Deep Ghose
About Deep Ghose
Deep Ghose is an ML Team Lead at iProov, specializing in AI systems designed to combat advanced threats like deepfakes. He has a strong background in machine learning and data science, with experience managing research teams and developing innovative solutions in the field.
Current Role at iProov
Deep Ghose currently serves as the ML Team Lead at iProov, a position he has held since 2023. In this role, he leads the Advanced Threats AI team, focusing on the development of deep learning systems aimed at detecting deepfakes. His leadership involves overseeing a team of research engineers and driving innovative projects in the field of artificial intelligence.
Previous Experience at iProov
Before becoming the ML Team Lead, Deep Ghose worked at iProov as a Machine Learning Engineer from 2021 to 2022 and as a Senior Machine Learning Engineer from 2022 to 2023. During his tenure, he contributed to various projects that enhanced the company's capabilities in AI and machine learning, particularly in combating advanced threats.
Educational Background
Deep Ghose studied at the University of Cambridge from 2014 to 2019, where he earned a BA (Hons) in Natural Sciences and Classics. He later pursued a Master of Science in Computer Science with a focus on Artificial Intelligence and Data Science at the University of Nottingham from 2019 to 2020. His educational background provides a strong foundation for his work in AI and machine learning.
Professional Experience in AI and Machine Learning
Deep Ghose has extensive experience in the field of AI and machine learning. He has held various positions, including Deep Learning Research Scientist at Phantom Tech from 2020 to 2021 and Machine Learning Developer at TDP Data Systems in 2020. His work has primarily focused on developing AI systems to counteract advanced threats, including deepfakes.
Internship Experience
Deep Ghose gained valuable experience through internships at Commerzbank AG, where he worked as a Software Engineer Intern in 2019 for one month and as a Data Science Intern in 2020 for one month. These roles provided him with practical insights into software engineering and data science, contributing to his overall expertise in the field.