About

Mayank Bhatia is a creative and results-oriented software engineer with over 3 years of experience in research and development, requirement gathering, design, and development of code for IoT, ML, and computer vision-based products and solutions. He is currently working as a Software Engineer at Data Semantics, where he is building TensorFlow-based models for custom object detection and deployment of inference models on various platforms. He is also working on Planogram compliance models based on retail stores/supermarkets and performing data analytics. Mayank has good exposure to computer vision-based use cases and KPI development for the retail and manufacturing industries. He has worked on object (human) detection and tracking projects using various deep learning models like YOLOv3, MobileNet SSD, and DeepSort. He has also worked on the CUDA toolkit (parallel computing platform) and utilized GPU to speed up the ML model performance. Mayank is proficient in Python machine learning and deep learning libraries such as OpenCV, TensorFlow, and Keras. He has worked on data visualization using Matplotlib and other libraries. He has also worked on constrained devices such as Nvidia Jetson Nano, Raspberry Pi 2/3/4, TI-CC3200, and Arduino. Mayank has developed python code (back-end) for configuring and using the MQTT communication protocol to send commands from edge devices and receive events on the Microsoft Azure IoT hub service. He has also worked on building a Users Interface (front-end) for real-time sensor data monitoring. Mayank has a Post Graduate Diploma in Internet of Things (IoT) from C-DAC and a Bachelor of Technology in Electronics and Communications Engineering from JIET Group of Institutions Jodhpur. He has also completed XII (Senior Secondary) and X (Secondary) from Kendriya Vidyalaya. Mayank's tech stack includes Software Engineering, ML, Computer Vision, Object detection, TensorFlow, Object Detection, Python, Deep Learning, Azure, Frontend, Backend, Keras, AI, OpenCV, and Research Scientist. He has a relevant experience of 4.20 years.