Administrative Assistant Clean Energy

Chirag Nagendra

Boston, MA 617-***-**** ******.********@*****.*** linkedin.com/in/chiragnagendra4575 Work Experience

Massachusetts Clean Energy Center (MASSCEC)Boston, Massachusetts Production Tracking System Fellow Jan 2025 - present 1.Analyzed and interpreted extensive data from 20 quarterly cycles using Microsoft SQL Server, providing critical insights to the PTS team at Massachusetts Clean Energy Center and directly influencing data-driven strategic decisions. 2.Developed interactive Power BI dashboards, visualizing KPIs and providing actionable insights. 3.Engineered production tracking systems for clean energy initiatives, improving project efficiency and effectiveness through data analysis and collaboration.

ANAMII Zürich, Switzerland

Lead Full-Stack Developer Key member of ANAMII's Core Development Team Nov 2020 - Nov 2022 1.Led the design and development of a fully responsive front-end that worked seamlessly across all devices, optimizing performance by 70% through techniques like image compression, CSS refactoring, and asynchronous loading. 2.Engineered a VUE-based analytics dashboard, powered by a Node.js backend, to process user interaction data, leading to a 20% surge in user engagement due to statistically-backed UI/UX enhancements. 3.Implemented machine learning algorithms to personalize user experiences and optimize website performance, resulting in a 25% boost in user engagement. Explored cutting-edge AI from OpenAI and Google DeepMind for enhanced analytics.

4.Engineered and deployed deep learning models using TensorFlow and PyTorch for advanced features like natural language processing, driving sophisticated content recommendation and sentiment analysis capabilities. Infosys Mysore, India

Specialist Programmer Web Developer Sept 2019 - Nov 2020 1.Initiated and built scalable web applications using the MEAN stack, improving performance and user engagement. 2.Led front-end development efforts, enhancing website responsiveness and cross-browser compatibility. 3.Automated testing caught 95% of critical web bugs early, boosting user experience and iteration. 4.Integrated web applications with Salesforce CRM, streamlining customer data management and enhancing workflows. 5.Integrated Java modules into web apps, improving efficiency and reducing deployment time by 20%. C-DAC (Center for Development of Advanced Computing) Bangalore, India Research Intern Web Development Intern Feb 2019 - July 2019 Research / Web Development Internship:

1.Enhanced data analysis methods by conducting in-depth research on unsupervised learning techniques, such as clustering and dimensionality reduction for the Karnataka State Funded Project, leading to improved data interpretation and decision-making.

2.Optimized high-dimensional datasets by eliminating redundancies and ambiguities, enhancing data clarity, and boosting analysis efficiency by 30%.

3.Successfully applied dimensionality reduction to extract latent features and enhanced data processing. 4.Leveraged TensorFlow and PyTorch to develop and implement neural network models for predictive analytics on sensor data, improving the accuracy of urban planning forecasts and resource allocation strategies. 5.Developed interactive data visualization dashboards and web applications using the React ecosystem and Next.js, providing intuitive access to complex analytical insights for stakeholders and facilitating collaborative decision-making. Publications

Published research on Biometric and Facial recognition for cardless ATM transactions in prestigious journals: International Journal of Scientific and Engineering Research (IJSER) and International Journal for Applied Science and Engineering Technology (IJRASET). I received departmental recognition and a grant for a top-ranked paper presentation at the IJSER conference in Delhi.

Education

University of Massachusetts, Boston Boston, MA

Master's in Information Science (Machine Learning Major)Jan 2023 - Dec 2024 Skills

Programming Languages: Java, JavaScript, TypeScript, Python, SQL, R, HTML5, CSS3, C/C++, Bootstrap, Mathematics Web & Application Frameworks: React, Angular, Node.js, Vue.js, Next.js, UX design, UX/UI Databases: SQL Server, MongoDB, Firebase, PowerBI, Tableau, Excel Cloud & DevOps Technologies: Docker, Kubernetes, AWS, Salesforce, Cloud CRM, JIRA, Agile, Cloud Computing Development skills: REST API, Full Stack developer, Git, Data structures, Cloud Computing, Gaming, CI/CD, Deep learning, Development Life cycle, Decision Making, cloud computing, Statistics, Azure, NLP, KPIs, Machine Learning, Artificial Intelligence, IoT, Pandas, SEO, web optimization, TensorFlow, Statistics, Business Analytics, Data Science, Data Visualization, Problem-solving, Business Intelligence, Algorithm design, Distributed storage, Troubleshooting, Spark, Oracle, Data Warehouse, computer vision, trade-off

Projects

1) Real-time Image Classification API with TensorFlow Serving

● Model Export: Train Keras image classification model, export in SavedModel format with defined inference signatures.

● TensorFlow Serving Setup: Deploy TensorFlow Serving via Docker, configure to serve exported SavedModel, specify model path.

● API Development: Build web API (Flask/FastAPI) accepting image uploads, preprocessing them for model input.

● Inference Request: API calls TensorFlow Serving (gRPC/REST) with preprocessed image for predictions, parses results.

● Deployment & Scalability: Containerize API and Serving, deploy on cloud (e.g., AWS, GCP) with autoscaling for load. 2) Sentiment Analysis Microservice with PyTorch and TorchServe

● Model Training & Serialization: Train PyTorch sentiment model; serialize it into a TorchScript module (.pt/.pth) for optimized deployment readiness.

● Custom Handler Development: Write a Python custom handler script defining preprocess, inference, and postprocess for text sentiment prediction.

● Model Archive Creation: Package the TorchScript model, custom handler, and dependencies into a .mar file using TorchServe's archiver tool.

● TorchServe Deployment: Deploy TorchServe, often in Docker, registering the .mar file to expose HTTP endpoints for sentiment inference.

● Client Application/Integration: Develop a client to send text to the TorchServe API, receiving real-time sentiment classification responses.

3) AI-Powered Content Recommendation Platform

● Backend AI Training (PyTorch/TensorFlow): Develop and train a recommendation model (e.g., collaborative filtering, content-based) using either PyTorch or TensorFlow for robust backend inference.

● API Layer (TensorFlow Serving/TorchServe): Deploy the trained AI model as a high-performance API endpoint using TensorFlow Serving or TorchServe for efficient, scalable inference requests.

● Frontend Framework (Next.js): Utilize Next.js to build a server-rendered, performant web application, handling routing and data fetching for the user interface.

● Interactive UI (React): Design and implement the user-facing interface with React components, enabling dynamic display of recommended content and user interaction.

● Data Flow & Integration: Orchestrate seamless data flow: Next.js fetches user preferences, sends to AI API, and React displays personalized recommendations from the model's response. 4) Dynamic Personal Portfolio with Next.js & Firebase

● Frontend Foundation (React & Next.js): Developed a blazing-fast, SEO-friendly personal portfolio using React for UI components and Next.js for server-side rendering and routing.

● Robust Development (TypeScript, HTML5, CSS3): Ensured type safety and maintainability with TypeScript. Crafted semantic structures with HTML5 and styled a responsive, modern design using CSS3.

● Content Management (Firebase): Integrated Firebase Firestore for seamless backend content management, allowing easy updates to projects, blogs, or resume sections.

● Deployment & Features: Implemented contact forms and project showcases, then deployed the full-stack application, demonstrating proficiency in modern web development practices.

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