About Me

I am Tejansh Sachdeva, currently working as a Data Analyst Intern at Bain and Company (BCN). I am a full stack web and app developer with experience in TypeScript, JavaScript, Python, and Flutter.

In my free time, I enjoy learning new technologies and working on side projects. I am also a competitive programmer, constantly honing my skills by solving DSA problems. Additionally, I have a strong interest in system design concepts and enjoy exploring how scalable, efficient systems are architected.

Tejansh Sachdeva

Experiences

Overview of My Professional Journey.

Software Developer Intern

May 2024 - July 2024

Havish M. Consulting

  • Created an Excel add-in "GoToColumn" using TypeScript to let clients access and manipulate columns easily.

  • Utilizes the Office JavaScript API for interacting with strongly-typed Excel objects including worksheets.

  • Developed a system to parse and consolidate bank statement PDFs into Excel using Python and Regex.

  • Increased productivity by reducing manual lookups through replacing Power Query Editor with Python code.

Projects

Here's what I have built throughout my journey.

CodeCrafter

June 2024 - Aug 2024

Github

Website

  • Crafted a robust real-time collaborative platform with integrated chat, coding, and sketching features.

  • Implemented auto-language detection and in-browser code execution using CodeMirror component.

  • Enabled WebSocket communication for instant messaging and real-time notifications on join/leave events and activities, ensuring security and integrity.

Cartero

June 2024 - July 2024

Github

  • User-friendly application for API testing and interaction, offering streamlined workflows for newbie developers.

  • Implemented request history and repeat requests features, making API testing more intuitive.

  • Provided code snippet generation for Axios and Fetch, simplifying coding with ready-to-use templates.

Go to Column AddIn

May 2024 - June 2024

Github

  • Enhanced Excel user experience with advanced column navigation and management, built using Typescript.

  • Significantly reduced time spent accessing columns across spreadsheets by over 50% while boosting accuracy and productivity.

  • Implemented features include hide/unhide, sheet locking, auto-refresh, and column profiling via Excel JavaScript API.

Swapsta

Sep 2023 - Nov 2023

Github

  • Team project where users can exchange items through a request system without involving currency.

  • Developed Add-Item screen ensuring an intuitive and responsive experience to enter item details with images

  • Connected app with Firebase to store the data

PDF Parser

Feb 2024 - Feb 2024

Github

  • Developed a Streamlit application for file upload, text extraction, and conversational querying using an AI chatbot.

  • Text extraction using PyPDF2 and python-docx, text chunking for OpenAI GPT-3.5 model input limitations

  • Designed a user-friendly interface for seamless interaction and improved user experience

Campus Placements Analysis

Oct 2023 - Nov 2023

Research Paper

  • Pinpointed key factors impacting student success, using data visualization libraries and analytics.

  • Analysed patterns linking academics, activities, internships, etc, for better career choices.

  • Achieved an impressive accuracy of 0.81 by implementing advanced ensembling techniques, contributing to enhanced predictive modelling capabilities for student success initiatives.

Clubs Management System

April 2023 - Nov 2023

Github

  • Team project for showcasing university-wide events and handling room booking.

  • Developed user and admin signup/login page and linked it with the backend to store credentials in encrypted form.

  • Developed infinite scroll sponsorship section for enhanced user experience.

AI Image Generation

June 2023 - July 2023

Github

  • Developed a full stack prompt-to-image generation website using React.js OpenAI API.

  • Generates High-Resolution images with a "surprise me" feature for random prompts.

  • Leveraged Cloudinary for image storage, streamlining MongoDB integration.

Research And Publications

Overview of My Research Journey.

Semantic Textual Similarity with Supervised and Unsupervised Learning

Sept 2024 - Nov 2024

Research Paper

  • Developed a hybrid model combining Supervised and Unsupervised Learning approaches for Semantic Textual Similarity (STS) tasks.

  • Utilized SVR, LightGBM, and XGBoost models, alongside feedforward neural networks, to achieve enhanced text similarity predictions.

  • Achieved industry-standard performance with a Pearson correlation of 0.84, Spearman correlation of 0.82, and MSE of 0.73 by leveraging novel ensemble techniques integrating SVR and Neural Networks.

  • Conducted experiments on benchmark datasets (SemEval 2012 Task 6), achieving robust cross-validation results across 5 folds for 24 candidates in 120 fits.

Campus Placements Analysis

Oct 2023 - Nov 2023

Research Paper

  • Pinpointed key factors impacting student success, using data visualization libraries and analytics.

  • Analysed patterns linking academics, activities, internships, etc, for better career choices.

  • Achieved an impressive accuracy of 0.81 by implementing advanced ensembling techniques, contributing to enhanced predictive modelling capabilities for student success initiatives.

Tech Stack

Languages, libraries and frameworks I know and use.

Languages

Front End

In Between

Back End

Tools

C++
Python
HTML
CSS & SCSS
Javascript
Typescript
Dart
Java
Reactjs
Nextjs
CSS-in-JS
TailwindCSS
Flutter
Rest APIs
Websockets
Node.js
Express.js
PostgreSQL
MySQL
Firebase
Redis
Docker
VSCode
Git
Notion
Figma
Aletryx
Tableau