ANERI DHRUVE

An enthusiast seeking an opportunity to utilize my analytical and problem-solving skills to serve your dynamic enterprise. A recent University of Waterloo graduate having specialization in AI ML and business leadership. I have experience in the processing industry and was curious to learn about the implementation of AI to enhance performance.

Generative AI Challenge | Waterloo Artificial Intelligence Institute, 05/2023, HealthCare - TherapAI - Team Synchronous - 3rd Place A pitch-deck challenge involving LLM architecture to provide a solution considering the impact of the proposed solution, feasibility of the LLM model, UI interface, Privacy, Safety and Bias considerations.

• WiE | Women in Engineering - Graduate Committee Fundraiser, University of Waterloo, 02/2024 - ongoing
• Game Day Staff - Waterloo Warriors, University of Waterloo, 01/2024 - 02/2024
• Strategic & Content Head | ISEE, Industrial Synergy for Electrical and Electronics Engineers, 05/2021 - 10/2021
• Training & Placement Cell Coordinator | FoTE, MS University, 03/2020 - 07/2021
• Core Committee Member | FootPrints - think BEYOND | FoTE, MS University 2020
  

• Multiple linear regression analysis and causal inference on New York State ELA Dataset :Statistical Analysis using Bayesian Estimation Models Optimization of Polynomial Regression using Lasso Regularization,
• Forest Fires dataset Image Clustering and Classification with Deep Learning, Used Fashion MNIST dataset, with 10 clothing item classes. Performed data pre-processing including PCA, LDA, t-SNE and autoencoders to facilitate unsupervised learning.
• Brain Tumor Detection and Segmentation - Deep Learning Techniques, Compared detection of brain tumor using VGG16, MobileNetV2 and ResNet50 architecture. Segmentation using AGSE-3D U-Net architecture on BRATS 2020 dataset.

• WiE | Women in Engineering - Graduate Committee Fundraiser, Waterloo, Canada, 02/2024, ongoing
• Game Day Staff - Waterloo Warriors, Waterloo, Canada, 01/2024, 02/2024
• Strategic & Content Head | ISEE, Industrial Synergy for Electrical and Electronics Engineers, 05/2021, 10/2021
• Training & Placement Cell Coordinator | FoTE, MS University, 03/2020, 07/2021
• Core Committee Member | FootPrints - think BEYOND | FoTE, MS University, 2020

Optimization of Polynomial Regression using Lasso Regularization - Forest Fires dataset Image Clustering and Classification with Deep Learning, Used Fashion MNIST dataset, with 10 clothing item classes. Performed data pre-processing including PCA, LDA, t-SNE and autoencoders to facilitate unsupervised learning. Brain Tumor Detection and Segmentation - Deep Learning Techniques, Compared detection of brain tumor using VGG16, MobileNetV2 and ResNet50 architecture. Segmentation using AGSE-3D U-Net architecture on BRATS 2020 dataset