Souvik Mandal

Software Engineer

Barpeta Road, Assam, India 0+ yrs exp 75 · Very Good

About

Computer Science & Engineering graduate with practical experience in Software Development, Artificial Intelligence, Machine Learning, and Cybersecurity. Successfully designed and developed real-world projects, including an AI-based Voice Deepfake Detection System and a Secure Login Dashboard, while gaining industry exposure through AI/ML and Cybersecurity internships. Skilled in developing efficient, secure, and user-focused applications with a strong foundation in programming, problem-solving, and software engineering. Eager to contribute technical expertise and continuously grow as a Software Engineer in an innovative organization.

Skills & Expertise (15)

Machine Learning Intermediate

7.3/10

0.1

Years Exp

Python Advanced

6.3/10

0.1

Years Exp

CNN Intermediate

6.3/10

0.1

Years Exp

LSTM Intermediate

6.3/10

0.1

Years Exp

Authentication Systems Intermediate

5.3/10

0.1

Years Exp

Network Security Fundamentals Intermediate

5.3/10

0.1

Years Exp

C++ Intermediate

4.3/10

JavaScript Intermediate

4.3/10

HTML5 Intermediate

4.3/10

CSS3 Intermediate

4.3/10

Audio Processing Intermediate

4.3/10

Librosa Intermediate

4.3/10

Git Intermediate

4.3/10

VS Code Intermediate

4.3/10

XAMPP Intermediate

4.3/10

Work Experience

Cybersecurity Intern

NIELIT, Guwahati

Jun 2025 - Jul 2025

Worked on authentication systems and secure login mechanisms. Learned secure coding practices and network security fundamentals. Assisted in implementing security-focused application design. Strengthened understanding of application and system security.

AI/ML Intern

NIELIT, Guwahati

Jul 2024 - Aug 2024

Assisted in developing machine learning models by performing data preprocessing, feature extraction, and model evaluation. Worked with Python and machine learning libraries to understand supervised learning workflows and model optimization. Collaborated on AI projects involving data analysis and feature engineering to improve model performance. Gained hands-on experience in the end-to-end machine learning development lifecycle.