I delivered an expert talk in the short term training program organized by the Department of Information Technology, Delhi Technological University (DTU) on Recent Trends in AI and Machine learning on July 30, 2019. The title of my talk was “Emotion Recognition from Physiological Signals” where I highlighted how physiological signals such as electro-dermal activity (EDA) and electroencephalogram (EEG) can be used for recognizing the emotional state of an individual. The talk witnessed an enthusiastic audience of young researchers from varying backgrounds, undergraduate students to faculties. I would like to thanks Dr. Dinesh K. Vishwakarma for giving me an opportunity to interact with the curious minds at the DTU campus.
I am glad to share that my two articles have been accepted for publication and oral presentation at the 28th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN 2019) conference which will take place in New Delhi, India from 14 – 18 Oct 2019. The first article is “Mapping Robotic Affordances with Pre-requisite Learning Interventions for Children with Autism Spectrum Disorder” in collaboration with Venkata Ratnadeep Suri (Assistant Professor, IIIT-Delhi), Jatin Garg (Student, IIIT-Delhi), Krit Verma (Student, IIIT-Delhi) and Prarthana Kansal (Student, IIIT-Delhi). The second article is “Stakeholder’s Acceptance and Expectations of Robot-Assisted Therapy for Children with Autism Spectrum Disorder” in collaboration with Joan Oliver (Researcher, IRD, Spain), Rebeca Oliván (Researcher, IRD, Spain), Annabel Folch (Researcher, UNIVIDD, Spain), Rafael Martínez-Leal (Researcher, UNIVIDD, Spain), Mireia Castellà (Researcher, UNIVIDD, Spain), Domenec Puig (Professor, URV, Spain). Thanks to all the collaborators along with the heartiest congratulations. If you are planning to visit RO-MAN conference, please feel free to drop me an email to discuss potential collaboration opportunities or just to share a cup of tea 🙂
I delivered two lectures in the Faculty Development Program (FDP) on EEG analysis and allied technologies (1-5 July 2019) organized by SBILab, IIIT-Delhi. The first talk was on the topic “Brain Machine Interfaces for Assistive Robotics” and the second talk was on the topic “Emotion Recognition from EEG Signals”. The FDP program witnessed an enthusiastic audience of researchers working on EEG related technologies. I would like to thanks Prof. Anubha Gupta for organizing this program and giving me an opportunity to interact with curious minds.
I conducted a session with the teachers of The Indian School on Artificial Intelligence (AI) on Thursday 16th May. I would like to thank Dr. Anu Singh, the Vice Principal and HOD Science at The Indian School for giving me an opportunity of wonderful interaction with the teachers. It was fun to be back in the school in a different role. I had planned an activity of the Wumpus World to learn about reasoning in AI and the teachers enjoyed it. I was glad to know that CBSE is planning to launch a course in AI for high school students. I strongly believe that India needs to have an aggressive plan on AI similar to China.
Our article Feature Extraction and Selection for Emotion Recognition from Electrodermal Activity got published in prestigious IEEE Transactions on Affective Computing. Individuals with a wide range of mental health concerns such as children with autism, individuals with intellectual disability etc. have limited ability in recognition and expression of their emotional states. In such cases, analysis of human emotions expressed in the pure unaltered form of physiological signals such as Electrodermal activity (EDA) emerges as the most useful method for monitoring their emotions. However, extracting information about the emotional state from EDA data can be challenging, especially if the processing is to be done online. Hence, it is important to automatically identify meaningful smaller subsets of various EDA features to achieve efficient emotion recognition from EDA signals. In this research, we found that approximately the same numbers of features are required from EDA signals to obtain the optimal accuracy for the arousal recognition and valence recognition. In addition, our research also showed that statistical features related to the Mel-Frequency Cepstral Coefficients (MFCC) give better classification than commonly used Skin Conductance Response (SCR) related features. Our research has opened venues for the future development of new emotion recognition systems based on EDA with higher accuracy and minimizing its computational cost, which is key for the development of emotion detection applications that may work in real time.
The article can be accessed online at https://ieeexplore.ieee.org/abstract/document/8653316
Congratulations to all the authors, Jainendra Shukla (Asst. Professor, IIIT-D, India), Miguel Barreda-Ángeles (Sr. Researcher, EURECAT, Spain), Joan Oliver (Researcher, IRD, Spain), G. C. Nandi (Professor, IIIT-A, India), Domènec Puig (Professor, URV, Spain)
I am offering a 2 credit course on Social Robotics during the current semester for senior undergraduate and graduate students. Today I had my first class in IIIT-Delhi and due to some confusion in the schedule, I almost miss it! Thanks to our Academics Manager Ms. Sheetu for reminding me. Fortunately, I had some introduction slides ready and the students did not leave even after 10 minutes of delay 🙂
I am glad to share that my recently published research article Robot Assisted Interventions for Individuals with Intellectual Disabilities: Impact on Users and Caregivers got a media coverage. In an interview with Hindustan Times, I talked about how robot assisted interventions can be employed to provide cognitive stimulation to individuals with a wide range of mental health concerns, including individuals with intellectual disability. The complete interview can be accessed at https://www.hindustantimes.com/health/research-on-to-find-robots-utility-in-treatment-of-mental-disorders/story-QChK6spQ07HpeSqMgAGLmJ.html