998 Ph.D., University of Toronto (Electrical Engineering), 2003 Research interests span machine learning frameworks, federated learning, adversarial attacks, and domain adaptation. His work often bridges theoretical foundations (e.g., generalization bounds) with practical applications in text classification and watermarking. Publications reflect a strong emphasis on machine learning theory and NLP applications, with recent trends toward improving model robustness and generalization. No scientific awards are explicitly listed, though his prolific output suggests significant recognition in the field. Advising and grants: While specific student names or grant details are not provided, his position as a Full Professor indicates active research supervision and likely grant involvement. His lab focuses on advancing AI and communication technologies through interdisciplinary approaches.
Professor
Anna Theakston is a Professor of Developmental Psychology at the University of Manchester where she holds the position of Head of Division for the Division of Psychology Communication and Human Neuroscience. She is also Co-director of the ESRC International Centre for Language and Communicative Development (LuCiD), a major research initiative focused on language development in children. Dr. Theakston completed her undergraduate degree in Psychology at the University of Nottingham and earned her PhD through research at the University of Manchester on early language development in children aged 2-3 years. She subsequently coordinated the Manchester-based Max Planck Child Study Centre before being appointed to her current professorship. Her research focuses on children's early language and communicative development during preschool and early school years, situated within a usage-based framework that emphasizes child-environment interactions and caregiver input. Her work spans multiple areas including early gestural communication, caregiver-child interactions, grammatical construction acquisition, grammatical error origins, inflectional morphology, and syntax-semantics-pragmatics interfaces in complex language development. She frequently conducts crosslinguistic comparisons and employs diverse methodologies from corpus analysis to behavioral experiments, often collaborating with computational modelers. Analysis of her recent publications reveals strong emphasis on children's comprehension and production of complex sentence structures, particularly adverbial and complement clauses, with investigations into how information structure, iconicity, and pragmatic factors influence language development. Her work increasingly examines applications in real-world contexts including schools, nurseries, and cultural institutions, with growing attention to supporting deaf children's communication development and multilingual education. Co-Director, ESRC International Centre for Language and Communicative Development (LuCiD) Active researcher with 111 research outputs including articles, datasets, and book chapters Recipient of research funding from ESRC and Max Planck Institute Professor Theakston supervises numerous PhD students investigating various aspects of language development, with recent projects examining tag questions, cultural institutions' role in language learning for minority populations, science interventions for deaf children, and Modern Foreign Language teaching in multilingual classrooms. Her research has practical impact through tools like the Teacher Toolkit for Teaching Primary MFL in Multilingual Key Stage 2 Classrooms and initiatives supporting deaf children's social communication skills. She maintains active collaborations with researchers across multiple disciplines and institutions, as evidenced by her extensive co-authorship network. Her work contributes to UN Sustainable Development Goals related to quality education and reduced inequalities.
Adjunct Associate Professor
David Palmer is an Affiliate Associate Professor in the Department of Astronomy and Astrophysics. He is affiliated with Los Alamos National Laboratory (LANL). His research focuses on speech recognition, natural language processing, and multilingual systems, with particular emphasis on information extraction from audio and speech data. His work bridges computational linguistics and machine learning, addressing challenges in automated systems for audio comprehension and cross-language processing. Key research interests include robust information extraction from speech transcriptions, error detection in speech recognition, and multilingual processing for operational users. He has contributed to advancements in speaker identification, text preprocessing techniques, and domain adaptation in speech processing systems. His publications span over two decades, reflecting a consistent focus on improving automated systems for handling audio and text data in dynamic environments. While no specific awards or grants are listed, his extensive publication record highlights sustained contributions to the fields of speech technology and computational linguistics. His work at LANL likely involves collaborative research in applied computational sciences, though specific lab affiliations or teams are not explicitly mentioned.
Professor
Katrin Erk is a Professor in both the Linguistics Department and Computer Science Department at the University of Texas at Austin. She is part of the UT Austin NLP and computational linguistics research groups. Her work focuses on computational semantics, particularly exploring word embeddings and contextualized word embeddings to study polysemous words and their meanings in context. She also investigates narrative schemas and their integration with sentence-level meaning representations, often employing logic-based frameworks. Research interests include understanding the nuanced and graded nature of word meanings, how these interact with sentence structures, and the theoretical implications of using distributional models in semantics. She has contributed to advancing methods that bridge formal semantic theories with data-driven approaches derived from large text corpora. Office hours for Fall 2024 are listed, and her contact includes an address at Patton Hall (RLP) and an email. No specific grants or awards are mentioned in the provided text.
Professor
E. Lea Johnston is the Clarence J. TeSelle Professor and Professor of Law at the University of Florida Levin College of Law. She is a leading expert in mental health law, criminal law, and criminal procedure, with her work appearing in top law reviews and peer-reviewed interdisciplinary journals. Her scholarship has been widely cited by legal scholars, appears in leading treatises, and has received attention from courts and social scientists. Her theory of sentencing forms part of the theoretical framework for the standard textbook for forensic psychiatry fellowship programs. Professor Johnston earned her A.B. from Princeton University and her J.D. (cum laude) from Harvard Law School. Before entering academia, she worked as a litigation associate at Arnold & Porter LLP in Washington, D.C., served as director of the Maryland Public Interest Research Group, and clerked for Judge Richard Tallman of the U.S. Court of Appeals for the Ninth Circuit. Johnston's research primarily focuses on the intersection of mental health and criminal justice. Her work examines how mental illness impacts criminal responsibility, competence to stand trial, sentencing, and diversion programs. She has made significant contributions to understanding diminished responsibility doctrines, insanity defenses, mental health courts, and assisted outpatient treatment. Her scholarship often employs interdisciplinary approaches, integrating legal analysis with insights from psychology, psychiatry, and behavioral sciences to develop more humane and just approaches to mentally ill offenders within the criminal justice system. Her publications demonstrate consistent scholarly output with significant impact across multiple disciplines. The trajectory of her work shows an evolution from foundational analyses of legal standards for mentally ill defendants toward more comprehensive reform proposals addressing systemic issues in how the criminal justice system handles mental illness. Elected to American Law Institute (2020) Former Chair of Criminal Justice Section, American Association of Law Schools Former Chair of Law and Mental Disability Section, American Association of Law Schools Member of Legal Scholars Committee, American Psychology-Law Society Professor Johnston has significantly influenced both legal scholarship and practice through her theoretical contributions and practical recommendations. Her work on sentencing theory for mentally ill offenders has been incorporated into forensic psychiatry training materials, demonstrating real-world impact beyond academia. While specific grant information isn't detailed in the provided text, her extensive publication record and leadership roles suggest substantial research support throughout her career. Her scholarship serves as a critical bridge between legal doctrine and clinical mental health practice, offering frameworks that balance therapeutic needs with justice considerations.
Professor
Michael J. Spivey is a Professor of Cognitive Science at the University of California, Merced, affiliated with the School of Social Sciences, Humanities and Arts. His research focuses on understanding human cognition through embodied and dynamic systems approaches, with particular expertise in eye-tracking methodologies and real-time language processing. As a faculty member in the Cognitive and Information Sciences department, he contributes to interdisciplinary research that bridges psychology, linguistics, and neuroscience. Dr. Spivey's educational background includes: Ph.D. in Brain and Cognitive Sciences from the University of Rochester (1996) M.A. in Brain and Cognitive Sciences from the University of Rochester (1995) B.A. from the University of California, Santa Cruz (1991) His research interests span psycholinguistics, visual perception, sensorimotor processing, embodied cognition, and dynamical systems theory. Dr. Spivey investigates how cognitive processes unfold in real-time through eye movements and other behavioral measures, challenging traditional modular views of cognition. His work emphasizes the continuous interaction between perception, action, and cognition, demonstrating how language processing is deeply embedded in our sensorimotor experiences. He has made significant contributions to understanding the time course of language comprehension, the role of visual context in linguistic processing, and the dynamic nature of cognitive representations. Analysis of Dr. Spivey's recent publications reveals a strong focus on embodied and dynamic approaches to cognition. His work spans diverse areas including eye-tracking and mouse-tracking methodologies, team cognition, creativity research, bilingual language processing, and the application of foraging theory to cognitive processes. A recurring theme across these publications is the investigation of real-time cognitive dynamics using continuous behavioral measures. His research increasingly incorporates ecological approaches, examining cognition in more naturalistic contexts while maintaining experimental rigor. The interdisciplinary nature of his work is evident in collaborations across psychology, linguistics, neuroscience, and even music cognition. Dr. Spivey is affiliated with the Center for Human Adaptive Systems and Environments and collaborates with researchers at Western University, Northwestern University, Brown University, and UCLA. His work with students likely focuses on training in advanced methodologies for measuring real-time cognitive processes.
Researcher
Martin Rajman is a Senior Scientist at École Polytechnique Fédérale de Lausanne (EPFL) with multiple affiliations across the institution. He holds positions in the School of Computer and Communication Sciences (SIN - Teaching, SCI IC MR Group, SSC - Teaching) as well as in the Vice Presidency for Strategic Development (VPS Artificial Intelligence) and the Vice Presidency for Academic Affairs (SNAI Administration). He serves as the Executive Director of Nano-tera.ch, a large Swiss Research Program funding collaborative multi-disciplinary projects in Health and the Environment. Rajman's research spans the intersection of artificial intelligence, natural language processing, and information retrieval. His work demonstrates a consistent focus on developing practical applications of computational linguistics and machine learning techniques. Early in his career, he contributed significantly to syntactic parsing, stochastic language models, and vector space representations for text. More recently, his research has expanded into deep learning applications for 3D reconstruction, empathetic conversational agents, and distributed analytics systems. His publications reveal a trajectory from foundational NLP research toward increasingly applied and interdisciplinary work connecting AI with healthcare, environmental monitoring, and human-computer interaction. Analysis of his recent publications (2015-2024) shows a clear evolution toward more applied AI research with strong interdisciplinary connections. While maintaining his core expertise in natural language processing and information retrieval, his work has expanded into computer vision, healthcare applications, and sustainable computing. The publications demonstrate increasing collaboration across disciplines, with applications in medical imaging, mental health support systems, environmental monitoring, and human-centered AI. His leadership role in the Nano-tera.ch program reflects this interdisciplinary approach, connecting computing research with real-world challenges in health and environmental contexts. Rajman has mentored several PhD students including Ailomaa Marita, Eckard Emmanuel, Melichar Miroslav, and Veselý Martin. His research has been supported through the Nano-tera.ch program, which has funded more than 100 research projects with over 95 million CHF in public funding. He has also managed more than 20 European projects during his tenure as Director of the EPFL Global Computing Center. As Executive Director of Nano-tera.ch, Rajman leads a significant research initiative connecting EPFL with national and international partners. His work bridges academic research with industry applications, notably through collaborations with eBay on product ranking technology and with Elsevier on article recommendation systems. His leadership extends to managing large-scale research programs while maintaining an active research agenda and mentoring the next generation of computer scientists.
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