Chetanpal Sra

Dynamic and results-driven Data Scientist Intern with hands-on experience at Netmax Technologies Pvt. Ltd. Proficient in Python and machine learning, I excel in transforming raw data into actionable insights. Adept at collaborating with teams, I ensure high-quality datasets and impactful visualizations, driving informed decision-making and enhancing project outcomes.

Extracurricular Activities & Sports

• Participated in university-level hackathons at GNDU, including HackerWrath24 (Team Pinkberry) and Hackwrath 2.0 (Team ARcademy), engaging in collaborative coding and skill-based workshops.
• Competed in Inter-School Badminton Tournaments and zonal matches; selected to represent the district team, demonstrating discipline and a strong competitive spirit.
• Completed the NCC 5K Mini Marathon at Guru Nanak Dev University (Oct 2025).
• Recognized with a Certificate of Appreciation by the Punjab State Blood Transfusion Council for voluntary blood donation (Jan 2025).

Seminars & Certifications

• Attended Technology Seminar: "The Future of Memory Chip Technology" by Dr. Gurtej Singh Sandhu (Oct 2025).
• Completed an Environmental Studies Field Visit to Pushpa Gujral Science City (Nov 2023).
• Completed a comprehensive, year-long Personality Development Course (June 2022 – June 2023).

REST API Data Extraction Suite, Python, Requests, RapidAPI, JSON, PrettyTable

• Developing automated utility scripts to query diverse third-party APIs for real-time COVID-19 statistics, OTT platform details, and PAN card verification.
• Engineered secure HTTP GET/POST requests with custom headers, parsed complex JSON responses, and transformed raw data into structured, exportable tabular formats.

MyPass - Secure Password Manager, Python, Tkinter, JSON

• Building a localized, graphical desktop application to securely generate, store, and retrieve complex passwords for various web services.
• Engineered a Tkinter GUI utilizing a grid layout and Canvas widget, while implementing robust messagebox dialogs for user validation, secure save confirmations, and instant credential search retrieval.

Interactive CLI Quiz Application, Python, Object-Oriented Programming (OOP), PrettyTable

• Building a highly customizable and dynamic trivia platform capable of filtering complex datasets based on user preferences for category, difficulty, and question type.
• Developed a fully modular, OOP-based command-line game utilizing lambda functions for robust data filtering and a clean, tabular user interface.

U.S. States Educational Game, Python, Turtle Graphics, Pandas

• Designing an interactive, map-based guessing game to test geographical knowledge while dynamically tracking user progress against a dataset.
• Developed a visual application utilizing a custom background map, processing user input via continuous dialog loops, and dynamically plotting correct state names at precise coordinates while maintaining a live fractional score.

Comprehensive MERN Authentication System, MERN Stack, JWT, Nodemailer

• Implementing a secure, scalable, and standardized user identity management system from scratch across the frontend and backend.
• Engineered a full-stack solution using JWT for secure session management and bcrypt for hashing, providing robust registration, login, protected routes, and essential recovery/verification features.

• Project IDX Certificate, Google Product Lead, 05/24
• Hackathon Participation - Hackwrath 2.0, Team ARcademy, 11/25
• Hackathon Participation - HackerWrath24, GNDU Amritsar, 10/24
• Career Essentials in Generative AI, Microsoft & LinkedIn
• C++ Technical Training Certification, 06/23

• Complex Network Analysis:Determining the most influential node (Ongoing)

Focus:This research project, "Identifying Influential Areas for Air Pollution Control in India: A Novel Approach" is being conducted under the supervision of Dr. Hardeep Singh, Assistant Professor in the Department of Computer Engineering and Technology at GNDU, Amritsar. The core objective of this work is to pioneer a sophisticated methodology to identify and prioritize specific geographical areas in India where airpollution control interventions will yield the maximum positive impact.

Contribution:The anticipated findings of this research are poised to offer direct, practical assistance to policymakers. By providing a clear identification of the most influential and sensitive areas, the project enables the implementation of targeted and cost-effective pollution control strategies. This shift from generic,wide-area mandates to data-informed, surgical interventions ensures that resources (financial, technological,and regulatory) are deployed where they will achieve the maximum environmental return on investment(ROI).

Concise Technical Methodology: Data Validation: Utilizing authoritative data from India’s Central Pollution Control Board (CPCB), including High-accuracy geospatial coordinates and the standardized Air Quality Index (AQI). Network Construction and Centrality measures: Employing Graph Theory to model CPCB monitoring stations as a complex network. Inter-station distances, critical for mapping pollution flow, arecalculated precisely using the Haversine formula, which determines the great-circle distance between twopoints and we apply robust centrality measures to systematically analyze the graph structure and identify influential nodes.