Pratyush Murmu

CSE UG IGIT Sarang’28 || Front-End Development || SSoC’26

Jagatsinghpur, Odisha, India

About

I'm a second-year undergraduate in Computer Science in Indira Gandhi Institute of Technology, Sarang.I'm passionate about building a strong foundation in programming and exploring the vast world of technology. I've completed C programming and am currently learning Java fundamentals, while also exploring various domains like web development, data structures, and more to find my true interest. I enjoy problem-solving and continuously seek opportunities to learn, build projects, and collaborate with like-minded peers. I'm open to projects and communities where I can contribute, grow, and gain real-world experience. Let's connect and learn together!

Experience

  • Contributor at Social(Formerly Script Foundation)
    Jun 2026 - Present · 2 mos

    Selected as a contributor for Social Summer of Code (SSoC'26), collaborating on real-world production codebases, implementing frontend optimizations, and managing end-to-end Git workflows across open-source repositories.

  • Core Programming Member at ROBOTICS SOCIETY IGIT SARANG
    Mar 2026 - Present · 5 mos

  • Member at Codex Crew
    Mar 2025 - Present · 1 yr 5 mos

  • AI-ML Intern at Central Tool Room & Training Centre (MSME) Government of India
    Jun 2026 - Jun 2026 · 1 mo

    Successfully completed one month intensive AI/ML industry training and internship program focused on practical machine learning pipelines, deep learning neural networks, and computer vision architectures. Key Contributions & Technical Milestones: • Built and deployed a functional Face Recognition Attendance System using Python, OpenCV, and Haar Cascade classifiers for real-time image capture, processing, and identity verification. • Conducted rigorous data cleaning, handling missing variables, resolving dimensional mismatches, and structuring image datasets to ensure high-accuracy model training. • Developed deep learning models using Keras and TensorFlow to solve complex supervised and unsupervised classification problems. • Implemented end-to-end data pipelines using standard Python libraries (NumPy, Pandas) for dataset consolidation, feature engineering, and robust preprocessing. • Engaged in direct technical mentorship under senior industry experts to translate core theoretical ML algorithms into scalable code.