Ashwin Chavda

AI Researcher

Bhuj, Gujarat, India8 mos experience

Key Highlights

Proficient in Machine Learning and Data Engineering.
Hands-on experience with AWS and data-driven projects.
Strong problem-solving mindset with collaborative work ethic.

Stackforce AI infers this person is a Data Scientist with expertise in Machine Learning and Smart City Solutions.

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Skills

Core Skills

Machine LearningData Engineering

Other Skills

AWSAnalytical SkillsC (Programming Language)C++Cascading Style Sheets (CSS)Cloud DeploymentCommunicationComputer NetworkingCybersecurityData AnalysisData CollectionData PreprocessingEngineeringEnglishEthical Hacking

About

I'm a Data Scientist with a strong foundation in Machine Learning, Data Analytics, and Statistical Modeling. I’ve completed my B.Tech in Information Technology from Silver Oak University, where I cultivated a passion for solving real-world problems using data. I’m skilled in Python, C++, Java, Algorithms, and AWS, with hands-on experience in building ML models, working on data-driven projects, and turning insights into action. Alongside my technical growth, I’ve earned certifications in public speaking, leadership, and ethical hacking — reflecting a well-rounded and proactive learning approach. 🔍 What I bring: Machine Learning model development & evaluation Data preprocessing & visualization (Pandas, NumPy, Matplotlib) Experience with tools like Scikit-Learn, Jupyter, and AWS services Strong problem-solving mindset and collaborative work ethic I’m excited to work on challenging ML problems that create meaningful impact. Let’s connect if you're looking for someone who combines technical expertise with a curious, growth-focused mindset.

Experience

Softvan pvt ltd | a sahana system group company.

Machine Learning Engineer

Nov 2024 – Apr 2025 · 5 mos · Ahmedabad, Gujarat, India · On-site

System Architecture Design: Designed the overall architecture of the SMTS using modular components such as traffic sensors, control systems, and cloud data processing.
Data Collection & Preprocessing: Collected simulated traffic data from urban intersections and performed preprocessing for model training.
Machine Learning Integration: Developed and trained models to predict traffic congestion and dynamically adjust traffic signal timings.
Image Processing Module: Implemented basic image recognition (via OpenCV) to detect vehicle density at intersections.
Cloud Deployment: Deployed key components on AWS for remote access and real-time scalability.
Team Collaboration: Coordinated with team members for backend integration, documentation, and performance testing.
Report Writing: Contributed significantly to the formal academic report, covering technical design, problem analysis, and evaluation metrics.

Machine LearningData CollectionData PreprocessingCloud DeploymentImage ProcessingData Engineering