Computer Science Student Software Developer

Location:

Posted:

June 19, 2026

AKSHITH REDDY PUTTA

Computer Science Student Software Development Enthusiast

+919********* *********************@*****.*** linkedin.com/in/akshithreddy-putta-052886329 Siddipet, INDIA

Summary

Motivated and detail-oriented Computer Science graduate with a passion for innovation and exploring the boundaries of technology. Experienced in

developing real-time and intelligent applications with a strong emphasis on problem-solving, creativity, and user-focused design. Known for being a

quick learner and an adaptable team player, committed to delivering meaningful outcomes in fast-paced environments. Driven by curiosity and a gro

-wth mindset, with a continuous desire to contribute to impactful, real-world solutions.

Education

Malla Reddy College Of Engineering Hyderabad, INDIA

B.Tech – Computer Science Engineering (72 %) 09/2021 - 06/2025

Narayana Junior College Hyderabad, INDIA

Intermediate - MPC (92 %) 07/2019 - 05/2021

Sri vidyarayan Avasa Vidyalam Siddipet, INDIA

SSC (83 %) 06/2018 - 05/2019

Skills

Python C Java(Basic) HTML CSS SQL GitHub - Postman - Swagger - MS Excel

Projects

Lung Cancer Prediction Using CNN (Python)

Developed a secure Python-based application with a CNN + ML pipeline for lung cancer prediction.

Achieved 90–95% accuracy on 1,000 histopathological images using VGG architecture and SVM, cutting analysis time by 40%.

Applied data augmentation, hashing, and graph-based segmentation for efficiency and precise localization.

Implemented a login authentication system (username/password) to ensure secure access.

Enhanced early detection and diagnostic accuracy, contributing to better patient outcomes.

Dark-Side of the Dark-Web Classification Based on Machine Learning

Designed and implemented a Dark Web text classification system using Text CNN with topic modeling weights, achieving higher accuracy and

efficiency compared to traditional classifiers.

Optimized feature extraction by focusing on class-specific keywords, reducing word vector dimensions by ~30–40% and cutting processing

time while improving classification performance.

Validated the model on two real-world Dark Web datasets, demonstrating superior effectiveness in detecting and categorizing Cyber threats.

Certifications

• Certification in IDEATHON-2023, IIC National Innovation Contest and HACKATHON-2023

• Certification in Contentstack for Developers +Luncch -Techsurf

• Certification in WebSite Development Quiz

• Secured 2nd place in District and State Level KABBADI

Languages

English Proficient Hindi Advanced Telugu Native