Instructors

Patrick J. Burns is Associate Research Scholar, Digital Projects at NYU's Institute for the Study of the Ancient World Library working in ancient-world data processing and historical language text mining and analysis. In his role at NYU Libraries, Patrick is primarily a Python programmer and has taught classes and led workshops designed to support the ISAW/NYU community in programming-based research methods. He has also long been active in the NYUDH community.

Makesh Srinivasan is a graduate/master's student pursuing a degree in Computer Science at New York University.

With a love of research and  working on fun projects, Makesh is interested in Artificial Intelligence, Technology, Mathematics and Data, with a background in Machine Learning, Deep Learning, Computer Vision and Leadership ventures in international profession societies (IEEE and ACM).

Makes has 3+ years of work experience across academia, research and industry, and has worked as a ML engineer in numerous research institutes and start-ups, including ASU's SURI programme, Nagasaki University, Vellore Institute of Technology, New York University, National Institute of Technology, Institute of Electrical and Electronics Engineers (IEEE), and more.

Makesh works as a Machine Learning Intern at Sabbath & Co, ML Research Assistant at NYU's College of Dentistry, and as AI Developer at Research & Instructional Technology NYU, with a focus on foundation models (LLMs), multimodal RAG, pure CV, MLOps and cloud deployments. He is also serving as an ML Specialist at AIfSR to build and deploy multi-modal AI tools for NYU.

Stuti Mishra’s experience in the intersection of Data Science and MLOps includes a dynamic internship at NITI Aayog, where she delved into Explainable AI and implemented GANs using TensorFlow and PyTorch, significantly enhancing medical data sets and optimizing machine learning models for healthcare applications.

As a DevOps intern, Stuti honed her skills in scalable analytics and machine learning, leveraging tools like Kubernetes, Docker, and GitOps practices. This experience allowed her to efficiently manage resources and ensure seamless deployment for advanced data workflows.

As the founder of Superposition, she is dedicated to promoting diversity in STEM and fostering inclusivity. Her contributions have been recognized with prestigious scholarships, including the Dan Kohn Diversity Scholarship by the Linux Foundation and the Shubhra Kar LiFT Scholarship.