He earned his PhD degree from the University of South Dakota in experimental nuclear and particle physics, specializing in neutrinoless double beta decay physics. He primarily worked with germanium-based neutrinoless double beta decay experiments named MAJORANA DEMONSTRATOR and LEGEND.

His primary research interests lie in nuclear and particle physics, particularly in physics beyond the Standard Model (BSM). He has expertise in big data analysis and the application of AI/ML for physics analysis.

At ANL, he focuses on the application of AI/ML to future high-energy physics (HEP) and nuclear physics (NP) detectors for real-time data processing. He also works on neuromorphic computing and large-scale simulations.

Selected Publications

• Tupendra Oli, and Majorana Collaboration. ​“Final Result of the Majorana Demonstrator’s Search for Neutrinoless Double-beta Decay in 76Ge.” Phys. Rev. Lett. 130, 062501 (2023) 
• Tupendra Oli, and Majorana Collaboration. ​“Energy calibration of germanium detectors for the Majorana Demonstrator” JINST 18 P09023 (2023)
• Tupendra Oli, and Majorana Collaboration. ​“Experimental study of 13C(α, n)16O Reactions in the Majorana Demonstrator Calibration Data.” Physical Review C 105, 064610 (2022)
• Tupendra Oli, Dmitry Chernyak, Daniel Pershey, Jing Liu, Keyu Ding, Nathan Saunders. ​“Prospect of undoped inorganic crystals at 77 Kelvin for low-mass dark matter search at Spallation Neutron Source.” Eur. Phys. J. C (2020)