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José A. Pérez DíezView profile

Lecturer

• Early Modern Drama
• Jacobean Drama
• Shakespeare Studies
• +12 more

José A. Pérez Díez is a Lecturer in Early Modern Drama at the School of English, University of Leeds, where he also serves as Director of Postgraduate Taught Programmes and Programme Leader for the MA in English Literature. He is actively involved in major editorial projects, including The Complete Works of John Marston (OUP) and The Revels Plays , and leads the Playhouse Lab, a practice-as-research initiative. Licenciado, Complutense University of Madrid MA in Shakespeare and Theatre, University of Birmingham PhD, University of Birmingham PGCert in Academic Practice, Open University His research centers on Jacobean drama, particularly the works of John Marston, John Fletcher, and Shakespeare, with a strong focus on Anglo-Spanish cultural relations in the Renaissance. He investigates how Spanish imaginative literature influenced English drama through diplomatic, bibliographic, and performance channels. His Leverhulme-funded project traced the material circulation of Spanish books in Jacobean England, analyzing ownership, patronage, and intellectual networks. He also engages deeply with theatre history and performance studies, having worked as dramaturg for the Royal Shakespeare Company and participated in over twenty Shakespearean productions. The recent articles reflect a consistent focus on textual editing, performance, and cross-cultural literary influence. His publications span critical editions, scholarly editing, book history, and dramaturgy, emphasizing both philological rigor and practical engagement with early drama. The keywords and sub-fields highlight interdisciplinary work across literature, history, bibliography, and theatre practice. His scientific recognition includes the prestigious Leverhulme Early Career Fellowship (2020–2023). He is also professionally active as Joint Chair of the British Shakespeare Association and Events Organiser for the Malone Society. José supervises postgraduate research and teaches across undergraduate and postgraduate levels, integrating performance workshops into his pedagogy. He leads the Playhouse Lab, which hosts script-in-hand performances to explore early drama practically. His work bridges academic scholarship and theatrical practice, contributing significantly to both the study and staging of Renaissance drama.

Jinchuan XingView profile

Professor

• Mobile Elements
• Human Genomic Variation
• Evolutionary Genetics
• +14 more

Jinchuan Xing is a Professor at Rutgers, The State University of New Jersey, where he leads the Xing Lab of Genomics. His research focuses on human genomic variation, mobile DNA elements, evolutionary and population genetics, and their implications for human disease. He integrates computational and experimental methods to study genome-wide variation, with applications in disease gene identification and genomic technology development. His research interests include: Mobile DNA element biology Human demographic history and population diversity Disease gene identification using whole-exome and whole-genome sequencing High-altitude adaptation genetics Transposable element regulation and expression piRNA and small RNA pathways His recent publications highlight a strong trend in reproductive genomics, particularly in identifying genetic risk factors for embryo aneuploidy in IVF patients, using advanced sequencing technologies. Other work spans evolutionary genomics in diverse species (bats, moths, Drosophila), structural variation in neurodevelopmental disorders, and proteogenomic discovery. His lab actively develops and applies bioinformatic tools for variant analysis and gene prioritization. Scientific awards and honors are not explicitly mentioned in the provided text. Jinchuan Xing advises several graduate students, including Nan Wang, Siqi, Ellie Lu, and Tongji Xing. His lab has received significant funding, including an R01 grant from NICHD on aneuploidy risk, a grant from the Center for Human Evolutionary Studies, and a Life Sciences Alliance Pilot Seed Funding grant in collaboration with the Department of Statistics. These grants support research in fertility genomics, disease gene discovery, and genomic tool development. The Xing Lab of Genomics is an active research group conducting interdisciplinary studies combining genomics, bioinformatics, and molecular biology. The lab welcomes new members regularly, including master’s and PhD students, and collaborates across departments. Current projects include understanding the genetic basis of meiosis, fertility, and high-altitude adaptation, as well as developing Markovian gene networks for disease gene discovery.

Tillman WeydeView profile

Academic

• Machine Learning
• Signal Processing
• Data Analysis
• +5 more

Dr. Tillman Weyde is a Reader in the Department of Computer Science at City, University of London , where he has been employed since 2021. He leads the Machine Intelligence and Media Informatics Research Group and is a member of the Machine Learning Group . Prior to this, he served as Senior Lecturer (2009–2021) and Lecturer (2005–2009) at City, and worked as a researcher at the University of Osnabrück (2001–2005), coordinating the MUSITECH project. His academic background includes PhD in Music Technology (2002), MSc in Computer Science (1999), and MSc in Mathematics, Music, Philosophy & Pedagogy (1994), all from the University of Osnabrück. Research Focus: Machine learning and signal processing methods for data analysis with applications in finance, audio, NLP, music, health, security, and education. His recent work emphasizes inductive biases in neural networks for rule-learning, extrapolation, generalization, and interpretability. Grants & Projects: Principal Investigator for the AHRC-funded Digital Music Lab (2012–2017) and Integrated Audio-Symbolic Model of Music Similarity (2017–present). Co-investigator in Innovate UK and EPSRC projects on safer gambling ( Advancing Consumer Protection , 2015–2018) and Raven (2012–2021). Collaborations: Affiliated with the Institute of Cognitive Science (Osnabrück), Intelligent Systems Research Laboratory (Reading), and the MPEG Ad-Hoc Group on Symbolic Music Representation. Awards: Co-author of the 2000 Comenius Medal-winning educational software Computer Courses in Music Ear Training and co-editor of the Osnabrück Series on Music and Computation . Publications: Over 150 peer-reviewed works including conference papers, journal articles, and book chapters, focusing on interdisciplinary applications of machine learning in music, health, and finance. Students: Supervised 13 PhD students across topics like grammar bias in neural networks, emotion recognition from audio, extrapolation behavior in neural networks, relation-based patterns, legal text parsing, and more.

Andrew MelnykView profile

Professor

• Philosophy of Mind
• Philosophy of Science
• Metaphysics
• +3 more

Andrew Melnyk is a Professor in the Department of Philosophy at the University of Missouri . His research focuses on philosophy of mind , philosophy of science , and metaphysics , particularly defending physicalism (or materialism) through the lens of realization theory. He is a member of the Heterodox Academy and the Academic Freedom Alliance . Education : B.A. in Literae Humaniores, Oxford University (1985) B.Phil. in Philosophy, Oxford University (1987) D.Phil. in Philosophy, Oxford University (1991) Research Interests : Defending physicalism via realization theory Philosophical methodology and naturalism Mind-body problem and phenomenal consciousness Reductionism vs. non-reductive physicalism Empirical evidence for materialism in neuroscience His publications, including the 2025 book Phenomenal Properties and the Intuition of Distinctness , critically engage with two-dimensionalism, supervenience, and the scientific plausibility of physicalism. His teaching includes Philosophy of Mind and Philosophy of Science courses at both undergraduate and graduate levels.

• Arabic Language Teaching
• Arabic Literary Anthologies
• Arabic Grammar
• +3 more

Prof. Atik Aydın is a full-time Professor in the Department of Arabic Language and Rhetoric at Ankara Social Sciences University's Faculty of Theology. He obtained his PhD from Ankara University (2004) after completing degrees at Marmara University (BA, 1993) and Sakarya University (MA, 1996). Before joining Ankara Social Sciences University, he taught at İnönü University (2010-2022) and conducted research at the University of Nottingham (2018). He also served at Qatar's Ministry of Defense School of Foreign Languages (2019-2022). His research spans: Arabic language pedagogy and grammar systems Historical development of Arabic literature Ottoman-era Arabic manuscripts Quranic linguistic analysis His publications focus on Arabic syntax, educational methodologies, and classical text analysis, with recurrent themes in Quranic exegesis and Ottoman linguistic heritage. Recent works analyze pedagogical frameworks (2020) and rhetorical structures in Islamic texts (2022). He advises graduate students on topics like classical Arabic poetry metrics and Quranic reception history. He co-developed the Abjad Arabic textbook series (2016-2021) and participated in a national project for Arabic language education materials.

• Linguistics
• Cognitive Linguistics
• Corpus Linguistics
• +5 more

Laura Alexis Janda is a Professor of Russian Linguistics at the UiT The Arctic University of Norway , where she has worked since 2008. She is a member of the CLEAR research group (Cognitive Linguistics: Empirical Approaches to Russian) and leads the THREAT-DEFUSER project funded by the Norwegian Research Council. Her academic profile spans Cognitive Linguistics , Construction Grammar , and Corpus Linguistics , with a focus on Russian, Slavic, and Sámi languages . Education: PhD in Slavic Linguistics & Certificate in Teaching ESL, UCLA (1984) Visiting Fellowships at Princeton University and UNC Chapel Hill Training in Persian, Czech, and Russian methodologies Research Interests: Janda’s work bridges constructional networks and grammatical profiling in Slavic languages, with emphasis on aspect , case semantics , numeral classifiers , and political discourse analysis . She explores how morphological units like Russian prefixes function as verb classifiers and investigates language change in Sámi and Russian contexts. Publication Trends: Recent articles analyze ChatGPT’s grammatical interpretation , constructicon architecture , and ideological messaging in Putin’s speeches . Her research integrates quantitative methods and FAIR data principles to address both theoretical and pedagogical challenges. Awards & Grants: 2021 Honorary Doctorate (University of Turku, Finland) 2018 Member of the Norwegian Academy of Science and Letters 2017 Open Data Champion (SPARC Europe) 2013-2015 Norwegian Research Council grant for 'Birds & Beasts: Shaping Events in Old Russian' 2007-2011 Norwegian Research Council grant for 'Exploring Emptiness: Russian Verbal Morphology and Cognitive Linguistics' Collaborative Networks: Janda mentors international researchers and collaborates with linguists in Russia, Norway, and the U.S. She co-developed the Russian Constructicon and Construxercise! pedagogical tool, emphasizing interdisciplinary applications of linguistic theory. Labs & Projects: She co-founded the Tromsø Construction Lab , advancing constructicon resources for Russian and Sámi languages. Her THREAT-DEFUSER project examines perceived threats in Russian and Norwegian political discourse.

Jennifer ReedView profile

Professor

• Systems Biology
• Metabolic Engineering
• Microbial Interactions
• +12 more

Jennifer Reed is the Karen and William Monfre Professor and Harvey D. Spangler Faculty Scholar at the University of Wisconsin Madison College of Engineering , with primary and additional affiliations in the Department of Chemical and Biological Engineering and Biomedical Engineering . Her research focuses on systems biology, metabolic engineering, and microbial interactions using computational and experimental approaches. Her work involves metabolic flux analysis , constraint-based modeling , and genotype-phenotype relationships , with applications in bioremediation , health , and chemical production . The research integrates experimental data to refine microbial network models and develop strain design algorithms. Recent articles highlight trends in computational methods for strain design , metabolic engineering , and microbial community analysis . Funding sources include the National Science Foundation , U.S. Department of Energy , and Gordon and Betty Moore Foundation , among others. Grants and research support include funding from the National Science Foundation , U.S. Department of Energy , Great Lakes Bioenergy Research Center , W.M. Keck Foundation , SERDP , and Gordon and Betty Moore Foundation .

• Natural Language Processing
• Computational Linguistics
• Artificial Intelligence
• +5 more

Marie Candito is a Lecturer at the School of Linguistics, Paris Cité University. She serves as Deputy Director of the Laboratoire de Linguistique Formelle (LLF, CNRS) since January 2025 and Head of the M2 Computational Linguistics program at Paris Cité University. Her research focuses on natural language processing, computational linguistics, and linguistic abilities of large language models. Current Projects : Co-PI of ANR SELEXINI (2021-2025) and scientific coordinator for LLF in ANR PANTAGRUEL (2023-2025) Past Projects : PI of ANR ASFALDA-French FrameNet (2013-2016), scientific coordinator for ANR PARSEME-FR (2015-2019), and member of ANR SEQUOIA (2010-2013) Her work involves measuring and mitigating biases in language models, inducing semantic lexicons from corpora, and studying human vs. LLM word associations. She supervises PhD students including Maria Andueza Rodriguez, Anna Mosolova, and David Kletz.

Tania AllenView profile

Professor

• Critical Cartography
• Design Research
• Participatory Design
• +6 more

Tania Allen is an Interim Department Head and Professor of Media Arts, Design and Technology at North Carolina State University's College of Design. She serves as a Faculty Fellow with the Center for Geospatial Analytics and co-directs the design research group co-lab, which focuses on critical mapping as a participatory design research tool. Her work bridges academic research with practical applications in community engagement and social justice. Her educational background includes: B.A. in History with Minors in Fine Arts/Graphic Design from Washington University Certificate in Visual Communication from the School of the Art Institute of Chicago Master of Graphic Design from North Carolina State University Allen's research centers on critical cartography and critical mapping as tools for design research. Building on theories from anthropology, action research, placemaking, and participatory design, her work seeks to 'thicken' the way data is visualized and the stories at the core of data collection and communication. Her approach emphasizes the reciprocal activity of encoding and decoding, bridging the researcher's perspective with the subject's lived experience. She challenges assumptions embedded in mapping processes while embracing cartography as both an analytic and synthetic research tool. Analysis of her publication trajectory reveals a clear evolution from foundational explorations of critical mapping toward concrete applications addressing social justice issues. Her recent work increasingly focuses on Confederate memorialization, urban development, and oppressive infrastructures, demonstrating her commitment to using design as a catalyst for community engagement and social change. This progression reflects growing sophistication in applying critical cartography to address systemic inequities. As a Faculty Fellow with the Office of Faculty Development, Allen helped create an online certificate program focused on higher-order thinking through critical and creative pedagogy. Her contributions to the TH!NK initiative have transformed campus teaching culture toward student-centered instruction that promotes critical thinking across disciplines. She has also taught Design Thinking, focusing on creative research strategies for beginning design students. Allen co-directs the cross-institutional colloquium 'Oppressive Infrastructures: Examining Systems of (in)Equity In/Through/By Data,' which investigates how data systems perpetuate inequality. Through her professional practice, she has worked with organizations including the Chicago Botanic Garden, Boston Symphony Orchestra, Accenture, MIT, and Harvard University, consistently focusing on design as a participatory process that empowers communities to address social issues and create change from the ground up.

Alexander SteenView profile

Assistant Professor

• Computational Logic
• Automated Reasoning
• Theoretical Computer Science
• +7 more

Alexander Steen is an Assistant Professor (Juniorprofessor) at the University of Greifswald within the Institute of Mathematics and Computer Science. His research focuses on computational logic, automated reasoning, and theoretical computer science, with significant contributions to higher-order logic (HOL) and non-classical reasoning systems. He leads the development of the Leo-III automated theorem prover, a versatile system supporting classical HOL with choice, polymorphic logics, and higher-order modal/deontic logics. Steen's academic journey includes a Dr. rer. nat. (summa cum laude) from Freie Universität Berlin (2018), followed by post-doctoral work at the University of Luxembourg (2018-2021) as a principal investigator for the AuReLeE project on legal reasoning automation. He holds a 2024 nomination for the University of Greifswald Teaching Award and was elected Fellow of the Academy of Sciences and Humanities in Hamburg (2022). Key Research Areas: Higher-Order Logic, Automated Reasoning, Non-Classical Logics, Legal Tech, Formal Methods in AI, Computational Ethics. Major Projects: Leo-III (DFG-funded automated prover), AuReLeE (FNR-funded legal reasoning), MET (modal logic embedding tool). His recent publications (2025-2022) explore diverse applications of HOL in non-classical reasoning, legal formalization, argumentation frameworks, and TPTP infrastructure extensions. Steen actively contributes to AI governance as co-speaker of the GI AI section and deputy member of Greifswald's Senate. He also engages in science communication through works like the 2024 science comic book Was wissen wir schon (What Do We Know?), featuring his automated reasoning research. Scientific Honors: CLAR 2023 Best Paper Award, IRIS 2020 LexisNexis Best Paper Award, CASC-27 LTB Division Winner, Woody Bledsoe Travel Awards (CADE 2018, 2016), GI Junior Fellowship (2018). Advising: Supervises ongoing PhD/MSc/BSc theses in logic-based AI, modal reasoning, and legal tech at University of Greifswald and Freie Universität Berlin.

• Software Engineering
• Workflow Management Systems
• Image Analysis
• +2 more

Michał Turek is a Professor at the Department of Applied Informatics within the Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering at AGH University of Science and Technology in Kraków, Poland. His primary workplace is located in room 303a of building C-2, and he maintains active contact through email (mitu@agh.edu.pl) and phone (+48 12 617 52 03), indicating current academic engagement. His research spans Software Engineering with particular emphasis on Workflow Management Systems integration with industrial applications, Image Analysis for 3D surface inspection, and Agile Methodologies implementation. Turek has pioneered innovations in Scrum adaptation for multi-project environments and software product lines, while developing formal verification frameworks for business processes and service-oriented architectures. His work bridges theoretical computer science with practical industrial solutions, especially in automated damage identification systems and workflow optimization. Analysis of his 15 most recent publications reveals consistent focus on workflow system intelligence (2020-2022), with significant contributions to automatic correction mechanisms and smart procedure integration. Earlier works (2010-2016) demonstrate deep expertise in formal verification methods, Scrum economics, and 3D surface analysis techniques. The publications show interdisciplinary convergence between software engineering, computer vision, and industrial automation, with recurring themes of system resilience and process optimization across both English and Polish scholarly outputs.

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +6 more

Prof. Fabio Galasso is a Full Professor in the Department of Computer Science at Sapienza University of Rome, where he heads the Perception and Intelligence Lab (PINLab). His research focuses on fundamental innovation in computer vision and machine learning, with particular emphasis on distributed intelligent systems, perception frameworks, and general intelligence within sustainable and interpretable AI contexts. His research interests span multiple domains of computer vision including video segmentation , motion forecasting , distributed intelligent systems , and shape reconstruction . Galasso's work emphasizes sustainable AI approaches that operate within constrained computational resources while maintaining interpretability and verifiability. His research bridges theoretical foundations with practical applications across retail, smart cities, and industrial settings. His recent publications demonstrate a clear progression toward increasingly complex human motion understanding and forecasting, with a strong emphasis on real-world applications. The research trajectory shows movement from foundational video segmentation techniques toward sophisticated motion prediction systems and anomaly detection frameworks that integrate multiple modalities. Key themes include temporal consistency, computational efficiency, and practical deployability in resource-constrained environments. His scientific achievements have been recognized with prestigious awards: 2019 IoT/WT Innovation World Cup 2019 Digital Champions Award 2018 Deutscher Digital Award Galasso has coordinated significant research initiatives including a Marie Sklodowska-Curie Actions project (Horizon 2020) and served as Principal Co-Investigator in multiple German-funded projects from the Ministry of Education and Ministry of Economics. His industry experience includes founding and directing OSRAM's Computer Vision Department in Munich, where he led R&D efforts connecting AI research with smart lighting applications, resulting in successful innovation transfers like the award-winning VISN product. He leads the Perception and Intelligence Lab (PINLab) at Sapienza University of Rome, fostering research that spans fundamental computer vision techniques to practical implementations in retail, smart cities, and industrial applications. The lab maintains strong connections with both academic institutions (including previous collaborations with University of Cambridge and Max Planck Institute) and industry partners.

• Gene Transcription
• Epigenetic Regulation
• RNA Regulation
• +1 more

Huanhuan CUI is a Research Associate Professor in the Department of Biology within the School of Life Sciences at Southern University of Science and Technology (SUSTech) in Shenzhen, China. She joined SUSTech in December 2018 and serves as a master's supervisor, contributing to both research and graduate education in molecular biology and genetics. Educational Background: PhD in Biology, Free University of Berlin (2011.09-2016.04) MS in Animal Genetics, Northwest A&F University (2008.09-2010.06) BE in Bioengineering, Northwest A&F University (2004.09-2008.06) Dr. CUI's research focuses on the mechanisms and method development of gene transcription and epigenetic regulation, with particular emphasis on RNA translation control. Her work spans multiple biological systems including cancer biology, developmental biology, and cardiovascular research, demonstrating a strong interdisciplinary approach that integrates molecular biology, genomics, and bioinformatics techniques. She has made significant contributions to understanding chromatin remodeling, transcriptional regulation, and RNA processing mechanisms. Dr. CUI's publication record shows a consistent trajectory of high-impact research, with publications in prestigious journals including Nature Communications, Nucleic Acids Research, and Cellular & Molecular Immunology. Her work demonstrates expertise in CRISPR-based technologies, epigenetic regulation, and multi-omics approaches to studying complex biological processes. Before joining SUSTech, Dr. CUI held positions as a Clinical Research Manager at BGI Genomics (2017.09-2018.11), a PostDoc at Charite Universitaetsmedizin Berlin (2016.05-2017.06), and a Research Assistant at Humboldt University of Berlin (2010.09-2011.08), building a diverse research background that bridges basic science and clinical applications.

• Theoretical Linguistics
• Formal Semantics
• Formal Pragmatics
• +6 more

Sophia A. Malamud is an Associate Professor in the Department of Computer Science at Brandeis University, where she directs the Meaning In Language Research Group (MILa) and is affiliated with the Language & Linguistics Program. Her research specializes in theoretical linguistics with a focus on formal semantics, formal pragmatics, discourse-syntax interactions, and semantics-pragmatics interface. Her educational background includes a Ph.D. in Linguistics with a dissertation on Semantics and pragmatics of arbitrariness and an M.A. in Mathematics exploring statistical decision theory in Entropy as relevance: maximizing entropy and minimizing loss . Malamud's research investigates discourse coherence, word order variations, indexicality, semantics of impersonals/plurals, speech acts, and utterance modifiers. She leads NSF-funded projects creating annotated corpora of spoken Russian (including the BiRCh Corpus), examining bilingual acquisition and heritage language phenomena. Her work employs corpus linguistics, experimental methods, and formal modeling. Her publications demonstrate consistent focus on pragmatic computation models, conversational dynamics, and cross-linguistic semantics, with frequent examination of Russian, Mandarin, and Greek data. Key themes include commitment avoidance strategies, conversational scoreboard modeling, and formal analyses of particles/pronouns. Awards include: NSF Grant BCS-1651083 for BiRCh Corpus development Mandel Foundation Faculty Grant for heritage language research Theodore and Jane Norman Award (2018) Multiple Brandeis Provost Research Grants Malamud has advised 8+ graduate/undergraduate theses on topics including heritage Russian pragmatics, utterance particles, reduplication, and distributivity. She collaborates internationally on corpus projects and directs research teams at Brandeis' Laboratory for Linguistics and Computation.

Chandi WitharanaView profile

Assistant Professor

• Remote Sensing
• Geospatial Analysis
• Arctic Permafrost Mapping
• +5 more

Dr. Chandi Witharana is an Assistant Professor in the Department of Natural Resources and the Environment at the University of Connecticut's College of Agriculture, Health, and Natural Resources. Previously, they served as Assistant Professor in Residence (2020-2023), Assistant Research Professor (2018-2020), and Visiting Assistant Professor (2016-2018) at UConn. Their academic journey includes a Postdoctoral Research Fellowship at SUNY Stony Brook (2014-2016) and graduate work at UConn where they earned their PhD in Remote Sensing in 2014. Dr. Witharana teaches courses in high-resolution remote sensing, geospatial analysis, and introductory geomatics. Dr. Witharana's educational background includes: PhD in Remote Sensing, University of Connecticut (2014) MS in GIScience, University of Connecticut (2009) BS in Geology, University of Peradeniya, Sri Lanka (2005) Dr. Witharana's research focuses on methodological developments for analyzing large volumes of multi-modal remote sensing data for environmental, industrial, and agricultural applications, with special emphasis on Arctic Permafrost remote sensing. They harness sub-meter resolution satellite imagery, AI, and high-performance computing resources to map permafrost landforms, monitor thaw disturbances, and assess risks to human-built infrastructure in the Arctic. Their work extends beyond research to include innovative applications of remote sensing in K-12 STEM education through imagery-enabled lesson plans. Dr. Witharana aims to use cutting-edge geospatial technologies as transformative learning instruments to help students understand complex human-environment interactions. The recent publications of Dr. Witharana demonstrate a strong focus on applying advanced AI and remote sensing techniques to Arctic permafrost monitoring and infrastructure risk assessment. Their work increasingly incorporates vision transformers and deep learning models for more accurate detection of permafrost features and unhealthy tree crowns. There's a clear trend toward developing scalable geospatial datasets with standardized approaches, particularly for retrogressive thaw slumps. Many publications address practical applications including power outage risk modeling, forest management for storm resistance, and infrastructure monitoring in changing Arctic landscapes. The research shows growing interdisciplinary collaboration across environmental science, computer science, and engineering domains. Dr. Witharana has secured significant research funding as PI or Co-PI on numerous grants totaling over $14 million, including: NSF's Permafrost Discovery Gateway project ($3,000,000) Google-funded research on tracking Arctic permafrost thaw ($5,000,000) NSF's role of capillaries in the Arctic hydrologic system ($2,000,000) USDA projects on drone imaging for nutrient deficiency detection ($200,000) Eversource Energy projects on tree risk modeling ($275,000) As an educator, Dr. Witharana mentors students through research projects funded by these grants and teaches specialized courses in remote sensing and geospatial analysis. They serve as Director of the Remote Sensing & Geospatial Data Analytics Graduate Program and as a Steering Committee Member for UConn's Data Science Masters Program. Dr. Witharana is also an Editorial Advisory Board Member for the ISPRS Journal of Photogrammetry and Remote Sensing and regularly reviews proposals for NSF and other agencies. Their research group leverages high-performance computing resources including Frontera/NSF and XSEDE allocations for large-scale geospatial analysis. Dr. Witharana leads research teams focused on Arctic permafrost monitoring and geospatial AI applications, collaborating with institutions including University of Alaska-Fairbanks, Woodwell Climate Research Center, and UC Santa Barbara. Their work involves developing advanced workflows for processing satellite imagery and implementing machine learning models for environmental monitoring. The research group actively engages in developing educational applications of remote sensing technology, particularly for K-12 STEM education.