Abhilash Mane Email & Phone Number

Programming Languages: Python ,C++, MATLAB, UML.Libraries: TensorFlow, PyTorch, Keras, NumPy, open3d, tensorflow-lite, OpenCV, PCL, pandas, sklearn, TensorRT. pycuda.Tools and framework:ROS, ROS2, Linux, RViz, Gazebo, Docker, MoveIt , Ouster-studio, AWS, Github, Gerrit, Pytest, CMake, CUDADomain Skills: Deep learning, Classical Computer vision, Motion planning, Bayesian Statistics, Machine learning, Control theoryDeep Learning Architectures: CNN, RNN,UNET, Attention based networks, encoder-decoder networks, LSTM, GAN, TransformersPassionate about pushing the boundaries of computer vision, robotics, and machine learning, I am a results-driven professional with a solid foundation in these cutting-edge technologies. With a Master's degree in Robotics and a strong academic background from the University of Maryland, I bring a wealth of knowledge and hands-on experience to tackle complex challenges in intelligent driving technologies.Throughout my career, I have successfully developed and deployed state-of-the-art algorithms and pipelines for a range of projects in computer vision, enabling smarter and safer driving experiences. My expertise spans deep learning architectures such as CNN, RNN, and GAN, as well as classical computer vision techniques, motion planning, and control theory.I have a proven track record of delivering impactful results, including enhancing perception for autonomous vehicles by evaluating 3D LiDARs, implementing advanced techniques like plane fitting and segmentation, and optimizing sensor calibration algorithms for improved precision in computer vision tasks. I have also played a key role in developing Docker-based software stacks tailored for computer vision applications, resulting in significant reductions in deployment time and enhanced compatibility across diverse hardware platforms.Proficient in programming languages such as Python, C++, and MATLAB, I have leveraged popular libraries and frameworks like TensorFlow, PyTorch, OpenCV, and ROS to develop robust solutions. My strong grasp of Bayesian statistics and machine learning enables me to develop and fine-tune machine learning models, achieving remarkable performance in object detection, segmentation, and classification tasks.With a keen eye for the latest advancements in computer vision, machine learning, and robotics, I consistently stay updated with state-of-the-art algorithms and publications. My work has been recognized through participation in prestigious robotics competitions, including being a finalist at the National Level e-Yantra Robotics Competition.

Listed skills include Robot Operating System, Arduino, Autocad, Matlab, and 18 others.