Experience

Lawrence Berkeley National Laboratory (LBNL)

Graduate Student Research Assistant

📍 Berkeley, CA, USA

📅 June 2024 – May 2025

📌Responsibilities:

• Worked as a Graduate Student Research Assistant at the National Energy Research Scientific Computing Center (NERSC), focusing on load-balancing in high-performance computing platforms.
• Collaborated closely with the AMReX (a block-structured adaptive mesh refinement (AMR) software framework) development team to investigate the current state of load-balancing algorithms.
• Worked voluntarily on refinements of developed novel algorithms and generated results with real-time experimental data.

📜Key Contributions:

• Expanded the current state of load-balancing algorithms in AMReX, parallelized a brute-force approach, developed a hybrid SFC-Knapsack and improved SFC bisection strategy using painter’s, achieved faster run-time, and 99.8–99.9% balanced efficiency at scale.
• Statistically analyzed the efficiency and runtime of these algorithms for sizes up to 512 ranks. Knapsack combined with painter’s achieved highest efficiency ranging 99.8–99.9%, while SFC with painter’s algorithm demonstrated faster runtime.
• Paper accepted at ACM PEARC (Practice & Experience in Advanced Research Computing) conference. Additionally created a pull request to incorporate the developed algorithms into the AMReX GitHub repository.

🧠Skill Sets:

• C++, Python, MPI, OpenMP, Algorithms, Distributed Learning, Dynamic Load Balancing, High-Performance Computing, Parallelization

Boolean Lab

Graduate Research Assistant

📍 San Diego, CA, USA

📅 September 2021 – Present

📜Key Contributions:

• Computational Biology: Analyzing large-scale biological datasets to identify Boolean relationships between genes and developing computational methods to accelerate the use of AI in pathology and drug discovery.
• AI Integration and Model Optimization: Developing multimodal approaches, foundation models, and fine-tuning strategies for vision and language-related tasks to generate biological hypotheses and identify biomarkers.

🧠Skill Sets:

• Python, Pandas, Open CV, NLP, PyTorch, TensorFlow, Linux, Keras, Theano, Kubernetes, GitHub, Hugging Face, Jupyter, AI/ML, Data Science, Computer Vision, LLM, Bioinformatics

Teradata

Software Engineer Intern

📍 San Diego, CA, USA

📅 June 2023 – September 2023

📌Responsibilities:

• Worked as a Software Engineer Intern with the Optimizer Development Team and contributed to optimizing Teradata's Object File Storage (OFS) system in Native Object Storage (like S3 for AWS).
• Researched, Designed, and Developed an automated framework for query performance testing and enhancing query execution efficiency.
• Collaborated with database engineers to ensure seamless integration with large-scale enterprise applications.

📜Key Contributions:

• Query Optimization: Leveraged Primary Index (PI) for efficient local aggregation and join capabilities to enhance Teradata’s Object File Storage (OFS) system and achieved 20% query cost reduction. Optimized data scenarios for 1B rows.
• Automated Framework: Developed an automated framework for data and query generation, simulated good and bad cases for DBQL performance benchmarking. Generated 512 objects with 700M rows (good case) and 233 objects with 48M rows (bad case).
• Benchmarking & Analysis: Evaluated system performance using key metrics such as Actual Cost and NOSFile read count to assess cost-effectiveness of OFS PI table usage.

🧠Skill Sets:

• Python, SQL, Docker, Teradata Software Systems (Optimization Engine, Databases, Object File Storage, Basic Teradata Query (BTEQ), Database Query Log (DBQL))

Teradata

Research Intern

📍 San Diego, CA, USA

📅 June 2022 – September 2022

📌Responsibilities:

• Worked as a Research Intern with the Technology Innovation Office (TIO) team and directly reported to the Engineering Fellows and Directors.
• Contributed to the proof-of-concepts and developed predictive models for platform configuration resource usage by analyzing Telemetry data from the Teradata Telemetry Collection Agent (TCA).

📜Key Contributions:

• Performance Optimization: Developed predictive models to forecast platform configuration resource usage by analyzing Telemetry data from the Teradata Telemetry Collection Agent (TCA), improving operational efficiency.
• Automated Framework: Designed and implemented an automated pipeline integrating data retrieval from TCA using REST API, data- preprocessing, and predictive modeling, streamlining the platform monitoring and forecasting process.
• Performance Assessment: Evaluated system performance using key metrics such as Mean Squared Error (MSE), R-Squared, and computational efficiency, ensuring robust model deployment and scalability.

🧠Skill Sets:

• Python, SQL, Jupyter, REST API, Flask, Supervised Learning, Statistic Modeling, Data Visualization, GitHub, Teradata Software Systems (Optimization Engine, Databases, Basic Teradata Query (BTEQ), Database Query Log (DBQL))

Accenture

Software Engineer II

📍 Bengaluru, KA, India

📅 September 2020 – August 2021

📌Responsibilities:

• Worked as a Software Engineer at Accenture Technology Labs (Application Engineering R&D) and contributed to the research, design, and development of software applications and frameworks to meet business processes.
• Responsible for being seen as a highly differentiated technology expert in robotics software development, application development and testing, machine learning, and automation. Accountable for leveraging these skills to deliver high-quality outcomes.

📜Key Contributions:

• Application Development: Designed and developed a novel robot software testing application (chaosRobo) utilizing chaos engineering principles to simulate real-world scenarios. Led the first-phase prototype development as part of a three-member team.
• Automated Framework: Contributed to backend GUI design, integrated Gazebo-ROS functionalities, and successfully deployed the system on AWS S3 and RoboMaker, enhancing robot simulation and testing efficiency.
• Performance Optimization: Implemented machine learning-based analytics in chaosRobo to assess system robustness, reducing failure detection time by 30% and improving overall testing accuracy by 20–25%.

🧠Skill Sets:

• Python, C++, ROS (Robot Operating System), Gazebo Open Source 3D simulator, Tkinter, PyQt, AWS RoboMaker

Accenture

Software Engineer I

📍 Bengaluru, KA, India

📅 July 2019 – September 2020

📌Responsibilities:

• Worked as a Software Engineer in Accenture Industry X Services, contributing to the design, development, automation, and testing of client-specific projects within the Product Lifecycle Management (PLM) team.
• Collaborated in a cross-functional and multifunctional team, developing an automation tool for Airbus Product Lifecycle Management functionalities using image and text-based recognition.
• Responsible for application development, customization, integration, deployment, testing, and automation, ensuring high-quality deliverables and system efficiency.

📜Key Contributions:

• Bedrock Automation Asset Development: Automated end-to-end user stories for Airbus PPR scenarios using image-based and text-based recognition. Developed a new testing methodology and integrated it into the 3D Experience software.
• Automated Framework: Worked on customization and integration using RESTful web services and hybrid app development using Apache Cordova, enhanced cross-platform functionality and user experience.

🧠Skill Sets:

• C++, Java, 3DEXPERIENCE Platform Dassault Systemes, CAA V6 for CATIA, REST API, HTML/CSS, Javascript, Apache Cordova, CI/CD, Jenkins, Selenium