ProfessorsProfessors of Purdue UniversityNimish Awalgaonkar

Nimish Awalgaonkar

Purdue University

H-index: 6

North America-United States

About Nimish Awalgaonkar

Nimish Awalgaonkar, With an exceptional h-index of 6 and a recent h-index of 6 (since 2020), a distinguished researcher at Purdue University, specializes in the field of Machine Learning, Bayesian Statistics.

His recent articles reflect a diverse array of research interests and contributions to the field:

Bayesian Methods for Learning and Eliciting Preferences of Occupants in Smart Buildings

Surrogate-based sequential Bayesian experimental design using non-stationary Gaussian Processes

Efficient learning of personalized visual preferences in daylit offices: An online elicitation framework

DEEVA: a deep learning and IoT based computer vision system to address safety and security of production sites in energy industry

Nimish Awalgaonkar Information

University	Purdue University
Position	Graduate Student Mechanical Engineering Department
Citations(all)	195
Citations(since 2020)	152
Cited By	112
hIndex(all)	6
hIndex(since 2020)	6
i10Index(all)	6
i10Index(since 2020)	6
Email	Access Email
University Profile Page	Purdue University
Google Scholar	View Google Scholar Profile

Nimish Awalgaonkar Skills & Research Interests

Machine Learning

Bayesian Statistics

Top articles of Nimish Awalgaonkar

Title	Journal	Author(s)	Publication Date
Bayesian Methods for Learning and Eliciting Preferences of Occupants in Smart Buildings		Nimish Awalgaonkar	2022
Surrogate-based sequential Bayesian experimental design using non-stationary Gaussian Processes	Computer Methods in Applied Mechanics and Engineering	Piyush Pandita Panagiotis Tsilifis Nimish M Awalgaonkar Ilias Bilionis Jitesh Panchal	2021/11/1
Efficient learning of personalized visual preferences in daylit offices: An online elicitation framework	Building and Environment	Jie Xiong Nimish M Awalgaonkar Athanasios Tzempelikos Ilias Bilionis Panagiota Karava	2020/8/15
DEEVA: a deep learning and IoT based computer vision system to address safety and security of production sites in energy industry	arXiv preprint arXiv:2003.01196	Nimish M Awalgaonkar Haining Zheng Christopher S Gurciullo	2020/3/2