With over 10 years of experience in software engineering and research, I specialize in developing virtual and augmented learning environments, multiuser serious games, and data-driven applications for academia, industry, NGOs, and governments. My key strengths lie in collaboratively working with interdisciplinary teams to develop solutions using diverse software and hardware frameworks that meet project requirements.
I completed my PhD at Aarhus University’s Extended Reality and Robotics lab, Aarhus University, my research focused on immersive virtual reality, haptics, biosignals, and learning analytics for effective skill training systems. At Aarhus University, I have also developed multiuser virtual environments to support teaching and have taught graduate-level courses on Python and Machine Learning. Previously, I led the Virtual Reality & Serious Games group at AMMACHI labs, where I developed and led various virtual reality training solutions for clients such as the Indian government and companies like Larsen & Toubro.
Interests
Virtual Reality/Augmented Reality
Haptics
Data Analytics
Tangible User Interfaces
Serious Games for Education
Social Robotics
Education
PhD, 2020 - 2023
Department of Business Development & Technology, Aarhus University, Denmark.
Masters in Computer Applications, 2007 - '10
Amrita School of Engineering, Amrita Vishwa Vidyapeetham University, India.
BSc in Computer Science, 2004 - '07
Amrita School of Arts & Sciences, Amrita Vishwa Vidyapeetham University, India.
This paper details the motivations, design, and analysis of a study using a fine motor skill training task in both VR and physical conditions. The objective of this between-subjects study was to (a) investigate the effectiveness of immersive virtual reality for training participants in the ‘buzz-wire’ fine motor skill task compared to physical training and (b) investigate the link between participants’ arousal with their improvements in task performance. Physiological arousal levels in the form of electro-dermal activity (EDA) and ECG (Electrocardiogram) data were collected from 87 participants, randomly distributed across the two conditions. Results indicated that VR training is as good as, or even slightly better than, training in physical training in improving task performance. Moreover, the participants in the VR condition reported an increase in self-efficacy and immersion, while marginally significant differences were observed in the presence and the temporal demand (retrieved from NASA-TLX measurements). Participants in the VR condition showed on average less arousal than those in the physical condition. Though correlation analyses between performance metrics and arousal levels did not depict any statistically significant results, a closer examination of EDA values revealed that participants with lower arousal levels during training, across conditions, demonstrated better improvements in performance than those with higher arousal. These findings demonstrate the effectiveness of VR in training and the potential of using arousal and training performance data for designing adaptive VR training systems. This paper also discusses implications for researchers who consider using biosensors and VR for motor skill experiments.
Virtual reality (VR) training offers the capability to industrial workers to acquire skills and address complex tasks by immersing them in a safe and controlled virtual environment. Immersive VR (IVR) training is adopted in many diverse settings, yet little systematic work currently exists on how researchers have applied it for industrial skills training and if it holds the potential to be applied remotely. In this review, 78 representative studies were analysed to answer three key questions: Is IVR an effective training method for industrial skills training? How is research in this field applied? And how can we make IVR training more effective and applicable for remote training? We can testify that IVR is a promising training method with high effectiveness scores. However, our analysis has uncovered several gaps in the application of IVR training, like the lack of learning theories in the design process and limited metrics beyond time and scores. Additionally, our review also exposed unexplored but intriguing avenues of research, like the utilisation of biosensors for users’ data collection, haptics that increases realism and applications with remote training potential.
Virtual Reality (VR) for skill training is seeing increasing interest from academia and industry thanks to the highly immersive and realistic training opportunities they offer. Of the many factors affecting the effectiveness of training in VR, the arousal levels of the users merit a closer examination. Though subjective methods of measuring arousal exist in VR literature, there is potential in using cost-effective sensors to directly measure these from bio-signals generated by the nervous system. We introduce the design of preliminary observations from a pilot study exploring user’s arousal levels and performance while executing a series of fine motor skill tasks (buzzwire tracing). Future directions of the work are also discussed.
Virtual Reality (VR) for skill training is seeing increasing interest from academia and industry thanks to the highly immersive and realistic training opportunities they offer. Of the many factors affecting the effectiveness of training in VR, the arousal levels of the users merit a closer examination. Though subjective methods of measuring arousal exist in VR literature, there is potential in using cost-effective sensors to directly measure these from bio-signals generated by the nervous system. We introduce the design of preliminary observations from a pilot study exploring user’s arousal levels and performance while executing a series of fine motor skill tasks (buzzwire tracing). Future directions of the work are also discussed.
We introduce Pepe, a social robot for encouraging proper handwashing behaviour among children. We discuss the motivation, the robot design and a pilot study conducted at a primary school located in the Western Ghats mountain ranges of Southern India with a significant presence of indigenous tribes. The study included individual & group interviews with a randomly selected sample of 45 children to gauge their perception of the Pepe robot across various dimensions including gender, animacy & technology acceptance. We also discuss some HRI implications for running user studies with rural children.
We present Haathi Mera Saathi (My Elephant Friend), a game concept which serves as a tool for teaching programming and computational thinking to underprivileged children in rural India. It provides a metaphor and gameplay for embodied and tangible games, and creates a soft early ramp up into the conceptual and digital space of learning to code. We discuss the urgency of digital inclusion for Indian rural children, with reference to technology as an amplifier which they need to learn to direct. We contrast the grounded, embodied style of Haathi Mera Saathi with the current crop of mini-languages and coding games, with particular emphasis on the need for physicality and tangibility in the very early stages of learning to code. We further discuss our experience conducting workshops for students from the tribal and rural belts of India, where we see HMS as an effective approach for taking them from a state of having no background in computers or computing, to a state where they create interactive applications in a Java based environment. Recommendations are given for researchers interested in working with rural village children.