Passionate about artificial intelligence algorithms and machine learning. Developing innovative solutions in embedded systems, robotics, and automation with cutting-edge technology.
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Quantitative precision at scale - AI-driven trading system with exceptional performance
Driven by multi-factor models, statistical arbitrage logic, and a deep learning inference engine leveraging 16+ real-time technical signals, CryptOn dynamically allocates margin across long/short hedged positions — optimizing for risk-adjusted return.
Advanced neural networks processing 16+ technical indicators in real-time for optimal trade execution
Sophisticated hedging strategies with dynamic margin allocation for maximum capital efficiency
Millisecond-level response times with continuous market monitoring and instant position adjustments
Combining technical expertise with innovative thinking to create impactful solutions
I am a multidisciplinary engineer specializing in Artificial Intelligence and Robotics Control Systems, with a strong foundation in Python, advanced algorithms, and embedded systems. My technical interests span machine learning, computer vision, deep learning, and model-based control, all converging to build intelligent, autonomous systems. On the AI side, I have developed and deployed advanced LSTM-based predictive models for cryptocurrency and stock market forecasting under my service platform, CryptOn Forecast. These models incorporate techniques such as sequence modeling, feature engineering, and hyperparameter tuning to achieve high-accuracy financial time-series predictions.
On the robotics side, I focus on advanced control and estimation techniques, including State-Space Control, LQR, and Model Predictive Control (MPC) for real-time motion planning. My work integrates sensor fusion and Kalman filtering for precise state estimation in embedded systems, along with ROS 2 and Gazebo for multi-DOF manipulator simulation. I design real-time feedback systems using PID, MRAC, and gain scheduling, and have hands-on experience with NI cDAQ, Delta RMC, and custom actuator feedback systems for aerospace-grade calibration tasks. My GitHub repository showcases neural network implementations with TensorFlow and PyTorch, computer vision pipelines using OpenCV, and ROS-based robotic control environments bridging AI with embedded systems to create robust, real-time mechatronic solutions.
Microcontrollers, Motor Drivers, FPGAs, Arduino, C/C++
PLC Programming, Siemens, OMRON, Robotic Systems
Python, TensorFlow, OpenCV, Deep Learning, Computer Vision
SolidWorks, AutoCAD, Proteus, PCB Design
Professional journey across leading technology companies
•LabVIEW •FPGAs •Position/Torque Control
•Computer Vision •TensorFlow •OpenCV •Deep Learning
•MySQL •HTML •CSS •Electronics •Automation •C/C++
•Embedded Systems •Electronics •TEXA Diagnostic Systems
•Electronics •Automation •OMRON PLC Systems
•Siemens Combustion Turbines •Industrial Systems
Academic journey in advanced engineering and robotics