💃Anurag Patil is a senior data engineer at a major healthcare company in the United States who is actively working to bridge Artificial Intelligence (AI) theory with real-world healthcare applications. His journey through engineering, Machine Learning (ML), and data science has fueled his passion for creating responsible and impactful AI solutions that drive meaningful change in healthcare.
ꦛThis drive to improve the lives of others has established Anurag as a leader in his field, inspiring other researchers and professionals to leverage AI to make a difference.
Anurag’s Education
🦂Anurag attended the Birla Institute of Technology and Science (BITS), Pilani, India, where he developed a solid understanding of engineering. His experiences at BITS stirred an interest in ML and data engineering, so Anurag decided to move to the United States in pursuit of a Master’s Degree in Computational Science, Engineering, and Mathematics in Austin at the University of Texas, where he further specialized in deep learning and biological data.
🌠“My career journey was inspired by a moment of realization during my master’s program at UT Austin,” Anurag recalls. “While working on a project to apply deep learning to biological data, I saw first-hand how AI could uncover insights from complex, noisy data that traditional methods struggled to interpret. This experience sparked a desire to create impactful solutions, driving me toward machine learning as a powerful tool for discovery.”
Realizing the Potential of ML and AI Models
🎐During this project, Anurag concluded that, with enough data, ML could eventually decode the hidden patterns of incredibly complex systems, including the human body. AI models are only as powerful as the data that shapes them, as they determine the model’s capacity to generate useful insights and create meaningful outcomes. With the vast amounts of data available to healthcare systems, an AI model could push the boundaries of possibility.
Anurag’s Initial Career as a Data Engineer
ꩲAnurag began his career at a major American electric vehicle manufacturer in Palo Alto, California, where he gained vital experience. He started as an intern and, within four months, transitioned to a full-time data engineer, tackling high-impact projects. Anurag’s key contribution was optimizing data pipelines for battery research and development (R&D).
꧂“The challenge of architecting systems at such a scale—and seeing the tangible results of data-driven improvements—solidified my passion for combining engineering and machine learning to tackle real-world problems. I recognized that advancing in this field would allow me to contribute to areas that deeply intrigued me, like healthcare and AI alignment, and eventually drive meaningful innovation across industries.”
A Significant Industry Impact
🍌Anurag’s efforts resulted in the design and development of a high-performance data pipeline, which massively reduced data ingestion time by about thirty times. This significantly impacted R&D throughput and accelerated the electric vehicle manufacturer’s battery innovation efforts. This experience equipped Anurag with hands-on expertise in building scalable solutions and solving complex challenges—skills he continues to rely on today.
A Shift Toward Human-Centered Problems
♌Determined to fulfill his long-held desire to work on human-centered problems, Anurag decided to take a position as a senior ML data engineer on the AI and human health team at a major healthcare system in New York City in the United States. In this role, he became responsible for engineering robust Extract, Transform, and Load (ETL) pipelines and implemented advanced Large Language Models (LLMs) like LLaMA to drive biomarker research.
♓With his unique array of interdisciplinary skills, Anurag is still eager to contribute to ML research while advancing knowledge of biological issues.
“I developed large-scale ETL pipelines to integrate diverse health data sources into a single, cohesive platform,” Anurag explains. “This integration is essential for transitioning from fragmented, single-purpose ML models to a comprehensive AI system capable of understanding human biology—a key breakthrough for future medical research. I built a custom Python module, datapilotꦇ, to automate and streamline data processing, working with tools like Airflow and NiFi on Azure. I also integrated advanced NLP models by fine-tuning LLaMA 3.1 on clinical notes, achieving a performance level that replaced a GPT-4-based solution, leading to significant cost savings and increased processing efficiency.”
Advancing Clinical Insights and Research With Data
🍨Anurag’s work has enabled researchers to access structured data in real-time, accelerating key clinical insights and biomarker research. His scalable systems have enabled teams to generate and test hypotheses rapidly and accurately across multiple studies.
🅺Based in New York City, Anurag is ideally situated to develop inclusive and equitable AI models that can address the needs of a demographically diverse population.
Mentorship and Workshops
🍸Beyond his professional career, Anurag is committed to mentorship and making key contributions to the industry. He actively mentors students from his alma mater, BITS Pilani, in engineering and AI technology, guiding them in data science and AI projects and encouraging them to develop both technical and professional skills to shape the next generation of engineers and researchers.
💮He actively leads initiatives to share knowledge and insights from his own work in the biomedical and ML fields with collaborators at the Digital Health Workshop in Berlin, Germany, conducting hackathons and sessions to familiarize researchers and students with medical data.
🔥Through these activities, he aims to empower aspiring professionals with hands-on experience and an understanding of the transformative potential of AI in healthcare.
A Vision for Ethical, Impactful AI
🎶Looking ahead, Anurag aims to continue creating AI systems that are not only technically advanced but also ethically aligned, accessible, and effective at improving patient care. Anurag hopes to continue pushing the field of AI toward advancements that meaningfully serve society as a whole.
🔯“I aspire to lead interdisciplinary projects that expand the frontiers of AI research, collaborate with experts from diverse fields like healthcare, and mentor the next generation of engineers and researchers,” Anurag concludes. “Through these efforts, I hope to help build AI systems that not only advance human understanding but also resonate with human values—making technology a true ally in healthcare.”
