AutismAI Lab

Research library

Publications & references.

Every claim on this site traces back to a source. Below are the peer-reviewed references our tools build on, alongside the lab's own manuscripts — listed by status while they are in preparation or under review.

Grovalin — concept-generalization learning

Assistive learning for children with autism, built on evidence-based intervention frameworks and an open-vocabulary computer-vision pipeline.

From the lab

  • Pandey, S., et al.. Grovalin: An Open-Vocabulary Computer Vision and Generative AI Pipeline for Personalized Object Extraction and Selective Verification in Assistive Learning for Children with ASD. In preparation
  • Pandey, S., Vasquez, E., & Shomaji, S.. A Caregiver-Mediated Generative AI System for Personalized Concept-Generalization Learning in Autism Spectrum Disorder. In preparation

Key external references

  1. Liu, S., Zeng, Z., Ren, T., Li, F., Zhang, H., Yang, J., et al. (2023). Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection. arXiv:2303.05499
  2. Ravi, N., Gabeur, V., Hu, Y.-T., Hu, R., Ryali, C., Ma, T., et al. (2024). SAM 2: Segment Anything in Images and Videos. arXiv:2408.00714
  3. Radford, A., Kim, J.W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., et al. (2021). Learning Transferable Visual Models From Natural Language Supervision (CLIP). International Conference on Machine Learning (ICML). arXiv:2103.00020
  4. Esser, P., Kulal, S., Blattmann, A., Entezari, R., Müller, J., Saini, H., et al. (2024). Scaling Rectified Flow Transformers for High-Resolution Image Synthesis. International Conference on Machine Learning (ICML). arXiv:2403.03206
  5. Maenner, M.J., Warren, Z., Williams, A.R., Amoakohene, E., Bakian, A.V., Bilder, D.A., et al. (2023). Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 8 Years — Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2020. MMWR Surveillance Summaries 72(2), 1–14. doi:10.15585/mmwr.ss7202a1
  6. Tager-Flusberg, H., & Kasari, C. (2013). Minimally Verbal School-Aged Children with Autism Spectrum Disorder: The Neglected End of the Spectrum. Autism Research 6(6), 468–478. doi:10.1002/aur.1329
  7. Bondy, A.S., & Frost, L.A. (1994). The Picture Exchange Communication System. Focus on Autistic Behavior 9(3), 1–19. doi:10.1177/108835769400900301
  8. Sundberg, M.L. (2008). VB-MAPP: Verbal Behavior Milestones Assessment and Placement Program. AVB Press. https://marksundberg.com/vb-mapp/
  9. Wong, C., Odom, S.L., Hume, K.A., Cox, A.W., Fettig, A., Kucharczyk, S., et al. (2015). Evidence-Based Practices for Children, Youth, and Young Adults with Autism Spectrum Disorder: A Comprehensive Review. Journal of Autism and Developmental Disorders 45(7), 1951–1966. doi:10.1007/s10803-014-2351-z

Volitiq — motor phenotyping

Objective, browser-based motor assessment grounded in sensorimotor-control research and markerless pose estimation.

From the lab

  • Pandey, S., & Shomaji, S.. Decoding Motor Signatures in Autism from Markerless Video. Scientific Reports. Under review
  • Pandey, S., & Shomaji, S.. Multi-Modal Deep Learning for Automated Detection and Classification of Stimming Behaviors. In preparation
  • Pandey, S., & Shomaji, S.. E-MotionSpec: A Web-Based Platform for Real-Time Body Motion Analysis. In preparation

Key external references

  1. Maenner, M.J., Warren, Z., Williams, A.R., Amoakohene, E., Bakian, A.V., Bilder, D.A., et al. (2023). Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 8 Years — Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2020. MMWR Surveillance Summaries 72(2), 1–14. doi:10.15585/mmwr.ss7202a1
  2. Fournier, K.A., Hass, C.J., Naik, S.K., Lodha, N., & Cauraugh, J.H. (2010). Motor Coordination in Autism Spectrum Disorders: A Synthesis and Meta-Analysis. Journal of Autism and Developmental Disorders 40(10), 1227–1240. doi:10.1007/s10803-010-0981-3
  3. Torres, E.B., Brincker, M., Isenhower, R.W., Yanovich, P., Stigler, K.A., Nurnberger, J.I., et al. (2013). Autism: The Micro-Movement Perspective. Frontiers in Integrative Neuroscience 7, 32. doi:10.3389/fnint.2013.00032
  4. Wolpert, D.M., Diedrichsen, J., & Flanagan, J.R. (2011). Principles of Sensorimotor Learning. Nature Reviews Neuroscience 12(12), 739–751. doi:10.1038/nrn3112
  5. Balasubramanian, S., Melendez-Calderon, A., Roby-Brami, A., & Burdet, E. (2015). On the Analysis of Movement Smoothness. Journal of NeuroEngineering and Rehabilitation 12, 112. doi:10.1186/s12984-015-0090-9
  6. Lugaresi, C., Tang, J., Nash, H., McClanahan, C., Uboweja, E., Hays, M., et al. (2019). MediaPipe: A Framework for Building Perception Pipelines. arXiv:1906.08172
  7. Cao, Z., Hidalgo, G., Simon, T., Wei, S.-E., & Sheikh, Y. (2019). OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields. IEEE Transactions on Pattern Analysis and Machine Intelligence 43(1), 172–186. doi:10.1109/TPAMI.2019.2929257
How we cite

External references are peer-reviewed and linked to their DOI or arXiv record. The lab's own papers are listed by status — in preparation or under review — and we publish specific results only once they are reproducible. Where a reproducible result exists today, such as Grovalin's computer-vision benchmark, it is stated on the relevant science page.

Collaborate on the science.

We work with researchers and clinicians on shared studies, datasets, and manuscripts. If our methods are useful to your work, we would like to hear from you.

Collaborate with the lab Research overview