Naeem Khoshnevis

Senior ML Research Engineer

Preferred Pronouns: He/Him
KEMPNER GLOBAL COMMUNITY I speak: English, Farsi, Azeri

Contact Information

Best way to contact me: Email

Social Media

Office Address

SEC 6.135

About

Naeem has a solid foundation in mathematics and statistics, enhanced by over a decade of expertise in high-performance computing (HPC) and more than three years in open-source software development, focusing on machine learning (ML) and statistical tools. Prior to his current role, he served as a senior research software engineer at the National Studies on Air Pollution and Health at Harvard T.H. Chan School of Public Health and the Edge Computing Lab at Harvard School of Engineering and Applied Sciences. Naeem has extensive experience with parallelization mechanisms, including shared and distributed memory systems. He has collaborated with a broad range of researchers, from numerical analysts to machine learning specialists, demonstrating a unique blend of programming proficiency in Python, R, C, and C++. His work emphasizes large-scale machine learning pipeline implementation and adherence to software engineering best practices.

Research & Engineering Focus

Naeem, as part of Kempner’s Research and Engineering team, is set to optimize the deployment of advanced deep learning models, leveraging the Kempner Institute’s computational resources efficiently. He’s tasked with guiding the team to meet the highest software engineering standards, focusing on creating efficient data pipelines and strategically allocating resources to boost system performance and scalability. His commitment extends to promoting reproducible research, ensuring methodologies and results are verifiable, and building a collaborative, scalable infrastructure with open-source tools. Additionally, Naeem will lead the adoption of MLOps practices to automate and refine the lifecycle of machine learning models, enhancing scalability, efficiency, and maintainability. He’ll also oversee architectural decisions for ML systems, contribute to grant proposals and technical reports, and mentor junior staff. By concentrating on optimizing algorithmic design and bridging the gap between GPU engineers, researchers, and data architects, Naeem aims to enhance the productivity of Kempner’s Research and Engineering team.