Currently working as an Associate Software Engineer at ServiceNow. Bachelor of Technology Major in Information Technology and Minor in Mathematics from NITK.
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ServiceNow
Data Scientist
June 18, 2026 – Present
TrashBox-testandvalid
June 14, 2022 – June 25, 2022
Dataset of trash objects for waste classification and detection
View ProjectTrashBox-VGG19_model
April 1, 2022 – April 1, 2022
TrashBox-VGG19_model — GitHub repository
View ProjectTrashBox
December 6, 2021 – May 21, 2023
Dataset of trash objects for waste classification and detection
View ProjectBuilding-Damage-Detection-and-Classification-using-Deep-Learning
November 27, 2021 – November 27, 2021
Building-Damage-Detection-and-Classification-using-Deep-Learning — GitHub repository
View ProjectMitigating-Unfairness-and-Bias-in-Cold-Start-Recommenders
November 24, 2021 – November 25, 2021
to study bias and fairness in recommender systems have focused on improving fairness and mitigating bias only in situations and for items where a history of the user profile already exists. In this project, we explore the bias against new items without any feedback history which are added to recommender systems.
View ProjectContext-based-Flagging-of-objects-in-Satellite-Imagery
April 30, 2021 – April 30, 2021
Context-based-Flagging-of-objects-in-Satellite-Imagery — GitHub repository
View ProjectForecasting-CPU-usage-using-LSTM
April 30, 2021 – April 30, 2021
Forecasting-CPU-usage-using-LSTM — GitHub repository
View ProjectFinancial-Time-series-analysis-for-High-Frequency-Trading
April 24, 2021 – August 30, 2021
Financial time-series forecasting has long been a challenging problem because of the inherently noisy and stochastic nature of the market. In the field of High-Frequency Trading (HFT), forecasting for trading purposes is even a more challenging task since an automated inference system is required to be both accurate and fast. In this project, we have implemented a shallow-architecture methodology for the forecasting of financial time-series data, which gives state-of-the-art results. This architecture has been trained and tested on the benchmark Limit Order Book(LOB) FI-2010 dataset, and the corresponding results are compared and analyzed using a variety of measures.
View ProjectAttack-and-Anomaly-Detection-in-IoT-Sensors-and-Sites-Using-Machine-Learning-Approaches
April 9, 2021 – April 9, 2021
Attack-and-Anomaly-Detection-in-IoT-Sensors-and-Sites-Using-Machine-Learning-Approaches — GitHub repository
View ProjectSalient-object-detection-using-MST
July 12, 2020 – August 19, 2021
Salient-object-detection-using-MST — GitHub repository
View ProjectCultural Fit Analysis
The candidate's project portfolio demonstrates a strong initiative and self-driven learning, which aligns well with a culture that values continuous improvement and exploration. The diversity of projects, from financial time-series to waste classification and IoT anomaly detection, indicates a broad interest in applying data science to various domains. The current role as a Data Scientist at ServiceNow suggests a professional alignment with the target role.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are concise, but there is no information on collaboration, problem-solving approaches, or communication style.