Akhil Muvva

Highly technical Computer Science Engineering student with an 8.2 CGPA and a published IEEE research paper. Expertly bridging the gap between hardware and decentralized software with a specialized focus on Blockchain Security, IoT, and Cybersecurity. Proven experience in auditing smart contracts using Slither/Mythril, performing network reconnaissance with Nmap, and developing autonomous, vision-based IoT systems.

Cybersecurity Intern at Edutantar (2025-09-15 – 2025-11-15)

Executed deep network reconnaissance and security auditing using industry-standard tools.

• Executed deep network reconnaissance and security auditing using Nmap and Wireshark.
• Identified and documented service-level vulnerabilities and open ports within simulated enterprise networks.
• Analyzed packet captures to detect protocol-level security risks and potential network anomalies.

AI/ML Research Intern at Digital Blinc (2025-06-04 – 2025-08-04)

Developed CNN-based deep learning models for image-based disease detection and computer vision applications.

• Developed CNN-based deep learning models for image-based disease detection, achieving high classification accuracy.
• Engineered custom data augmentation pipelines to improve model robustness on diverse medical imaging datasets.
• Researched and applied state-of-the-art computer vision techniques to classify pathological features in real-time.

Bachelor of Technology in Computer Science Engineering – Centurion University (2027)