PAVAN CHANDRA

Graduate student in Information Systems with a strong foundation in data analytics, business strategy, and digital communication. Skilled in extracting insights from data using tools like Power BI, Excel, and SQL. Experience includes CRM platforms, academic data projects, and social media analytics. Passionate about transforming data into actionable insights to support business growth.

• Project Estimation of Impurities in Iron Ore Using Machine Learning was published in a book at the International Conference on Soft Computing and Signal Processing.
• Successfully built and maintained a movie-themed social media page for over 5 years, with 150K+ followers on Facebook and 185K+ on Instagram.

• Participated in electronics workshop for interdisciplinary learning.
• Completed 15km OMR student run promoting wellness.
• Volunteered for nonprofit charity activities.
• Organized cultural fests and technical events in college.
• Mentored junior students on career development and academic guidance.
• Participated in blood donation drives and community clean-up programs.

Healthcare Analytics Dashboard 

Developed a full-stack web application to visualize and predict healthcare risks such as diabetes, heart attacks, and lung cancer. Used HTML, CSS, JavaScript for the frontend, Python (Flask) for the backend, and integrated basic machine learning logic for risk prediction. Focused on user experience, interactive visuals, and real-time health data insights.

Task Manager Web Application 

Designed and built a responsive web-based task management app using HTML, CSS, and JavaScript. Features included task categorization, deadline tracking, and a dynamic UI to enhance user productivity and organization.

Estimation of Impurities in Iron Ore Using Machine Learning 

Coordinated and developed a machine learning web app to predict impurity levels in iron ore. Used Python (pandas, scikit-learn) for modeling, Flask for backend integration, and HTML/CSS/JavaScript for UI. Presented at the International Conference on Soft Computing and Signal Processing.

Dynamic Price Prediction for Cabs 

Built a predictive model using real-time cab fare datasets to analyze and forecast price fluctuations. Applied data preprocessing in Excel, implemented logic in Python, and showcased output through custom visual interfaces. Helped uncover pricing patterns and demand trends.

• English
• Hindi
• Telugu

• CRM Tools (Salesforce, HubSpot)
• Jira
• Power BI
• Figma

• Excel Skills for Business: Essentials – Coursera (Macquarie University)
• Supply Chain Foundations – Coursera (Rutgers University)