جست‌وجوی استاد و پژوهشگر

Mikkel Lønborg Friisمشاهده پروفایل

دانشیار بالینی

• Surgical Simulation
• Medical Education
• Ultrasound Training
• +۷ مورد دیگر

Mikkel Lønborg Friis is a Clinical Associate Professor at Aalborg University, affiliated with the Department of Clinical Medicine under The Faculty of Medicine. He also serves as a senior consultant ( Ledende overlæge ) at Aalborg University Hospital, where he leads simulation-based training initiatives at NordSim – Centre for Skills Training and Simulation. His dual academic and clinical roles position him at the intersection of advanced surgical practice and innovative medical education. Clinical Associate Professor, Aalborg University Ledende overlæge (Chief Physician), Aalborg University Hospital Member, NordSim – Centre for Skills Training and Simulation His research interests focus on enhancing surgical and diagnostic competencies through technology-driven education. Key areas include simulation-based training, artificial intelligence in fetal and surgical ultrasound, robotic surgery assessment using deep learning, and curriculum development for cross-specialty ultrasound education. He actively contributes to improving clinical outcomes in pilonidal sinus disease and advancing AI integration in medical imaging. The recent publications highlight a strong trend toward interdisciplinary innovation, particularly in blending AI, simulation, and medical education. His work spans clinical surgery, educational methodology, and computational analysis of surgical performance. A significant portion of his research involves designing and evaluating training protocols, developing datasets for skill assessment, and exploring ethical and practical implications of AI in clinical settings. Mikkel Friis has not been publicly recognized with scientific awards in the provided text, but his leadership in simulation and curriculum design suggests significant institutional impact. He is involved in mentoring and advising through collaborative research projects, particularly in simulation and ultrasound education. While formal students are not listed, his role in study protocols and dataset creation implies supervision of junior researchers and medical trainees. He participates in funded or institutionally supported research activities related to medical education innovation and surgical technology. His involvement in press and media coverage further underscores his role as a thought leader in clinical simulation careers. Friis is deeply embedded in NordSim – Centre for Skills Training and Simulation, where he contributes to developing and implementing simulation-based assessment tools, particularly for abdominal ultrasound and surgical skills. His team collaborates across departments and institutions, focusing on creating standardized, scalable training models that integrate emerging technologies like AI and virtual reality.

• Computer Vision
• Autonomous Systems
• Robotics
• +۱۲ مورد دیگر

Dr Lounis Chermak is a Lecturer in Computer Vision and Autonomous Systems at the Centre for Electronic Warfare, Information and Cyber, part of Cranfield Defence and Security at Cranfield University, UK. He leads the Joint Autonomy Lab and is actively involved in research and education in autonomous systems with applications in defence and space. Research Interests: His work focuses on situational awareness in autonomous platforms, with core expertise in computer vision, sensor fusion, artificial intelligence, robotics, and navigation. He investigates perception, decision-making, and mobility across aerial, ground, maritime, and space systems, developing robust solutions for challenging environments including low visibility and extreme illumination. The recent publications reflect a strong trend in autonomous navigation, particularly for space and defence applications, using advanced computer vision techniques such as thermal stereo odometry, HDR imaging, stixel-based scene understanding, and lightweight 3D descriptors. Research also extends to cybersecurity of autonomous systems, including impersonation attack detection and optical countermeasures. Scientific Awards: No scientific awards mentioned in the provided text. Advising and Grants: Dr Chermak leads research activities supported by postdoctoral researchers, PhD, and MSc students. His work is funded and applied in collaboration with major clients including aerospace organizations (ESA, UK Space Agency, Thales Alenia Space), defence agencies (MoD, DSTL, BAE Systems, MBDA), and technology companies (Samsung, Astroscale). He supervises research students in robotics and autonomous systems across civilian and defence domains. Labs and Teams: He leads the Joint Autonomy Laboratory, a 200 m² indoor facility equipped with drone netting, motion capture systems, virtual reality test benches, UAV and ground robot fleets, electric vehicles, and multiple sensors for vision, ranging, and motion. This lab supports both educational and cutting-edge research in autonomous systems.

Stan Sclaroffمشاهده پروفایل

استاد

• Computer Vision
• Pattern Recognition
• Machine Learning
• +۳ مورد دیگر

Stan Sclaroff is a Professor of Computer Science and Dean of the College of Arts & Sciences at Boston University. He holds affiliated faculty status in the Department of Electrical and Computer Engineering. His research focuses on computer vision, pattern recognition, and machine learning, with expertise in tracking, human motion analysis, and multimedia retrieval systems. He co-leads the Image and Video Computing research group and has contributed pioneering work like the ImageRover content-based image retrieval system. Education: PhD in Media Arts & Sciences from MIT (1995), SM from MIT (1991), and BS in Computer Science and English from Tufts University (1984). Research Interests: Human motion tracking, sign language analysis, deformable shape matching, and multimedia indexing. Notable contributions include early work on content-based image retrieval and foundational techniques in video analysis. Honors: IEEE & IAPR Fellowships, NSF CAREER Award (1996), ONR Young Investigator Award (1996), and BU's Mentor of the Year (2018). Over 40+ students advised, many now in academia and industry leadership roles. Key roles: Chair of BU Computer Science (2007–2013), Associate Dean for Mathematical & Computational Sciences (2015–2018), Interim Dean (2018–2019), and current Dean since 2019.

François Brémondمشاهده پروفایل

پژوهشگر

• Computer Vision
• Cognitive Vision
• Video Understanding
• +۲۲ مورد دیگر

François Brémond is a Research Director (DR1) at INRIA Sophia Antipolis, where he leads the STARS research team, which he founded on January 1, 2012. He was previously head of the PULSAR team starting September 2009. He is also a co-founder of the CoBTeK team at Nice University in collaboration with Nice Hospital, focusing on behavioral disorders in elderly patients with dementia. His research is centered on dynamic scene interpretation using video and sensor data, with applications in surveillance, healthcare, transportation, and ambient intelligence. Research Interests: Computer Vision: video processing, object detection and tracking, motion analysis, pattern recognition Cognitive Vision: video understanding, scene understanding, event recognition, behavior analysis, multi-sensor fusion, multimedia interpretation Machine Learning: deep learning architectures, self-attention, knowledge distillation, contrastive learning, self-learning, lifelong learning, knowledge-based systems, spatio-temporal reasoning Autonomous Systems: real-time systems, system evaluation, parameter tuning, system design, 3D visualization His work bridges low-level pixel data with high-level semantic behavior modeling, enabling systems to detect and interpret complex human and vehicle activities in real-world environments. Applications include crowd monitoring, fraud detection, airport operations, homecare for the elderly, and biological monitoring. He has authored or co-authored over 200 scientific papers and has (co-)supervised 18 PhD theses. He has participated in 12 European projects (e.g., FP6, FP7), 12 French national projects (ANR, DGE), and numerous industrial collaborations with companies such as Thales, SNCF, RATP, STMicroelectronics, and Alstom. He also serves as an expert reviewer for ANR and the European Commission. Scientific Leadership and Technology Transfer: Co-founder of Keeneo (acquired by Digital Barriers), Ekinnox, and Neosensys — startups in intelligent video monitoring and business intelligence Reviewer for top-tier journals (PAMI, CVIU, AIJ) and conferences (CVPR, ICCV, AVSS) Contributor to the ARDA workshops on video event ontology He has taught numerical classification at Nice University and video understanding at a Master’s level engineering school. His research program emphasizes generic, scalable systems for behavior modeling and long-term activity mining. Research Projects: Stress ID dataset (ECG and video for stress detection) Toyota Smarthome (Activities of Daily Living) SafEE2 (Homecare for elderly with autonomy loss) Praxis dataset (RGB-D upper-body gestures) GER'HOME, CARETAKER, RATP Project, ETISEO, AVITRACK, CASSIOPEE, ADVISOR, PASSWORDS

Kai Essigمشاهده پروفایل

استاد

• Human Factors
• Interactive Systems
• Eye Tracking
• +۱۵ مورد دیگر

Prof. Dr. Kai Essig is a Professor of Human Factors and Interactive Systems at the Faculty of Communication and Environment, Rhine-Waal University of Applied Sciences, Kamp-Lintfort, Germany. He has a strong interdisciplinary background combining computer science, cognitive science, and human-computer interaction, with a focus on eye tracking, visual perception, and assistive technologies. Master of Science in Computer Science and Chemistry, Bielefeld University (1998) Ph.D. in Computer Science, Bielefeld University (2007) His research centers on eye tracking, human-computer interaction, usability engineering, visual attention, and cognitive interaction technology . He investigates how movement expertise influences visual perception and how multimodal software can support real-time human actions. His work integrates computer vision, machine learning, and neuroscience to develop intelligent systems that adapt to user behavior. The 15 most recent publications reflect a consistent trend in eye movement analysis, mental representations, brain-machine interfaces, and assistive technologies . These works span domains such as sports psychology, robotics, augmented reality, and cognitive neuroscience, demonstrating a strong interdisciplinary approach. Key themes include gaze-based interaction, automated annotation of visual behavior, and the implementation of smart systems for daily living assistance. Scientific recognition includes: Landmark in the Land of Ideas (2018) – for the ADAMAAS project, awarded by 'Land of Ideas', a joint initiative of the German government and the Federation of German Industries Prof. Essig has been actively involved in research projects such as ADAMAAS (Adaptive and Mobile Action Assistance in Daily Living Activities), which received national recognition. He has collaborated extensively with the Neurocognition and Action-Biomechanics Research Group at Bielefeld University and the Excellence Cluster CITEC. While no formal advising of students is listed, his publications suggest mentorship and collaboration with junior researchers. His lab work is centered on eye-tracking systems, multimodal interaction, and cognitive modeling , particularly within applied environments like smart glasses and assistive technologies.

Klara Dolkمشاهده پروفایل

مدرس ارشد

• Gender pedagogy
• Equal treatment
• Children's rights
• +۵ مورد دیگر

Klara Dolk is a Senior Lecturer at Stockholm University's Department of Child and Youth Studies, specializing in early childhood education. She teaches in the Programme in Early Childhood Education and is an active member of the Practice-based research in and about early childhood education and care (PraFF) research group. Her work focuses on integrating critical perspectives into preschool educational practices across Sweden. Dr. Dolk's research interests center on gender pedagogy, equal treatment, children's rights, and norm-critical perspectives in early childhood education. Her work examines how preschools address sensitive social issues including poverty, economic inequality, and social vulnerability. She employs poststructuralist and feminist theoretical frameworks to analyze power relations between children and adults within educational settings, with particular attention to how children's resistance can challenge and transform educational practices. Her recent publications (2020-2023) reveal a growing focus on how preschools handle controversial social phenomena like begging, economic inequality, and class perspectives. These works demonstrate her commitment to examining how norm-critical approaches can be effectively implemented in early childhood education to address societal challenges while maintaining educational integrity. Her research shows consistent engagement with ethical dilemmas in preschool settings and the practical challenges of implementing fundamental values education. Dr. Dolk has contributed significantly to scholarly discourse through numerous publications in both Swedish and international journals. Her work spans theoretical explorations of gender and power to practical examinations of how preschools address real-world social issues. She has published in journals such as Lambda Nordica, International Journal of Equity and Innovation in Early Childhood, and Tam-Revy, demonstrating her interdisciplinary approach to early childhood education research. As a dedicated educator and researcher, Dr. Dolk actively contributes to advancing critical approaches in early childhood education through her teaching, research projects on preschool attendance and social vulnerability, and participation in the PraFF research group. Her work bridges theoretical frameworks with practical educational challenges, providing valuable insights for both academic and practitioner communities in the field of early childhood education.

• Historical Linguistics
• Grammaticalization
• Collocations
• +۵ مورد دیگر

Joop van der Horst is an associate professor at Károli Gáspár Reformed University, Faculty of Humanities and Social Sciences, specializing in Dutch Studies. Previously, he held professorial roles at KU Leuven and the University of Amsterdam. PhD in Linguistics (University of Amsterdam, 1986) MA in Dutch Language and Literature (Leiden University, 1975) His research spans historical linguistics, focusing on grammaticalization, collocations, and language change, as well as descriptive linguistics (syntax, morphology) and sociolinguistics. He has extensively studied fixed verb constructions, Dutch-French grammatical comparisons, and long-term language-society interactions. His publications and conference contributions from 2002-2013 highlight trends in Dutch syntax evolution, comparative German-Dutch verb patterns, and the decline of Renaissance language culture in Europe. Key themes include grammatical theory, European multilingualism, and language education reforms. LOT Publication Award Our Language Award He has supervised PhD students Freek Van de Velde, Judith Schonenboom, and Bert Cappelle, while serving as an opponent in doctoral defenses including Evie Coussé and Rinaldo Neels. His guest professorships include institutions in Berlin, Maastricht, Cologne, Münster, and Wroclaw.

Mahir Arzokyمشاهده پروفایل

مدرس

• Artificial Intelligence
• Search Based Software Engineering
• Intelligent Data Analysis
• +۴ مورد دیگر

Dr Mahir Arzoky is a Lecturer in the Department of Computer Science at Brunel University London's College of Engineering, Design and Physical Sciences. He holds a PhD from Brunel University London (2015) and has extensive research experience in artificial intelligence and software engineering. His research focuses on: Artificial Intelligence and Intelligent Data Analysis Search Based Software Engineering (SBSE) Clustering algorithms and heuristic search methods Software refactoring and quality assessment Data mining applications in healthcare and education Analysis of his 15 most recent publications (2018-2022) reveals strong interdisciplinary work bridging computer science with healthcare (diabetes patient modeling, medical imaging) and education (chatbot design, algorithm visualization). His technical focus centers on clustering optimization, refactoring impact analysis, and explainable AI, with frequent use of empirical validation methods. Key collaborations include researchers like Stephen Swift, Steve Counsell, and Giuseppe Destefanis. Dr Arzoky has secured significant research funding through EPSRC grants including: AQUATIC project (EP/M024083/1): Assessing Test Suite Quality in Industrial Code FIAR-NET (EP/N011627/1): Fault Analyses in Industry and Academic Research Network His professional network includes active collaborations across computer science, healthcare informatics, and educational technology domains, with recent work extending into transformer models for healthcare SQL conversion and graph partitioning for software modularization.

• Biometrics
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

Raghavendra Ramachandra is a Professor at the Department of Information Security and Communication Technology (IIK) , within the Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU) in Gjøvik. His research focuses on biometric systems, particularly in face, fingerprint, and finger vein recognition, with emphasis on presentation attack detection, morphing attack detection, and deep learning applications. Current research projects include: SALT (2022-2026) : Developing privacy-preserving facial biometric authentication systems. OffPAD (2022-2025) : Creating cryptographic tools and presentation attack detection for fingerprint biometrics. SWAN (2015-2020) : Developing biometric countermeasures against presentation attacks. His recent publications demonstrate technical expertise in: Face morphing attack detection using vision transformers and point cloud networks Image fusion techniques for multispectral biometrics GAN-based synthetic data generation for security evaluation Explainable AI approaches for biometric verification Professor Ramachandra also supervises PhD and Master’s students, and has extensive experience in leading national and EU research initiatives.

Anthony Clarkمشاهده پروفایل

استادیار

• Autonomous Robotics
• Evolutionary Robotics
• Computer Vision
• +۷ مورد دیگر

Anthony Clark is an Assistant Professor of Computer Science at Pomona College, where he has been teaching since 2020. Previously, he served as an Assistant Professor at Missouri State University from 2016 to 2020. He directs the ARCS (Autonomous Robotics and Complex Systems) Lab, which focuses on improving the robustness and adaptability of autonomous robots, particularly small-scale systems that can navigate unpredictable terrain and adapt to potential damage. Clark earned his Ph.D. in Computer Science from Michigan State University in 2016, where he worked under Dr. Philip K. McKinley, and his B.S. in Computer Engineering from Kansas State University, graduating magna cum laude. His research centers on making autonomous robots more robust and adaptive through optimization algorithms and multimodal systems. He specializes in evolutionary robotics, computer vision, neural networks, and simulation methods for developing control systems that leverage multiple locomotion mechanisms. His recent work demonstrates strong trends across several domains: developing hybrid locomotion systems (wheel/leg transformations), applying deep learning to terrain classification and pathfinding, using simulation environments for training, and exploring pretraining techniques for evolutionary robotics. His research shows a consistent focus on bridging simulation and real-world applications while addressing challenges in robot adaptability and robustness. Faculty Excellence in Teaching, Missouri State University (2018) Best Paper Award, Workshop on Evolutionary and Reinforcement Learning (2013) Best Paper Award, ALIFE Conference, Behavior and Intelligence Track (2012) Outstanding Reviewer, Elsevier (2018) Master Advisor Certification, Missouri State University (2017) Clark has advised numerous undergraduate and graduate students through the ARCS Lab, with current research involving projects like the Adabot (a robot with multiple locomotion mechanisms) and thermal semantic segmentation for aerial field robots. His teaching portfolio includes courses on data structures, algorithms, neural networks, computer systems, and mobile robotics. He has also served as a Visiting Associate at Caltech's ARC Lab from 2023-2024, working with Dr. Soon-Jo Chung. The ARCS Lab develops simulation environments, optimizes control systems, and fabricates physical robots. Current projects include the Adabot with its geared coaxial shaft mechanism for hybrid locomotion, thermal semantic segmentation using satellite data, and creating dynamic simulation environments with Unreal Engine 5. The lab emphasizes practical applications of theoretical research while training students in both hardware and software aspects of robotics.

Jason Gaigerمشاهده پروفایل

استاد

• Aesthetics
• Art Theory
• Theories of depiction and visual meaning
• +۲ مورد دیگر

Jason Gaiger is Professor of Aesthetics and Art Theory at the University of Oxford and a Fellow of St Edmund Hall. He serves as Head of Art History and Theory at the Ruskin School of Art and acts as the Undergraduate Admissions Co-Ordinator. Previously, from 2010 to 2014, he was Head of the Ruskin School of Art and currently serves as Director of Graduate Studies. Professor Gaiger received his education in art history and philosophy at the universities of St Andrews, Essex and Heidelberg. Before joining Oxford in 2010, he was Senior Lecturer and Director of Research in the Art History Department at the Open University. Jason Gaiger's research spans aesthetics and art theory from the seventeenth century through to the present day, with additional focus on theories of depiction and visual meaning, and contemporary art practice and theory. His scholarly work is informed by both the historical resources of the German aesthetic tradition and debates in contemporary analytic philosophy. He has published extensively on topics including painting theory, sculpture, rhythm in visual art, visual perception, and the historical development of art theory. His most significant contribution is Philosophy of Painting: Ancient, Modern, Contemporary (2022), which provides a historically informed analysis of painting's contemporary relevance. Professor Gaiger's publication record demonstrates a consistent focus on the philosophical dimensions of visual art, particularly examining the temporal aspects of viewing, the relationship between materiality and meaning, and the historical continuity of aesthetic concepts. His work bridges historical analysis with contemporary philosophical inquiry, often drawing connections between eighteenth and nineteenth-century aesthetic theories and current debates in visual culture. The recurring themes across his publications include the nature of pictorial representation, the cognitive processes involved in art viewing, and the philosophical foundations of art historical interpretation. Professor Gaiger has supervised numerous graduate students, with recent theses under his direction exploring topics such as The Epistemic Value of Contemporary Art , Modes of Presence in the Contemporary Sculptural Encounter , and Affective Vision: Urban Landscape Photographs and their Paratexts . His mentorship reflects his broad expertise across historical and contemporary art theory.

Brian Weeksمشاهده پروفایل

دانشیار

• Evolutionary Ecology
• Climate Change Biology
• Biodiversity Conservation
• +۵ مورد دیگر

Brian Weeks is an Associate Professor in the School for Environment and Sustainability at the University of Michigan, where he joined as an Assistant Professor in 2019. His research focuses on understanding how species and communities respond to human-induced environmental changes, with particular emphasis on avian systems. Weeks leads an active research group that integrates museum specimen-based work, genomics, and field studies to investigate biodiversity responses to global change. Weeks' research interests span evolutionary ecology, climate change biology, and biodiversity conservation. His work primarily examines how bird species and communities have responded to environmental change through morphological adaptations. He combines museum-, field-, and lab-based approaches to study evolutionary processes across multiple scales, from macroevolutionary patterns in the Solomon Islands to contemporary changes in North American migratory birds. His lab has developed innovative methods like Skelevision for high-throughput measurement of functional traits from museum skeletal specimens. His publication record shows a strong focus on climate-driven morphological changes in birds, with recent work demonstrating how warming temperatures drive size reductions while simultaneously increasing wing length. His research has revealed that smaller-bodied species change at faster rates, and that migration timing shifts are decoupled from morphological changes. Weeks' lab also investigates biodiversity-ecosystem functioning relationships and extinction risk prediction. Packard Fellowship in Science and Engineering (2022) Ecological Society of America's George Mercer Award (2022) Katma Award, American Ornithological Society ISI Highly Cited paper (2021) Weeks advises multiple PhD and Master's students, and his lab collaborates extensively with researchers across institutions. His work has received significant media attention, with coverage in Science, The Wall Street Journal, The Washington Post, BBC News, and numerous international outlets. His research on birds shrinking due to climate change achieved an Altmetric score higher than 99.98% of papers tracked, reflecting its substantial scientific and public impact.

Le Luمشاهده پروفایل

پژوهشگر

• Medical Imaging
• Artificial Intelligence
• Oncology Imaging
• +۳ مورد دیگر

Dr. Le Lu serves as Researcher & Senior Director leading global Medical AI R&D efforts at Alibaba DAMO Academy since August 2021. His career spans prestigious institutions including the National Institutes of Health, Clinical Center, Radiology and Imaging Science Department, NVIDIA AI-Infra division, and Siemens corporate research where he was a senior staff scientist from 2006 until 2013. Ph.D. in Computer Science from Johns Hopkins University (2007) Dr. Lu specializes in medical imaging AI with significant contributions to oncology imaging and computer vision applications in healthcare. His research bridges advanced AI techniques with clinical applications, particularly in cancer screening and diagnostic imaging. He has published over 250 peer-reviewed articles in top-tier journals including Nature Medicine, Nature Communications, and IEEE Transactions on Pattern Analysis and Machine Intelligence, with more than 23,880 citations as of January 2024. Dr. Lu has received numerous accolades including IEEE Fellowship and recognition for publishing the most cited papers in IEEE TMI and CVPR medical imaging categories over the past decade. His innovative work has resulted in over 100 patent filings across multiple jurisdictions. IEEE Fellow (Computer Society) for contributions to medical imaging, AI and oncology imaging IEEE Signal Processing Society Distinguished Industrial Speaker (2021-2023) Associate Editor for IEEE Trans. Pattern Analysis and Machine Intelligence (IF: 24.3) Associate Editor for IEEE Signal Processing Letters and Frontiers in Oncology MICCAI society board member Through his leadership at Alibaba DAMO Academy, Dr. Lu directs research initiatives focused on making AI-driven healthcare solutions accessible globally, with recent presentations on 'AI for Health for All' and cancer screening paradigms.

Ahmad Lotfiمشاهده پروفایل

استاد

• Computational Intelligence
• Ambient Intelligence
• Robotics
• +۷ مورد دیگر

Ahmad Lotfi is a Professor of Computational Intelligence and Head of Department of Computer Science at Nottingham Trent University , with a Visiting Professor role at Tokyo Metropolitan University . He leads the Computational Intelligence and Applications (CIA) research group and has supervised over 30 PhD students to completion. PhD in Learning Fuzzy Systems (University of Queensland, 1995) MTech in Control Systems (Indian Institute of Technology, India) BSc in Control Systems (Isfahan University of Technology, Iran) His research spans computational intelligence , ambient intelligence , robotics , and machine learning , with applications in dementia monitoring , smart environments , and healthcare technology . Recent work focuses on using thermal sensor arrays for privacy-preserving human activity analysis. He has secured funding from Innovate UK , EPSRC , The Royal Society , and Horizon 2020 , with projects like iCarer (assistive living), SmartBerry (agricultural AI), and BigSpark (financial data augmentation). His 15 most recent articles demonstrate expertise in Wi-Fi-based activity recognition , EEG fall detection , and thermal sensor fusion . Senior Member IEEE Member of British Computer Society (MBCS) Editorial roles in Soft Computing and Journal of Ambient Intelligence and Smart Environments He has served as Program Chair for conferences like PETRA and ICCRT , and as Keynote Speaker at PETRA 2023 . His 28+ years of academic leadership include organizing UKCI and UKRAS conferences.

Bradley Hayesمشاهده پروفایل

دانشیار

• Human-Robot Interaction
• Explainable AI (XAI)
• Collaborative Robotics
• +۵ مورد دیگر

Bradley Hayes is an Associate Professor of Computer Science and Director of the Collaborative AI and Robotics (CAIRO) Laboratory at the University of Colorado Boulder. His work focuses on enabling autonomous agents and robots to collaborate safely and effectively with humans through techniques in human-robot interaction, explainable AI, and learning from demonstration. PhD in Computer Science, Yale University (2015) Postdoctoral Associate, MIT Interactive Robotics Group Research interests span collaborative robotics, dependable AI systems, and imitation learning for human-robot teaming, with applications in manufacturing, healthcare, and autonomous vehicles. His lab develops methods for task planning, motion prediction, and trust calibration in human-machine partnerships. Recent publications emphasize explainable sequential decision-making, neuromorphic learning architectures, and augmented reality interfaces for robotic training. Awards include Sustainability Recognition (2025) for motion planning efficiency Best Student Paper Runner-up (AAMAS 2022) Best Technical Paper Runner-up (HRI 2019) As lab director, he has mentored 12 PhD/Master students to completion, including Matthew Luebbers, Aaquib Tabrez, and Christine Chang. Funding sources include NSF grants and industry partnerships like Circadence, where he serves as Chief Technology Officer.