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Vidhan jain

@vidhanjain

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Computer Science (AI) student building production-grade machine learning and full-stack AI systems.

India

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What I'm looking for

I’m looking for a role where I can build and ship production-grade ML/AI systems end-to-end—multimodal pipelines, REST APIs, and responsive app experiences—while learning from strong mentors and contributing to real user impact.

I’m a Computer Science (AI) student at VIT Pune with hands-on experience building machine learning systems, RESTful APIs, and full-stack applications. I’ve delivered production-grade AI solutions—from multimodal inference pipelines to behavioral analytics platforms—using Python, C++, React.js, and PostgreSQL.

In my projects, I engineered a real-time multimodal infant health monitoring pipeline with MFCC-based audio classification and EfficientNet visual symptom detection, reducing diagnostic latency to under 2 seconds and improving end-to-end accuracy by 15% using confidence-score fusion. I also built a crisis-driven stock market simulation platform to analyze behavioral risk exposure, and I’ve proven my drive by ranking Top 25 of 100+ teams at the GDG Cloud Pune AI Hackathon.

Experience

Work history, roles, and key accomplishments

Crisis-Driven Stock Simulation

Behavioral Risk Analytics

Developed a full-stack stock market simulation platform using Python, React.js, and PostgreSQL across 5+ crisis scenarios to analyze user risk exposure and behavioral decision patterns. Created a real-time portfolio tracking and order execution engine with interactive analytics dashboards to visualize volatility impact across user cohorts and surface behavioral finance biases under stress.

Python React JavaScript PostgreSQL Portfolio Analytics Data Visualization

AmberisAI Multimodal Health

AmberisAI

Built a real-time multimodal AI inference pipeline for infant health monitoring, combining MFCC audio classification with EfficientNet visual symptom detection to reduce diagnostic latency to under 2 seconds. Implemented confidence-score fusion and an XAI layer to improve end-to-end classification accuracy by 15% and generate parent-readable health alerts via a Web App.

Python TensorFlow scikit learn Flask Random Forest XGBoost

Education

Degrees, certifications, and relevant coursework

Vishwakarma Institute of Technology

Bachelor of Technology, Computer Science Engineering (Artificial Intelligence)

2024 -

Grade: 8.78 / 10

Activities and societies: Projects: AmberisAI multimodal infant health monitoring; Crisis-Driven Stock Market Simulation for behavioral risk analytics.

Pursuing a B.Tech in Computer Science Engineering (Artificial Intelligence) at Vishwakarma Institute of Technology, Pune. CGPA is 8.78/10.