About

Selwyn Gomes is a highly skilled Software Engineer and Research Scientist with a focus on Machine Learning and Data Science. He is currently working as a Software Engineer Intern at Qualcomm, where he is part of the XR software team and working on the Snapdragon Spaces developer platform. Selwyn is also a graduate student at UC San Diego, specializing in Machine Learning and Data Science. Selwyn has a wealth of experience in the field of Machine Learning and Data Science, having previously worked as a Graduate Student Researcher at UC San Diego and as a Research Assistant at the National University of Singapore. In his role at UC San Diego, Selwyn provided support for the end-to-end deployment of machine learning models for low latency inference on Alveo FPGA boards leveraging the Xilinx Vitis flow. His contribution was made towards the hls4ml open source project. At the National University of Singapore, Selwyn worked on providing theoretical guarantees and experimental evidence for using 1-bit compressive sensing with generative priors. He also explored a relaxed optimization problem in Gaussian process bandits and put forward theoretical bounds along with modified acquisition algorithms for faster convergence in the given setting. Selwyn also investigated the potential application of gradient-based methods in high dimensional Black-Box optimization using a probabilistic posterior function over the derivative space. Selwyn has a strong educational background, having completed a Master's degree in Machine Learning and Data Science from the University of California, which he is expected to complete in December 2023. He also holds a Bachelor of Engineering in Electronics and Instrumentation Engineering from Birla Institute of Technology and Science, Pilani, and a Minor in Finance from the same institute. Selwyn's technical skills include Software Engineering, Research Science, Machine Learning, and Data Science. He has 1.85 years of relevant experience and is passionate about using his skills to solve complex problems in the field of Machine Learning and Data Science.