Ojas Pradhan PhD | Data Science for Buildings


I am a doctoral researcher in the Building Science and Engineering Group (BSEG) led by Professor Jin Wen at Drexel University.

My research interests include application of machine learning, big data tools and timeseries analysis to develop innovative AI-based solutions to address environmental challenges and promote sustainable practices. My current work focuses on developing data-driven strategies to optimize performance and control of smart Grid-interactive Efficient Buildings (GEBs).



June 2023 - Succesfully defended my PhD Thesis titled A Dynamic Bayesian Networks Framework for Data-Driven Fault Diagnosis and Prognosis of Smart Building Systems. More details here.

May 2023 - Nomiated for Drexel University's 2023 Research Excellence Award for completing creative and innovative research with significant impact in the field

April 2023 - Our review paper on data-driven Fault Detection and Diagnostics (FDD) is published in Applied Energy. This paper was a collaborative effort of an international team of around 20 experts from ANNEX 81 (Data-Driven Smart Buildings) project. More details on Drexel team's contirbutions can be found here.

March 2023 - Invited to showcase my ongoing research at the 2023 Green Tech Trends hosted by World Technology Partners - a series of sustainability 'chats' from participants across the world to discuss smart engineering solutions

July 2022 - Presented our paper Lagged-kNN Based Data Imputation Approach for Multi-Stream Building Systems Data at the 2022 Herrick Conferences held in Purdue University

May 2022 - Awarded the Linda Latham Scholarship to attend the 2022 ACEEE Summer Study on Energy Efficiency in Buildings providing an excellent opportunity to interact with energy efficiency experts from around the world and acquire new research ideas

April 2022 - Invited as a PhD Fellow to attend the FoBI Workshop and present during the Durham School PhD Symposium held in University of Nebraska-Lincoln (UNL)

November 2021 - Presented our paper Dynamic Bayesian Network-based Fault Diagnosis for ASHRAE Guideline 36 at the 1st ACM International Workshop on Big Data and Machine Learning for Smart Buildings and Cities held as part of BuildSys'21

June 2021 - Presented our paper Dynamic Bayesian Network for Fault Diagnosis at the 2021 ASHRAE Virtual Conference

July 2020 - Presented our paper Development and Validation of a Simulation Testbed for the Intelligent Building Agents Laboratory (IBAL) using TRNSYS at the 2020 ASHRAE Virtual Conference

January 2020 - Received the ASHRAE Graduate Student Scholarship - Presented by ASHRAE Philadelphia Chapter

March 2019 - Received the ASHRAE Undergraduate Student Scholarship - Presented by ASHRAE Philadelphia Chapter

December 2018 - Attended the 2019 ASHRAE Winter Conference held in Atlanta, Georgia - Sponsored by ASHRAE Philadelphia Chapter

March 2018 - Received the Sustainable Energy Fund Scholarship to attend the 2018 Energypath Conference held in DeSales University - Presented by Sustainable Energy Fund