Amitash Nanda

Amitash Nanda

Ph.D. Student

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Experience

Lawrence Berkeley National Laboratory (LBNL)

Graduate Student Research Intern

📍 Berkeley, CA, USA

📅 June 2024 – Present

📌Responsibilities:

  • Worked as a Graduate Student Research Intern with 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.
  • Currently, working voluntarily on refinements of developed novel algorithms and generating results with real-time experimental data.

📜Key Contributions:

  • Expanded the current state of load-balancing algorithms in AMReX by investigating the parallelization of a brute force algorithm, a novel hybrid load-balancing algorithm combining SFC and Knapsack, and an improved SFC bisection strategy using the painter’s algorithm.
  • Statistically compared the efficiency and time to identify the best use cases of these algorithms.
  • Submitted the work to the ACM PEARC (Practice & Experience in Advanced Research Computing) conference. Additionally, creating 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:

  • Analyzing large biological datasets to identify Boolean relationships between genes in tissues across different organs.
  • Designing computational approaches to accelerate the application of AI and Data Science in pathology and drug discovery.
  • Developing multimodal approaches to analyze spatial transcriptomics data, predicting cell trajectory, generating biological hypotheses, and identifying biomarkers.
  • Developing fine-tuning strategies and optimization methods for neural networks and transformer-based models, enhancing performance in vision and language-related tasks.

🧠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:

  • Performance Optimization: Improved query efficiency by leveraging the OFS Primary Index (PI) for local aggregation and join capabilities.
  • Automated Framework: Developed an automated framework that includes Data Generation, Query Generation, and Test Run functionalities to generate queries simulating diverse data scenarios (bad, mixed, and good) by inserting 1 billion rows into the OFS.
  • 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, directly reporting 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 and improving overall testing accuracy.

🧠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