Hung-Jui Guo
Hung-Jui is a Ph.D. candidate in the Software Engineering Department at the University of Texas at Dallas who successfully defended his Ph.D. proposal on April 2023. His research focuses on developing and measuring Mixed Reality (MR)/Augmented Reality (AR) systems on Microsoft HoloLens 2. He aims to address common issues in virtual environments, such as depth perception and occlusion of collaboration objects over long distances.
One of his primary working experiences during his Ph.D. has been working on an open project with the US Army Research Lab (ARL). This opportunity has helped him develop strong communication skills and collaborate effectively in a team setting.
Ninad Arun Khargonkar
Ninad is pursuing a PhD in Computer Science at UT Dallas. His research interests are in problems on Computer Vision and Machine Learning with applications to scene generation and robotics. Previous work was on developing a system for marker-less tele-rehabilitation of upper body joints using Kinect and force estimation. Current research focus is along 3D scene understanding and automated pipeline for real world scans to VR scenes.
Yu Yen Chung
Yu Yen is a C.S. PhD candidate at UT Dallas. He joined the multimedia lab in 2018. His research interests include deep learning, humanoid reconstruction, multimedia system, virtual reality, and human-computer interaction. His current work focuses on designing home-based immersive exergame systems for training and rehabilitation.
Hiranya Garbha Kumar
Hiranya is pursuing a PhD in Computer Engineering at UT Dallas. His research focus encompasses Computer Vision, Machine Learning, and Mixed Reality systems. Hiranya’s primary research interests revolve around 3D semantic reconstruction and the application of Deep Learning algorithms in various tasks involving 3D data. His current projects include semantic reconstruction of real-world 3D scenes in VR, matching CAD model retrieval, and 3D object pose estimation.
Sristi Dakshit
Sristi is a first-year PhD student at The University of Texas at Dallas, specializing in Machine Learning in Healthcare. She also has a keen interest in Computer Vision and Deep Neural Networks and aims to contribute to advancements in healthcare technology.
Currently, her research focuses on exploring resampling methods to understand its effects and enhance the performance of Machine Learning algorithms,with a particular emphasis on time-series signals within the healthcare sector.
Ms. Dakshit’s contributions have been recognized through her research publications in esteemed journals and conferences such as the Journal of Healthcare Informatics, the IEEE International Conference on Healthcare Informatics and IEEE International Joint Conference on Biometrics. In addition to her academic pursuits, Ms. Dakshit actively contributes to the academic community as both a Teaching Assistant and a Research Assistant at UTD.
Omeed Eshaghi Ashtiani
Omeed is a Ph.D. candidate in the Computer Science Department at the University of Texas at Dallas. His research focus is on Mixed Reality and Augmented Reality applications with machine learning. His work includes working on Color Depth Experiment with HoloLens2 which involves Real-time object detection with mixed reality and Automated emotion detection for COVID tweets (2019) using Siamese networks for topic pairing.
Meghana Spurthi Maadugundu
Meghana is a dedicated and passionate Computer Science PhD student with a strong focus on leveraging multimedia systems for healthcare applications. With unwavering enthusiasm, she is committed to making a lasting impact in the field of rehabilitation. By harnessing the power of medical AI and computer vision, she strives to create transformative solutions that improve lives.