About

Kanish Garg is a highly skilled Software Engineer with expertise in Artificial Intelligence, Machine Learning, and Data Science. He is currently working at Google, where he is engaged in solving challenging problems using his knowledge of computer science concepts. Prior to joining Google, Kanish worked as an Analyst in Quantitative Investment Strategies at Goldman Sachs, where he gained practical experience in the field of finance. Kanish is a graduate of the prestigious Indian Institute of Technology, Delhi, where he majored in Electrical Engineering and minored in Computer Science. He has a strong coding and quantitative background and is proficient in Machine Learning, Algorithms, Probability, and Statistics. Kanish has also gained practical experience in Data Science, Deep Learning, and Software Development by working on various projects at IITD, Goldman Sachs, and his internship at Samsung Research Institute, Noida. Kanish's interest centers around Artificial Intelligence, and he wishes to contribute to the field by working on challenging problems. He has research papers in top AI conferences, including WACV'21 USA, ICPR'20 Italy, and IVPR'20 Japan. Kanish is a highly motivated individual with a passion for learning and a desire to make a positive impact in the world. In addition to his professional experience, Kanish is also a Research Scientist and has worked as an Undergraduate Research Fellow at the Singapore University of Technology and Design. He has published a research paper on "Automatic Detection of Arrhythmia using Deep Learning" in IEEE Xplore. Kanish's technical skills include Software Engineering, Research Scientist, AI, Deep Learning, ML, and Data Science. He has relevant experience of 2.35 years and is constantly seeking new challenges to improve his skills and knowledge.