Hi
Hi
Cinay
Dilibal
PhD Student @ Boston University Interactive Computing Lab
PhD Student @ Boston University Interactive Computing Lab
About me
Hi, I'm Cinay, a PhD student in Computer Science at Boston University and a member of the Interactive Computing Lab, advised by Prof. Chang Xiao. My research explores AR/VR, medical simulation, cyber-physical systems, and human-AI interaction to develop technologies that augment human capabilities.
Publications
JF. Hou, S. Viswanath, C. Dilibal, B. Wu, T. Shende, C. Dagdeviren, “Real-time 3D Ultrasound in Augmented Reality Accelerates Training and Narrows Novice–Expert Performance Gaps”, Nature Communications Engineering 5, 107 (2026).
Ultrasound imaging requires users to infer three-dimensional anatomy from two-dimensional slices, imposing steep training demands that limit broader adoption. Here we present AR-VIU, a mixed-reality platform that streams real-time volumetric ultrasound as point-cloud renderings into an augmented-reality headset with true-scale spatial registration. To isolate the contributions of volumetric imaging and immersive display, we tested four conditions—two-dimensional imaging on a screen, two-dimensional imaging in augmented reality, three-dimensional imaging on a screen, and three-dimensional imaging in augmented reality—in a controlled study with 18 participants (9 novices, 9 experts). Participants performed object recognition and localization tasks. The augmented-reality volumetric system was associated with the highest accuracy, lowest variability, and near-elimination of the novice-expert performance gap. These results demonstrate technical feasibility for real-time three-dimensional ultrasound in mixed reality and establish an evaluation framework for perceptual and cognitive performance in clinically relevant scenarios, with near-term applications in training and education.
Check back for more details.
Usability testing and user feedback analysis
Interaction design and micro-animations
C. Dilibal, Y. Tur, “Implementation of Developed Esantem Smart Healthcare System in Metaverse”, IEEE International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), 2022.
Abstract: The advancement of digital transformation in virtual healthcare technologies have increased exponentially, creating a diverse range of state-of-the-art devices and software to optimize the revealed limitations within the healthcare industry. The recent trends in virtual healthcare was enhanced during COVID-19 pandemic which fostered the development of metaverse, a virtual space that forms digital identities and interfaces consisting of an interconnected network of digital devices. Metaverse can act as multi-scale layer of advanced computer-human interaction and can provide new opportunities for digitalized healthcare system. It can provide a wide range of assistance through medical examinations, meetings regarding mental well-being, and clinical appointments. Since the patient medical data is fully digitalized, metaverse offers a space in which artificial intelligence and augmented reality-assisted telehealth can function optimally. The accurate medical data provided by the wearable biomedical devices with the integration of metaverse and augmented reality technologies is becoming the efficient way of the telemedicine approach. While the digitalization of healthcare system within metaverse can ease the burden on conventional healthcare, the security of digital patient medical data becomes one of the main concerns for the proposed metaverse implementations. In this study, several aspects of the proposed implementation process of the embedded Esantem smart healthcare system in the metaverse, including the adaptations of conventional healthcare in metaverse, the opportunities for advanced human-computer interaction, and the handling of wearable biomedical device medical data and its security in a digital environment are examined. In addition, the main limitations against the development of such an implementation are unveiled with possible solutions such as blockchain for the security of patient data for future research directions.
C. Dilibal, B. L. Davis, C. Chakraborty, “Generative Design Methodology for Internet of Medical Things (IoMT)-based Wearable Biomedical Devices”, IEEE Human-Computer Interaction and Robotic Applications (HORA) International, 2021.
Abstract: Application-driven generative design concept produces multiple solutions in varied fields in the industry. Generative design is an iterative design process that involves a machine learning algorithm that creates varied outputs that meet pre-determined constraints. This methodology provides an efficient tool for creating different design options for biomedical devices. Biomedical devices need different functionality and complexity. The generative design combined with additive manufacturing increases the functionality of the biomedical device with reduced material and total cost. Using artificial intelligence (AI) algorithm and the cloud, generative design enables to develop creative design options for the internet of medical things (IoMT)-based biomedical devices. In this study, the crucial role of generative design methodology is revealed for creating functional IoMT-based biomedical devices.
C. Dilibal, “Development of Edge-IoMT Computing Architecture for Smart Healthcare Monitoring Platform”, IEEE 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), 2020.
Abstract: The age of virtual healthcare has created new opportunities to reconsider traditional methods for the preliminary medical examinations and clinical doctor-patient appointments. The COVID-19 pandemic has forced medical systems for strengthening online services in each medical field. Implementations of novel digital health technologies will dramatically reduce inessential hospital visits of patients for early diagnosis. Moreover, the telehealth based medical platforms will allow the medical services to be time- and cost-effective with convenient media for both patients and doctors. In this study, an internet of medical things (IoMT)-based smart healthcare monitoring platform architecture is proposed to remotely telecommunicate with optimized bandwidth efficiency and latency for a rapid decision-making process management for preliminary diagnosis in a virtual environment. The proposed edge-IoMT computing architecture framework will allow filtering and squeezing of raw medical data of the real-time video footage of the patients with functional algorithms.
C. Dilibal, A. Hacimustafaoglu, S. Dilibal, “Development of IoMT Device for Mobile Eye Examination Via Cloud-based TeleOphthalmology”, IEEE 21st International Conference on Research and Education in Mechatronics (REM), pp. 1-5, 2020.
Abstract: A periodic visit of an ophthalmologist is crucial for monitoring the eye health regularly. However, the periodic visit to the ophthalmologist may become difficult to handle in the cases of the patient’s visual status varies; personal location is far away from the hospital or special cases; such as COVID-19 pandemic. In this study, a novel ophthalmologist-and-patient-in-the-loop telemedicine platform is built to remotely examine the corneal surface of the eye. An internet-of-medical-things (IoMT)-based biomedical device is developed with ophthalmologist dashboard and patient interface. The developed biomedical device, Mobile XMI, is validated by testing in the ophthalmologist-and-patient-in-the-loop telemedicine system. The preliminary results showed that the cloud-based teleophthalmology architecture provides a potential tool for the early detection and diagnosis of the corneal related symptoms and diseases. Additionally, the developed medical platform facilitates the remote eye examination of the patients with disability or patients who locate far away from the ophthalmologist or hospital.
news
NOV 2026
Selected as a Student Volunteer for ACM UIST 2026 in Detroit, MI
SEP 2026
Started PhD at Boston University CS, advised by Prof. Chang Xiao!
AUG 2026
Awarded Boston University Computer Science Department Chair Award - $5,000
Awarded Boston University Computer Science Department Chair Award - $5,000
JUN 2026
Graduated from Dartmouth College with a Bachelor's degree in Computer Science, earning High Honors.
Graduated from Dartmouth College with a Bachelor's degree in Computer Science, earning High Honors.
JUN 2026
Awarded John G. Kemeny Innovation Computing Prize - $10,000
MAY 2026
Awarded Dartmouth HOP Outstanding Achievements in Interactive Design Award - $500
Projects
Media & Awards
Hi
Hi
Cinay
Dilibal
PhD Student @ Boston University Interactive Computing Lab
PhD Student @ Boston University Interactive Computing Lab
About me
Hi, I'm Cinay, a PhD student in Computer Science at Boston University and a member of the Interactive Computing Lab, advised by Prof. Chang Xiao. My research explores AR/VR, medical simulation, cyber-physical systems, and human-AI interaction to develop technologies that augment human capabilities.
Publications
JF. Hou, S. Viswanath, C. Dilibal, B. Wu, T. Shende, C. Dagdeviren, “Real-time 3D Ultrasound in Augmented Reality Accelerates Training and Narrows Novice–Expert Performance Gaps”, Nature Communications Engineering 5, 107 (2026).
Ultrasound imaging requires users to infer three-dimensional anatomy from two-dimensional slices, imposing steep training demands that limit broader adoption. Here we present AR-VIU, a mixed-reality platform that streams real-time volumetric ultrasound as point-cloud renderings into an augmented-reality headset with true-scale spatial registration. To isolate the contributions of volumetric imaging and immersive display, we tested four conditions—two-dimensional imaging on a screen, two-dimensional imaging in augmented reality, three-dimensional imaging on a screen, and three-dimensional imaging in augmented reality—in a controlled study with 18 participants (9 novices, 9 experts). Participants performed object recognition and localization tasks. The augmented-reality volumetric system was associated with the highest accuracy, lowest variability, and near-elimination of the novice-expert performance gap. These results demonstrate technical feasibility for real-time three-dimensional ultrasound in mixed reality and establish an evaluation framework for perceptual and cognitive performance in clinically relevant scenarios, with near-term applications in training and education.
Check back for more details.
Usability testing and user feedback analysis
Interaction design and micro-animations
C. Dilibal, Y. Tur, “Implementation of Developed Esantem Smart Healthcare System in Metaverse”, IEEE International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), 2022.
Abstract: The advancement of digital transformation in virtual healthcare technologies have increased exponentially, creating a diverse range of state-of-the-art devices and software to optimize the revealed limitations within the healthcare industry. The recent trends in virtual healthcare was enhanced during COVID-19 pandemic which fostered the development of metaverse, a virtual space that forms digital identities and interfaces consisting of an interconnected network of digital devices. Metaverse can act as multi-scale layer of advanced computer-human interaction and can provide new opportunities for digitalized healthcare system. It can provide a wide range of assistance through medical examinations, meetings regarding mental well-being, and clinical appointments. Since the patient medical data is fully digitalized, metaverse offers a space in which artificial intelligence and augmented reality-assisted telehealth can function optimally. The accurate medical data provided by the wearable biomedical devices with the integration of metaverse and augmented reality technologies is becoming the efficient way of the telemedicine approach. While the digitalization of healthcare system within metaverse can ease the burden on conventional healthcare, the security of digital patient medical data becomes one of the main concerns for the proposed metaverse implementations. In this study, several aspects of the proposed implementation process of the embedded Esantem smart healthcare system in the metaverse, including the adaptations of conventional healthcare in metaverse, the opportunities for advanced human-computer interaction, and the handling of wearable biomedical device medical data and its security in a digital environment are examined. In addition, the main limitations against the development of such an implementation are unveiled with possible solutions such as blockchain for the security of patient data for future research directions.
C. Dilibal, B. L. Davis, C. Chakraborty, “Generative Design Methodology for Internet of Medical Things (IoMT)-based Wearable Biomedical Devices”, IEEE Human-Computer Interaction and Robotic Applications (HORA) International, 2021.
Abstract: Application-driven generative design concept produces multiple solutions in varied fields in the industry. Generative design is an iterative design process that involves a machine learning algorithm that creates varied outputs that meet pre-determined constraints. This methodology provides an efficient tool for creating different design options for biomedical devices. Biomedical devices need different functionality and complexity. The generative design combined with additive manufacturing increases the functionality of the biomedical device with reduced material and total cost. Using artificial intelligence (AI) algorithm and the cloud, generative design enables to develop creative design options for the internet of medical things (IoMT)-based biomedical devices. In this study, the crucial role of generative design methodology is revealed for creating functional IoMT-based biomedical devices.
C. Dilibal, “Development of Edge-IoMT Computing Architecture for Smart Healthcare Monitoring Platform”, IEEE 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), 2020.
Abstract: The age of virtual healthcare has created new opportunities to reconsider traditional methods for the preliminary medical examinations and clinical doctor-patient appointments. The COVID-19 pandemic has forced medical systems for strengthening online services in each medical field. Implementations of novel digital health technologies will dramatically reduce inessential hospital visits of patients for early diagnosis. Moreover, the telehealth based medical platforms will allow the medical services to be time- and cost-effective with convenient media for both patients and doctors. In this study, an internet of medical things (IoMT)-based smart healthcare monitoring platform architecture is proposed to remotely telecommunicate with optimized bandwidth efficiency and latency for a rapid decision-making process management for preliminary diagnosis in a virtual environment. The proposed edge-IoMT computing architecture framework will allow filtering and squeezing of raw medical data of the real-time video footage of the patients with functional algorithms.
C. Dilibal, A. Hacimustafaoglu, S. Dilibal, “Development of IoMT Device for Mobile Eye Examination Via Cloud-based TeleOphthalmology”, IEEE 21st International Conference on Research and Education in Mechatronics (REM), pp. 1-5, 2020.
Abstract: A periodic visit of an ophthalmologist is crucial for monitoring the eye health regularly. However, the periodic visit to the ophthalmologist may become difficult to handle in the cases of the patient’s visual status varies; personal location is far away from the hospital or special cases; such as COVID-19 pandemic. In this study, a novel ophthalmologist-and-patient-in-the-loop telemedicine platform is built to remotely examine the corneal surface of the eye. An internet-of-medical-things (IoMT)-based biomedical device is developed with ophthalmologist dashboard and patient interface. The developed biomedical device, Mobile XMI, is validated by testing in the ophthalmologist-and-patient-in-the-loop telemedicine system. The preliminary results showed that the cloud-based teleophthalmology architecture provides a potential tool for the early detection and diagnosis of the corneal related symptoms and diseases. Additionally, the developed medical platform facilitates the remote eye examination of the patients with disability or patients who locate far away from the ophthalmologist or hospital.
news
NOV 2026
Selected as a Student Volunteer for ACM UIST 2026 in Detroit, MI
SEP 2026
Started PhD at Boston University CS, advised by Prof. Chang Xiao!
AUG 2026
Awarded Boston University Computer Science Department Chair Award - $5,000
Awarded Boston University Computer Science Department Chair Award - $5,000
JUN 2026
Graduated from Dartmouth College with a Bachelor's degree in Computer Science, earning High Honors.
Graduated from Dartmouth College with a Bachelor's degree in Computer Science, earning High Honors.
JUN 2026
Awarded John G. Kemeny Innovation Computing Prize - $10,000
MAY 2026
Awarded Dartmouth HOP Outstanding Achievements in Interactive Design Award - $500
Projects
Media & Awards
Hi
Hi
Cinay
Dilibal
PhD Student @ Boston University Interactive Computing Lab
PhD Student @ Boston University Interactive Computing Lab
About me
Hi, I'm Cinay, a PhD student in Computer Science at Boston University and a member of the Interactive Computing Lab, advised by Prof. Chang Xiao. My research explores AR/VR, medical simulation, cyber-physical systems, and human-AI interaction to develop technologies that augment human capabilities.
Publications
JF. Hou, S. Viswanath, C. Dilibal, B. Wu, T. Shende, C. Dagdeviren, “Real-time 3D Ultrasound in Augmented Reality Accelerates Training and Narrows Novice–Expert Performance Gaps”, Nature Communications Engineering 5, 107 (2026).
Ultrasound imaging requires users to infer three-dimensional anatomy from two-dimensional slices, imposing steep training demands that limit broader adoption. Here we present AR-VIU, a mixed-reality platform that streams real-time volumetric ultrasound as point-cloud renderings into an augmented-reality headset with true-scale spatial registration. To isolate the contributions of volumetric imaging and immersive display, we tested four conditions—two-dimensional imaging on a screen, two-dimensional imaging in augmented reality, three-dimensional imaging on a screen, and three-dimensional imaging in augmented reality—in a controlled study with 18 participants (9 novices, 9 experts). Participants performed object recognition and localization tasks. The augmented-reality volumetric system was associated with the highest accuracy, lowest variability, and near-elimination of the novice-expert performance gap. These results demonstrate technical feasibility for real-time three-dimensional ultrasound in mixed reality and establish an evaluation framework for perceptual and cognitive performance in clinically relevant scenarios, with near-term applications in training and education.
Check back for more details.
Usability testing and user feedback analysis
Interaction design and micro-animations
C. Dilibal, Y. Tur, “Implementation of Developed Esantem Smart Healthcare System in Metaverse”, IEEE International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), 2022.
Abstract: The advancement of digital transformation in virtual healthcare technologies have increased exponentially, creating a diverse range of state-of-the-art devices and software to optimize the revealed limitations within the healthcare industry. The recent trends in virtual healthcare was enhanced during COVID-19 pandemic which fostered the development of metaverse, a virtual space that forms digital identities and interfaces consisting of an interconnected network of digital devices. Metaverse can act as multi-scale layer of advanced computer-human interaction and can provide new opportunities for digitalized healthcare system. It can provide a wide range of assistance through medical examinations, meetings regarding mental well-being, and clinical appointments. Since the patient medical data is fully digitalized, metaverse offers a space in which artificial intelligence and augmented reality-assisted telehealth can function optimally. The accurate medical data provided by the wearable biomedical devices with the integration of metaverse and augmented reality technologies is becoming the efficient way of the telemedicine approach. While the digitalization of healthcare system within metaverse can ease the burden on conventional healthcare, the security of digital patient medical data becomes one of the main concerns for the proposed metaverse implementations. In this study, several aspects of the proposed implementation process of the embedded Esantem smart healthcare system in the metaverse, including the adaptations of conventional healthcare in metaverse, the opportunities for advanced human-computer interaction, and the handling of wearable biomedical device medical data and its security in a digital environment are examined. In addition, the main limitations against the development of such an implementation are unveiled with possible solutions such as blockchain for the security of patient data for future research directions.
C. Dilibal, B. L. Davis, C. Chakraborty, “Generative Design Methodology for Internet of Medical Things (IoMT)-based Wearable Biomedical Devices”, IEEE Human-Computer Interaction and Robotic Applications (HORA) International, 2021.
Abstract: Application-driven generative design concept produces multiple solutions in varied fields in the industry. Generative design is an iterative design process that involves a machine learning algorithm that creates varied outputs that meet pre-determined constraints. This methodology provides an efficient tool for creating different design options for biomedical devices. Biomedical devices need different functionality and complexity. The generative design combined with additive manufacturing increases the functionality of the biomedical device with reduced material and total cost. Using artificial intelligence (AI) algorithm and the cloud, generative design enables to develop creative design options for the internet of medical things (IoMT)-based biomedical devices. In this study, the crucial role of generative design methodology is revealed for creating functional IoMT-based biomedical devices.
C. Dilibal, “Development of Edge-IoMT Computing Architecture for Smart Healthcare Monitoring Platform”, IEEE 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), 2020.
Abstract: The age of virtual healthcare has created new opportunities to reconsider traditional methods for the preliminary medical examinations and clinical doctor-patient appointments. The COVID-19 pandemic has forced medical systems for strengthening online services in each medical field. Implementations of novel digital health technologies will dramatically reduce inessential hospital visits of patients for early diagnosis. Moreover, the telehealth based medical platforms will allow the medical services to be time- and cost-effective with convenient media for both patients and doctors. In this study, an internet of medical things (IoMT)-based smart healthcare monitoring platform architecture is proposed to remotely telecommunicate with optimized bandwidth efficiency and latency for a rapid decision-making process management for preliminary diagnosis in a virtual environment. The proposed edge-IoMT computing architecture framework will allow filtering and squeezing of raw medical data of the real-time video footage of the patients with functional algorithms.
C. Dilibal, A. Hacimustafaoglu, S. Dilibal, “Development of IoMT Device for Mobile Eye Examination Via Cloud-based TeleOphthalmology”, IEEE 21st International Conference on Research and Education in Mechatronics (REM), pp. 1-5, 2020.
Abstract: A periodic visit of an ophthalmologist is crucial for monitoring the eye health regularly. However, the periodic visit to the ophthalmologist may become difficult to handle in the cases of the patient’s visual status varies; personal location is far away from the hospital or special cases; such as COVID-19 pandemic. In this study, a novel ophthalmologist-and-patient-in-the-loop telemedicine platform is built to remotely examine the corneal surface of the eye. An internet-of-medical-things (IoMT)-based biomedical device is developed with ophthalmologist dashboard and patient interface. The developed biomedical device, Mobile XMI, is validated by testing in the ophthalmologist-and-patient-in-the-loop telemedicine system. The preliminary results showed that the cloud-based teleophthalmology architecture provides a potential tool for the early detection and diagnosis of the corneal related symptoms and diseases. Additionally, the developed medical platform facilitates the remote eye examination of the patients with disability or patients who locate far away from the ophthalmologist or hospital.
news
NOV 2026
Selected as a Student Volunteer for ACM UIST 2026 in Detroit, MI
SEP 2026
Started PhD at Boston University CS, advised by Prof. Chang Xiao!
AUG 2026
Awarded Boston University Computer Science Department Chair Award - $5,000
Awarded Boston University Computer Science Department Chair Award - $5,000
JUN 2026
Graduated from Dartmouth College with a Bachelor's degree in Computer Science, earning High Honors.
Graduated from Dartmouth College with a Bachelor's degree in Computer Science, earning High Honors.
JUN 2026
Awarded John G. Kemeny Innovation Computing Prize - $10,000
MAY 2026
Awarded Dartmouth HOP Outstanding Achievements in Interactive Design Award - $500