Software Engineering Machine Learning

Siya Singh

•602-***-**** • ********@***.*** •linkedin.com/in/siya-singh-01asu/

EDUCATION

Master of Science in Software Engineering May 2026 Arizona State University, Tempe, AZ GPA: 3.78

Coursework: Algorithms, Foundation of Software Engineering, Software Testing, Knowledge Representation Bachelor of Engineering in Computer Science May 2024 Mahatma Jyotiba Phule Rohilkhand University, INDIA GPA: 3.72 Coursework: Data Structures,Artificial Intelligence, Data Mining, R programming TECHNICAL SKILLS

Programming & Development: Python, Golang, Java, JavaScript, HTML5, CSS3, C/C++, R, Angular, C#, SQL, jQuery Frameworks: ReactJS, React Native, Docker, REST APIs, Agile, Backend, Compliance, Fraud Detection, Data Science, Machine Learning, Pytorch, Keras, State Management, front-end, Software Development Life Cycle, Lambda, NodeJS, Web Development Tools & Collaboration: Linux, UNIX, Command Line Interface (CLI), DynamoDB, MySQL, Oracle, Git, Jira, Unit Testing, AWS, Azure, GCP, Team Player, Computer Vision, TypeScript, User Interface, Video Editing, Front-End, Full-Stack, UI design, Web Services, SQL, WPF

PROFESSIONAL EXPERIENCE

Data Analyst Intern: Indian Institute of Technology Ropar, INDIA June 2023 - April 2024 Biodiversity Sensor Project

● Led development and deployment of an AI-powered bee detection system using a YOLO-based model in AWS SageMaker to identify 3 bee species in real time across 7 countries.

● Managed a centralized biodiversity data repository of bee images and weather data, utilizing AWS S3 and Azure Data Lake.

● Reduced detection time from 10 minutes to 100 seconds per frame by optimizing the YOLO model with an expanded dataset.

● Preprocessed and cleaned weather data, reducing errors by 10%, improving accuracy of predictions.

● Achieved 96% accuracy in identifying peak daytime pollination activity using SVM regression delivering first use case. Python Software Developer Intern: IIT Kanpur, INDIA June 2021 - August 2021 E-Learning Website

● Assisted in development of automation software with Python and Django, enhancing operational efficiency and saving 20 hours of manual work each week.

● Collaborated with 5 software engineers to design and test application procedures using Pytest, increasing test coverage by 12%.

● Regularly shared biweekly progress updates and engaged in discussions for upcoming project plans. PROJECTS

Sign Language Detection to Regional Text Conversion November 2024 - May 2024

● Spearheaded creation of a Sign Language to Regional Text Conversion system with a 1000-image dataset.

● Developed real-time sign recognition system integrating visual input with NLP-based regional language output, accomplishing a fine-tuning accuracy of 96.84% and a testing precision of 93.14%.

● Integrated a new user-friendly interface, resulting in a 30% increase in average session duration and a 20% improvement in user retention rates.

● Employed CNNs for gesture classification and built a dynamic Django interface for live text rendering. License Plate Detection using YOLO and text extraction app May 2023 - August 2023

● Collected and labeled 1,500 real-time license plate images using a Python-based GUI (PyQt) to streamline parking management at MJPRU.

● Enhanced dataset by preprocessing images, adjusting brightness, and rotation to include different variations.

● Trained a YOLO model in TensorFlow 2.8 to detect license plates, passing the Region of Interest (ROI) to an OCR tool for text extraction.

● Developed a Flask web app to extract and display license plate text, including detected Region of Interest(ROI).

● Attained a 98% accuracy rate in license plate detection and 93% accuracy in character recognition. Malware Detection and Mitigation using HoneyPots May 2021 - July 2021

● Initiated and deployed TelecomPot (TPot), an open-source honeypot, to distinguish and mitigate server attacks.

● Analyzed 54 features and built models using machine learning algorithms. PUBLICATION

Pawan Kumar, Siya Singh, Durgesh Kumar Sharma, & Sudhir Kumar; Theoretical investigation of gas sensing properties of a monolayer gallenene: First-principles insight, Materials Today Communications; Volume 40, 109268, (2024) https://doi.org/10.1016/j.mtcomm.2024.109268

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