Ronak Dedhiya

Hi, I am Ronak

I am an experienced Machine Learning and Deep Learning researcher with over 8 years of experience in developing and deploying end-to-end AI solutions in challenging, data-scarce environments. Strong academic foundation with a Master’s thesis focused on generating 3D models from minimal data, coupled with multiple publications. Specialized in novel technologies, particularly in medical applications such as thermal imaging. Adept at working in startup environments, leading projects from concept to production with cloud and on-premise deployments.

MY CV Project Research Papers Resources

Github Linkedin

Project

  1. Transformer from scratch Code
  2. Self Supervised Pre Training Code
  3. Simple VAE Code Report
  4. Diffusion Model Code Report
  5. Training MOCO Code Report
  6. Video Blur Detection Code PPT Paper
  7. Automatic Defect Inspection of solar farm using drones Code
  8. Spark Data Analysis on YouTube trending videos Code PDF
  9. Sample Efficient Actor Critic with Experience Replay Code PPT
  10. Qualitative assessment of learned latent factors of basic VAE, conditional VAE in conjugation with β - VAE Code Paper
  11. Learning Single-View & Multiple-View 3D Object Reconstruction Code PPT Paper
  12. 3D Breast Surface Reconstruction Using 2D Thermal Images [MTech Thesis] [Under IPR] [Yet to be released].

Resources

  1. Multiple AI/ML Assignments Code
  2. Linear and Non-Linear Optimization Code Tutorials
  3. Reinforcement Learning Tutorials

Theory Paper Analysis/Review/Report

  1. Introduction to Variational AutoEncoder Link
  2. Improving Variational Inference using Autoregressive Flows Link
  3. Domain-Adversarial Training of Neural Networks Link
  4. Your Classifier is secretly an energy based model and you should treat it like one Link
  5. Diffusion Model Link

Research Papers

  1. Dedhiya, Ronak, et al. “Evaluation of Non-Invasive Thermal Imaging for Detection of Viability of Onchocerciasis Worms.” 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE, 2022. Link
  2. Dedhiya, Ronak, et al. “Non-invasive Thermal Imaging for Estimation of the Fecundity of Live Female Onchocerca Worms.” MICCAI Workshop on Medical Image Assisted Blomarkers’ Discovery. Cham: Springer Nature Switzerland, 2022. Link
  3. Saha, Arka Prabha, et al. “3D-BreastNet: A Self-supervised Deep Learning Network for Reconstruction of 3D Breast Surface from 2D Thermal Images.” MICCAI Workshop on Artificial Intelligence over Infrared Images for Medical Applications. Cham: Springer Nature Switzerland, 2023. Link
  4. Dedhiya, Ronak, et al. “Thermal Radiomics for Early Detection of Diabetic Foot Ulcers Using Infrared Thermography” [To be published in MICCAI 2024].