جست‌وجوی استاد و پژوهشگر

Jan von Delftمشاهده پروفایل

استاد

• Correlated electron systems
• Quantum impurity models
• Quantum criticality
• +۷ مورد دیگر

Jan von Delft is a Professor (chair) at Ludwig-Maximilians-University (LMU) Munich, working in the Faculty of Physics within the Chair of Theoretical Solid State Physics. His research group consists of postdocs, PhD students, and master's students working on various aspects of strongly correlated electron systems, with physical space located at Theresienstr. 37 (Room A420) in Munich. von Delft's research focuses on correlated electron and spin systems, with particular interest in dynamical and transport properties, quantum impurity models, Hund metals, unconventional superconductors, quantum magnets, and quantum criticality. His methodological expertise includes many-body field theory, parquet formalism (FRG), DMFT, and tensor networks (NRG, DMRG, PEPS, XTRG, etc.). His work bridges theoretical concepts with computational approaches to understand complex quantum phenomena in condensed matter systems. He has developed a distinctive emphasis on real-frequency calculations and numerical methods for studying quantum critical phenomena. Analysis of von Delft's recent publications reveals a strong focus on developing and applying advanced computational methods to study strongly correlated electron systems. His group has made significant contributions to numerical renormalization group techniques, tensor network methods, and the parquet formalism for calculating real-frequency correlation functions. His research shows increasing sophistication in handling quantum criticality, particularly in heavy-fermion systems, and exploring unconventional superconductivity mechanisms. Notably, his group has developed specialized computational libraries like KeldyshQFT to make these advanced methods more accessible to the broader physics community. von Delft actively mentors a substantial research group consisting of one postdoc (Markus Scheb), eleven PhD students (Anxiang Ge, Sasha Kovalska, Mathias Pelz, Marc Ritter, Nepomuk Ritz, Changkai Zhang, Markus Frankenbacher, Felipe Picoli, Simone Fodera, Ming Huang), and two master's students (Ester Pages, Gianluca Grosso). His detailed Style Guide for scientific communication demonstrates his commitment to high-quality research presentation. The group appears well-funded with ongoing research activities spanning theoretical development, computational implementation, and physical interpretation of complex quantum phenomena.

• Robotics
• Photogrammetry
• Simultaneous Localization and Mapping (SLAM)
• +۱۲ مورد دیگر

Cyrill Stachniss is a Full Professor at the University of Bonn , where he heads the Lab for Photogrammetry and Robotics and is affiliated with the Lamarr Institute for Machine Learning and Artificial Intelligence . He was previously a Visiting Professor in Engineering at the University of Oxford until 2025. His academic journey includes positions at the University of Freiburg, University of Zaragoza, and the Swiss Federal Institute of Technology. University: University of Bonn School: Faculty of Engineering Department: Department of Photogrammetry Academic Rank: Professor His research spans robotics, photogrammetry, SLAM, autonomous navigation, perception systems, agricultural robotics, and unmanned aerial vehicles . He emphasizes probabilistic techniques for mobile robots and has made significant contributions to visual and LiDAR-based localization, scene understanding, and 3D reconstruction. The recent publications highlight a strong trend toward neural implicit representations, agricultural phenotyping, radar-based perception, and active learning . His team develops robust systems for real-world deployment in dynamic and unstructured environments, particularly in precision farming and autonomous vehicles. Scientific Awards: IEEE RAS Early Career Award (2013) Microsoft Research Faculty Fellow (2010) 7th EURON Georges Giralt Award (2008) Multiple Best Paper Awards at ICRA, IROS, RSS, and RAL Faculty Teaching Award, University of Freiburg He has advised numerous students and leads the DFG Cluster of Excellence PhenoRob and Research Unit FOR 1505 Mapping on Demand . His lab has co-founded three startups, reflecting strong industry and societal impact. He also runs the educational video series 5 Minutes with Cyrill , explaining key robotics concepts.

Christoph Keplingerمشاهده پروفایل

استاد

• Soft Robotics
• Functional Polymers
• Energy Capture
• +۴ مورد دیگر

Christoph Keplinger serves as Managing Director of the Max Planck Institute for Intelligent Systems (MPI-IS) in Stuttgart, Germany, leading the Robotic Materials Department since 2020 and assuming overall institute leadership in 2023. He holds dual academic appointments as Honorary Professor at the University of Stuttgart and Eminent Visiting Professor of Soft Robotics at the University of Colorado Boulder, establishing him as a pivotal figure in bridging fundamental materials science with advanced robotics. His interdisciplinary approach integrates physics, chemistry, and engineering to pioneer breakthroughs in soft robotic systems. Keplinger's academic foundation includes a PhD in Soft Matter Physics from Johannes Kepler University Linz, Austria, followed by postdoctoral research at Harvard University focusing on mechanics and chemistry of soft materials. This unique background enabled his transition into robotics innovation, particularly in electrohydraulic actuation systems. His research program centers on three synergistic pillars: (I) soft robotics development through novel actuator technologies like HASEL artificial muscles; (II) energy capture mechanisms using soft materials; and (III) functional polymers engineered for robotic applications. This work produces transformative hardware that mimics biological functionality, with significant implications for human-robot interaction, medical devices, and sustainable robotics systems. His group employs cutting-edge materials synthesis and characterization techniques to create lifelike robotic components. Analysis of recent publications reveals dominant trends in wearable haptic interfaces, electrohydraulic actuation systems, and tremor-suppression technologies. The research consistently leverages HASEL (Hydraulically Amplified Self-healing Electrostatic) technology to achieve muscle-like performance in soft actuators, with applications spanning from fingertip haptic feedback to underwater manipulation systems. This trajectory demonstrates a clear progression from fundamental material properties toward practical implementations in medical rehabilitation and human augmentation. His exceptional contributions have earned prestigious recognition: 2017 Packard Fellowship for Science and Engineering, awarded for high-impact interdisciplinary research 2021 Alexander von Humboldt Professorship (declined to remain at MPI-IS), Germany's most valuable international research award 2013 EAPromising European Researcher Award from the European Scientific Network for Artificial Muscles As principal investigator, Keplinger leads a dynamic interdisciplinary research group while securing competitive funding for frontier projects. His entrepreneurial vision materialized in 2018 through co-founding Artimus Robotics, where he serves as Chief Science Officer to commercialize HASEL technology. This dual commitment to academic research and industry translation exemplifies his dedication to real-world impact, particularly in creating biodegradable and sustainable soft robotic solutions. The Robotic Materials Department operates state-of-the-art facilities for materials fabrication, robotic integration, and haptic interface development. The team maintains strong collaborations across MPI-IS departments and external institutions including the University of Colorado Boulder, fostering innovation in sustainable robotics through initiatives like biodegradable electrohydraulic actuators. Current projects focus on wearable tremor suppression systems, electrohydraulic locomotion platforms, and energy-autonomous soft robots that address critical challenges in medical rehabilitation and human augmentation.

Alessandro Golkarمشاهده پروفایل

استاد

• Space Systems Engineering
• CubeSat and Nanosatellite Technology
• Satellite Constellations
• +۵ مورد دیگر

Prof. Alessandro Golkar is a Professor at the Technical University of Munich (TUM), leading the Chair of Picosatellites, Nanosatellites, and Satellite Constellations. He joined TUM in September 2022 and previously served as one of the founding faculty members at Skoltech, a Moscow-based graduate research university. His research focuses on advanced space mission concepts, systems engineering for picosatellites, and federated satellite systems. Prior to academia, he held roles at Airbus CTO, contributing to technology roadmapping and planning. His academic background includes expertise in aerospace engineering, systems design, and agile development methodologies for space hardware. Key research areas include CubeSat constellations, distributed satellite systems, and the integration of AI tools like Large Language Models (LLMs) into spacecraft design processes. He has pioneered projects such as the FSSCat mission, winner of the ESA Sentinel Small Satellite Challenge, and has explored applications of additive manufacturing for lunar missions. Prof. Golkar’s awards include the 2021 Karman Fellowship and IEEE Senior Membership (2018). His recent work emphasizes optimizing satellite networks, digital twin implementation, and orbital maneuvering for collision avoidance. He actively contributes to technology roadmapping, focusing on future human landing systems and lunar infrastructure development. Education: Ph.D. in Aerospace Engineering (details not explicitly stated). Grants & Funding: Extensive grants for CubeSat projects, federated systems research, and space technology innovation. Labs/Teams: Leads the Chair’s research group at TUM and collaborates with industry partners like Airbus on advanced mission concepts. His publications span over two decades, addressing topics like constellation design, machine learning in space, and agile processes for hardware development. He advocates for hybrid agile methodologies to bridge traditional systems engineering and modern product development.

Mark Heitmannمشاهده پروفایل

استاد

• Artificial Intelligence in Marketing
• Social Media Marketing
• Brand Management
• +۵ مورد دیگر

Prof. Mark Heitmann is a Professor of Marketing & Customer Insight at the University of Hamburg Business School. He holds a visiting appointment at Nova School of Business and Economics. His research focuses on AI-driven marketing strategies, social media analytics, brand equity, and consumer decision-making. He has held academic roles at institutions including the University of St. Gallen and Christian-Albrechts-University in Kiel before joining Hamburg in 2011. Academic Career: Holds a PhD (2004) and post-doctoral Habilitation (2007) from the University of St. Gallen. Visiting researcher at Columbia University and the Max Planck Institute for Human Development. Research Interests: Applications of artificial intelligence in marketing Social media and digital transformation Ethical consumer behavior Brand self-expression and visual design Marketing technology (MarTech) innovations Key Achievements: Over 20 peer-reviewed publications in top journals like Journal of Marketing Research and Harvard Business Review . Award-winning research includes the MSI/H. Paul Root Award and IJRM-EMAC Best Article Award. Active in translating research into scalable commercial solutions through software-as-a-service ventures. Team & Collaborations: Leads a research team including M.Sc. candidates Sammar Rath, Julia Rosada, Maximilian Witte, Tijmen Jansen, Claus Hegmann-Napp, and Magdalena Heynicke. Engages in interdisciplinary projects with industry partners.

• Earthquake Seismology
• Seismic Tomography
• Subduction Zone Processes
• +۴ مورد دیگر

Andreas Rietbrock is Professor and Director of the Geophysical Institute (GPI) at the Karlsruhe Institute of Technology (KIT) , Germany, where he also serves as Dean of Studies for Geophysics . He is a leading expert in earthquake seismology, seismic tomography, and subduction zone dynamics, with a strong focus on integrating advanced observational techniques and computational methods. Education: While specific degrees are not listed in the provided text, his extensive publication record and leadership roles indicate advanced academic training in geophysics and seismology. Research Interests: His work spans a wide range of topics including: Seismic imaging of subduction zones (e.g., Nazca, Lesser Antilles) Earthquake rupture dynamics and fault mechanics Volcanic seismology and magma transport Full waveform inversion and AI-enhanced seismic analysis Distributed Acoustic Sensing (DAS) applications Induced seismicity and reservoir monitoring Research Trends: His recent publications (2022–2025) emphasize the use of dense seismic arrays, AI-based data processing, and multi-method tomography to study complex tectonic environments. Key themes include high-resolution imaging of slab structures, fluid migration in subduction zones, and the integration of DAS and machine learning for seismic monitoring. Scientific Contributions: Andreas has led major international projects such as the ANTICS Large-N deployment in Albania and the VoiLA project in the Lesser Antilles. He has published extensively in top-tier journals like Nature , Geophysical Research Letters , and Journal of Geophysical Research , with over 200 peer-reviewed articles. Teaching and Supervision: He teaches courses such as "Introduction to Geophysics II", "Seismology", and "Current Topics in Seismology and Risk". While specific student names are not listed, his role as Dean and principal investigator on numerous projects indicates active supervision of graduate students and postdocs. Labs and Teams: He leads the seismology group at GPI, coordinating large-scale deployments of seismic instruments, including ocean-bottom seismometers and fiber-optic DAS systems. His team collaborates globally with institutions in Europe, South America, and Asia.

• Recommender Systems
• Machine Learning
• Natural Language Processing
• +۴ مورد دیگر

Julian McAuley is a Professor in the Department of Computer Science and Engineering at the University of California, San Diego's Jacobs School of Engineering. His research spans recommender systems, machine learning, natural language processing, music information retrieval, and multimodal learning. He maintains an active research group with numerous PhD students and postdocs working on cutting-edge AI problems. His research interests focus on developing advanced algorithms for personalized recommendation systems, with particular emphasis on sequential recommendation, multimodal learning, and integrating large language models with traditional recommendation approaches. His work bridges the gap between theoretical machine learning and practical applications across multiple domains including e-commerce, music, and healthcare. McAuley has published extensively in top-tier conferences including NeurIPS, ICML, KDD, SIGIR, and ACL, with his most recent work exploring the intersection of large language models and recommendation systems. His publications reveal a strong trend toward multimodal approaches that combine text, vision, and audio for more comprehensive understanding and recommendation. He has received significant research funding from major technology companies including Google, Amazon, Facebook, Adobe, and Samsung, as well as government agencies like the National Science Foundation and Department of Defense. His work has practical applications across multiple industries, with a focus on improving user experience through better personalization. McAuley advises numerous PhD students who have gone on to successful careers at leading technology companies and academic institutions. His former students include Wang-Cheng Kang and Jianmo Ni at Google DeepMind, Chris Donahue and Zachary Lipton as assistant professors at CMU, and Ruining He at Google Deepmind.

• Nuclear Medicine
• GATE Simulation
• Internal Radiation Therapy
• +۲ مورد دیگر

Francesca De Benetti is a Researcher at the Chair of Computer Aided Medical Procedures (Prof. Navab) at the Technical University of Munich (TUM), affiliated with the Interdisciplinary Research Laboratory (IFL) and NARVIS Lab at the Garching Campus. Her research focuses on Nuclear Medicine and Machine Learning for medical image processing, particularly in internal radiation therapy simulations and AI-driven segmentation. Education : M.Sc. in Biomedical Computing (TUM, 2018-2020), B.Sc. in Information Engineering (Università di Padova, 2015-2018) Francesca's recent publications highlight her work in Monte Carlo dosimetry , dynamic PET tracer modeling , and deep learning-based anomaly detection in medical imaging. Her projects emphasize personalized radiation therapy and cross-modality image translation , often involving collaborations with nuclear medicine experts and radiologists. She contributes to teaching at TUM, leading lectures and practical courses on topics including Medical Augmented Reality , Computer Aided Medical Procedures , and Deep Learning for Medical Applications . Francesca is actively involved in labs such as the IFL Lab and NARVIS Lab , focusing on interdisciplinary applications of computer vision and generative AI in medicine.

Ignacio Ojea Quintanaمشاهده پروفایل

استادیار

• Social Epistemology
• Philosophy of Data Science
• Ethics of Autonomous Decision Making
• +۴ مورد دیگر

Ignacio Ojea Quintana serves as Assistant Professor at Ludwig Maximilian University of Munich's Faculty of Philosophy, Philosophy of Science and Religious Studies within the Chair of Philosophy of Science. He joined LMU in 2022 after a three-year research fellowship at the Australian National University's School of Philosophy. His academic foundation includes a PhD in Philosophy from Columbia University (2019), supervised by Philip Kitcher with focus on formal social epistemology, and prior Masters/BA degrees in Philosophical Logic from the University of Buenos Aires where he collaborated with the Buenos Aires Logic Group. Ojea Quintana's research employs formal methodologies to examine digital technologies' impact on knowledge organization across scientific and public spheres. His work intersects Social Epistemology , Philosophy of Data Science , and Autonomous Systems Ethics , with significant contributions to social media network analysis of controversial movements. Current projects analyze Twitter dynamics in racial justice movements, ethical constraints in AI decision systems, and consensus formation in scientific modeling. His 2021-2022 publications reveal an interdisciplinary trajectory bridging philosophy, computer science, and social sciences. Key trends include computational analysis of online discourse, formal modeling of group rationality under uncertainty, and ethical frameworks for AI systems. Works appear in high-impact venues including Nature Humanities and Social Sciences Communications and the AAAI/ACM Conference on AI, Ethics, and Society. Ojea Quintana maintains active collaborations with the "Humanising Machine Intelligence" initiative (formerly at ANU) and the Buenos Aires Logic Group. His research program demonstrates sustained engagement with technology's societal implications through formal modeling approaches and empirical digital trace analysis.

Steffen Marburgمشاهده پروفایل

استاد

• Numerical Methods in Vibroacoustics
• Aeroacoustics
• Structural Optimization
• +۶ مورد دیگر

Prof. Dr. Steffen Marburg is a Full Professor at the Chair of Acoustics of Mobile Systems within the TUM School of Engineering and Design at the Technical University of Munich. His research focuses on numerical methods in vibroacoustics, structural optimization, and acoustic modeling for applications in automotive, maritime, and musical instrument domains. Education: PhD from Technical University of Dresden (1998). Academic Career: Junior Professor at TU Dresden (2004), Chair of Technical Dynamics at University of the Federal Armed Forces Munich (2010), Full Professor at TUM (2015–present). Editorial Roles: Co-Editor-in-Chief of Journal of Theoretical and Computational Acoustics, Associate Editor of Journal of the Acoustical Society of America, Editor of Acoustics Australia and Mechanical Systems and Signal Processing. His research integrates computational acoustics, boundary element methods, and machine learning to address noise control and structural optimization challenges. Recent work explores acoustic metamaterials, viscothermal losses, and data-driven modeling. He has co-authored over 150 publications and led advancements in multifrequency solution methods and noise-insulating structures. Scientific awards include the Innovation Award of the Industrieclub Sachsen e.V. (1999). His editorial contributions and leadership in journals highlight his influence in computational acoustics and structural dynamics.

• Energy Systems Optimization
• Conceptual Process Design
• Life Cycle Assessment
• +۸ مورد دیگر

Prof. Dr. André Bardow is a Full Professor in Energy and Process Systems Engineering at ETH Zurich , leading research at the intersection of thermodynamics, machine learning, and sustainable energy systems. Previously, he held professorships at RWTH Aachen University (2010-2020) and TU Delft (2007-2010). He also served as part-time director at Forschungszentrum Jülich (2017-2022) and visiting professor at UC Santa Barbara (2015/16). His work focuses on energy systems optimization , computer-aided molecular design , and CO2 capture & utilization . PhD from RWTH Aachen University Current ETH Zurich affiliation Former roles at RWTH Aachen, TU Delft, Jülich Research Center His research integrates machine learning with thermodynamic modeling to optimize processes like crystallization and electrochemical cooling . Recent publications demonstrate advancements in solvent design, CO2 transport LCA, and ORC working fluid optimization. He chairs the VDI Technical Committee for Thermodynamics (2016-2024) and has received multiple awards including the Covestro Science Award and Arnold-Eucken-Award . Current projects address carbon circular economies , electrified chemical production , and AI-driven process optimization . His lab at ETH Zurich develops cutting-edge technologies like ML-CAMPD frameworks for sustainable separation processes and photoacid-based CO2 capture systems. Funding from the H2020 Systemic Expansion of Circular Ecosystems (grant 101036854) supports these initiatives. 2024 Clarivate Highly Cited Researcher 2022 Inaugural Lecture: "To sustainability and beyond: A computer-animated story on energy & chemicals" Recipient of multiple teaching and research excellence awards

Marco Platznerمشاهده پروفایل

استاد

• Reconfigurable Computing
• Approximate Computing
• Self-Aware Computing
• +۷ مورد دیگر

Marco Platzner is a Professor for Computer Engineering at Paderborn University , Germany. He serves as the Dean of Research for the Faculty of Computer Science, Electrical Engineering and Mathematics and heads the Department of Computer Science. Previously, he held research positions at ETH Zurich, Stanford University, GMD (now Fraunhofer IAIS), and Graz University of Technology. Education: Diploma and PhD in Telematics (Graz University of Technology, 1991 and 1996), Habilitation in Hardware-Software Co-Design (ETH Zurich, 2002) Research Interests focus on reconfigurable computing, approximate computing, self-* computing, and embedded systems. His work addresses hardware security, FPGA design, and sustainable AI in data centers. Current projects include energy-efficient AI through deep neural network approximation for FPGAs (EKI-App) and lifecycle sustainability of socio-technical systems (SAIL). Publication Trends show expertise in FPGA security, approximate circuit synthesis, robotics, and hardware acceleration. Collaborations span robotics (ROS 2 integration), AI (transformer optimization), and cybersecurity (Trojan detection). Scientific Awards: ACM SIGDA Hall of Fame (2020) Significant Paper Award (FPL 2015) Best Paper Awards at IEEE ISVLSI (2024), ARC (2018), IEEE ReConFig (2015), and others Weierstraß Prize for Teaching (2008) Leadership Roles include membership in the board of Paderborn Center for Parallel Computing (PC2) and the Jenny Aloni Centre for Early Career Researchers. He has contributed to EU FP7 FET project EPiCS and German priority programs on embedded systems and organic computing.

• Computer Vision
• Machine Learning
• 3D Human Modeling
• +۴ مورد دیگر

Michael J. Black is a Professor and Honorarprofessor at the University of Tübingen's Faculty of Science, Department of Computer Science, and a founding Director of the Max Planck Institute for Intelligent Systems, leading the Perceiving Systems department. He holds a B.Sc. from the University of British Columbia (1985), M.S. from Stanford (1989), and Ph.D. in Computer Science from Yale (1992). His research focuses on computer vision, 3D human modeling, motion capture, and AI-driven digital humans. Key contributions include the SMPL body model, optical flow algorithms, and datasets like Middlebury Flow and Sintel. He has received major awards such as the PAMI Distinguished Researcher Award, multiple Koenderink and Longuet-Higgins Prizes, and is a member of the German National Academy of Sciences Leopoldina and Royal Swedish Academy of Sciences. His commercial ventures include co-founding Body Labs (acquired by Amazon) and Meshcapade, advancing 3D human generation and interaction technologies. Recent work includes markerless motion capture systems (e.g., MAMMA, PICO), 3D hair and garment synthesis, and AI tools like ChatHuman for 3D human interaction analysis. His research bridges vision, graphics, and robotics, with applications in animation, healthcare, and robotics.

Volker Ahrensمشاهده پروفایل

استاد

• Systems Engineering
• Production Management
• Lean Production
• +۵ مورد دیگر

Volker Ahrens is a Professor of Production Management at NORDAKADEMIE since 2007. He also serves as Head of the Industrial Engineering (B.Sc.) program and the International Business & Administration (B.Eng.) program, while acting as Coordinator of the Department of Engineering. His career spans academic and industrial roles, including leadership positions in medium-sized industrial companies and editorial work on VDI standards. Education: Diplom-Ingenieur in Mechanical Engineering (1989, Universität Hannover); Doktor-Ingenieur (1997, Universität Hannover) Industrial Experience: 10 years of executive management in industry, including König Metall GmbH & Co. KG and Wilhelm Schröder GmbH His research focuses on Systems Engineering and Production Management, with emphasis on lean production, quality management, and Industry 4.0. His publications since 2025 explore systemic approaches to socio-technical systems, cardboard engineering for collaborative design, and human-technology interaction in production environments. He has contributed extensively to process modeling, simulation of production systems, and meta-process frameworks like PDCA cycles. The 15 most recent articles highlight trends in systemic production design, lean manufacturing, and Industry 4.0 applications. Key keywords include Systems Engineering, Production Management, Lean Production, and Quality Management. Subfields span socio-technical systems, simulation techniques, human-centered design, and cyber-physical system integration across industrial contexts. Volker Ahrens is actively involved in teaching, serving as a lecturer at Hochschule Karlsruhe (1998–2013) and Fachhochschule Vorarlberg (since 2017). He contributes to academic governance as a member of the NORDAKADEMIE faculty and chairs VDI committees on simulation standards for production systems. His advisory roles include peer reviewing for quality assurance agencies like FIBAA and ZEvA.

• Natural Language Processing
• Computational Linguistics
• Event Detection and Understanding
• +۴ مورد دیگر

Teruko Mitamura is a prominent researcher at Carnegie Mellon University with over three decades of contributions to natural language processing, computational linguistics, and artificial intelligence. Her work spans from foundational research in event representation to advanced applications in multimodal systems and question answering. Her research interests focus on event detection and understanding, question answering systems, information retrieval, and multimodal processing. She has made significant contributions to event coreference resolution, timeline construction, and cross-document event analysis, developing methodologies that have become standard in the field. Her work often bridges theoretical advances with practical applications, particularly in complex information environments requiring deep semantic understanding. Natural Language Processing : Specializing in event extraction, coreference resolution, and narrative understanding with over 179 publications Question Answering Systems : Developing advanced techniques for complex question answering, particularly through NTCIR QA Lab and PoliInfo tasks Multimodal Processing : Integrating textual, visual, and temporal information for richer understanding in systems like ProMQA Evaluation Methodologies : Creating robust frameworks for assessing NLP systems through TAC KBP Event Tracks Her recent publication trends show a strong focus on leveraging large language models for event understanding, multimodal question answering, and timeline construction. She has expanded her research into specialized domains including patent analysis and novelty examination, demonstrating the breadth of her research impact across academic and practical applications. Active participant in major NLP conferences including ACL, EMNLP, NAACL, and AAAI with consistent publications Long-standing collaborator with researchers at CMU's Language Technologies Institute including Eduard H. Hovy and Eric Nyberg Contributor to shared tasks that have shaped research directions in event processing and question answering Organizer of multiple NTCIR QA Lab tasks focused on political information question answering Dr. Mitamura has mentored numerous researchers who have gone on to make their own contributions to the field, as evidenced by her extensive co-authorship network and the progression of her former students and collaborators into faculty and research positions. Her work continues to evolve with the field while maintaining her focus on deep semantic understanding of events and narratives.