Updated Headshot _ Richa_Headshot_2022 Cropped (1)
Richa Rai

Richa is a doctorate student under Dr. Torres supervision. She has completed her MSci in Psychology and is preparing for the MSci in Computer Science. She has years of experience in the space of biosensors, developing methods to analyze biorhythmic data and adapting them to studies of neonates and infants. Richa has devoted a great deal of time to public service connecting researchers and practitioners with the needs of the autistic community.

Richa’s work is centered around scalability of research for balanced equity of maternal – infant health across all societal levels. Leveraging commercially available technology like cameras embedded in smart phones, she has developed methods that engage parents as active collaborators of her research endeavor to longitudinally track the neonate’s motor development. Using these digital means integrated with machine learning and artificial intelligence, her research assesses the progression of neurological and physical growth during these critical first months of life. Through brief, three-minute-long videos collected with an APP, she can remotely track the baby’s motions and growth, augmenting the criteria from General Movements Assessment theory with interpretable digital biometrics from the lab. 

Richa also adapts digitized clinical screeners for use with toddlers and young children and analyzes open access data from mom – infant dyads to learn about their hearts’ entrainment patterns.

If you're a new parent or pregnant mom, you can sign up for the project using the form below

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Richa also analyzes open access data involving biorhythmic activities of the heart shared between mom and baby.

Papers

  • Bermperidis, T., Rai, R., Ryu, J., Zanotto, D., Agrawal, S. K., Lalwani, A. K., & Torres, E. B. (2021). Optimal time lags from causal prediction model help stratify and forecast nervous system pathology. Scientific reports, 11(1), 1-24. https://doi.org/10.1038/s41598-021-00156-2 
  • Bokadia, H., Rai, R., & Torres, E. B. (2020). Digitized Autism Observation Diagnostic Schedule: Social Interactions beyond the Limits of the Naked Eye. Journal of personalized medicine, 10(4), 159. 
  • https://doi.org/10.1162/neco_a_01263 
  • Torres, E. B., Rai, R., Mistry, S., & Gupta, B. (2020). Hidden Aspects of the Research ADOS Are Bound to Affect Autism Science. Neural computation, 32(3), 515–561. https://doi.org/10.1162/neco_a_01263 
  • Torres, E. B., Vero, J., & Rai, R. (2018). Statistical Platform for Individualized Behavioral Analyses Using Biophysical Micro-Movement Spikes. Sensors (Basel, Switzerland), 18(4), 1025. https://doi.org/10.3390/s18041025