Likhith Allu-
-
Mudinepalli, Andhra Pradesh
Professional Summary
Bachelor's in Computer Science Engineering and expertise in Java and Python. Proven ability to design, develop, and optimize scalable software
solutions on AWS. Adept at leveraging data structures, algorithms, and cloud technologies to drive product improvements and efficiency gains.
Collaborative team player focused on delivering high-quality, impactful results through continuous learning and modern development practices.
Experience
Blockchain Developer
Metaacrafters | Remote
2023/JUN – 2023/SEP
Reduced gas consumption in existing smart contracts by 15%, saving 1000+ users $5,000 in transaction fees over 3 months and improving
platform performance.
Developed and deployed a decentralized identity solution using Hyperledger Fabric for a consortium of 5 partner organizations, decreasing
identity verification costs by 30% and enhancing data security for 5000+ users.
Projects
2025/JAN – 2025/MAY
Genarative AI for Creating Synthetic Data from Videos
Designed and implemented a GAN-based pipeline using TensorFlow and Python, increasing object detection model accuracy by 30%
compared to training on solely real-world data, impacting 10,000+ model iterations.
Optimized GAN training process by implementing a custom loss function and hyperparameter tuning, achieving a 20% reduction in training
time and a 15% improvement in synthetic image fidelity (FID score).
2024/JUN – 2024/DEC
Object Detection
Developed a YOLOv5 object detection pipeline using PyTorch, enhancing detection accuracy by 15% on a dataset of 10,000+ images through
optimized hyperparameter tuning and custom loss function implementation.
Imbalance issues using a focal loss function and data augmentation techniques, resulting in a 20% improvement in F1-score for minority
classes during object detection, enabling more accurate event classification.
2023/SEP – 2024/JAN
Sentimental Analysis for Product Review
Built a sentiment analysis model using BERT and TensorFlow, improving accuracy by 15% over existing solutions in classifying product
reviews across a dataset of 1000+ entries, improving customer insights.
Implemented a scalable data pipeline with Apache Kafka and Spark to process real-time product reviews, reducing latency by 40% and
enabling immediate identification of negative feedback trends within 15 minutes.
Refined the sentiment analysis algorithm using hyperparameter tuning and feature engineering, leading to a 20% reduction in processing time
while maintaining accuracy and decreasing computational costs by 10%.
Certifications
2025/JUN
AI Engineer
Oneroadmap
2024/JUL
Introduction to Cybersecurity
Cisco
2023/JUN
Blockchain Technology using Ethereum and Polygon
Metacrfters
Skills
Java
Python
AWS Cloud
SQL
Data Structures and Algorithms
JavaScript
TensorFlow
PyTorch
API Development
Scalable Systems
Education
Chandigarh University
Bachelor's of Engineering in Computer Science
2021/08 – 2025/05
