Palagummi Sai Lalith

Personal Information

• 📍 Hyderabad, Telangana, India
• ✉️ [email protected]
• 📱 +91-7032042286
• LinkedIn: linkedin.com/in/lalith-palagummi-5b8874352
• GitHub: github.com/nvidax-sailalith
• GitLab: (https://code.swecha.org/lalithsaipalagummi)

About Me

I am a motivated Computer Science undergraduate at Sreenidhi Institute of Science and Technology (SNIST), pursuing my B.Tech degree and expected to graduate in 2026. I have a strong foundation in software development, machine learning, and web technologies. As a quick learner with a passion for innovation, I enjoy building projects that solve real-world problems.

Education

B.Tech, Computer Science Engineering
Sreenidhi Institute of Science and Technology (SNIST), 2022 – 2026
GPA: 9.4/10

XII, Narayana Junior College, 2022
Telangana Board of Secondary Education — Percentage: 96%

X, Narayana High School, 2020
Telangana Board of Intermediate Education — CGPA: 10.0/10

Skills

Programming Languages

• C, C++, Python, Java, JavaScript, SQL

Web Technologies

• HTML, CSS, JavaScript, React

Tools & Frameworks

• VS Code, Jupyter Notebook, IntelliJ IDEA Ultimate, MySQL

Domains & Concepts

• Machine Learning, Artificial Intelligence, Database Management Systems (DBMS), Data Structures & Algorithms, Web Development

Projects

Story Generator Project

• Developed an AI-powered Story Generator during the AI Hack Days Hackathon at SNIST, Hyderabad.
• Leveraged GitHub Copilot for efficient coding and Gemini for advanced narrative generation.
• Focused on prompt engineering, iterative feedback, and user-centric design to create engaging and coherent stories.

[Early Disease Detection]

• Designed a machine learning model for early detection of heart disease using patient health indicators such as age, blood pressure, and cholesterol levels.
• Applied classification algorithms and evaluated model performance using accuracy, precision, recall, and F1-score.
• Technologies: Python, Pandas, NumPy, Scikit-Learn, Matplotlib, Seaborn, Jupyter Notebook.

[Property Price Prediction]

• Developed a machine learning model to predict property prices in California based on district-level features such as income, number of rooms, and geographical location.
• Utilized linear regression techniques and performed data preprocessing, exploratory data analysis, and model evaluation using MSE, RMSE, and R².
• Technologies: Python, Pandas, NumPy, Scikit-Learn, Matplotlib, Seaborn.

Internships

AICTE Internship – Full Stack Web Development (Oct 2024 – Dec 2024)
Intern • Hyderabad, India

• Developed a responsive website using HTML, CSS, JavaScript, and React.
• Implemented user signup and login process for seamless access.
• Assisted in debugging and optimizing code, reducing load time by 20%.

Internshala Trainings – Machine Learning Training (Oct 2024 – Dec 2024)
Trainee • Online

• Completed an intensive 8-week training covering Introduction to Machine Learning, Fundamentals of Data, Python Programming, and Data Analytics & Visualization.
• Explored supervised (Regression & Classification) and unsupervised (Clustering) learning techniques, gaining practical insights.

Certifications

• Web Full Stack Development — EduSkills Foundation®
• DRONE WORKSHOP — NXT WAVE
• Data Analytics and Visualization Job Simulation — ACCENTURE — Forge
• Solutions Architecture Job Simulation — AWS — Forge
• Machine Learning — INTERNSHALA TRAININGS

Extracurricular Activities

ICNSIET 2025 — Documentation Team

• Collaborated with organizers to develop documentation strategy and templates for official materials.

Feel free to connect with me on GitHub and GitLab to explore my work and contributions!