Hassam Khan Wazir

Ph.D.

New York University

New York City, USA

Hi and welcome to my website!

I’m a Research Scientist at the Mechatronics, Controls, and Robotics Lab at NYU Tandon School of Engineering, specializing in digital health, ambient assistive technology, and telerehabilitation, particularly for the geriatric population. My research leverages connected and wearable devices, alongside commercially available technologies, to improve healthcare outcomes. My work spans robotics, mechatronics, wireless networks, augmented/virtual reality, computer vision, audio, and deep learning, with contributions to research in stroke and lymphedema rehabilitation.

With a strong background in robotics, electrical, mechanical, and mechatronics engineering, I specialize in collecting data from human subjects under IRB protocols, analyzing that data, training deep learning models, and designing wearable sensors. My experience includes designing and developing wearable inertial sensors for motion capture, developing control systems for robotic manipulators, and implementing computer vision and audio analysis for human-robot interaction. Sometimes, I also design and fabricate robotic systems for theatrical productions , and build hexapods , which is a lot of fun!

news

Jul 17, 2024	Presented a Poster at the 2024 IEEE Engineering Medicine and Biology Conference 📊
Jul 15, 2024	Started a Research Scientist Position at NYU Tandon School of Engineering!
Apr 23, 2024	Successfully defended my Ph.D. dissertation! 🎓

latest posts

Dec 21, 2023	NYU HPC Setup
Feb 23, 2020	The z-domain transfer function and the Bilinear transformation.
Feb 21, 2020	Classical Controllers (P, I, D)

selected publications

Frontiers
A COVID-19 emergency response for remote control of a dialysis machine with mobile HRI

Hassam Khan Wazir, Christian Lourido, Sonia Mary Chacko, and 1 more author

Frontiers in Robotics and AI, 2021

Abs Bib HTML PDF Video

Healthcare workers face a high risk of contagion during a pandemic due to their close proximity to patients. The situation is further exacerbated in the case of a shortage of personal protective equipment that can increase the risk of exposure for the healthcare workers and even non-pandemic related patients, such as those on dialysis. In this study, we propose an emergency, non-invasive remote monitoring and control response system to retrofit dialysis machines with robotic manipulators for safely supporting the treatment of patients with acute kidney disease. Specifically, as a proof-of-concept, we mock-up the touchscreen instrument control panel of a dialysis machine and live-stream it to a remote user’s tablet computer device. Then, the user performs touch-based interactions on the tablet device to send commands to the robot to manipulate the instrument controls on the touchscreen of the dialysis machine. To evaluate the performance of the proposed system, we conduct an accuracy test. Moreover, we perform qualitative user studies using two modes of interaction with the designed system to measure the user task load and system usability and to obtain user feedback. The two modes of interaction included a touch-based interaction using a tablet device and a click-based interaction using a computer. The results indicate no statistically significant difference in the relatively low task load experienced by the users for both modes of interaction. Moreover, the system usability survey results reveal no statistically significant difference in the user experience for both modes of interaction except that users experienced a more consistent performance with the click-based interaction vs. the touch-based interaction. Based on the user feedback, we suggest an improvement to the proposed system and illustrate an implementation that corrects the distorted perception of the instrumentation control panel live-stream for a better and consistent user experience.
@article{wazir2021covid, title = {A COVID-19 emergency response for remote control of a dialysis machine with mobile HRI}, author = {Wazir, Hassam Khan and Lourido, Christian and Chacko, Sonia Mary and Kapila, Vikram}, journal = {Frontiers in Robotics and AI}, volume = {8}, pages = {612855}, year = {2021}, publisher = {Frontiers Media SA}, url = {https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2021.612855/full}, google_scholar_id = {IjCSPb-OGe4C}, }