About

Dhwanit Agarwal is an experienced Machine Learning Engineer with a PhD in Computational and Applied Mathematics from the University of Texas at Austin and a Master's degree in Computational Science from the same institution. He also holds a Master's degree in Mathematics from the Indian Institute of Technology, Kanpur, and a Bachelor's degree in Mathematics from the same institution. Dhwanit has a strong background in solving complex problems using scientific computing, machine learning, and deep learning. He has experience in multidimensional data analysis, multivariate optimization, and numerical analysis. He is skilled in machine learning with packages like PyTorch, Scikit, and R. He is proficient in high-performance parallel computing in C++ and Fortran using OpenMP and MPI, as well as general-purpose GPU programming in CUDA, GPU acceleration in Python, and Matlab. Currently, Dhwanit is a Machine Learning Engineer at Adobe, where he applies his expertise in developing state-of-the-art deep learning architectures for multimodal translation, specifically text-assisted image manipulation. Previously, he worked as a Data Scientist and Machine Learning Researcher at Adobe, where he was part of a team that developed a novel and complete framework named EnTwine for identity resolution in online social networks. He also developed a new method for prior feature analysis using statistical methods instead of domain knowledge and heuristics, and introduced a clustering step to reduce space complexity. Dhwanit's educational background and technical skills make him a valuable asset to any organization working in the fields of machine learning, deep learning, and scientific computing. He is a highly analytical and results-driven individual with a passion for solving complex problems. With 1.54 years of relevant experience, he is well-equipped to take on challenging projects and deliver high-quality results.