Gaurav Arwade Email & Phone Number

Ann Arbor, Mi, Us

Milpitas, California, Us

Ames, Iowa, Us

- As a Graduate Research Assistant at Iowa State University, I specialize in precision healthcare through the application of data science and statistical machine learning. In the project "Ensemble of Interpretable Simple Structures," I designed advanced algorithms, achieving a notable improvement of 9% and 7% in machine learning model fit on stroke and COVID-19 mortality data. My role extends to developing foundational principles and assumptions, rigorously validated through statistical simulations and bootstrapping. In the ongoing project "Interpretable Machine Learning Informed Diagnosis for Heart Failure in Primary Care," I am pioneering a three-step sequential interpretable data science model, achieving performance comparable to complex models like neural networks and XGBoost. Actively contributing to the implementation of this innovative data science model in real-world healthcare settings, I am dedicated to advancing the field of data-driven healthcare solutions.- Design and Simulation of Automatic Seed Storage and Retrieval - Analysis of existing system, proposing a new system, simulation of the proposed system, resource allocation, and optimization.

Basel, Basel, Ch

I developed robust foundational model for an agriculture vision task, with a primary focus on transformers. Leveraging advanced generative AI techniques, I adapted a state-of-the-art transformer-based generative model for reducing annotation costs by an impressive 95%. The model surpassed traditional and CNN-based vision algorithms, achieving a remarkable 10% improvement in accuracy. This experience underscores my ability to harness the transformative power of transformers and highlights my nuanced understanding of cutting-edge technologies, particularly in the context of foundational models and their applications in computer vision tasks.

Basel, Basel, Ch

I developed diverse computer vision algorithms aimed at quantifying various plant phenotypes, encompassing measurements such as plant height, corn cob dimensions, and plant maturity. I seamlessly integrated both Convolutional Neural Networks (CNN) and traditional vision and machine learning tools into my approach. This role not only allowed me to leverage the power of CNNs for intricate pattern recognition but also demonstrated my proficiency in employing conventional vision and machine learning techniques to address nuanced challenges in plant phenotype analysis. By embracing a hybrid approach, I successfully contributed to the accurate measurement and analysis of critical agricultural parameters, showcasing versatility and adaptability in the application of cutting-edge technologies to real-world challenges.

- While working with the organization my responsibilities include quality control of wax moulds, root cause amalysis and production scheduling in investment casting. - Vendor quality control- Continuous quality control and assurance. - Process planning of new casting right from die development to final machining.- Time and motion study to reduce the overtime and increase the number of batches in a shift.

Doctor Of Philosophy - Phd, Operations Research, Computer Science

Master'S Degree, Operations Research And Machine Learning

Bachelor Of Technology, Mechanical Engineering