Machine Learning Development Engineer

VEDANT JAYANT PADOLE

602-***-**** • *******@***.*** • linkedin.com/in/vedant-padole-719114212/ • github.com/VedantPadole1405 SUMMARY

Innovative Software Development Engineer and Machine Learning Specialist pursuing a master’s in computer science at Arizona State University (GPA: 4.0/4.0). Proficient in Web Development, Machine Learning, and Agile methodologies, with a proven track record in leveraging AWS and TensorFlow to deliver high-performance solutions. KEY ACHIEVEMENTS

• Scalable Traffic Management System: Engineered a distributed toll collection and congestion mitigation system, increasing toll revenue by 40% and decreasing congestion by 32%, leveraging YOLOv8 and AWS architecture.

• Uric Acid Detection App: Built an AI-driven smartphone app for medical diagnostics, enhancing detection accuracy by 82% and diminishing diagnostic errors from 11% to 2%

• Drowsiness Detection: Developed a real-time YOLOv5-based model with 15% decreased latency, enhancing road safety in driver monitoring systems.

• Academic Research: Published papers in IEEE and TIJER journals on sentiment analysis and driver monitoring, contributing to advancements in scalable AI applications. EDUCATION

Masters of Science, Computer Science Graduating May 2020 Arizona State University, Tempe, AZ 4.00 GPA

Ira A. Fulton Schools of Engineering

Relevant coursework: Statistical Machine Learning, Information Assurance and Security, Data Mining TECHNICAL SKILLS

Programming Languages: Python, C, C++, Java, JavaScript Distributed System: AWS (EC2, RDS, S3), Azure, Google Cloud, Kubernetes Machine Learning Frameworks : PyTorch, SciKit, Keras, Tensorflow, NLP, GANs, GenAI, LLM, YOLO, SSD Web Development: HTML, CSS, Bootstrap, React, Node.js, Express.js, RESTful APIs, MySQL, MongoDB PROFESSIONAL EXPERIENCE

Persistent Systems Pvt Ltd., Pune, India: Software Engineer Jan 2024 – Aug 2024

• Designed a scalable traffic management system with distributed number plate recognition in a team of 5 testing model on 50,000 vehicles and leveraging YOLOv8 for real-time data processing.

• Achieved 32% congestion reduction through multi-threaded algorithms and AWS-based architecture compared to previous architectures.

• Utilized Agile and Scrum Methodologies for sprint planning, retrospectives, and cross-functional collaboration, enhancing team productivity by 25%.

Tools Web, Nagpur, India: Full Stack Development Intern May 2023 – Sep 2023

• Developed a dynamic web application using React and Node.js, with MongoDB for backend storage, revamping user query processing speed by 8%.

• Optimized CI/CD pipelines on AWS, reducing deployment time by 25% and increased overall development by 20%

• Enhanced system performance through RESTful API integration and streamlined CRUD operations, achieving a 30% reduction in latency

Bio Spectronics, Nagpur, India: Machine Learning Intern Oct 2023 – Jan 2023

• Built an AI-driven smartphone app for uric acid detection, reducing diagnostic errors from 11% to 2%, improving data reliability by 35%.

• Implemented data cleaning pipelines and anomaly detection models to revamp reliability, resulting 10% higher accuracy in diagnostic results

• Deployed application using Kubernetes, enabling containerized microservices and overhauling system scalability and fault tolerance by 20% .

ACADEMIC PROJECTS

Real-Time NLP-Based Disaster Sentiment Classification Fall 2024 – Spring 2025 Collaborated in a team of four to design model for Real-Time Sentiment Classification.

• Attained an 85% classification accuracy by fine-tuning BERT models and reducing false positives from 12% to 8% through advanced topic modeling, enabling more precise semantic understanding of disaster related tweets.

• Enhanced dataset diversity with 50,000 multilingual entries, revamping contextual analysis of informal language and regional variations for scalable global applicability.

• Increased product recommendation accuracy by 15% by integrating real-time customer sentiment analysis, aligning with customer obsession and driving personalized insights. American Sign Language Detection and Translation Fall 2024 - Spring 2025 Led team of four to design and develop a LLM based model for Sign Language translation and prediction.

• Built a web application for real-time sign language interpretation Bi-LSTM and LRCN, achieving a 20% reduction in response time through optimized model architecture and integration with distributed systems for scalability

• Overhauled accessibility by deploying on AWS Heroku and S3, resulting in a 25% increase in user engagement.

• Evaluated model against other benchmarks, achieving 43% higher performance metrics, demonstrating superior accuracy and efficiency over existing solutions and models. Drowsiness Detection and Hypnosis Recognition Fall 2024 - Spring 2025 Collaborated with a team of six to improve the existing model to recognize Drowsiness

• Designed and deployed a real-time driver drowsiness detection system using YOLOv5, improving accuracy by 18% compared to previous models.

• Reduced detection latency by 15%, ensuring high responsiveness in distributed computing environments and leading to a 22% improvement in system reliability and model accuracy.

• Coordinated with front-end team for API integration and optimized backend endpoints, diminishing response time by 35% and ensuring seamless data flow between client and server. CERTIFICATIONS

• Neural Networks and Deep Learning

Issuer: DeepLearning.AI Date: December 2024 Credential ID: 6OD6OFBNSSZJ

• YOLOv7-YOLOv11: Deep Learning Course

Issuer: Udemy Date: November 2024 Credential ID: UC-96651b70-2665-4a65-b943-a7b76a164c60

• AWS Cloud Technical Essentials

Issuer: Amazon Web Services (AWS) Date: December 2023 Credential ID: 6REDBS4QSAHR

• Introduction to Deep Learning & Neural Networks with Keras Issuer: IBM Date: May 2023 Credential ID: 4KZ5DVSD9DPV

• AWS Fundamentals: Addressing Security Risk Specialization Issuer: AWS Date: December 2022 Credential ID: DYHHESPE8UQ4

• AWS Fundamentals: Building Serverless Applications Issuer: AWS Date: December 2022 Credential ID: SDR27ZGUE43B

• AWS Fundamentals: Migrating to the Cloud

Issuer: AWS Date: December 2022 Credential ID: 7KZPE9ANTK33 PUBLICATIONS AND PATENT

• Driver Monitoring Based Drowsiness and Yawning Detection, IEEE Journal

• Effects of Sentiment Analysis for Enhanced Stock Market Predictions, TIJER Journal

• Electronic Component Cutter

• Modern Water Bottle

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