About

Akash Basudevan is a highly skilled Machine Learning Engineer with over 4 years of experience in building and implementing AI integrated solutions for business use cases across multiple domains, with a particular focus on computer vision and natural language processing. He has a strong background in building end-to-end deep learning pipelines and building software systems around machine learning both on cloud and on the edge. Akash has a proven track record of accelerating inference for AI models on edge devices such as Raspberry Pi, NVIDIA Jetson, and Google Coral. Currently working as a Machine Learning Engineer in the research team of Amazon One team, he is involved in the domain of computer vision. He has participated in various machine learning hackathons, giving him exposure to structured machine learning pipelines. Akash also loves participating in algorithmic challenges. Akash's interest lies in research roles in the field of artificial intelligence and building scalable machine learning solutions. He possesses a diverse skill set that includes ML, AWS, computer vision, AI, NLP, Python, deep learning, object detection, Docker, TensorFlow, OpenCV, Keras, image processing, Scikit, data scientist, Pandas, iOS, Pytorch, Azure, integration, mobile, and backend. Currently, Akash is working as a Python Back-end Development Intern at Kritikal Solutions, where he designed and implemented the back end for a Remote Video Surveillance (RVS) system using Python, FFMPEG, and OpenCV. He deployed the system on AWS and completely automated AWS management steps using the boto library of Python. He also generated different perspectives of an image using the Keras library of Python and produced over 10 million images from 0.6 million images. Additionally, he made frame extraction from video 50% more efficient by splitting videos into segments and mapping the frame numbers from the large video to the splitted videos. In the past, Akash worked as a Google Code In Mentor at TensorFlow and as a Trainee Machine Learning Engineer at Nagarro. At Nagarro, he conducted extensive exploratory data analysis on a multi-level dataset and built base classification models to predict intermediate features. He also wrote a library to randomly generate chart data with object detection annotations using Matplotlib and Seaborn to automate data generation for any type of chart data with annotations. Moreover, he developed a tool called Line Chart Knowledge Extraction, which automatically extracts information from research paper line graph images with a limited scope. Akash holds a Bachelor’s Degree in Communication and