Experience
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years shipping production AI & full-stack systems — Wipro, DashClicks, SUNY Buffalo research.
SYS·EXP · STATUS: ACTIVE
GitHub
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public repos
LeetCode
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problems solved
npm
grapesjs-advance-components
published · open source
Projects
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built & deployed →
The Human
Vaibhav Bansal
the one FRIDAY works for →Status
Open to opportunities
featured projects
Disaster Response AI Copilot
Crypto Trade Prediction
Heart Disease Prediction with Generative AI
Car Price Prediction — MLflow + Kafka + Debezium
Data Science Salary Prediction Platform
Realtime Logs Processing — Airflow + Kafka + Elasticsearch
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Skills &
Expertise
From production AI systems to scalable full-stack apps — I work across the entire product lifecycle, from design through deployment.
Obstacle Avoidance Using Stereo Vision and Depth Maps for Visual Aid Devices
Proposed an integrated real-time obstacle detection framework for visually impaired users, combining dual CCD stereo cameras with ultrasonic sensors to produce dense depth maps via disparity estimation. The algorithm categorises 3D point vertices into near/far zones — ultrasonic handles close-range hazards (<2 m) while stereo vision covers mid-to-long range. A Raspberry Pi processes frames on-device; alerts are delivered through a buzzer, voice module, and SMS via GPS co-ordinates. The system overcomes the depth-blindness of monocular approaches and achieves reliable detection in both indoor corridors and outdoor environments. Published June 2020 in Springer Nature · SN Applied Sciences, Vol. 2, Issue 6, Article 1131. DOI: 10.1007/s42452-020-2815-z.
Year
2020
Venue
Springer Nature
Domain
Deep Learning · NLP
ORCID
0000-0002-5433-0385