جست‌وجوی استاد و پژوهشگر

Johanna Mattissenمشاهده پروفایل

پژوهشگر ارشد

• Linguistic Typology
• Legal Linguistics
• Morphosyntax
• +۷ مورد دیگر

Johanna Mattissen is a Research Fellow in the Department of Linguistics at the University of Cologne, specializing in European Legal Linguistics. Her office is located at Bernhard-Feilchenfeld-Str. 11, 50969 Köln, with postal address Albertus-Magnus-Platz, 50923 Köln. Contact is available by appointment via telephone (+49-221-470-3012) or email. Her research spans: Linguistic typology with focus on polysynthesis, morphological complexity, and endangered languages (Nivkh, Japanese, Laz, Greenlandic, Basque) Legal linguistics analyzing multilingual EU legislation, coordination phenomena, and terminology in European law Cross-linguistic analysis of discourse markers, modality, and reference-tracking in legal texts Machine translation challenges in human vs neural approaches for specialized domains Her recent publications (2021-2023) predominantly examine linguistic structures in EU legal instruments, investigating coordination ambiguity, terminological precision, and multilingual equivalence in binding texts. Earlier works establish foundations in polysynthesis typology and morphological theory.

• Multi-agent Systems
• Intelligent Tutoring Systems
• Artificial Intelligence in Education
• +۵ مورد دیگر

Ricardo Azambuja Silveira is a Professor at the Federal University of Santa Catarina, Brazil, with a distinguished research career spanning over two decades in the fields of multi-agent systems, intelligent tutoring systems, and semantic web technologies for education. His work bridges artificial intelligence with educational technology, creating innovative frameworks for adaptive learning environments and intelligent educational agents. Dr. Silveira's research interests focus on developing agent-based approaches to enhance educational experiences through technologies like BDI (Belief-Desire-Intention) architectures, ontology-based systems, and multi-context reasoning. His work particularly emphasizes the integration of intelligent agents with learning management systems to create personalized educational experiences. His recent publications demonstrate a continued evolution from foundational multi-agent frameworks to sophisticated neural-symbolic integrations and context-aware educational technologies. Throughout his career, he has published over 60 scholarly works, with consistent output from 2001 through 2024, demonstrating sustained research productivity. His publication trends show a clear trajectory from early work on JADE (Java Agent Development Framework) for distance education to current research on neural-symbolic integration in agent systems. The majority of his publications appear in prominent conferences like PAAMS, MICAI, and ICAART, reflecting his standing in the multi-agent systems community. Dr. Silveira has mentored numerous researchers who have become his frequent collaborators, including Arnoldo Uber Junior, Rodrigo Rodrigues Pires de Mello, and Thiago Ângelo Gelaim. His research has been supported through various academic grants that enabled the development of frameworks like Sigon (a multi-context system framework) and iEnsemble (for committee machine learning). He has been actively involved in the organization of academic events, particularly the Methodologies and Intelligent Systems for Technology Enhanced Learning (MIS4TEL) conference series, where he has served as both participant and organizer. His work contributes significantly to the theoretical foundations and practical implementations of intelligent educational technologies.

• Big data analytics
• Data analysis
• Data management
• +۸ مورد دیگر

Daniele Apiletti is an Associate Professor at the Polytechnic University of Turin , affiliated with the Department of Control and Computer Engineering (DAUIN). He serves as a member of the Interdepartmental Center SmartData@PoliTO and acts as Academic Advisor for the Master's degree program in Data Science and Engineering. Research Groups: DBDM - Database and Data Mining Group (DAUIN) ERC Sectors: Algorithms, Artificial Intelligence, Machine Learning, Web and Information Systems Research Interests span Big Data Analytics, Data Science, Machine Learning, Computer Vision, and Quantum Computing. His work focuses on integrating data-driven and theory-guided approaches for heterogeneous data querying, cloud continuum machine learning, and spatio-temporal models for crisis management. Recent Publications highlight trends in medical image segmentation, predictive industrial modeling, and fault-tolerant data systems. Key subfields include AI in healthcare, scalable manufacturing analytics, and vision-language models for game tutorials. Teaching roles include course ownership of Big Data: Architectures and Data Analytics and Internships across multiple academic years. He has collaborated on courses in Data Science, Database Technologies, and Data Management. PhD Students Supervised: Etibar Vazirov (Cloud Continuum Machine Learning) Gabriele Scaffidi Militone (Cloud Storage Microservices) Daniele Rege Cambrin (Spatio-Temporal Ecology Models) Simone Monaco (Theory-Guided Data Science) Research Projects include commercial contracts on: - Natural language querying of corporate research archives - National tourism ecosystem platforms - AI for thermotechnical system design - Machine Learning in clinical trials and supply chains

Matthew Collinsonمشاهده پروفایل

مدرس ارشد

• Logic
• Theoretical Computer Science
• Information Security
• +۱۲ مورد دیگر

Matthew Collinson is a Senior Lecturer in Computing Science at the University of Aberdeen, where he also serves as Head of Computing Science and Academic Line Manager. He holds an affiliation with the Scottish Informatics and Computer Science Alliance (SICSA) and leads the EPSRC-funded project SSPEDI (Supporting Security Policy with Effective Digital Intervention). Education: BSc Mathematics, University of Edinburgh (1997) MSc Mathematical Logic, University of Manchester (1998) PhD Computer Science, University of Manchester (2003) Research Interests: His research spans theoretical computer science and cybersecurity , focusing on non-classical logics (intuitionistic, modal, substructural), semantics of computation , concurrency theory , and type theory . He applies these foundations to information security , particularly in modelling security policies, access control, and the economics of cybersecurity decisions. His work integrates formal verification , simulation tools (e.g., Gnosis), and game-theoretic models . Publications Trends: Recent publications (2016–2022) emphasize human-centred security , exploring how persuasion and behavioural interventions can reduce cybersecurity vulnerabilities. Earlier works (2008–2015) concentrate on mathematical systems modelling , layered graph logics , and trust domains , bridging high-level policy and low-level system configurations. Projects & Grants: SSPEDI (2017–2020, EPSRC): Human dimensions of cybersecurity policy compliance. ALPUIS (EPSRC consortium): Algebra and logic for security policy and utility. Trust Domains (RCUK/TSB, 2011–2014): Framework for modelling secure information sharing. Seconomics (EU FP7, 2012–2015): Socio-economic impacts of cybersecurity regulation. PhD Supervision: He has successfully supervised PhD students including Kevin McDonald (2014), Barry Taylor (2015), and Robert (Bob) Duncan (2016), whose theses addressed logic-based security architectures, vulnerability analysis, and cloud stewardship respectively. Labs & Teams: His research is conducted within the Computing Science section of the School of Natural and Computing Sciences, leveraging collaborations with National Grid, HP Labs, and other academic partners.

Dominique Unruhمشاهده پروفایل

استاد

• Quantum Computing
• Quantum Cryptography
• Post-Quantum Cryptography
• +۵ مورد دیگر

Dominique Unruh is a Professor at RWTH Aachen University , leading the Chair for Quantum Information Systems . Additionally, they hold a Professorship in Cryptography at the Institute of Computer Science of the University of Tartu , Estonia. Their research spans quantum computing , quantum cryptography , post-quantum cryptography , and formal verification of cryptographic protocols and programs. Research Focus : Quantum programs, zero-knowledge proofs, lattice-based cryptography, and quantum random oracle model. Key Contributions : Advancements in NTRU encryption efficiency, quantum Hoare logic, and rewinding techniques for security proofs. Tools : Active development in the EasyCrypt framework for cryptographic verification. Email : unruh@cs.rwth-aachen.de

Renata Iwickaمشاهده پروفایل

پژوهشگر

• Nationalism
• East Asian Cultural Studies
• Cultural Anthropology
• +۶ مورد دیگر

Dr. Renata Iwicka is a researcher at Jagiellonian University's Department of Comparative Civilization Studies, Faculty of Oriental Studies. Specializing in Japanese and Sinology within literary studies, she holds a PhD in Cultural Studies and maintains significant translation work of Japanese literature from the Taishō period, particularly focusing on Akutagawa Ryūnosuke. Key Research Areas: Nationalism in East Asia, Japanese-Korean cultural relations, social media impact on national identity, and demonology in historical contexts. Academic Contributions: Edited volumes on male image representations, explored post-war reconciliation mechanisms through media, and analyzed the evolution of masculinity in Korean television. Publications Trend: Recent works focus on internet-era nationalism (Kamikakushi, Dokdo disputes) and cultural cross-pollination between Japan and Korea, with methodological approaches combining narrative analysis, cultural anthropology, and media studies. Awards: Pro Arte Docendi Award (2016/17), ID.UJ research funding (2023) Projects: Neonationalism on the Internet, Zainichi ethnic minority studies, and historical analysis of Japanese demonology. Her non-scientific interests include physics and toxicology, while maintaining active research trips and interdisciplinary approaches blending literary analysis with cultural theory.

• Software Security
• IoT Security
• Software Supply Chains
• +۲ مورد دیگر

Mojtaba Moazen is a PhD student and researcher at the Division of Theoretical Computer Science , part of KTH Royal Institute of Technology in Sweden. He is actively involved in the WASP – Wallenberg AI, Autonomous Systems and Software Program and the NEST CyberSecIT project, focusing on securing IoT applications and software supply chains. His work bridges academic research with critical real-world cybersecurity challenges. Education: PhD (ongoing) in Theoretical Computer Science, KTH Royal Institute of Technology Master of Science in Information Technology, Sharif University of Technology Bachelor of Science in Computer Engineering, K. N. Toosi University of Technology Research Interests: Mojtaba specializes in software security , IoT security , and software supply chains , with a focus on developing robust security mechanisms for emerging technologies. His recent publications highlight advancements in Android malware detection and continuous integration testing. Courses Assisted: Applied Cryptography (DD2520) Computer Security (DD2395) Internet Programming (DD1386) Language-Based Security (DD2525) Programming Techniques (DD1310)

Alessandro Del Tombaمشاهده پروفایل

پژوهشگر

• Historical Linguistics
• Indo-European Studies
• Oriental Studies
• +۴ مورد دیگر

Alessandro Del Tomba is a Tenure-Track Researcher in Linguistics and Glottology at Sapienza University of Rome, specializing in historical linguistics, Indo-European studies, and Central Asian philology. He holds a PhD in Linguistics from Sapienza and Comparative Indo-European Linguistics from Leiden University. Historical linguistics Indo-European studies Eastern Iranian philology Language contact theories His research focuses on Khotanese and Tocharian languages, with recent publications analyzing manuscript transmission, morphological variation, and phonological developments. He serves as Principal Investigator for the FIS project "Khotanese language and texts in contexts (KhoTxt): A multimodal approach to the classification and periodisation of the Khotanese language and its texts within the cultural and historical framework of medieval Central Asia". He teaches General Linguistics at undergraduate levels and Linguistics courses at the graduate level in Modern Philology. Active in international academic networks, he participates in conferences across Italy, Europe, and Asia.

Kobus Barnardمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Scientific Applications
• +۳ مورد دیگر

Kobus Barnard is a Professor in the Department of Computer Science at the University of Arizona, with his office located in GS 708. His research bridges computer vision, machine learning, and interdisciplinary scientific applications across diverse domains. Education: Ph.D. from Simon Fraser University (1999) His research interests focus on extracting meaningful insights from complex data through computer vision and probabilistic modeling. Key areas include machine learning for environmental monitoring (flood detection, plant disease analysis), social dynamics (interpersonal coordination, emotional coregulation), astronomy (transient classification), and multimodal learning (visual-linguistic integration). His work consistently applies deep learning to real-world problems requiring high-resolution data interpretation. Analysis of his 2022-2025 publications reveals three dominant trends: (1) Environmental applications using satellite imagery for flood mapping and agricultural monitoring, (2) Cognitive modeling of human teams and emotional dynamics through probabilistic frameworks, and (3) Astronomical data analysis leveraging host galaxy properties for transient classification. These threads demonstrate his commitment to solving practical scientific challenges through computational innovation. While scientific awards aren't documented in available sources, his leadership in projects like FloodPlanet and ToMCAT indicates significant contributions to data infrastructure. His advising and grant activities remain unreported in the source material, though his extensive interdisciplinary collaborations suggest substantial mentorship impact. Barnard's work operates at the intersection of multiple scientific communities, evidenced by applications spanning neuroscience, agriculture, astronomy, and social science. His current focus on high-resolution data fusion and multimodal modeling positions him at the forefront of real-world AI deployment.

• Chinese Philosophy
• Ancient Greek Philosophy
• Ethics
• +۴ مورد دیگر

Professor Eric Hutton at the University of Utah's College of Humanities specializes in Chinese and Ancient Greek philosophy, with particular emphasis on ethics, moral psychology, and cross-cultural comparisons. His academic journey began with a BA in Classics and Chinese from Stanford University, followed by an MA in Chinese from Harvard University, culminating in a PhD in Philosophy from Stanford University (2001). Professional Timeline: Assistant Professor (2001-2009), Associate Professor (2009-2019), Professor (2019-present) Key Research Areas: Chinese philosophy, Ancient Greek philosophy, ethics, moral psychology, ritual studies, and political philosophy His recent publications focus on: Comparative analysis of early Chinese and Greek political concepts (e.g., wei in 2024 work) Intersections between ethics and the arts in classical Chinese thought Epistemological aspects of Confucian tradition Philosophical dialogues between Xunzi and contemporary virtue ethics Historical transmission of classical texts (e.g., Matteo Ricci's sources in 2025 publication) Hutton's teaching portfolio includes specialized graduate and undergraduate courses in classical Chinese philosophy, Plato's Republic, contemporary ethics, and virtue ethics seminars.

Tya Collinsمشاهده پروفایل

استادیار

• Critical Black Youth Studies
• Critical Disability Studies
• Inclusive and Special Education
• +۵ مورد دیگر

Tya Collins serves as Assistant Professor in the Faculty of Education at the University of Ottawa, leveraging 20 years of multifaceted experience across preschool, elementary, secondary, ESL/FSL, special education, and university contexts. Her interdisciplinary work bridges education, sociology, critical youth studies, Black studies, and disability studies to dismantle systemic barriers in educational pathways for marginalized youth. Her academic credentials include: PhD in Education from Université de Montréal SSHRC Postdoctoral Fellowship at McGill University Professor Collins' research investigates critical intersections of Blackness, disability, language, and systemic trauma through Black-affirming theories and methodologies. She positions youth as knowledge producers while examining special education placement processes, postsecondary outcomes, and resistance to structural inequalities. Her francophone-anglophone bilingual research uniquely addresses Quebec's linguistic minority context, emphasizing racial justice and decolonial approaches in educational spaces. Analysis of her 2021-2025 publications reveals consistent application of Disability Critical Race Theory (DisCrit) to expose how special education systems perpetuate anti-Black racism and ableism. Her work demonstrates increasing focus on immigrant student experiences, postsecondary transitions, and methodological innovation through counter-narrative and ethnographic approaches. These contributions advance critical scholarship in educational equity, disability justice, and community-centered research within North American minority contexts. Her scientific recognition includes: SSHRC Postdoctoral Fellowship Professor Collins actively partners with community organizations including the Observatoire des communautés noires du Québec, Réseau de recherche sur les communautés québécoises d’expression anglaise, Avenues (supporting minority youth transitions), and serves as Ontario representative on Desjardins Foundation’s Research Advisory Council. Recent institutional announcements confirm her involvement in nationally funded projects as reported by the University of Ottawa in August 2024. She advises graduate students while teaching core courses including Introduction to Research in Education (EDU 5190), Inclusive and Special Education (EDU 5113), and Equity in Education: Theory and Practice (PED 3124).

• Software Engineering
• Information Security
• Computer Systems
• +۵ مورد دیگر

Hironori Washizaki is a Professor at Waseda University's School of Fundamental Science and Engineering, Department of Information and Computer Science, and serves as Director of the Global Software Engineering Laboratory. He also holds a visiting professorship at the National Institute of Informatics and serves as outside director at SYSTEM INFORMATION CO.,LTD. and eXmotion Co., Ltd. With a Doctorate in Information and Computer Science from Waseda University (2003), he has established himself as a leading researcher with 384 publications and an h-index of 36 according to Google Scholar. His research spans multiple domains including software engineering methodologies, security patterns, programming education, and the application of machine learning to software development. His work has significantly contributed to the fields of software patterns, quality assurance, and educational tools for programming. With over 20 years of academic experience, his career progressed from Research Associate (2002-2004) to Assistant Professor (2004-2008), Associate Professor (2008-2016), and Professor (2016-present). Washizaki's recent publications demonstrate a strong focus on applying AI and machine learning techniques to software engineering challenges, including prompt engineering patterns, program repair methods, and vulnerability assessment. His work bridges theoretical research with practical applications in both educational and industrial contexts, particularly in B2B software development and programming education for diverse age groups. KDDI Foundation Award (2022) Spirit of the Computer Society Award (2022) Distinguished Contributor, IEEE Computer Society (2022) IEEE Computer Society Golden Core Member (2022) Fellow, International Academy, Research, and Industry Association (2022) Computer Research Contribution Award, APSCIT (2016) Washizaki has served as chair of the IEEE CS Japan Chapter and SEMAT Japan Chapter, director of ACM-ICPC 2014 Asia Regional Tokyo Contest, and Convenor of ISO/IEC/JTC1/SC7/WG20. His editorial work includes positions at IEICE Transactions on Information and Systems and International Journal of Software Engineering and Knowledge Engineering. His leadership extends to programming education initiatives like SamurAI Coding, demonstrating his commitment to developing the next generation of software engineers.

Marco L. Della Vedovaمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence and Machine Learning
• Interpretable and Explainable AI
• Geospatial AI
• +۷ مورد دیگر

Marco L. Della Vedova is a Senior Lecturer in Applied Artificial Intelligence at Chalmers University of Technology, Sweden. He works in the Vehicle Engineering and Autonomous Systems division within the Department of Mechanics and Maritime Sciences, as part of Prof. Mattias Wahde's research group. Since 2025, he has served as Director of the Data Science and AI master's programme (MPDSC) at Chalmers, where he teaches courses including Introduction to Artificial Intelligence and Digitalization in Sports. Dr. Della Vedova earned his academic foundation at the University of Pavia, Italy, where he completed his BSc (2006), MSc (2009), and PhD (2013) in Computer Engineering. His doctoral research focused on "Real-Time Physical Systems and Electric Load Scheduling" under Prof. Tullio Facchinetti. During his PhD studies, he spent a year at U.C. Berkeley hosted by Prof. Francesco Borrelli at the Model Based Predictive and Distributed Control Lab. His research spans multiple AI domains with a strong emphasis on interpretability. Dr. Della Vedova develops interpretable methods for conversational AI, naturalness evaluation of forests using canopy height models, and geospatial applications. His work bridges theoretical AI with practical societal benefits, particularly in environmental monitoring, transportation systems, and orienteering. He has previously contributed to cloud computing, hate speech detection, and cyber-physical energy systems, demonstrating his interdisciplinary approach to AI research. Dr. Della Vedova's publication record reveals a consistent trajectory of impactful research across multiple domains of artificial intelligence. His recent work shows a strong focus on interpretability in AI systems, with significant contributions to natural language processing, geospatial analysis, and causal inference. The research demonstrates both theoretical depth and practical applications, particularly in environmental monitoring and social media analysis. His methodology often combines traditional machine learning approaches with novel interpretability techniques, creating bridges between complex AI systems and human understanding. Dr. Della Vedova has received several prestigious recognitions for his work: Best PhD thesis award from the Order of the Engineers of Bergamo (2013) Italian champion of Il Cervellone (2012) Top Italian performer in IEEEXtreme 6.0 programming competition (148th overall globally, 2012) Premio Arturo Schena award from Fondazione Credito Valtellinese (2010) With over 50 students supervised through bachelor's and master's theses, Dr. Della Vedova has established himself as a dedicated mentor in the AI community. His current PhD students include Minerva Suvanto working on interpretable NLP and Vivien Lacorre developing AI for railway infrastructure inspection. His supervision spans diverse topics from forest naturalness evaluation to hate speech detection and transportation optimization. Beyond formal supervision, he actively contributes to educational initiatives including serving as Director of Chalmers' Data Science and AI master's program and developing innovative teaching methods that connect theoretical concepts with real-world applications. Dr. Della Vedova is deeply embedded in both academic and professional communities. He leads the Applied Artificial Intelligence research group at Chalmers while maintaining strong connections with European research networks through projects like the ERASMUS+ EUrienteering initiative. His interdisciplinary approach is reflected in collaborations across computer science, environmental science, and social sciences. Notably, he applies his AI expertise to orienteering both as a researcher developing localization methods and as a licensed Event Advisor for the International Orienteering Federation, demonstrating how his professional and personal interests converge in innovative ways.

Laura Stateمشاهده پروفایل

پژوهشگر ارشد

• Artificial Intelligence
• AI Ethics
• Explainable AI
• +۳ مورد دیگر

Laura State serves as a Research Fellow at the Humboldt Institute for Internet and Society (HIIG) in Berlin, Germany, where she contributes to the AI & Society Lab's Impact AI project. This initiative develops transdisciplinary auditing methodologies to evaluate artificial intelligence systems' contributions to societal transformation and ecological sustainability through rigorous impact assessment frameworks. Her academic credentials include: PhD in Data Science from Scuola Normale Superiore, Pisa, Italy (Advised by Salvatore Ruggieri and Franco Turini) MSc in Neural Information Processing from the University of Tübingen BSc in Physics from the University of Rostock State's research synthesizes hard sciences with social perspectives to investigate AI's societal and planetary implications. She specializes in transparency and accountability mechanisms for non-interpretable machine learning models, developing assessment methodologies to determine how AI can foster sustainable futures. Her interdisciplinary approach integrates technical AI development with regulatory frameworks and ecological impact analysis, emphasizing real-world applicability through industry-academia collaboration. Her 2023-2025 publications reveal a cohesive research trajectory centered on explainable AI and regulatory compliance, particularly regarding GDPR requirements. Key themes include legal-technical alignment for explanation systems, bias/fairness policy frameworks, and innovative evaluation tools like REASONX. The work consistently bridges machine learning theory with societal accountability, demonstrating methodological rigor in translating technical capabilities into public-interest applications. As a core member of HIIG's AI & Society Lab, State collaborates on transdisciplinary teams examining AI's role in sustainability transitions. The Impact AI project coordinates researchers from computer science, law, and social sciences to develop evaluation frameworks that measure AI's contribution to UN Sustainable Development Goals, with active engagement in policy dialogues and public science initiatives like Lange Nacht der Wissenschaften.

Raffi Khatchadourianمشاهده پروفایل

دانشیار

• Software Engineering
• Programming Languages
• Software Evolution
• +۵ مورد دیگر

Raffi Khatchadourian is an Associate Professor in the Department of Computer Science at Hunter College and the Graduate Center of the City University of New York (CUNY). His research focuses on techniques for automated software evolution, particularly automated refactoring and source code recommendation systems, with the goal of easing the burden associated with evolving large and complex software through automated tools. He also conducts research on the automated analysis of Object-Oriented programs. Ph.D., Computer Science & Engineering, Ohio State University (2011) MS, Computer Science & Engineering, Ohio State University (2010) BS, Computer Science, Monmouth University (2004) Khatchadourian's research spans multiple areas of software engineering and programming languages, with particular emphasis on automated software evolution techniques. His work addresses critical challenges in refactoring legacy systems to modern language constructs, optimizing parallel processing in Java 8 streams, and addressing technical debt in machine learning systems. His recent research has expanded into deep learning program transformation, where he develops techniques to convert imperative deep learning code to more efficient graph execution models while ensuring safety. His approach combines static analysis, program transformation, and empirical validation to create practical tools that developers can integrate into their workflows. Analysis of Khatchadourian's recent publications reveals a strong focus on bridging the gap between theoretical program analysis and practical software engineering challenges. His work increasingly intersects with machine learning systems, examining both how to improve ML code through refactoring and how to ensure safety in deep learning frameworks. The research demonstrates consistent evolution from foundational work on Java language features toward more complex systems involving concurrency, deep learning, and automated program transformation. Distinguished Paper Award at SCAM '18 for work on Java 8 stream optimization EAPLS Best Paper Award at FASE '20 for study on Java 8 stream usage EAPLS Distinguished Paper Award at FASE '25 for Deep Learning refactoring work Best Paper Award nominee at IJCAI '24 for AI safety framework Khatchadourian actively mentors graduate and undergraduate students, with several advisees going on to successful academic and industry positions. His former Ph.D. student Tatiana Castro Vélez accepted a tenure-track Assistant Professor position at the University of Puerto Rico. He has supervised numerous master's theses and undergraduate research projects, often resulting in co-authored publications at top software engineering venues. His research has been supported by various grants, though specific funding details are not prominently featured in the available information. Through his work on tools like Fraglight for aspect-oriented programming and Hybridize Functions for deep learning refactoring, Khatchadourian has established a research group focused on practical program analysis and transformation. His lab develops Eclipse plugins and other IDE-integrated tools that help developers with automated refactoring, bug detection, and code optimization. The group maintains active collaborations with researchers at other institutions and contributes to open-source projects on GitHub.