SYSTEM_STATUS: INITIALIZING...01. ABOUT_ME
I am a Force Multiplier. I view problems through a unique, multi-dimensional lens, enabling me to tackle complex challenges with precision where others see dead ends. My track record demonstrates a consistent ability to not just solve problems, but to ensure that every domain I touch—from startup ecosystems to industrial R&D—flourishes and improves drastically.
From optimizing SLAM algorithms for autonomous agents to architecting scalable cloud infrastructure for construction AI, I bridge the gap between research-grade deep learning and production-ready systems.
SKILL_MATRIX
Computer Vision
Deep Learning
Engineering
02. CAREER_LOGS
Professional trajectory and industrial engagements.
Senior AI Engineer
- Derived and optimized object detection models for construction defect identification, improving 2D-3D localization accuracy.
- Established a complete 360-camera-based Structure from Motion (SfM) product line, ranging from core spatial reconstruction algorithms to automated cloud workflows and 360-degree defect detection.
- Engineered an in-house, customized SLAM system exhibiting extreme accuracy in degenerate conditions and adaptability across highly dynamic environments.
- Orchestrated, designed, and built a state-of-the-art, PTP-synchronized sensor fusion SLAM scanner with sub-1µs inter-sensor latency.
Product Development Engineer
- Developing and managing scalable MLOps pipelines for Observance, an AI-driven construction management platform.
- Creating and integrating advanced automation tools along with next-generation computer vision and sensor fusion algorithms.
Computer Vision Intern
- Orchestrated and built a flexible and robust 'Automated Processing Pipeline Management' system allowing for multiple parallel deployments.
- Reduced cloud resource costs by approximately 40%.
- Redesigned and unified the processing pipeline codebase, providing seamless integration support for various SLAM algorithms (Fast-LIO, PV-LIO, R3live, PointLio).
- Integrated data from diverse RGB cameras and thermal devices into LOAM algorithms.
Deep Learning Intern
- Worked as a full-time research intern to develop cutting-edge deep learning solutions.
- Designed optimized Computer Vision models for object detection and analysis.
- Built efficient methods of interpreting Point-Cloud data and LiDAR-based 3D object detection using Single-stride Sparse Transformers (SST).
- Experimented with Point-Cloud captioning and LiDAR-to-Image generation using LidarCLIP.
Intern - PowerApps & AI
- Designed an automated framework for an existing application as a full-time intern.
- Architected an end-to-end AI-based entry system which increased user interaction time in the app by 3x.
- Utilized company standard methods to perform strategy assessments and implementations.
Community Founder
- Founded AIHub.io, a startup focused on delivering AI solutions to healthcare providers.
- Managed product development and successfully secured three major clients within the first year.
03. BRAIN_DUMPS :: BLOGS
Thoughts, research notes, and technical deep dives.
04. PROJECT_DATABASE
Selected works in perception, planning, and control systems.
Multi-Sensor Fusion SLAM
Real-time synchronization of LiDAR, IMU, and Camera data for robust localization.
3D Point Cloud Segmentation
Deep learning model for semantic segmentation of large-scale 3D scans.
Autonomous Navigation Stack
Path planning (A*) and obstacle avoidance for mobile robots.
Object Detection & Tracking
YOLO-based detection with DeepSORT tracking for dynamic environments.
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