جست‌وجوی استاد و پژوهشگر

Stéphane BAUDRONمشاهده پروفایل

استاد پژوهشی

• Coordination Chemistry
• Metal-Organic Frameworks
• Molecular Materials
• +۴ مورد دیگر

Stéphane BAUDRON is a CNRS Research Director at the Laboratory for the Synthesis and Functions of Molecular Architectures within the Faculty of Chemistry at the University of Strasbourg. His research spans multiple areas of molecular materials chemistry, with particular expertise in coordination polymers, metal-organic frameworks, and supramolecular architectures. Dr. BAUDRON's educational background includes undergraduate studies at the National School of Chemistry of Paris (1998), a Ph.D. from the University of Angers under Dr. Patrick Batail (2002), and postdoctoral research at the University of California Berkeley with Prof. Jeffrey R. Long (2002-2004). He joined CNRS as a researcher in 2004, received his Habilitation from the University of Strasbourg in 2009, and was promoted to CNRS Research Director in 2019. His primary research interests focus on dipyrrin-based complexes and assemblies for luminescent materials and heterometallic frameworks, conducting coordination polymers using redox-active ligands, and the application of deep eutectic solvents for sustainable synthesis of porous materials. His work bridges fundamental coordination chemistry with practical applications in materials science. Analysis of his recent publications reveals a strong trend toward green chemistry approaches for synthesizing metal-organic frameworks, with increasing focus on deep eutectic solvents as environmentally friendly alternatives to traditional solvents. His research spans both fundamental coordination chemistry and applied materials science, with particular emphasis on structure-property relationships in crystalline materials. Lavoisier fellowship (French Ministry of Foreign Affairs) JSPS short-term invitation fellowship at Kyoto University USIAS fellowship ANR DEEPCatCOF project (Principal Investigator) Dr. BAUDRON has successfully mentored numerous graduate students who have gone on to careers in both industry and academia, including positions at Michelin, BASF, and various universities. His current research is supported by multiple grants, including the ANR DEEPCatCOF project focused on deep eutectic solvents for catalytic metal-organic frameworks. His laboratory maintains strong international collaborations with research groups in Japan, Portugal, and other European institutions. Based at the University of Strasbourg's Institute Le Bel, Dr. BAUDRON leads a research team within the Laboratory for the Synthesis and Functions of Molecular Architectures, which is part of the larger Faculty of Chemistry structure. His group actively collaborates with other laboratories within the chemistry faculty, particularly those working on spectroscopy, mass spectrometry, and molecular modeling.

Erik Learned-Millerمشاهده پروفایل

استاد

• Machine Learning
• Computer Vision
• Artificial Intelligence
• +۱۱ مورد دیگر

Erik Learned-Miller is a Professor and Chair of the Faculty at the Manning College of Information and Computer Sciences (CICS), University of Massachusetts Amherst. He is based in the Department of Computer Science and leads the Computer Vision Lab, with strong affiliations to the Center for Data Science. His work bridges machine learning and computer vision, focusing on foundational and ethical aspects of visual recognition systems. Education: PhD in Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 2002 MS in Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 1997 BA in Psychology, Yale University, 1988 Learned-Miller's research centers on machine learning methods for computer vision problems, particularly in scenarios with limited labeled data. His work includes one-shot learning , face detection and recognition , image and video segmentation , joint image alignment , and text recognition . He emphasizes unsupervised, self-supervised, and semi-supervised learning paradigms, and is actively involved in addressing societal concerns around the regulation of face recognition technology. His contributions have had a major impact on the computer vision community, most notably through the creation of widely used benchmarks such as Labeled Faces in the Wild and the Face Detection Database and Benchmark , which have become standard evaluation tools in the field. Scientific Awards and Honors: NSF CAREER Award (2006) Mark Everingham Award (2019) Microsoft-MIT Graduate Student Fellowship Learned-Miller has played significant roles in the academic community, including serving as Program Chair for the 2015 Conference on Computer Vision and Pattern Recognition (CVPR) and as a member of the editorial board of the Journal of Machine Learning Research . He has secured competitive research funding, including the NSF CAREER award, supporting his long-term research agenda. While specific advisees are not listed, he mentors graduate students through his lab and departmental roles. He leads the Computer Vision Lab at UMass Amherst, a research group focused on advancing the state of the art in visual understanding through machine learning. The lab is part of the broader research ecosystem within CICS and collaborates with the Center for Data Science, contributing to interdisciplinary efforts in AI and data-driven science.

Florian Schäferمشاهده پروفایل

استادیار

• Numerical Analysis
• Computational Mathematics
• Machine Learning
• +۹ مورد دیگر

Florian Schäfer is an Assistant Professor at the School of Computational Science and Engineering at Georgia Tech. His research spans numerical computation, statistical inference, and competitive games, with applications in materials science, turbulence modeling, computer graphics, and computational geometry. He will join the Courant Institute at NYU in September 2025. PhD in Applied and Computational Mathematics, Caltech Bachelor’s and Master’s in Mathematics, University of Bonn His work focuses on information geometric mechanics to design structure-preserving numerical methods for continuum mechanics. This includes: State-of-the-art solvers for elliptic PDEs via Gaussian elimination and conditional independence Efficient multi-agent optimization algorithms Information geometric regularization for compressible fluid dynamics Enabling the first compressible fluid simulation exceeding 100 trillion grid cells His recent research trends integrate: Machine learning for materials science (e.g., active learning, Bayesian approaches) Stochastic modeling of microstructures and phase-field problems Neural operators for super-resolution fluid dynamics Generative models for polycrystalline material datasets Optimal transport and diffusion models for conditional density transformations High-performance computing at extreme scales Florian collaborates with researchers including Houman Owhadi, Jessie Liu, Spencer Bryngelson, Tamer Zaki, and Ali Mani. He actively presents at conferences like SIAM and UCLA seminars, and is recruiting PhD students for work at the Courant Institute starting 2025.

Supratik Chakrabortyمشاهده پروفایل

استاد

• Formal Methods
• Formal Verification
• Automated Synthesis
• +۷ مورد دیگر

Supratik Chakraborty serves as the Bajaj Group Chair Professor in the Department of Computer Science and Engineering at Indian Institute of Technology Bombay. He maintains dual affiliations with the Centre for Formal Design and Verification of Software and the Centre for Liberal Education at IIT Bombay, demonstrating his cross-disciplinary engagement. Professor Chakraborty's research spans formal methods with focus on formal verification, rigorous analysis of system models, and automated synthesis of systems from specifications. His work bridges theoretical foundations with practical applications, particularly in developing mathematically provable guarantees for increasingly complex hardware, software, and intelligent systems. Current research interests include constrained counting and sampling, scalable formal verification of software and hardware systems, automated synthesis of programs and circuits, and applications of automata, logic and finite model theory to practical verification challenges. His publication trajectory shows a significant evolution from traditional hardware and software verification toward addressing verification challenges in machine learning and AI systems. Recent work increasingly focuses on interpretability of black-box models, verification of neural networks, and synthesis techniques applicable to intelligent systems. The research demonstrates strong interdisciplinary connections between formal methods, programming languages, and artificial intelligence. IIT Bombay Excellence in Thesis (CSE) Award 2011 (for Bhargav Gulavani's thesis) IIT Bombay Excellence in Thesis (CSE) Award 2017 (for Abhisekh Sankaran's thesis) Best Paper in Algorithms and Architecture track at IEEE International Conference on Computer Design: VLSI in Computers and Processors, 1998 Professor Chakraborty has successfully supervised 11 doctoral students, with research spanning formal verification techniques, Boolean functional synthesis, constrained counting, and applications to hardware and software systems. His students have gone on to positions at major institutions including Microsoft Research, TCS Research, Georgia Tech, and BARC, reflecting the strong industry and academic impact of his mentorship. Current research directions show increasing emphasis on verification challenges posed by machine learning systems and AI. His research group at IIT Bombay, while not explicitly named in the materials, appears to focus on formal methods with strong connections to the Centre for Formal Design and Verification of Software. The group maintains active collaborations with international researchers including Moshe Y. Vardi at Rice University, and has made significant contributions to verification tools like VeriAbs that bridge theoretical advances with practical applications.

Jingtong Huمشاهده پروفایل

دانشیار

• Cyber-Physical Systems
• Infrastructure Security
• Non-Volatile Memory Systems
• +۶ مورد دیگر

Jingtong Hu is an Associate Professor at the Swanson School of Engineering, University of Pittsburgh, where he also holds the William Kepler Whiteford Faculty Fellowship. His research focuses on Cyber-Physical Systems and Infrastructure Security, with significant contributions to embedded systems, non-volatile memory architectures, and hardware/software co-design for energy-constrained environments. Dr. Hu received his PhD from the University of Texas at Dallas (2007-2013) and his Bachelor of Engineering from Shandong University (2003-2007). His research spans multiple interdisciplinary areas including energy harvesting systems, non-volatile processors, FPGA acceleration, and machine learning at the edge. His recent publications demonstrate a strong focus on algorithm-hardware co-design, particularly for vision transformers, federated learning, and non-volatile memory systems. His work often addresses the challenges of implementing AI on resource-constrained edge devices, with emphasis on energy efficiency, reliability, and performance optimization. The trend in his publications shows increasing focus on sustainable AI processing, heterogeneous computing architectures, and personalized machine learning for IoT applications. Selected Awards: IEEE Transactions on Computer-Aided Design Donald O. Pederson Best Paper Award (2021) ACM SIGDA Meritorious Service Award (2019) Multiple Best Paper Award nominations at top conferences including DAC, ASP-DAC, and CODES+ISSS Dr. Hu's research has been supported by multiple grants focusing on energy-efficient computing, non-volatile memory systems, and hardware acceleration for machine learning. His collaborative work spans numerous institutions and involves interdisciplinary teams working at the intersection of computer architecture, embedded systems, and artificial intelligence. His publications show extensive collaboration with researchers at the University of Pittsburgh, particularly with Albert K. Jones and Yiyu Shi. His laboratory work focuses on implementing practical systems for energy harvesting powered devices, non-volatile processors, and hardware accelerators for machine learning applications. Current projects appear to emphasize sustainable AI processing at the edge, heterogeneous FPGA acceleration, and personalized federated learning for health monitoring applications.

Yali Tangمشاهده پروفایل

استادیار

• Fluid Dynamics
• Multiphase Flow
• Physicochemical Conversions
• +۷ مورد دیگر

Yali Tang is an Assistant Professor in the Department of Mechanical Engineering at Eindhoven University of Technology (TU/e), specializing in fluid dynamics and transport phenomena within multiphase flows and physicochemical conversions . Her work targets Iron Power technology , green steel production , and alkaline water electrolysis for hydrogen generation, combining advanced computational models with experimental validation . Education: Master's in Chemical Engineering from Sichuan University (2011) PhD in Mechanical Engineering at TU/e (2015) with Prof. Hans Kuipers Research Interests: She focuses on interphase interactions , interfacial transport mechanisms , and high-resolution simulations (down to 40 nm mesh) to predict bubble coalescence and film dynamics. Her studies on hydrogen bubble growth , dendritic iron formation , and gas distribution in electrolyzers aim to refine reactor design and industrial processes. Collaborations with industrial partners ensure practical applicability of her computational models. Recent Publications: Her 2025 work includes dimensional analysis of liquid film formation, solutal Marangoni effects in electrolysis, and X-ray validation of gas distribution models. Earlier studies (2020–2023) cover defluidization behavior of iron fines, CFD-DEM modeling of raceways, and acoustic field applications in particle dynamics. Labs & Collaborations: She leads computational efforts within the Power & Flow group under Prof. Niels Deen, contributing to the EIRES Research cluster. Her work bridges academic research with industrial innovation in fluid dynamics and energy transition technologies.

Dimitra Psychogiouمشاهده پروفایل

استاد

• Microwave Engineering
• RF Filters
• Millimeter-wave Technology
• +۴ مورد دیگر

Dimitra Psychogiou is a Full Professor of Microwave Engineering at University College Cork and Principal Investigator at Tyndall National Institute's CONNECT Centre in Cork, Ireland. She leads the Advanced RF Technology Group, driving innovation in reconfigurable RF systems for next-generation wireless networks. Her academic credentials include: Dipl.-Eng. in Electrical and Computer Engineering, University of Patras (2008) Ph.D. in Electrical Engineering, ETH Zurich (2013) Prof. Psychogiou's research pioneers reconfigurable microwave filters , non-reciprocal RF components , and additive manufacturing for antenna systems . Her work bridges theoretical microwave engineering with practical implementations in 5G/6G front-ends, emphasizing sustainability through hyperflexible filtering architectures that reduce hardware complexity and energy consumption. Key innovations include acoustic-wave resonator filters and 3D-printed RF components enabling unprecedented miniaturization. Analysis of her 2022-2025 publications reveals a strategic shift toward multifunctional RF integration , where filtering coexists with isolation, amplification, and switching in single modules. This trend addresses critical industry needs for compact, software-defined radio front-ends in satellite communications and IoT networks, with increasing emphasis on reflectionless topologies and spatiotemporal modulation techniques. Her scientific recognition includes: 2023 MTT-S Outstanding Young Engineer Award 2021 Roberto Sorrentino Prize 2021 SFI Research Professorship 2020 NSF CAREER Award 2020 URSI Young Scientist Award UC Boulder Junior Faculty Research Award Prof. Psychogiou actively shapes her field through leadership roles as Chair of IEEE MTT-13 Committee and Secretary of USNC-URSI Commission D, while serving as Associate Editor for IEEE MWCL and IJMWT. Her group collaborates extensively with semiconductor foundries and wireless infrastructure companies to transition lab innovations to commercial applications. The Advanced RF Technology Group operates state-of-the-art facilities for GaAs MMIC prototyping, 3D-printed RF component fabrication, and full-wave electromagnetic characterization, supporting Ireland's strategic position in European telecommunications research.

Benjamin Mako Hillمشاهده پروفایل

دانشیار

• Peer Production
• Online Communities
• Collective Action
• +۷ مورد دیگر

Benjamin Mako Hill is an Associate Professor in the University of Washington Department of Communication and an Adjunct Associate Professor in Human-Centered Design & Engineering , the Paul G. Allen School of Computer Science & Engineering , and the Information School at UW. He is a Faculty Associate at the Berkman Klein Center for Internet and Society at Harvard University and a Fellow at the Center for Information Technology Policy at Princeton University during the 2023–2024 academic year. Educational Background : PhD in an interdepartmental program at Massachusetts Institute of Technology (MIT) , involving the MIT Sloan School of Management and the MIT Media Lab , advised by Eric von Hippel, Yochai Benkler, Tom Malone, and Mitch Resnick. MS in Media Arts and Sciences from MIT. B.A. in Technological and Legal History from Hampshire College . Research Interests span peer production, online communities, collective action, cooperation, learning, and computer-mediated communication. His work explores how communication and information technologies shape social outcomes in collaborative environments like Wikipedia and Linux, focusing on governance, moderation, anonymity, and educational platforms such as Scratch. Article Trends : His publications analyze peer production dynamics, privacy in open collaboration, and computational thinking in youth. Topics include underproduction in open source software, algorithmic fairness, taboo knowledge production, and legitimate peripheral participation in online communities. Methodologies combine big data, quasi-experimental, and comparative analyses. Scientific Awards : Dordick Award for Best Dissertation (2013). CHI '22 Best Paper Honorable Mention (2022). CSCW '18 Best Paper Honorable Mention (2018). CHI '17 Best Paper Honorable Mention (2017). CSCW '13 Best Paper Award (2013). CHI '11 Best Paper Honorable Mention (2011). Advising and Grants : He co-founded the Community Data Science Collective and collaborates with researchers like Aaron Shaw. Grants include multiple National Science Foundation awards for studies on digital knowledge commons, anonymous participation, and collaborative success, as well as a Sloan Foundation grant for modeling underproduction in peer production. Labs and Teams : He leads the Community Data Science Collective , an interdisciplinary research group studying online communities, and contributes to open-source projects like Debian and Ubuntu . He actively edits Wikimedia projects and participates in the Cascadia Wikimedians User Group .

• Environmental Science and Engineering
• Photocatalytic Materials
• Water Quality Engineering
• +۳ مورد دیگر

Jaehong Kim is the Henry P. Becton Sr. Professor of Engineering at Yale University, where he serves as Professor and Chair of Chemical and Environmental Engineering in the School of Engineering and Applied Science. Prior to joining Yale in 2013, he held the Georgia Power Distinguished Professor position at the Georgia Institute of Technology. His research bridges environmental science, chemical engineering, and nanotechnology, focusing on photocatalytic materials, water quality engineering, and sustainable solutions for global health contexts. Ph.D., Environmental Engineering, University of Illinois at Urbana-Champaign (2002) M.S., Chemical and Biological Engineering, Seoul National University (1997) B.S., Chemical and Biological Engineering, Seoul National University (1995) Kim’s work addresses water treatment through advanced oxidation processes , electrochemical systems , and single-atom catalysts , with applications in nitrate removal, fluoride transport, and solar disinfection. His research emphasizes nanotechnology for environmental remediation and public health engineering in developing regions. Recent publications highlight electrified membranes for nitrate conversion, photothermal water disinfection , and single-atom catalysts for pollutant degradation. His team explores atomic-scale engineering and green chemistry approaches to enhance reaction efficiency and material durability. Georgia Power Distinguished Professor Yale Superfund Research Center investigator Kim leads interdisciplinary efforts in environmental health through collaborations with Yale School of Public Health and the School of the Environment. His lab develops monolithic catalytic membranes and nanobiochars for sustainable water treatment, balancing technical innovation with global accessibility.

Urs Jenalمشاهده پروفایل

استاد

• Bacterial Signal Transduction
• Microbiology
• Antibiotic Resistance
• +۵ مورد دیگر

Professor Urs Jenal is a Full Professor at the Biozentrum of the University of Basel, Switzerland, where he has led research on bacterial signal transduction since 2008. His laboratory investigates the molecular mechanisms of bacterial persistence and antibiotic resistance, with particular focus on pathogens causing chronic infections in humans. Previously, he served as Associate Professor (2002-2008) and Assistant Professor (1996-2002) at the same institution, and completed postdoctoral training at Stanford University and ETH Zurich. Education 2000: Habilitation and VENIA DOCENDI in Microbiology, University of Basel 1987-1991: PhD in Molecular Microbiology, ETH Zurich (supervisor: Prof. T. Leisinger) 1982-1986: Studies of Experimental Biology, ETH Zurich 1977-1981: Gymnasium with Matura Type C, Chur Research Focus Prof. Jenal's research centers on understanding how bacterial pathogens persist in the human body despite antibiotic treatments. His laboratory investigates cyclic nucleotides, particularly c-di-GMP, as signaling molecules that control bacterial biofilm formation, virulence, and antibiotic tolerance. His team studies pathogenic Escherichia coli causing recurrent urinary tract infections and Pseudomonas aeruginosa causing long-term lung infections in cystic fibrosis patients. Recent work has revealed how "sleeping" bacteria survive antibiotic treatments and how pathogens breach respiratory epithelia through goblet cell invasion. Scientific Recognition 2014: Elected member of the European Academy of Microbiology (EAM) 2013: ERC Advanced Investigator Award 2012: Elected member of the European Molecular Biology Organization (EMBO) 2011: Elected member of the American Academy of Microbiology (AAM) Mentorship and Collaborations Prof. Jenal has mentored numerous PhD students and postdocs, many receiving awards for their research. His laboratory is part of the NCCR AntiResist initiative focused on developing novel approaches against antibiotic resistance. He collaborates extensively with clinical researchers and has developed innovative models, including human mini-lungs, to investigate pathogen-host interactions. His recent publications demonstrate how understanding bacterial persistence mechanisms can lead to new therapeutic strategies against chronic infections.

• Robotics
• Mechatronics
• Humanoid Robots
• +۴ مورد دیگر

Atsuo Takanishi is a distinguished Professor at Waseda University's Faculty of Science and Engineering, School of Creative Science and Engineering, with appointments in both the Department of Bioscience and Biotechnology and the Department of Modern Mechanical Engineering. With over 700 publications, 10,399 citations, and an h-index of 47, Professor Takanishi has established himself as a leading figure in robotics research. His work spans multiple institutions, including visiting positions at Showa University School of Dentistry and KDDI Research, Inc. Professor Takanishi received his Doctor of Engineering degree from Waseda University in 1985, following his undergraduate studies in the Faculty of Science and Engineering at the same institution, which he completed in 1980. His academic journey began with positions as an Assistant at Waseda University (1985-1988), Lecturer (1988-1990), and Associate Professor (1990-1997) before achieving his current Professor status. Professor Takanishi's research interests center around robotics and intelligent systems, with particular expertise in humanoid robotics, surgical dentistry applications, and biomechatronics. His work demonstrates a unique integration of mechanical engineering principles with biological systems, resulting in innovative robotic platforms that mimic human capabilities. Notably, his laboratory has developed the Waseda Anthropomorphic Saxophonist Robot series and various medical training simulators that have significantly advanced the field of human-robot interaction. His research in experimental psychology complements his robotics work, particularly in human-robot interaction studies. Analysis of Professor Takanishi's recent publications reveals a strong focus on practical applications of robotics technology, particularly in assistive devices for elderly mobility, medical training simulators, and agricultural robotics for Synecoculture environments. His work consistently bridges theoretical robotics with real-world implementation, with recent papers emphasizing reinforcement learning approaches, haptic feedback systems, and computer vision techniques for complex environments. The Waseda Anthropomorphic Saxophonist Robot series represents a culmination of decades of research in humanoid robotics and musical expression. IEEE Fellow (2020-present) Robotics Society of Japan Fellow (2012-present) Japan Society of Mechanical Engineers Fellow (2007-present) Multiple Best Paper Awards from IEEE conferences (ICRA, IROS, ROMANSY) BusinessWeek Asia's Stars Bloomberg (2001) IFToMM Award of Merit (2010) Professor Takanishi has maintained extensive collaborations with research institutions worldwide, particularly with Italian institutions through the Italy-Japan Workshop series. His laboratory has secured substantial funding from Japanese government agencies including the Japan Science and Technology Agency, with particular emphasis on projects bridging robotics with medical applications and human-centered technologies. His international recognition is evidenced by his numerous visiting professorships and collaborative projects across continents. Professor Takanishi leads the Takanishi Laboratory at Waseda University, which maintains specialized facilities for humanoid robotics development, medical robotics research, and human-robot interaction studies. The laboratory has developed several notable robotic platforms including the WABIAN series of bipedal humanoid robots, the WASEDA FLUTIST ROBOT, and various medical training simulators used in clinical education settings. His work on the WASEDA SAXOPHONIST ROBOT represents a unique fusion of musical artistry and robotics engineering.

• Cognitive Robotics
• Developmental Robotics
• Human-Robot Interaction
• +۵ مورد دیگر

Tetsuya Ogata is a Professor at the Faculty of Science and Engineering, School of Fundamental Science and Engineering at Waseda University. He also holds joint appointments as a Fellow at the Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST), and as a visiting professor at the National Institute of Informatics (NII). Professor Ogata serves as director of the Institute of AI and Robotics at Waseda University, chairperson of the AI Robot Association (AIRoA), and research supervisor of JST CREST "Fundamentals and Core Technologies for Embodied AI" since 2025. Professor Ogata received his B.S., M.S., and D.E. degrees in mechanical engineering from Waseda University in 1993, 1995, and 2000, respectively. He began his academic career as a Research Associate at Waseda University (1999-2001), followed by positions as a Research Scientist at RIKEN Brain Science Institute (2001-2003), Lecturer (2003-2005) and Associate Professor (2005-2012) at Kyoto University's Graduate School of Informatics, before becoming a Professor at Waseda University in 2012. He was also a JST PRESTO Researcher from 2009 to 2015. Professor Ogata's research focuses on cognitive developmental robotics, deep predictive learning, and the integration of vision, language, and action (VLA) for human-robot interaction. His work explores how robots can learn through experience and interaction with humans and environments, developing models that allow for flexible behavior generation and adaptation. His research has significant implications for creating robots that can understand human intentions, collaborate effectively in real-world settings, and continuously learn from their experiences. The integration of multimodal information processing with predictive models forms the core of his approach to embodied artificial intelligence. Analysis of Professor Ogata's recent publications reveals a strong focus on deep predictive learning frameworks that enable robots to anticipate future states and generate appropriate actions. His research spans multiple domains including soft object manipulation, bimanual coordination, transparent object grasping, and integration of large language models with robotic systems. A notable trend is the increasing emphasis on multimodal integration, combining visual, tactile, and linguistic information to create more robust and adaptable robotic systems. His recent work also shows growing interest in the application of foundation models to robotics, aiming to create more general-purpose robotic capabilities. Best Paper Award, Advanced Robotics, The Robotics Society of Japan (2024) Best paper award Nomination Finalist, IEEE/SICE International Symposium on System Integration (2024) Frontiers of Science Awards, The International Congress for Basic Science (2023) Minister of Education, Culture, Sports, Science and Technology Award (2023) Fellow, Japan Society of Mechanical Engineering (2023) Fellow, The Society of Instrument and Control Engineers (2022) Fellow, The Robotics Society of Japan (2022) IBM Academic Awards (2017) Professor Ogata has been instrumental in establishing collaborative research frameworks between academia and industry, serving in leadership roles for multiple professional organizations including the Robotics Society of Japan, Japanese Society for Artificial Intelligence, and Japan Deep Learning Association. His research has been supported by significant grants including JST CREST funding for "Fundamentals and Core Technologies for Embodied AI." He has mentored numerous researchers who have gone on to contribute to the field of robotics and AI, with many of his former students now holding positions in leading academic and industrial research institutions. Professor Ogata directs the Ogata Laboratory at Waseda University, which focuses on cognitive developmental robotics and deep predictive learning. The lab maintains strong collaborations with industry partners including major robotics companies and technology firms. In 2025, he played a key role in establishing the AI Robot Association (AIRoA), which brings together companies like Toyota, Nissan, and KDDI to advance the development of practical AI robotics technologies. His research group is known for its interdisciplinary approach, combining insights from neuroscience, cognitive science, and engineering to create more human-like robotic capabilities.

Mary Lanzerottiمشاهده پروفایل

استادیار

• Signal Processing
• Control Systems
• Medical Technology
• +۴ مورد دیگر

Mary Lanzerotti is a Collegiate Assistant Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. She specializes in signal processing, control systems, and medical evacuation technology. Her research focuses on hoist stabilization for MEDEVAC rescues, RF signal estimation, and material science involving liquid films. She is also deeply involved in educational initiatives, including hybrid course development and student advising strategies. Education: A.B. summa cum laude from Harvard College (1989), M. Phil. from the University of Cambridge (1991), M.S. and Ph.D. from Cornell University (1994–1997). Research Interests: Signal processing algorithms, mechanical stabilization of hoist systems, quantum computing verification, and integrated circuits design. Recent work includes gyroscopic data-driven control systems and multi-tier RF signal estimation methods. Service Roles: Member of faculty search committees, assessment committees, and the Graduate Honor System panel. Active in institutional accreditation and curriculum modernization efforts. Labs/Teams: Collaborates with interdisciplinary teams on projects involving aerospace rescue systems, laser material interaction studies, and microelectronics verification.

Qian Yangمشاهده پروفایل

استادیار

• Human-AI Interaction
• User Experience (UX) Design
• Healthcare Technology
• +۴ مورد دیگر

Qian Yang is an Assistant Professor in Information Science at Cornell University, with a faculty appointment in Computer Science. Her research focuses on human-AI interaction, designing AI applications for healthcare, autonomous systems, and UX design. She holds a PhD in Human-Computer Interaction from Carnegie Mellon University and has industry experience in design consultancy (2007–2014). Yang co-directs the Cornell Digital and AI Literacy Initiative and is a Senior Fellow at the Cornell Brooks Tech Policy Institute. Her work emphasizes bridging AI technologies with societal needs, supported by awards like the Schmidt Futures AI2050 Fellowship. She leads the DesignAI research group, focusing on AI-driven design methods and tools for practitioners. Education: PhD in HCI (Carnegie Mellon), M.S. in HCI (CMU), M.Des in Design, B.Eng in Industrial Design (Shanghai Jiao Tong University). Research interests include AI ethics, healthcare decision support systems, and context-aware mobile services. Notable contributions include: Developing AI systems for life-critical healthcare decisions (e.g., artificial heart implants) Innovating UX design methods for integrating AI into practice Advancing human-centered AI evaluation frameworks Awards include the SIGCHI Outstanding Dissertation Award and AI2050 Fellowship. She actively collaborates across disciplines, with work published in top HCI venues like CHI and ACM Transactions.

• Photogrammetry
• Geoinformation
• Remote Sensing
• +۷ مورد دیگر

Prof. Christian Heipke is a distinguished academic serving as Dean of the Faculty of Civil Engineering and Geodetic Science at Leibniz University Hannover, Germany. He also holds the position of Executive Director at the Institute of Photogrammetry and GeoInformation (IPI), one of the leading research institutions in geospatial sciences within the faculty. His leadership extends across multiple committees including the Curriculum and Teaching Committee, Admissions and Examination Boards for Geodetic Science and Geoinformatics, and Navigation and Environmental Robotics. As a Professor at IPI, he maintains active research while overseeing significant academic and administrative responsibilities at the university. Professor Heipke's research spans multiple domains within geospatial sciences, with particular emphasis on: Advanced photogrammetric techniques and algorithms Remote sensing applications for environmental monitoring Computer vision approaches for geospatial data analysis Urban development monitoring using satellite imagery Machine learning applications in geoinformatics Disaster prediction and management systems His recent scholarly output reveals a strong focus on integrating cutting-edge computer vision and deep learning techniques with traditional photogrammetric methods. Analysis of his 15 most recent publications shows a clear trajectory toward more sophisticated AI-driven approaches for processing geospatial data, with particular attention to time-series analysis, uncertainty quantification, and multi-view systems. His work bridges theoretical advancements with practical applications in flood forecasting, deforestation monitoring, urban planning, and construction materials analysis. The geographic scope of his research has expanded significantly, with recent projects focusing on international case studies in the Philippines and tropical regions. Professor Heipke leads the Institute of Photogrammetry and GeoInformation, a major research hub that has celebrated 75 years of contributions to the field. His leadership extends to the Graduiertenkolleg 2159: "Integrity and Collaboration in Dynamic Sensor Networks," where he serves as a professor overseeing doctoral research. The institute maintains state-of-the-art facilities for processing satellite imagery, aerial photography, and developing novel algorithms for geospatial data analysis. Under his direction, the institute has strengthened its international collaborations and interdisciplinary research approaches, particularly in addressing Sustainable Development Goals through geospatial technologies.