جستجوی استاد راهنمای دانشگاهی

Chris Donahueمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Music Technology
• +۵ مورد دیگر

Chris Donahue is an Assistant Professor in the Computer Science Department at Carnegie Mellon University . He also serves as a part-time Research Scientist at Google DeepMind on the Magenta team. His work focuses on leveraging generative AI to enhance human creativity, particularly in music. Education: PhD in Computer Science (UC San Diego), Postdoctoral Scholar (Stanford University) His research spans controllable generative modeling of music and audio , with a focus on real-time interactive systems. Projects like Piano Genie , Beat Sage , and Copilot Arena demonstrate his commitment to real-world deployment. His Generative Creativity Lab (G-CLef) explores AI applications beyond music, including programming and natural language. Recent publications highlight advancements in multimodal music evaluation , real-time adaptation , and AI-driven sound morphing . He co-developed Magenta RealTime , an open-weight real-time music generation model, and MusicFX DJ Mode . Scientific Awards: Best Paper Award (top 1) at NAACL Student Research Workshop 2025 Best Paper Award (top 1% of submissions) at CHI 2025 Best Paper Runner-up at ISMIR 2021 He co-advises PhD students like Wayne Chi (NDSEG Fellow) and mentors Irmak Bukey . His lab receives support from the AIxArts incubator fund at CMU .

• Computer Vision
• Machine Learning
• Human Perception Modeling
• +۵ مورد دیگر

Deva Ramanan is a Professor at the Robotics Institute of Carnegie Melllon University, where he leads research in computer vision and machine learning. His work focuses on modeling human visual perception, leveraging large-scale visual data, and developing systems for 3D understanding, neural rendering, and autonomous systems. He advises a large group of PhD students and has mentored numerous postdoctoral researchers now in leading roles across industry and academia. His research interests include computer vision, machine learning, human perception modeling, 3D scene understanding, neural rendering, autonomous driving, video understanding, and multimodal foundation models. These areas reflect his focus on both foundational models and their application to real-world problems in robotics and AI. The recent publications highlight a strong trend toward multimodal and 3D-aware models, with increasing use of diffusion models, neural fields, and large vision-language systems. Key themes include scene flow, 3D reconstruction from monocular video, autonomous driving perception, and robust evaluation of vision-language models. There is a clear emphasis on both methodological innovation and practical deployment in dynamic environments. Marr Prize, Honorable Mention (ICCV 2021) Best Paper, Honorable Mention (ECCV 2020) Best Paper Finalist (WACV 2024) Best Paper Award (WACV 2016) Best Industrial Paper, Honorable Mention (BMVC 2017) Marr Prize winner (ICCV 2009) Deva Ramanan has advised numerous PhD and master’s students, many of whom are now at top institutions and companies including Apple, Meta, Google, Nvidia, OpenAI, and Princeton. He has received substantial funding from IARPA, DARPA, NSF, Intel, Google, and Facebook for projects in video analytics, dispersed computing, visual cloud systems, and multi-task recognition. His group has developed influential datasets and benchmarks used widely in the community. He leads a vibrant research lab focused on advancing computer vision through deep learning and multimodal integration. His team works on core challenges in perception, including 3D reconstruction, motion modeling, object detection, and scene understanding, with applications in robotics and autonomous systems.

Yaser Sheikhمشاهده پروفایل

دانشیار

• Computer Vision
• Computer Graphics
• Machine Learning
• +۳ مورد دیگر

Yaser Sheikh is an Associate Professor at the Robotics Institute of Carnegie Mellon University (on leave) and Director of the Facebook Reality Lab, Pittsburgh . He holds appointments in the Mechanical Engineering Department and focuses on ' metric telepresence ' for AR/VR interactions. His research spans machine perception , computer vision , computer graphics , and machine learning , with applications in social behavior modeling and dynamic 3D reconstruction. University: Carnegie Mellon University Roles: Associate Professor (Robotics Institute), Director (Facebook Reality Lab) Contact: yaser@cs.cmu.edu, yasers@fb.com Research Interests include: Computer Vision: Pose estimation, 3D reconstruction, camera calibration Computer Graphics: Face/Hand animation, photorealistic rendering Machine Learning: Neural rendering, unsupervised learning for landmark detection AR/VR: Telepresence, immersive social interactions Notable Trends in Publications reveal a focus on real-time pose estimation (e.g., OpenPose), dynamic 3D reconstruction , and codec avatars for VR/AR. Recent works emphasize universal priors and neural rendering for photorealistic avatars. Scientific Awards include: Popular Science’s Best of What’s New Award Honda Initiation Award (2010) Best Paper Awards: WACV (2012), SCA (2010), ICCV THEMIS (2009) Hillman Fellowship for Excellence in Computer Science Research (2004) Advising and Grants: He has advised numerous PhD students (e.g., Hanbyul Joo, Tomas Simon) and received funding from the National Science Foundation , DARPA, and industry partners like Intel , Disney , and Honda . Labs & Teams: Leads the Facebook Reality Lab in Pittsburgh, collaborating with institutions like Carnegie Mellon University and Disney Research.

Steve Chaseمشاهده پروفایل

استاد

• Computational Neuroscience
• Neural Engineering and Technology
• Systems Neuroscience
• +۴ مورد دیگر

Steve Chase is a Professor at Carnegie Mellon University , affiliated with the Biomedical Engineering , Electrical and Computer Engineering , Neuroscience Institute , and Robotics Institute departments. His research spans Computational Neuroscience , Neural Engineering , and Systems Neuroscience , with a focus on neural circuits, motor control, and brain-computer interfaces (BCI). Research Areas: Sensation & Perception, Methods Development, Diseases & Disorders, Physiological & Anatomical Methods. Lab Highlights: Development of the RotaWheel, memory trace studies in the motor cortex, and investigations into BCI stabilization and learning dynamics. Scientific Contributions: His lab has published extensively in journals like Neuron , Nature Computational Science , eLife , and PNAS , with notable works on neural activity patterns, dimensionality reduction in calcium imaging, and sensory constraints on motor cortex modulation. Students and postdocs in his lab have received awards, including the CNBC best paper award.

Howie Chosetمشاهده پروفایل

استاد

• Robotics
• Medical Robotics
• Snake Robots
• +۱۱ مورد دیگر

Howie Choset is a Professor of Robotics at the Robotics Institute, Carnegie Mellon University. He directs the Undergraduate Robotics Minor and leads the Biorobotics Laboratory, where his research focuses on snake robots, motion planning, and medical robotics. He is also affiliated with the Manufacturing Futures Institute. Ph.D., Mechanical Engineering, California Institute of Technology (1996) M.S., Mechanical Engineering, California Institute of Technology (1995) B.S.E., Computer Science and Engineering, University of Pennsylvania (1990) B.S., Economics, The Wharton School of Business (1990) Choset's research centers on robotics for confined and complex environments, particularly through the development of snake robots. His work integrates mechanism design, path and motion planning, and estimation to enable applications in surgery, manufacturing, infrastructure inspection, and search and rescue. He is a pioneer in medical robotics and has co-founded Medrobotics to commercialize minimally invasive surgical robots. His recent publications highlight a strong focus on ergodic exploration, multi-agent systems, motion planning under uncertainty, and medical robotics. Themes include optimizing robot trajectories for information gathering, solving complex path planning problems with dynamic obstacles, and advancing autonomous systems for disaster response and space exploration (e.g., the EELS robot for Enceladus). MIT Technology Review Top 100 Innovators under 35 (2002) Best Paper Award, RIA (1999) Best Paper Award, ICRA (2003) Best Paper, IEEE Bio Rob (2006) Best Video, ICRA (2011) Nominations for best papers at ICRA, IROS, and CLAWAR Choset has advised numerous students, many of whom have won top awards. His lab has received significant funding for robotics research, including projects in surgical robotics, additive manufacturing, and autonomous exploration. He is the lead author of the textbook Principles of Robot Motion and is actively involved in educational innovation through custom robotics labs. He leads the Biorobotics Laboratory at CMU, which develops advanced robotic systems like snake robots and the EELS (Exobiology Extant Life Surveyor) robot for NASA missions. The lab collaborates with industry and government agencies on applications ranging from surgery to space exploration.

Nancy Pollardمشاهده پروفایل

استاد

• Computational Neuroscience
• Computer Graphics
• Robotics
• +۴ مورد دیگر

Nancy Pollard is a Professor at Carnegie Mellon University, affiliated with both the Robotics Institute and the Computer Science Department. Her research focuses on understanding physical interaction with the environment through robotics and computer graphics, particularly in areas like dexterous manipulation, human motion analysis, and soft robotics. She explores how human examples can inform robot control policies and create natural-looking animations. Her work bridges robotics and graphics to solve challenges such as optimizing motion for humanoid robots and improving the realism of animated hands. Key projects include developing fast physically plausible motion techniques, studying hand motion complexity, and creating intuitive tools for modeling hand-object interactions. She also investigates the physical correctness thresholds in graphics and the design of affordable soft robotic hands for real-world applications like agriculture. Recent publications highlight advancements in motion retargeting for anthropomorphic manipulations, co-optimization of soft robotic hand design and control, and frameworks for sensor placement in soft hands. Her research emphasizes human-inspired approaches to robotics and the application of biomechanical insights to improve robotic dexterity. Pollard advises students such as Arjun Lakshmipathy and collaborates on projects involving both academic and industrial applications. Her work has been supported by grants focused on robotics design and simulation-based manipulation capture.

• Computer Vision
• Computer Graphics
• Machine Learning
• +۵ مورد دیگر

Hanbyul Joo is an Assistant Professor in the Department of Computer Science and Engineering at Seoul National University (SNU). Prior to joining SNU, he was a Research Scientist at Facebook AI Research (FAIR) in Menlo Park. He completed his Ph.D. in the Robotics Institute at Carnegie Mellon University, working with Yaser Sheikh, and received his M.S. in Electrical Engineering and B.S. in Computer Science from KAIST, Korea. Dr. Joo's educational journey began at KAIST, where he earned both his Bachelor's and Master's degrees. He then pursued his Ph.D. at Carnegie Mellon University's Robotics Institute, completing his dissertation titled "Sensing, Measuring, and Modeling Social Signals in Nonverbal Communication." His doctoral work focused on developing the Panoptic Studio, a unique sensing system with over 500 synchronized cameras for capturing social interactions. Dr. Joo's research primarily focuses on endowing machines and robots with the ability to perceive and understand human behaviors in 3D . His goal is to build "social Artificial Intelligence" that can interact with humans using social signals (body languages). He pursues this direction using data-driven methods where data is collected by measuring the wide spectrum of social signals transmitted during interpersonal social interaction. His research spans computer vision, machine learning, computer graphics, and robotics , with particular emphasis on 3D human pose estimation, human-object interaction, and social signal processing. His recent publications demonstrate a clear trend toward leveraging diffusion models for 3D reconstruction and generation tasks, with a focus on human-centric applications. His work bridges the gap between 2D image understanding and 3D scene reconstruction, often utilizing pre-trained models to overcome data limitations. The research consistently addresses fundamental challenges in understanding human behavior, interaction with objects, and social dynamics in 3D space. Dr. Joo is a recipient of several prestigious awards including the Samsung Scholarship and the CVPR Best Student Paper Award in 2018 . His paper "Total Capture: A 3D Deformation Model for Tracking Faces, Hands, and Bodies" received this honor at CVPR 2018. His research has been widely recognized in top computer vision and AI conferences, with multiple oral presentations at venues like CVPR, ICCV, and ECCV. Dr. Joo actively mentors a large group of students, with approximately 15 current students working toward MS/PhD degrees under his supervision. His lab, the SNU VCLab, focuses on cutting-edge research in computer vision and graphics. He has secured significant research funding through his work, though specific grant details aren't provided on his website. Dr. Joo frequently serves as an area chair for major conferences including CVPR, ICCV, and NeurIPS, demonstrating his standing in the academic community. Dr. Joo leads the SNU VCLab, which has developed several notable datasets and tools including SNU ParaHome, FrankMocap, and the CMU Panoptic Studio Dataset. His lab maintains strong industry connections, with students interning at leading companies like Meta. The lab's research focuses on building the infrastructure and algorithms needed for social AI, with an emphasis on practical applications that can be deployed in real-world settings.

Fernando De la Torreمشاهده پروفایل

استاد مدعو

• Machine Learning
• Computer Vision
• Augmented Reality
• +۴ مورد دیگر

Fernando De la Torre is a Courtesy Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University, with an affiliation to the Robotics Institute where he has been a research faculty member since 2005. He holds a Ph.D. in Electronic Engineering from Ramon Llull University (2002). His research focuses on machine learning and computer vision, with applications in human health, augmented/virtual reality, generative models, and data-centric methodologies. He directs the Human Sensing Laboratory, which explores technologies for human behavior analysis and health monitoring. Notable contributions include founding FacioMetrics LLC (acquired by Meta), advancing facial recognition and 3D human digitization, and developing frameworks for robust visual models. His work bridges theory and practice, with over 225 peer-reviewed publications and editorial roles, including Associate Editor for IEEE Transactions on Pattern Analysis and Machine Intelligence. Recent research trends emphasize generative AI applications in satellite imagery analysis, VR/AR rendering optimizations (e.g., Gaussian splatting), and clinical motion recognition for healthcare. His projects often intersect with industry, addressing challenges in wearable health monitoring and immersive technologies. His lab collaborations span academia and industry, focusing on scalable solutions for 3D human modeling, adversarial robustness, and multimodal data fusion. Key achievements include pioneering work on 3D face animation from speech and garment reconstruction from single images.

Jana Kainerstorferمشاهده پروفایل

استاد

• Biomedical Optics
• Neurophotonics
• Medical Devices
• +۳ مورد دیگر

Jana Kainerstorfer is a Professor of Biomedical Engineering at Carnegie Mellon University (CMU), with courtesy appointments in the Neuroscience Institute and Electrical & Computer Engineering. She serves as Associate Department Head for Faculty and Graduate Affairs within the College of Engineering. Her research focuses on developing non-invasive optical imaging methods for disease detection and treatment monitoring, particularly in diffuse optical imaging. Key areas include cerebral hemodynamic monitoring in traumatic brain injury and handheld devices for breast cancer imaging. Dr. Kainerstorfer holds senior membership in the Optical Society of America and has received prestigious awards such as the NIH Trailblazer Award and AHA Scientist Development Grant. She leads the Biophotonics Lab, which bridges engineering and clinical applications, emphasizing translational research. Education: PhD from University of Vienna/NIH (2010), Postdoc at Tufts University Research Interests Her work revolves around biomedical optics , neurophotonics , and medical device innovation . Current projects include: Non-invasive cerebral hemodynamic monitoring Transabdominal fetal pulse oximetry Optical imaging in extreme environments (e.g., freediving physiology) Her lab develops tools like wearable NIRS for marine mammals and self-calibrating pulse oximetry algorithms. Research spans clinical translation and physiological mechanism discovery , with emphasis on microvascular imaging. Awards & Recognition NIH Trailblazer Award (2020) AHA Scientist Development Grant SPIE Fellow (2022) George Tallman Ladd Award (CMU) Lab & Collaborations The Biophotonics Lab collaborates with neurosurgery, oncology, and marine biology teams. Projects address clinical needs in neurocritical care and fetal monitoring, leveraging optical technologies for real-time diagnostics. Ongoing work includes: Optical assessment of cerebral metabolic rates Non-invasive intracranial pressure estimation Multi-modal EEG-NIRS fusion for neural source localization

Marlene Behrmannمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Cognitive Science
• Visual Perception
• +۴ مورد دیگر

Marlene Behrmann is the Thomas S. Baker University Professor of Psychology and Cognitive Neuroscience at Carnegie Mellon University (CMU), affiliated with the Dietrich College of Humanities and Social Sciences. She leads the Behrmann Lab, which moved to the University of Pittsburgh in 2023. Her research focuses on visual cognition, object recognition, and neural mechanisms of perception, with a particular emphasis on face and word recognition. Behrmann holds a B.A. and M.A. in Speech and Hearing Therapy and a Ph.D. in Psychology from the University of Toronto. She is a leader in her field, recognized by her induction into the National Academy of Sciences (2015) and the American Academy of Arts and Sciences (2019). Her work combines neuropsychological studies of patients with brain damage, neuroimaging, and computational modeling to explore visual processing. Recent research highlights include studies on dorsal-ventral pathway interactions, functional reorganization post-hemispherectomy, and autism-related sensory processing differences. Behrmann has advised numerous graduate students and postdocs, contributing to their academic and professional development. Key awards include her National Academy of Sciences membership and American Academy of Arts and Sciences fellowship. Her lab collaborates widely, publishing in top journals like Cerebral Cortex , PNAS , and Trends in Cognitive Sciences . She also engages in translational research to improve interventions for perceptual and cognitive disorders.

O. Burak Ozdoganlarمشاهده پروفایل

استاد

• Micro and Nano Manufacturing
• Mechanics of Material Removal
• Dynamics and Vibrations in Micro-scale Systems
• +۳ مورد دیگر

O. Burak Ozdoganlar is a Professor in the Departments of Mechanical Engineering and Biomedical Engineering at Carnegie Mellon University. His research focuses on multiscale (meso/micro/nano) manufacturing science, combining theoretical, numerical, and experimental analyses to advance three-dimensional device fabrication. He leads the Multiscale Manufacturing and Dynamics Laboratory (MMDL), with applications spanning medical, biomedical, energy, robotics, and aerospace fields. B.S., Istanbul Technical University, Turkey M.S., Ohio State University, Columbus Ph.D., University of Michigan, Ann Arbor Post-doc, University of Illinois at Urbana-Champaign Senior Member of Technical Staff, Sandia National Labs His work addresses mechanics of micro-scale material removal, dynamics of micro-scale structures, novel micro/nano-manufacturing techniques, and application-driven research. Key contributions include scalable fabrication of microneedle arrays, freeform 3D ice printing for vascular networks, and high-density soft-matter electronics. His research emphasizes predictability and precision in manufacturing processes. Recent publications highlight advancements in dissolvable microneedle arrays for transdermal delivery, freeform 3D printing of ice structures for biomimetic vascularization, and scalable methods for porous and soft-matter electronics. His work bridges fundamental mechanics with medical device innovation. Blackall Machine Tool and Gage Award, ASME, 2011 Russell V. Trader Career Faculty Fellow, CMU, 2009-2011 NSF CAREER award, 2006 Kuo K. Wang Outstanding Young Engineer, SME, 2007 Organizer, 'Manufacturing...The Future' symposium, NAE EU-American Frontiers Conference, 2011 Best paper award, NAMRI SME, 2007-2008 Struminger Teaching Fellow, CMU, 2007-2008 Ozdoganlar's Multiscale Manufacturing and Dynamics Laboratory (MMDL) develops cutting-edge manufacturing solutions for biomedical applications, including neural probes, cartilage implants, and biosensors. His research integrates mechanics, materials science, and process engineering to address challenges in device predictability and scalability.

Victoria Webster-Woodمشاهده پروفایل

دانشیار

• Biohybrid Robotics
• Organic Robotics
• Biologically Inspired Robotics
• +۱۰ مورد دیگر

Victoria Webster-Wood is an Associate Professor at the College of Engineering , Carnegie Mellon University , where she leads the Biohybrid and Organic Robotics Group (B.O.R.G) . Her research integrates organic materials into robotics as structures, actuators, sensors, and controllers for biohybrid robots and prosthetics. Education: Ph.D., Mechanical Engineering, Case Western Reserve University (2017) M.S., Mechanical Engineering, Case Western Reserve University (2013) B.S., Mechanical Engineering, Case Western Reserve University (2012) Research Interests focus on biohybrid robotics , biologically inspired systems , soft robotics , additive manufacturing , biomechanics , and computational modeling . Her work spans applications in medical robotics , micro/nano manufacturing , and environmental monitoring . Scientific Awards include being named to ASME’s 2025 MechE Watch List and awarded MIT Technology Review’s 35 Innovators Under 35 (2023) . Collaborations involve projects like neurodegenerative disease therapy tools and soft robotic tactile sensors for manufacturing , supported by the Manufacturing Futures Institute and NextManufacturing Center .

Keenan Craneمشاهده پروفایل

دانشیار

• Computer Science
• Mathematics
• Scientific Computing
• +۷ مورد دیگر

Keenan Crane is the Michael B. Donohue Associate Professor of Computer Science and Robotics at Carnegie Mellon University , with membership in the Center for Nonlinear Analysis and mentorship in the Geometry Collective . His research bridges differential geometry and computer science to develop fundamental algorithms for geometric data processing. Education : BS from University of Illinois at Urbana-Champaign, PhD from Caltech Fellowships : Google PhD Fellow, NSF Mathematical Sciences Postdoctoral Fellow Research focuses on Discrete Differential Geometry , addressing PDE solutions, mesh processing, and geometric modeling through methods like: Walk on Spheres for PDEs Intrinsic Triangulations for robust geometry Repulsive Energy formulations for collision avoidance Recent publications span 2025–2021 , emphasizing grid-free algorithms , anisotropic mesh generation , and differentiable systems . Scientific accolades include Packard Fellowship and NSF CAREER Award . Students include Nicole Feng , Olga Gutan , and Zoë Marschner . During his 2024 sabbatical at Roblox , he does not accept new researchers. Key software contributions include Penrose (math diagram generation) and I♥Mesh (domain-specific language for mesh algorithms).

Minchen Liمشاهده پروفایل

استادیار

• Computer Graphics
• Machine Learning
• Robotics
• +۴ مورد دیگر

Minchen Li Assistant Professor at Carnegie Mellon University's School of Computer Science (Computer Science Department). Formerly an Assistant Adjunct Professor at UCLA's Mathematics Department. Holds a Ph.D. from the University of Pennsylvania's SIG Center for Computer Graphics, followed by a postdoctoral position there. Research focuses on physics-based simulation, integrating numerical analysis, high-performance computing, and machine learning. Notable contributions include the IPC method for frictional contact simulation and large-scale material point methods. Education Ph.D., Computer and Information Science, University of Pennsylvania (2020) M.Sc., Computer Science, University of British Columbia (2018) B.Eng., Computer Science and Technology, Zhejiang University (2015) Research Interests Advances in physical simulation for visual computing, robotics, and manufacturing. Specializes in robust and efficient methods for solid/fluid dynamics, contact modeling, and GPU acceleration. Combines numerical analysis with machine learning to address challenges in simulation accuracy and versatility. Awards 2021 ACM SIGGRAPH Outstanding Doctoral Dissertation Award 2024 SCA Early Career Researcher Award Advising & Labs Leads the Simulation Intelligence Group (SIG) at CMU Graphics Lab. Advises PhD students Guying Lin, Juntian Zheng, Michael Liu, and Zhaofeng Luo. Collaborates with industry and academic partners on projects like VR-based modeling systems and scalable simulation frameworks.

Barbara Shinn-Cunninghamمشاهده پروفایل

استاد

• Auditory Neuroscience
• Cognitive Neuroscience
• Perception
• +۵ مورد دیگر

Barbara Shinn-Cunningham is the Glen de Vries Dean of the Mellon College of Science at Carnegie Mellon University (CMU) and holds professorships in Psychology, Biomedical Engineering, and Electrical and Computer Engineering. She is also the founding director of CMU's Neuroscience Institute. Her research focuses on auditory neuroscience, particularly auditory attention, binaural hearing, and multisensory integration, with applications to hearing disorders and assistive technologies. Shinn-Cunningham earned her B.S. from Brown University and her M.S. and Ph.D. from MIT in Electrical and Computer Engineering. Education: B.S., Electrical Engineering, Brown University (1986) M.S., Electrical & Computer Engineering, MIT (1988) Ph.D., Electrical & Computer Engineering, MIT (1994) Research Interests: She investigates how the brain processes sound in complex environments, including spatial hearing, auditory attention deficits in aging and clinical populations, and the neural mechanisms underlying cochlear synaptopathy. Her work integrates behavioral studies, neuroimaging (EEG, fMRI), and computational modeling to bridge basic science and translational research. Awards & Recognition: Fellow, Acoustical Society of America (2009) Alfred P. Sloan Research Fellow (2000) National Security Science and Engineering Faculty Fellow (2008) Helmholtz-Rayleigh Interdisciplinary Silver Medal (2019) Advising & Grants: She mentors a diverse team of graduate students and postdocs, focusing on training the next generation of auditory neuroscientists. Her grants include funding from NSF, NIH, and the Department of Defense. She leads the LiMN Lab, which explores neural mechanisms of sensory processing and attention. Labs & Teams: Director of the Lab in Multisensory Neuroscience (LiMN) at CMU, part of the Carnegie Mellon Neuroscience Institute. Collaborates with engineers, clinicians, and marine biologists to advance auditory technology and neuroimaging techniques.