Saikrishnan

About

Computer Science & Engineering student with hands-on experience building data science, machine learning, and full-stack web applications. Active in leadership and community roles, with a strong foundation in Python, ML workflows, and modern web development.

Experience

• Cybersecurity Awareness Volunteer
  WNS Cares Foundation
  Jun 2025 – Jul 2025
• Event Manager
  Club Google
  Aug 2024 – Aug 2025

Education

• Bachelor of Technology
  Lovely Professional University
  Computer Science & Engineering · Jul 2024 – 2028
• 12th / Higher Secondary (Class 12)
  St. Anthony's Public School
  PCM + CS · 2023 – 2024
• 10th / Secondary (Class 10)
  Dr GR Public School
  2021 – 2022

Skills

• SQL
• C
• Python
• Prompt Engineering
• CSS3
• Java
• JavaScript
• Node.js
• Matplotlib
• NumPy
• Pandas
• scikit-learn
• React
• Flask
• Seaborn
• Resource Management
• API Integration Understanding
• HTML5
• Design Systems
• Quantitative Reasoning
• Responsible AI
• Copilot
• Pwa

Projects

• InSync – Dual-Role Cycle Tracker & Partner Support App ↗
  React.js, Firebase (Firestore, Auth, Hosting), Tailwind CSS, Cloud Functions

  Engineered a dual-role menstrual health Progressive Web Application (PWA) to help women track their cycle with personalized workout, nutrition and period-supply recommendations. Designed a Partner Translation feature that converts cycle and comfort information into actionable suggestions, helping partners better understand her needs and respond appropriately. Reached 600+ users within 10 days, with 160+ dynamically served daily tips and an instant mode switch between in-person and long-distance support.

• Sentinel Ledger — Banking Fraud Detection App
  Python (Flask, scikit-learn, Pandas), JavaScript, Chart.js

  Developed a full-stack fraud detection system that flags suspicious banking transactions in real time, combining a trained ML classifier with rule-based risk logic to catch fraud that pure statistical models miss. Trained a Random Forest classifier (150 trees, balanced class weights) with engineered features (amount-to-balance ratio, night-time flag) to handle a 0.89% fraud rate. Launched a live dashboard with 6 Chart.js visualizations and a real-time fraud checker to help identify and explain suspicious transactions.

• Crime Data Analysis — ML Predictive Pipeline
  Python, Pandas, scikit-learn, Matplotlib, Seaborn

  Built a machine learning pipeline to find patterns in crime data and identify useful insights about when and where crimes are more likely to occur. Processed a 50,000+ record dataset using Pandas for automated preprocessing and trained a Random Forest classifier achieving 87% accuracy. Tackled messy, inconsistent raw data by automating the resolution of 6 distinct inconsistency categories, cutting pipeline prep time by approximately 40% and surfacing 5 high-risk factor patterns for further analysis.

• Poopify — Gut Health Tracking PWA ↗
  React, Firebase (Firestore, Auth, Hosting), Recharts, html2canvas

  Architected and launched an account-free gut-health tracking PWA using React and Firebase, designed for quick and frictionless daily tracking. Enabled users to securely save and access their tracking data without creating an account, while adding native sharing, clipboard, and haptic features to provide a smooth, mobile-like experience. Built 7-day health trend visualizations and a shareable “Wrapped”-style summary card, helping the app reach 500+ active users.

Courses & certifications

• Data Science Training & Certification · ICT Academy of Kerala · 2026
• Generative AI Fluency & Essentials · Anthropic & Microsoft/LinkedIn · 2026
• Object Oriented Programming using C++ · Centre for Professional Enhancement, Lovely Professional University · 2026
• Database Management System, Parts I & II · Infosys Springboard · 2026
• Programming using C++ · Infosys Springboard · 2025

⚽ Extracurricular activities

• Event Manager

  Planned and managed 8+ technology events and workshops, including Tech Tussle with 200+ participants, coordinating 15+ volunteers. Helped grow active club membership by 30% over two semesters through event planning, student engagement, and technical activities.

• Cybersecurity Awareness Volunteer

  Conducted cybersecurity awareness workshops for 60+ participants aged 15–55, covering phishing, password safety, and social engineering. Explained safe digital practices to participants with different levels of technical knowledge, making cybersecurity concepts easy to understand and apply.