Hi, my name is Abhishek Joshi
I'm a Software Engineer.

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About Me

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Expertise in full-stack development. Quick to master new technologies, with industry experience in projects across healthcare, e-commerce, and research. Adept at building high-performance, scalable applications while optimizing workflows and collaborating across teams to deliver seamless user experiences.

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Experience

Josh Technology Group

Front End Developer at Josh Technology Group

Developed front-end applications with TypeScript, React, MUI, SCSS, and API integration. Worked with Nx for monorepo management and AngularJS for maintaining legacy healthcare code. Utilized Sentry for error tracking, Jira for issue management, and integrated FHIR standards. Optimized performance and build processes using Webpack, Vite, and RTK Query. Collaborated on full-stack features with Angular, .NET, and MySQL, focusing on efficient data management and API integration. Improved code maintainability and deployment through SDK cleanups and config refinements, while ensuring high-quality UI updates and feature research.

Cynoteck Technology Solutions

Full Stack Developer Intern at Cynoteck Technology Solutions

Contributing to the provision of Cloud and CRM services, aiding businesses in optimizing their operations and enhancing customer relationship management. Developing full-stack solutions utilizing React.js for the frontend and MongoDB database with Express.js for the backend.

HERE Technologies

Web Scraping Intern at HERE Technologies

Conducting extensive web scraping using Python Scrapy to extract and transform data into GeoJSON format for enhanced geographical data representation. Effectively utilizing Trello’s Kanban boards and Slack for seamless stakeholder collaboration and Agile project management.

KEK

Grid Computing R&D Intern at KEK

Collaborating with Brookhaven National Laboratory and Deutsches Elektronen-Synchrotron as a Belle II intern. Performed a feasibility study evaluating LLMs and their integration in BelleDIRAC for providing summarization of scheduled jobs. Incorporated python scripts using basf2 and gbasf2 in a command line linux environment. Utilizing GitLab for seamless CI/CD, optimizing development workflows.

Projects

Intrusion Detection System

Currently developing a system that detects and prevents cybersecurity threats such as DDoS attacks, malware, and unauthorized access. Use machine learning algorithms to identify patterns and anomalies in network traffic.

Nextron Electronics

This project is a modern e-commerce platform built with React.js, featuring Redux Toolkit for state management, React Router for navigation, and Razorpay for secure payments. The backend, developed with Express.js and a MongoDB database, ensures scalable data storage and retrieval. REST API endpoints enable seamless product listing and filtering, offering an optimized and immersive user experience.

SummaEase

Developed a comprehensive summarization system that can efficiently extract key insights and valuable information from both written text and spoken language inputs. The system utilizes state-of-the-art large language models (LLMs) and natural language processing (NLP) techniques to generate high-quality summaries. We are developing a groundbreaking system that leverages the potential of large language models (LLMs) to revolutionize how people interact with information.

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RealEstimate

This project compares house price prediction using machine learning algorithms: Regression (including Lasso and Ridge) and Random Forest. The analysis involves data cleaning and model training with cross-validation. Linear Regression offers interpretability, while Random Forest excels in capturing complex data relationships, achieving superior accuracy. Future work entails exploring advanced algorithms and optimizing parameters to enhance predictive robustness and performance.

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Net-Route

This Java project implements various algorithms (Dijkstra's, Bellman-Ford, A*) for finding shortest paths in a network represented by nodes connected with edges of different metrics (cost, latency, bandwidth). The project reads network data from a CSV file, filters active connections, and allows users to choose an algorithm and metric for path computation. It then outputs paths and optionally their total metric values to another CSV file. This tool facilitates network analysis and optimization based on user-defined criteria, supporting decision-making in network planning and management.

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Contact

Interested in working together? Let's connect! I'm currently open to job opportunities and collaborations in AI, ML, and software engineering.

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