About

Nishant Ravinuthala is an ambitious and highly skilled graduate student aiming to specialize in Big Data systems with a focus on machine learning. With a Bachelor's degree in Computer Science and Engineering from IIIT Hyderabad and currently pursuing a Master's degree in Computer Science with a concentration in Big Data Systems from Arizona State University, he has a solid foundation in the field of computer science. Nishant has gained extensive experience in machine learning, statistical and probabilistic learning, deep learning (for computer vision), reinforcement learning, online learning, and traditional AI techniques. As an undergraduate research assistant at the Center for Visual Information Technology (CVIT), he worked under the guidance of Prof. Anoop Namboodiri, where he applied machine learning to address problems in computer vision. At CVIT, Nishant built an assistive technology to help blind people navigate using CV and ML, developed a pipeline that predicts how expressive and attentive a person is from video snippets given as input, and identified issues with deep networks for videos. He boosted performance from an initial 75% to a final 93.6% by using audio features in addition to the video inputs. Nishant has also worked as an undergraduate research assistant at the Cognitive Science Lab, where he mined musicality from fMRI responses and distinguished brain voxel responses of musicians from non-musicians using sequential deep learning. Nishant has also worked as a Research Intern at Siemens, where he solved key problems in intelligent road traffic control and management using machine learning, computer vision, and reinforcement learning. He developed a network capable of detecting road accidents from CCTV footage, augmented the existing dataset with synthetic data using RL, and adapted the synthetically created dataset to the real-world scenario dataset. With 4.95 years of relevant experience, Nishant is actively seeking full-time roles as a software engineer, data scientist, and ML engineer. He is proficient in technologies such as Tensorflow, Python, and AI and has a strong background in research, making him a valuable asset to any organization.