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Senior Product Manager, Mgmt at NVIDIA
Experienced Software Engineer and Technical Program Manager with a 7-year tenure at NVIDIA, demonstrating a strong track record in both technical and leadership roles. Initially specialized as a Deep Learning Engineer in the autonomous vehicles department, developing and optimizing end-to-end lane-following neural networks. Transitioned to the Healthcare team as a Senior Software Engineer before advancing to a Technical Program Management role. Proven ability to collaborate with cross-functional teams of ~20 members, ensuring timely and consistent monthly releases. Skilled in risk identification and mitigation, having successfully managed six month-to-month releases with a 95% on-time delivery rate. Proficient in defining and tracking key performance indicators (KPIs) to drive accountability and continuous improvement in engineering and product teams.
Rutgers University
Master's Degree, Signal Processing and Communications
January 1, 2014 – January 1, 2016
Amrita University
Bachelor's Degree, Electrical, Electronics and Communications Engineering
January 1, 2010 – January 1, 2014
NVIDIA
Senior Product Manager, Mgmt
March 1, 2026 – Present
NVIDIA
Product Manager
September 1, 2024 – Present
NVIDIA
Technical Program Manager
October 1, 2023 – September 1, 2024
NVIDIA
Sr System Software Engineer
January 1, 2020 – May 1, 2024
NVIDIA
System Software Engineer
December 1, 2017 – December 1, 2019
NVIDIA
Deep Learning R&D Engineer
July 1, 2016 – December 1, 2017
Rutgers University
Research Assistant / Graduate Thesis
October 1, 2015 – December 1, 2016
GE Global Research
Research Intern: Statistical Feature Based ROI Selection and Analysis for Tissue Characterization
June 1, 2015 – August 1, 2015
Bengaluru Area, India
Rutgers University
Research Assistant: Tracking Functional Connectivity of Brain in a BCI cursor movement task
January 1, 2015 – December 1, 2015
Rutgers University
Study on Sparse Fourier Transform (SFT)
November 1, 2014 – December 1, 2014
IIIT Hyderabad
A study on Motor imagery EEG data
May 1, 2013 – July 1, 2013
Hyderabad Area, India
Infotech Enterprises IT Services Pvt Ltd ( Infotech IT )
RFID Networks
December 1, 2011 – January 1, 2012
Hyderabad Area, India
Multi-View 3D Reconstruction and Augmented Reality
November 1, 2015 – Present
Multiple views of a static scene are captured using a calibrated camera. For every image pair feature matching is performed using Minimum Eigen Value Algorithm. Triangulation method is employed for 3D sparse and dense reconstruction from every image pair. On the sparsely 3D reconstructed scenes, Bundle adjustment is performed by euclidian distance optimization algorithm. The obtained bundle adjustment result is compared against that of Visual SFM software. All the programming is done on Python and MATLAB platforms. A virtual cube was inserted on the pre-selected plane of a 2D image using OPENCV toolbox in Python.
Automated Artifact Removal of EEG Signals Using DWT and ICA
November 1, 2014 – Present
Developed a fully automated artifact removal algorithm for EEG data. The algorithm successfully identifies and eliminates different kinds of simulated artifacts like eyeblinks, electrical noise and DC shift from the data. Used the Discrete Wavelet Transform (DWT) and Independent Component Analysis (ICA) tools to decompose the signal into components. Further distinguishing statistical features like entropy, kurtosis were calculated for artifact identification. Algorithm was tested by adding simulated noise and the recognition accuracy was 100%.
Undergrauate Thesis - A Study on Blind Source Separation
May 1, 2014 – Present
The thesis involved study of various Blind Source Separation (BSS) techniques like Time frequency BSS (TFBSS), PCA, ICA and SVD. These techniques were tested for various cases such as separating Mother and foetus ECG and separating music from a mixture. The results were compared against each other and important conclusions were drawn. The data from Electro Encephalogram (EEG) was taken and the above discussed methods were used for pre-processing. The results suggest that ICA algorithm is the most robust compared to the others.
Low Cost Waste Sorter Using Eddy Current Separator
November 1, 2011 – Present
Designed a low cost waste sorting machine to sort out magnetic and non-magnetic materials from garbage. The project Won IIIrd prize and a $1000 USD funding at IEEE-IBM SMARTER PLANET CHALLENGE.
Learning Cloud Computing: The Cloud and DevOps
LinkedIn Learning 2
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's background is heavily rooted in academic research and deep technical roles, particularly in signal processing and AI/ML. While the target role is 'Data Analyst', their experience leans more towards research scientist or ML engineer. The projects demonstrate a strong inclination towards complex algorithmic development and scientific inquiry. The transition to product management at NVIDIA shows adaptability and a broader business perspective, but the core technical experience is more aligned with advanced data science or machine learning engineering than a typical data analyst role. The diversity of projects, from 3D reconstruction to biomedical signal processing, indicates intellectual curiosity and a broad technical interest.
Soft Skills & Operational Fit
The candidate's experience at NVIDIA, transitioning from engineering to technical program management and then product management, suggests strong organizational, leadership, and communication skills. Their ability to manage 20+ engineers, implement agile methodologies, and deliver releases indicates operational effectiveness. The research assistant roles and project descriptions also highlight problem-solving, analytical thinking, and presentation skills (e.g., presenting at SFN-2015).