About Myself

I am a mechanical engineer with a strong technical background in machine learning. My commitment to continuous learning has enabled me to take on new challenges and consistently deliver remarkable performance. I am passionate about applying deep learning to solve real-world problems. With a strong technical foundation, extensive interdisciplinary research experience, and hands-on industry know-how, I am confident in my ability to bring value to any organization I join.

  • 2012-2016

    Undergraduate

    Tribhuvan university
    Kathmandu, Nepal

  • Aug'19- May'24

    Graduate school (Ph.D)

    Rensselaer Polytechnic Institue
    New York, USA

Reach me to collaboratr on ML project

Click each name to visit the account.

GITHUB

An avid open-source contributor. Check my account to get full access to my open source projects.

LINKEDIN

I post my latest projects and news on LinkedIn.

RESEARCHGATE

My papers are made online at researchgate soon after being published.

GOOGLE SCHOLAR

Full list of peer reviwed papers are available on google scholar.

Latest Projects
( Website underconstruction... adding more projects)

Either completed or working on them!

Slicestream

SliceStream aims to develop an interactive user interface for high-quality segmentation and object tracking in videos, with a focus on reducing the reliance on labor-intensive data annotation and initialization.

Image generation

Varitational autoencoder (VAE) used for novel images generation.

GIF GIF

Temporal Attention

Temporal attention embeded Graph neural network for spatio-temporal attention learning.

Image identification

CLIP model based image identification

Selected publications

  1. Anil Kamat, C. Eastmond, A. Gao Yuanyuan, et al., “Assessment of surgical tasks using neuroimaging dataset (astaund),” Sci Data (Nature), vol. 10, no. 699, 2023.
  2. Anil Kamat, B. Makled, J. Norfleet, et al., “Directed information flow during laparoscopic surgical skill acquisition dissociated skill level and medical simulation technology,” NPJ science of learning, Nature, vol. 7, no. 1, pp. 1–13, 2022.
  3. Anil Kamat, B. Makled, J. Norfleet, X. Intes, A. Dutta, and S. De, “Brain network effects related to physical and virtual surgical training revealed by granger causality,” in 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), IEEE, 2021, pp. 1014–1017.
  4. Anil Kamat, B. Makled, J. Norfleet, et al., “Efference information flow during skill acquisition medi- ates its interaction with medical simulation technology,” bioRxiv, 2021.
  5. Anil Kamat and A. Sah, “Early detection of covid-19 waves from cases in a neighboring country with an open border,” Frontiers in public health, vol. 9, 2021.
  6. A. Dutta, Anil Kamat, B. Makled, J. Norfleet, X. Intes, and S. De, “Interhemispheric functional con- nectivity in the primary motor cortex distinguishes between training on a physical and a virtual sur- gical simulator,” in International Conference on Medical Image Computing and Computer- Assisted Intervention, Springer, Cham, 2021, pp. 636–644.
  7. A. Nemani, Anil Kamat, Y. Gao, et al., “Functional brain connectivity related to surgical skill dexterity in physical and virtual simulation environments,” Neurophotonics, vol. 8, no. 1, pp. 015 008–015 008, 2021.