Summary
Dr Nitesh Bhatia is a Virtual Reality (VR) researcher with a background in Perceptual Computing, Information Design & Human Machine Interface. At Imperial College London, he works in the chemical engineering department as a Research Associate with Matar Fluids Group under Prof. Omar K. Matar. Dr Bhatia helps develop a setup that involves a visual, audio and haptic VR multimodal interactive system. He develops algorithms for data analytics and the full coupling of the three modalities (audio, haptic, and visual) to use the above setup and algorithms to study spatio-temporal three-dimensional phenomena in fluid mechanics for flow (and pressure) fields generated using CFD software (provided by the Matar Fluids Group). The research offers scope for Dr Bhatia to learn about experimental design, collecting, analysing, and modelling human data, theoretical topics in cognitive science, and developing projects that involve building more extensive infrastructures for VR educational analytics. A crucial part of his work includes the development of non-invasive methods for analysing the data associated with the students’ behaviour to assess the effectiveness of VR-based teaching. Approaches that are currently under investigation include concept mapping sessions, capture, and analysis of student in-session activity data (how they move, what they interact with, etc.), measures of speed-of-uptake from in-app formative assessment, biometric data (e.g., gaze tracking), and potentially more sophisticated approaches involving brain-computer interfaces. The objective is to demonstrate VR educational use-cases using matrices for making informed decisions on-the-fly to influence and improve student engagement. This extra layer of human behavioural analytics can help make VR-based training activities more effective and improve learning-retention rates, especially across high-impact industries like education, health, manufacturing, emergency responses, and public safety. Dr Bhatia also provides training, technical advice, and mentorship to undergraduate and post-graduate students and supervises less experienced researchers where appropriate.
Useful Links:
- Innovative virtual reality software developed to enhance fluid dynamics lectures. https://www.imperial.ac.uk/news/189866/innovative-virtual-reality-software-developed-enhance/
- Immersive VR teaching for Fluid Dynamics at Imperial College London. https://www.youtube.com/watch?v=ccb0Lth1k2g
- Fluid Dynamics teaching. https://www.imperial.ac.uk/immersive-technology-initiative/fluid-dynamics-teaching/
- Seeing is believing and believing is seeing. From hologram lectures to the gamification of pure maths, technology is transforming teaching at Imperial. https://www.imperial.ac.uk/stories/seeing-is-believing
Selected Publications
Journal Articles
Bhatia N, Bryk K, Salazar E, et al., 2019, Towards Gamified Learning in Immersive Teaching of Fluid Mechanics, Bulletin of the American Physical Society, Vol:64
Picinali L, Kahouadji L, Mason L, et al., 2019, Use of Multi-sensory Immersive Technologies in Fluid Dynamics Education, Bulletin of the American Physical Society, Vol:64
Conference
Bhatia N, Xu E, Uddin F, et al., 2021, Fluid mechanics education using a mixed reality approach, Pages:T19-002
Mahmoud K, Harris I, Yassin H, et al., 2020, Does immersive VR increase learning gain when compared to a non-immersive VR learning experience?, International Conference on Human-Computer Interaction, Springer International Publishing, Pages:480-498, ISSN:0302-9743
Bhatia N, Müller EA, Matar O, 2020, A GPU accelerated Lennard-Jones system for immersive molecular dynamics simulations in virtual reality, International Conference on Human-Computer Interaction, Springer International Publishing, Pages:19-34, ISSN:0302-9743
Bhatia N, Ricardo Constante Amores C, Matar O, 2020, Visualizing CFD data in 3D augmented reality as an extension of 2D figures in scientific publications, Pages:Q01-009
Bhatia N, Goncalves G, Kahouadji L, et al., 2020, Visualizing time varying complex CFD flows in Virtual Reality, Pages:Q01-001