Sushant
Kumar
Gupta.
MCA Graduate & Software Developer based in Bengaluru. Bridging heavy backend logic with intelligent predictive systems.
Education
MCA @ Dayananda Sagar College of Engineering
CGPA: 8.85 — Specialized in Data Structures, OOP & Machine Learning.
Location
BLR
Bengaluru, Karnataka, India
Machine Learning
React.js
Java
Node.js
Python
Technical Expertise
Experiences
TechCiti Software Consulting
Software Developer Intern • Bengaluru
Jun 2025 – Aug 2025
View Certificate
- 01 Contributed to Java-based software development projects following SDLC practices.
- 02 Implemented and debugged application features using OOP principles and core Java.
- 03 Assisted in fixing bugs, improving code quality, and optimizing existing modules.
- 04 Collaborated with senior developers to understand real-world software requirements.
- 05 Used version control (Git) and followed coding standards and documentation practices.
DeepCept AI Private Limited
Junior AI/ML Development Intern • Bengaluru
Nov 2024 – Jan 2025
View Certificate
- 01 Worked on machine learning model development, including data preprocessing and training.
- 02 Applied regression techniques and evaluated models using standard performance metrics.
- 03 Built interactive AI applications using Gradio UI for real-time predictions.
- 04 Assisted in cloud-based deployment of ML models for scalable access.
- 05 Collaborated with team members to test, analyze, and improve model performance.
Major Works
- • Developed an image classification neural network model to detect plant diseases for early mitigation.
- • Preprocessed and trained the model achieved over 95% accuracy.
- • Implemented deep learning techniques for multi-class image classification.
- • Built backend services using FastAPI to serve real-time prediction APIs.
- • Developed a responsive frontend using React.js for visualization.
- • Developed a machine learning model to predict calories burned based on age, weight, heart rate, and duration.
- • Performed data preprocessing, feature selection, and regression analysis.
- • Evaluated model performance using Mean Squared Error (MSE) and R² score.
- • Implemented the solution using Python, NumPy, Pandas, and scikit-learn.
- • Gained insights into key factors influencing calorie expenditure.