Summary
Arunava Nag is a postdoctoral scholar at the University of Chicago with 11 years of experience applying machine learning and imaging to biomedical questions, currently developing spatial-omics-driven insights into lupus nephritis using human and mouse renal biopsies. He combines a strong robotics and vision background—spanning ROS, UAV odor-plume simulation, and real-time 3D vision-guided manipulation—with rigorous statistical modeling and Kalman filtering on multi-sensor datasets. His work bridges engineered systems and biology, translating simulation-tested algorithms (e.g., COSMOS odor simulator integrated with Gazebo and UAVs) into experimental platforms. Arunava has a PhD from University of Nevada, Reno and a history of building practical tools for autonomy and human-robot collaboration in both academic and industrial settings. Known for turning complex sensor data into robust, real-time estimators, he brings both hands-on systems engineering and data-driven research to interdisciplinary problems. Based in the Greater Chicago Area, he blends experimental rigor with applied software and robotics expertise to tackle translational biomedical challenges.
11 years of coding experience
9 years of employment as a software developer
High School, High School at DAV Schools Network
Master's Degree, Master's Degree at North Carolina State University
Bachelor of Engineering (B.E.), Bachelor of Engineering (B.E.) at Visvesvaraya Technological University
Doctor of Philosophy - PhD, Doctor of Philosophy - PhD at University of Nevada, Reno
Hindi, Bengali, English