I have done MS in Electrical Engineering, and a Professional Machine learning and Embedded System Engineer specialized and experienced in various machine and deep learning, Artificial Intelligence (AI) and data science projects and have 4+ years of experience in hardware and software development for smart IoT device development and manufacturing.
✅ Experienced in Embedded systems with firmware and software programming of different categories of microcontrollers with embedded C programming and even micro python programming (if supported in some microcontroller) on different microcontroller platforms like RP2040, PIC, STM32 ESP32, etc. microcontroller.
✅Experienced in bare metal embedded system coding, operation mode of cortex Mx Processor, Memory Map, bus Interface, writing linker script, Processor fault analysis and handling, stacks, AAPCS, Implementation of a simple task scheduler using Pendsv and systick and embedded Driver API development
✅Specialized in OpenSTM32 System-Workbench, STM32 CUBE mx, STM32 HAL, Low level Processor specific hardware initialization and Peripheral High- & Low-Level Initialization, developing STM32 HAL Peripheral data handling APIs, UART Data communication, CAN, low power modes and RTC driver Development
✅Specialized in Free RTOS API development for ARM Cortex M processor
✅Specialized in Microcontroller DMA controller internals, Driver development, programming with various peripherals (ADC, GPIO, UART_RX/TX), Multi AHB bus matrix and ARM Cortex M Bus interfaces, MCU Master/ Slave communication over bus matrix and DMA different transfer modes (like M2P, P2M, M2M) and troubleshoot DMA issues
✅Specialized in flashing a given application binary using Bootloader, Flash related configurations like setting up read and write protections for different sectors, Mass erase, Encrypt and Decrypt the firmware sent by the host using AES
✅Specialized in ROM –Uboot-Kernel boot process on Linux-ARM systems and Testing, configuring sub systems of AM335x SOC such as GPIOs, I2C, MMC, boot modes and ARM-board configuration files
✅ Specialized in machine learning with projects including Data preprocessing, and various types of Regression techniques (like Linear, Multiple, polynomial, SVR, Decision Tree, Random Forest etc.)
✅Classification with different methods (K-NN, SVM, Naive Bayes, Decision tree and Random Forest), K- means and hierarchal clustering, Reinforcement learning, Natural Language Processing, Dimensionality Reduction using principal component analysis (PCA) and Linear discriminant Analysis (LDA) in Python and R programming
✅ Specialized in Deep learning with ANN, CNN, RNN, Self-Organizing Maps (SOM), Boltzmann Machines and various Artificial Intelligence Model and projects including Q – Learning, Deep Q – Learning, Deep Convolutional Q – Learning and A3C
✅ Specialized in Data science and Data mining techniques with steps involved visualization, regression and Data preprocessing including data wrangling and error handling