جست‌وجوی استاد و پژوهشگر

Marcus Bellamyمشاهده پروفایل

دانشیار

• Supply Chain Management
• Sustainable Operations
• Innovation
• +۶ مورد دیگر

Marcus Bellamy is an Associate Professor of Operations and Technology Management at the Questrom School of Business, Boston University . His research focuses on innovation , environmental sustainability , and performance dynamics in supply networks, using empirical models to analyze spatial resource proximity and interdependence. Education : PhD in Operations & Technology Management from Georgia Tech (2015), MS in Industrial Engineering (2010), BS in Aerospace Engineering from University of New Mexico (2006). His research bridges supply chain structure with outcomes like CSR practices , resilience , and economic welfare . He employs visual analytics and computational tools to study industries ranging from automotive to electronics , addressing policy impacts and platform economies like Uber . Recent work trends include analyzing two-sided sharing platforms , environmental disclosure in supply chains, and network resilience under risks. His empirical studies often integrate spatial spillovers and collaborative ecosystems . Scientific Awards : Isabel Anderson Career Development Professorship 2019 AOM Best Paper in Supply Chains 2013 AOM Operations Management Division Best Student Paper Fulbright Scholar (Madrid, Spain) NSF STEP Fellow Bellamy has served as a founder of the PhD Project Committee under the White House Initiative on Hispanic Education and collaborated with corporations like Lockheed Martin and General Motors on supply chain risk & resilience. His methodological contributions include interactive visual analytics systems for network evaluation.

• Computational Humanities
• Music Information Retrieval
• Audio Analysis
• +۷ مورد دیگر

Christof Weiß is a Professor for Computational Humanities at the CAIDAS / Institute of Computer Science, Julius-Maximilians-Universität Würzburg (JMU), Germany. He serves as Head of the DFG-funded Emmy Noether group on Computational Analysis of Music Audio Recordings: A Cross-Version Approach. His academic journey includes previous positions as Visiting Researcher at University Télécom Paris (2021), Visiting Lecturer at Karlsruhe University of Music (2020, 2021), and Research Assistant at International Audio Laboratories Erlangen (2015-2022) and Fraunhofer Institute for Digital Media Technology (2012-2015). His educational background encompasses a PhD in Media Technology from University of Technology Ilmenau (2017), Concert Diploma in Composition from Würzburg University of Music (2012), Physics Diploma from University of Würzburg (2012), and Music Diploma in Composition from Würzburg University of Music (2011). This unique combination of technical and artistic training forms the foundation of his interdisciplinary research approach. Weiß's research operates at the critical intersection of computer science and musicology, developing novel computational methods for analyzing musical structures in audio recordings. His work bridges technical audio processing with musicological insights, creating methodologies for tonal analysis, key estimation, and cross-version comparison of musical performances. His approach combines deep learning techniques with music theory to extract meaningful patterns from large music corpora, enabling new forms of musicological corpus studies that were previously impossible. His recent publications reveal a clear research trajectory toward integrating advanced machine learning with fundamental musicological questions. The consistent theme across his work involves analyzing classical music structures through computational lenses, with particular emphasis on cross-version consistency in performances, tonal complexity measurement, and developing datasets that support computational musicology. His publications span both highly technical audio processing journals and musicology-focused venues, demonstrating his commitment to bridging these disciplines. Best paper award at the 4th conference on Computational Humanities Research (CHR), 2023 KlarText award for science communication of the Klaus Tschira Foundation, 2018 2nd prize at Festival Pablo Casals composition competition, Prades (France), 2013 Youth Cultural Advancement Award (Kulturförderpreis) of the city of Amberg, Germany, 2011 As principal investigator of the DFG Emmy Noether group, Weiß leads a multidisciplinary research team investigating computational analysis of music audio recordings through a cross-version approach. His research has secured significant funding including the prestigious Emmy Noether program, supporting doctoral and postdoctoral researchers working on various aspects of music information retrieval and computational humanities. His collaborative network spans institutions across Europe, including University Télécom Paris, Queen Mary University of London, and multiple German research centers. Weiß leads the Computational Humanities research group at CAIDAS, which focuses on developing computational methodologies for music analysis with particular emphasis on classical repertoire. The lab creates specialized datasets (including the Wagner Ring Dataset and Schubert Winterreise Dataset), develops algorithms for structural music analysis, and applies these tools to address musicological questions that require computational scale and precision. Their work bridges the gap between technical audio processing capabilities and humanities research questions, creating new pathways for understanding musical structure and evolution.

• Economics
• Development Economics
• Macroeconomics
• +۸ مورد دیگر

Emel YILDIZ is an Assistant Professor in the Department of Business Administration at Trakya University's Faculty of Economics and Administrative Sciences . Since 2014, she has served as Deputy Head of Department and Cooperatives USA Presidency, focusing on economic development and policy analysis. Bachelor's, Master's, and PhD in Economics from Marmara and Trakya Universities Role: Academic leadership in Cooperative Economics and Development Economics Research spans macroeconomic policy, social capital, education economics, and sustainable development Her research integrates macroeconomic frameworks with socioeconomic outcomes. Key themes include: Econometric analysis of monetary and fiscal policies Education's role in human capital formation Cooperative models for sustainable energy Technology's impact on employment Publishing trends show emphasis on Turkey-Azerbaijan trade dynamics, G20 competitiveness, and vocational education integration into the information economy. Supervised theses address SMEs' strategic planning, fast food localization, and Turkey's cooperative energy policies.

Lili Qiuمشاهده پروفایل

استاد

• Internet Networking
• Wireless Networking
• Mobile Systems
• +۶ مورد دیگر

Lili Qiu is a Professor in the Department of Computer Science at The University of Texas at Austin, where she has been a faculty member since January 2005. She is an active member of the Wireless Networking and Communications Group (WNCG) and has made significant contributions to the field of networking research. Dr. Qiu previously spent 2001-2004 as a researcher at Microsoft Research in Redmond, WA, before joining UT Austin. Dr. Qiu's research spans Internet and wireless networking with a current focus on wireless network management and content distribution in mobile networks. Her work extends into diverse applications including acoustic imaging, metasurface applications, healthcare sensing technologies, and AI systems. She has pioneered research in areas such as acoustic motion tracking, passive RFID sensing, and wireless network optimization. Her research demonstrates a consistent pattern of innovation that bridges theoretical networking concepts with practical real-world applications, particularly in mobile and wireless systems. Her extensive publication record shows a clear evolution from fundamental networking research to increasingly interdisciplinary work that combines wireless systems with healthcare applications, AI, and novel sensing technologies. Recent publications demonstrate growing integration of machine learning techniques with traditional networking problems, as well as expansion into healthcare applications like Parkinson's disease modeling and non-invasive glucose monitoring. ACM Fellow IEEE Fellow National Academy of Inventors (NAI) Fellow ACM Distinguished Scientist NSF CAREER award Google Faculty Research Award Best paper award at ACM MobiSys'18 Best paper award at IEEE ICNP'17 Dr. Qiu has supervised numerous students, including a PhD dissertation that won the SIGMOBILE best dissertation award in 2020. She has served in significant leadership roles including chair of ACM SIGMOBILE, General co-chair for ACM MobiCom 2025, and various conference chair positions for IEEE ICNP, ACM CoNEXT, and other major networking conferences. Her research has been supported by substantial grants from NSF, Google, and other organizations, enabling her to lead cross-disciplinary research teams. As a member of the Wireless Networking and Communications Group at UT Austin, Dr. Qiu leads research efforts that combine networking expertise with innovations in sensing technologies, metasurfaces, and AI systems. Her lab has produced numerous influential results in mobile networking, wireless sensing, and network management, with applications spanning healthcare, consumer electronics, and communication infrastructure.

Md. Zoheb Hassanمشاهده پروفایل

استادیار

• Spectrum sharing and management
• Wireless communication systems
• Communications and network control and regulation systems
• +۱ مورد دیگر

Md. Zoheb Hassan serves as an Assistant Professor in the Department of Electrical Engineering and Computer Engineering at Laval University, where he leads cutting-edge research in wireless communications and spectrum management. His academic role includes graduate recruitment and active participation in the university's research ecosystem, particularly through the Establishment of the Next Generation of Professors program funded by FRQNT. Dr. Hassan's research centers on spectrum sharing and management, wireless communication systems, and communications network control systems. He pioneers the integration of digital twin technology and machine learning to solve critical challenges in next-generation networks, including interference management in 5G/6G aerial corridors, Internet of Vehicles, and satellite-terrestrial integration. His work emphasizes practical implementations such as proof-of-concept demonstrations for tactical networks and proactive resource allocation in dynamic environments. Analysis of his 2024-2025 publications reveals a dominant trend toward AI-driven wireless resource optimization, with 12 of 15 recent papers featuring digital twins for interference management, spectrum sharing, and energy efficiency. Key thematic clusters include vehicular communications (4 papers), underwater IoT networks (2 papers), and hardware-impairment resilient designs (3 papers), demonstrating his focus on bridging theoretical advances with real-world deployment challenges across diverse network topologies. Dr. Hassan has secured significant competitive funding for his research initiatives: Digital Twin-Enhanced Interference Management for Next-Generation Radio Access Networks in the FR3 Band (FRQNT, 2025-2027) Center for Radio Frequency and Communications Systems, Technologies and Applications (FRQNT, 2024-2030) Context-Aware Spectrum Sharing and Management for Next Generation Wireless Networks (NSERC, 2024-2029) Development of innovative technologies for modeling predictive systems in urban mobility (MITACS, 2022-2026) Springboard to Discovery supplement for Context-Aware Spectrum Sharing (NSERC, 2024-2025) He actively mentors doctoral candidates, currently supervising Mahima Karim (PhD in Electrical Engineering, expected 2025) and Mohammadamin Parhizgar (PhD in Electrical Engineering, expected 2024). His supervisory approach combines theoretical rigor with practical problem-solving, focusing on spectrum management algorithms and digital twin implementations for next-generation networks. While specific laboratory affiliations aren't detailed in the source material, his projects indicate strong alignment with Laval University's wireless research infrastructure and the Center for Radio Frequency and Communications Systems.

Arnab Nandiمشاهده پروفایل

استاد

• Database Systems
• Human-Computer Interaction
• Human-in-the-Loop Data Analytics
• +۵ مورد دیگر

Arnab Nandi is a Professor of Computer Science and Engineering at The Ohio State University, with a courtesy appointment in Biomedical Informatics. He holds leadership roles including Steering Committee Member for the Human-in-the-Loop Data Analytics (HILDA) Workshop and has served as Workshops co-chair for SIGMOD 2025-26 and Demonstrations co-chair for SIGMOD 2024. His research focuses on bridging human interaction and data infrastructure, spanning database systems, human-in-the-loop data analytics, and next-generation query interfaces. Nandi's work emphasizes interactive data exploration through projects like DICE (Distributed Interactive Cube Exploration), GestureDB (Querying Beyond Keyboards), and Omni (Multimodal Data Exploration). His recent research explores integrating LLMs into database education, augmented reality interfaces for data analytics, and multimodal approaches to video querying. Nandi has received numerous honors including the NSF CAREER Award, Google Faculty Research Award, IEEE TCDE Early Career Award, and the University's Alumni Award for Distinguished Teaching. He was also named to Columbus Business First's '40 under 40' and became an ACM Distinguished Member in 2024. As an educator, he teaches courses including CSE 3241 (Introduction to Database Systems), CSE 5242 (Advanced Database Systems), and CSE 5251 (Introduction to Software Startups). His educational innovations include DBTutor, which integrates LLMs into database systems education. At Ohio State, Nandi co-founded the OHI/O Program, which fosters tech culture through hackathons, and The STEAM Factory, an interdisciplinary research collaboration network. Prior to academia, he was founder and CEO of Mobikit, a connected vehicles data analytics startup acquired by Azuga Inc. (a Bridgestone company). His research has been supported by the NSF and industry partnerships, with applications spanning precision agriculture (CropFusion), clinical data pipelines (ICARUS), and interactive visualization systems (Perceptvis).

• Data Mining
• Machine Learning
• Reinforcement Learning
• +۹ مورد دیگر

Dr. Yanjie Fu is an Associate Professor in the School of Computing and AI at Arizona State University, part of the Ira A. Fulton Schools of Engineering. He maintains his office in BYENG 506 at the Tempe campus and can be reached at yanjie.fu@asu.edu. Dr. Fu received his Ph.D. from Rutgers University in 2016, the B.E. degree from the University of Science and Technology of China, and the M.E. degree from the Chinese Academy of Sciences. His industry research experience includes positions at Microsoft Research Asia and IBM Thomas J. Watson Research Center. His research focuses on developing disruption-robust machine intelligence that can handle imperfect and complex data. Dr. Fu's work spans two major efforts: Data for AI (D4AI), exploring how structure knowledge of data can guide AI, and AI for Data (AI4D), investigating how AI can augment, reprogram, and knowledgeize data. His current research interests include space-time intelligence, data-centric AI, sim2decision, multimodal reasoning, and LLM with agentic AI. His lab has contributed projects including D4AI-spatial, D4AI-timeseries, D4AI-causal outliers, AI4D-RL, AI4D-Gen, and AI4D-LLM. Dr. Fu's recent publications reveal a strong trend toward integrating causal reasoning with deep learning for robust anomaly detection, advancing time series forecasting with novel normalization techniques, and applying generative AI to urban planning. His work increasingly bridges traditional machine learning with large language models, particularly focusing on data-centric approaches for tabular data transformation and feature engineering. US NAE FOE early career engineer (2023) US NSF CAREER (2021) NSF CRII (2018) ACM KDD18 Best Student Paper Finalist IEEE ICDM Best Paper Finalist (2014, 2021, 2022) ACM SIGSpatial Best Paper Runner-up (2020) 2022 Baidu Scholar global top Chinese young scholars in AI 2021 Aminer.org AI 2000 Most Influential Scholar Award Honorable Mention Dr. Fu has successfully mentored multiple Ph.D. students who have secured tenure-track faculty positions at prestigious institutions including University of Kansas, Chinese Academy of Sciences, Great Bay University, Portland State University, and University of Macau. His research has been supported by significant grants including the NSF CAREER award, and he currently serves as Associate Editor of ACM Transactions on Knowledge Discovery from Data. He is also a senior member of both ACM and IEEE. Dr. Fu leads a research group focused on developing trusted and safe machine intelligence. The lab connects computing issues across representation learning, self-supervised learning, interactive learning, adaptive learning, and stream learning to build disruption-robust frameworks. The group executes two key steps: data representation construct (integrating structure knowledge, self-optimization, explainability) and learning strategy construct (integrating robust representations with adaptive and interactive learning).

Christian Russمشاهده پروفایل

مدرس ارشد

• Digital Leadership
• IT Strategy
• Business-IT Alignment
• +۴ مورد دیگر

Dr. Christian Russ is a Senior Lecturer at the Institute of Business Information Technology , Zurich University of Applied Sciences (ZHAW), with expertise in digital transformation, IT leadership, and business-IT alignment. His work spans healthcare, education, and automotive sectors, focusing on agile IT governance and adaptive business models. Current roles: Program Director MAS IT-Leadership and TechManagement Key projects: ZHAW Digital Culture Assessment, Monitoring eCH Standards Research interests include digital transformation , agile IT , health informatics , and emerging technologies . Recent publications analyze post-pandemic organizational culture, medical AI regulation, and cloud infrastructure in healthcare. 2025: Organizational culture shifts during/after pandemic 2024: ML solutions in Swiss hospitals under MDR 2023: iPaaS cloud security in healthcare 2023: Agile transformation in non-profits Scientific recognitions: Best Paper Award at SMART 2018 "Educate to lead" award (Soroptimist International Europa, 2016) Active in the ZHAW Digital Health Lab, he leads projects on tech startup coaching, digital ecosystems, and IT governance. His teaching covers IT strategy, digital transformation, and enterprise service management at ZHAW.

Tamas Monaمشاهده پروفایل

پژوهشگر

• Epidemiology
• Plant Pathology
• Meteorology
• +۵ مورد دیگر

Dr. Tamas Mona is a Postdoctoral Research Associate in the Department of Plant Sciences at the University of Cambridge , affiliated with the Epidemiology and Modelling Group . His work focuses on environmental suitability models for large-scale epidemiological forecasting, particularly in wheat rust outbreaks across Africa, the Middle East, and Asia. Collaborations include the UK Met Office, CIMMYT, and institutions in Ethiopia, Kenya, Bangladesh, and Nepal. PhD in Environmental Sciences (2019), Eötvös Loránd University MSc in Meteorology (2013), Eötvös Loránd University BSc in Physics with Meteorology (2011), Eötvös Loránd University Research interests integrate meteorological applications with epidemiological models to predict crop disease outbreaks. Key projects involve tracking transmission pathways for stem rust pathogens and analyzing how irrigation creates green bridges for intercontinental pathogen spread. Publications emphasize environmental science and computational epidemiology . Current collaborations span Sub-Saharan Africa (EIAR, ATI, KARLO) and South Asia (BWMRI, NARC) through initiatives like the Global Food Security IRC . Modeling frameworks developed by Mona contribute to policy advisory systems for emerging pest threats, aligning with DEFRA and UK government strategies.

Tomoyuki Tanakaمشاهده پروفایل

استاد

• Chromosome Segregation
• Mitosis
• Cell Cycle Regulation
• +۷ مورد دیگر

Professor Tomoyuki Tanaka holds the Chair of Cell and Molecular Biology at the University of Dundee within the School of Life Sciences . He serves as the Academic Lead of Dundee Imaging Facility (since 2018) and Deputy Head of the Division for Molecular Cell & Developmental Biology (since 2022). His research focuses on chromosome segregation mechanisms in mitosis and their implications in genetic diseases and cancer . Member of European Molecular Biology Organisation (EMBO, 2008–) Fellow of Royal Society of Edinburgh (2009–) Wellcome Trust Investigator (2020–) His lab investigates two key processes in early mitosis: chromosome reorganization (resolution and compaction of sister chromatids) and kinetochore-spindle interactions . These mechanisms are critical for preventing errors linked to aneuploidy, congenital disorders, and cancers . Using budding yeast as a model organism, his group combines genetic, proteomic, and imaging techniques to uncover conserved biological principles. Recent publications highlight discoveries in condensin exclusion during prophase , Aurora B kinase spatial regulation , and error correction mechanisms for accurate chromosome inheritance. The lab also contributes to in vitro reconstitution of chromosomal processes, including a 2021 breakthrough on chromosome positioning networks . 2020: Wellcome Investigator Award 2013: ERC Advanced Grant 2007: Hooke Medal (British Society for Cell Biology) 2000: EMBO Young Investigator He supervises PhD students and contributes to Level 3 undergraduate teaching (BS31006 Gene Regulation) and Honours research projects . His work aligns with UN Sustainable Development Goals for health and well-being through genetic disease research.

Amir Aryaniمشاهده پروفایل

دانشیار

• Data Science
• Social Data Analytics
• Public Health Informatics
• +۵ مورد دیگر

Amir Aryani is an Associate Professor at the School of Business, Law and Entrepreneurship , Swinburne University of Technology . He leads the Social Data Analytics (SoDA) Lab within the Social Innovation Research Institute , focusing on data-driven solutions for health and social challenges. His work involves large-scale cross-institutional projects with international collaborators including the British Library , ORCID , and NIH . Research Focus: Data modeling, real-time analytics, and information retrieval for social-good initiatives Collaborations: CERN, Data Archiving and Networked Services (DANS), and Global Information Systems (GESIS) His research explores data science applications in mental health, community resilience, and sustainable development. Key trends in his publications include: Mapping research to United Nations Sustainable Development Goals Developing hybrid expert-finding models using NLP and graph algorithms Creating interoperable research graphs for cross-platform discovery Assessing social impact of data projects in non-profit sectors Amir is actively involved in PhD supervision and has secured funding from Australian Research Council , National Health and Medical Research Council , and philanthropic foundations . He also contributes to community data projects through the SoDA Lab , which builds tools for social connection analysis and humanitarian response optimization.

Taein Kwonمشاهده پروفایل

پژوهشگر ارشد

• Egocentric Vision
• Action Recognition
• Contextual AI
• +۶ مورد دیگر

Taein Kwon is a postdoctoral research fellow at the Visual Geometry Group (VGG) within the Department of Engineering Science at the University of Oxford, working under Prof. Andrew Zisserman. Previously, he completed his PhD at ETH Zurich under Prof. Marc Pollefeys and earned master's and bachelor's degrees from UCLA and Yonsei University, respectively. His educational background includes: Bachelor's in Electrical Engineering from Yonsei University, Seoul, Korea Master's degree from UCLA PhD from ETH Zurich (defended July 2024) His research spans Egocentric Vision, Action Recognition, Hand-object Interaction, Video Understanding, AR/VR, and Multi-modal Learning, with emphasis on first-person perspective analysis for AI assistants and human-computer interaction. His work integrates 3D reconstruction, pose estimation, and multimodal signals to model complex human activities and physical interactions. Analysis of his 2021-2025 publications reveals a consistent focus on egocentric vision datasets (H2O, HoloAssist, EgoPressure) and novel frameworks for hand-object interaction, action recognition, and gesture understanding. His research demonstrates strong interdisciplinary connections between computer vision, robotics, and human-centered AI, with increasing emphasis on pressure sensing, co-speech gestures, and cross-modal alignment. His scientific recognition includes: CVPR Egovis 2022/2023 Distinguished Paper Award for HoloAssist (July 2024) SNSF Postdoc.Mobility fellowship (May 2024) He actively mentors students on egocentric vision projects, supervising master's theses, semester projects, and collaboration initiatives leading to publications at top conferences. His research is supported by the SNSF fellowship and industry collaborations with Meta Reality Labs and Microsoft Research. As part of Oxford's Visual Geometry Group, he contributes to cutting-edge computer vision research while maintaining strong ties with ETH Zurich's computer vision community through ongoing collaborations and dataset development efforts.

• Telecommunications
• Communication Systems
• Satellite Communications
• +۷ مورد دیگر

Roberto Garello is a Tenured Associate Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino . He specializes in Communication Systems , Satellite Networks , and Channel Coding , with a focus on 5G/6G Technologies and Non-Terrestrial Networks . His work aligns with the School of Master’s Programmes and Lifelong Learning . Research Interests: Satellite communications systems, Direct-to-Satellite IoT constellations, Mega-constellation services in space, and physical layer advancements for 5G/6G. Teaching: Offers courses like Information Theory for Data Science , Communication and Network Systems , and Space Exploration and Resources , while supervising Applied Signal Processing Laboratory . Projects: Leads initiatives such as DitDSSS (satellite localization), RESTART (future telecommunications), and TESL@ (ICT energy efficiency). Scientific Awards: Received Best Paper Awards at CTRQ 2010 and COCORA 2013. Students: Supervises PhD candidates including Alessandro Compagnoni, Agbotiname Lucky Imoize, and Riccardo Tuninato, focusing on topics like Wireless Communication, Machine Learning, and Non-Terrestrial Networks. Publications: His recent work explores OTFS vs. OFDM, spectrum sensing algorithms, MIMO with cylindrical arrays, and 5G NTN synchronization, reflecting trends in satellite IoT and machine learning integration.

Carla Curadoمشاهده پروفایل

دانشیار

• Knowledge Management
• Human Resource Management
• Organizational Behavior
• +۳ مورد دیگر

Carla Curado is an Associate Professor with Habilitation in Organizational Behavior and Human Resource Management at ISEG – Lisbon School of Economics and Management, University of Lisbon. She serves as a founding researcher at the ADVANCE research center and holds leadership roles including Master's Program Coordinator for Human Resource Management and Business Sciences. She represents the University of Lisbon at the International Organization for Standardization and is an Associate Editor for the Journal of Organizational Effectiveness: People and Performance . Her research explores: Knowledge Management in healthcare, SMEs, and NGOs Digital leadership and workplace happiness HRM's role in innovation and sustainability Mixed-method approaches to organizational analysis Recent publications (2023-2025) emphasize digital transformation, healthcare efficiency, and methodological innovations in operations management. Key trends include configurational analysis of leadership and knowledge behaviors in hybrid work environments. Awards: Stanford's Top 2% World Scientist (2021, 2022, 2023) She supervises 65+ Master's students with theses on: Knowledge sharing mechanisms Leadership/organizational commitment Healthcare workplace dynamics Sustainability in HR practices At ADVANCE Research Center, she contributes to teams studying management innovation and organizational resilience, with active participation in EU research consortia.

Michihiro Yasunagaمشاهده پروفایل

استادیار

• Large Language Models
• Multimodal Models
• Reasoning Systems
• +۶ مورد دیگر

Michihiro Yasunaga is an Assistant Professor in the Department of Computer Science at Stanford University's School of Engineering. He received his PhD in Computer Science from Stanford, advised by Percy Liang, Jure Leskovec, and Chris Manning. Prior to his faculty position, he worked as a researcher at Google DeepMind and Meta. His research focuses on building LLMs and agents that assist humans in diverse tasks, with particular expertise in post-training techniques (RL, reward models, and evaluation), reasoning systems (AnalogicalReasoner), retrieval and tool use for LLMs (LinkBERT, QAGNN, DRAGON, REPLUG, HippoRAG), and multimodality (RA-CM3, Med-Flamingo, Transfusion). His work spans both theoretical foundations and practical applications of large language models. Yasunaga's publication record demonstrates significant contributions to the field of AI, with 15 recent articles (2023-2025) covering diverse aspects of language model development, evaluation, and application. His research shows a clear trajectory toward building more capable, efficient, and reliable multimodal AI systems, with particular emphasis on knowledge integration and robust evaluation frameworks. Among his notable achievements is the Best Paper Award at AAAI 2023 Deep Learning on Graphs Workshop for the DRAGON paper. He has also been deeply involved in major benchmarking efforts including HELM and HEIM, which provide comprehensive evaluation frameworks for language and vision-language models. Yasunaga actively contributes to the research community through service roles including Organizing Committee for the Workshop on Knowledge-Augmented Methods for NLP (ACL 2024), Workshop on Structured and Unstructured Knowledge Integration (NAACL 2022), and the Workshop on Scientific Document Summarization (SIGIR 2017-2020). He has also served on program committees for top conferences including NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, and ICCV from 2020-2025.