Hardware and Software Accelerators for Big Data Machine Learning Workloads - Nitin Nitin (2017)

Food Science Spectroscopy Model Training: Improving Data Efficiency Using Active Learning and Semi-Supervised Learning. - Huanle Zhang; Nicharee Wisuthiphaet; Hemiao Cui; Nitin Nitin; Xin Liu 002; Qing Zhao (CoRR, 2021)

Special report: AI Institute for next generation food systems (AIFS). - Ilias Tagkopoulos; Stephen F. Brown; Xin Liu 002; Qing Zhao; Tarek I. Zohdi; J. Mason Earles; Nitin Nitin; Daniel E. Runcie; Danielle G. Lemay; Aaron D. Smith; Pamela C. Ronald; Hao Feng; et al. (Comput. Electron. Agric., 2022)

Spectroscopy Approaches for Food Safety Applications: Improving Data Efficiency Using Active Learning and Semi-supervised Learning. - Huanle Zhang; Nicharee Wisuthiphaet; Hemiao Cui; Nitin Nitin; Xin Liu 002; Qing Zhao (Frontiers Artif. Intell., 2022)

The AIFS Institute: Building a better food system through AI. - Ilias Tagkopoulos; J. Mason Earles; Danielle G. Lemay; Xin Liu 002; Nitin Nitin; Aaron D. Smith; Tarek I. Zohdi; Stephen F. Brown (AI Mag., 2024)

Enhancing AI microscopy for foodborne bacterial classification via adversarial domain adaptation across optical and biological variability. - Siddhartha Bhattacharya; Aarham Wasit; Mason Earles; Nitin Nitin; Luyao Ma; Jiyoon Yi (CoRR, 2024)