Devin Gulati
About Devin Gulati
Devin Gulati is a Machine Learning Engineer with expertise in deep learning algorithms and neural network architectures. He teaches at Rutgers IEEE and has experience in various roles, including co-director of the Machine Learning/AI Division and internships in programming and machine learning.
Work at ZeroEyes
Devin Gulati has been employed as a Machine Learning Engineer at ZeroEyes since 2022. In this role, he focuses on developing and implementing machine learning solutions that enhance the company's capabilities. His work involves applying advanced algorithms and neural network architectures to solve complex problems within the organization.
Education and Expertise
Devin Gulati studied Computer Science at Rutgers University, where he earned a Bachelor of Science degree from 2018 to 2022. Prior to that, he completed his secondary education at South Brunswick High School from 2014 to 2018. His academic background provides a solid foundation in computer science principles, particularly in machine learning and artificial intelligence.
Background in Machine Learning
Devin has extensive experience in designing and implementing deep learning algorithms. He is proficient in various neural network architectures, including Deep Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, and Long Short-Term Memory Networks. His expertise allows him to tackle a range of challenges in the field of machine learning.
Leadership at Rutgers IEEE
Devin served as the Co-Director of the Machine Learning/AI Division at Rutgers IEEE from 2019 to 2022. In this position, he taught the fundamentals of Neural Networks and Deep Learning to club members, fostering both his own understanding and that of his peers. He led collaborative coding teams for research and competitions, emphasizing innovative applications of machine learning.
Internship Experience
Devin has held several internships that contributed to his professional development. He worked as a Lead Machine Learning Intern at Atlas Systems for seven months in 2021, where he focused on practical applications of machine learning. Additionally, he interned as a Computer Programmer at NYU Langone Health from 2017 to 2018, gaining valuable experience in programming and software development.