About

Meha Shukla is an upcoming Software Engineer who is currently pursuing a Bachelor of Technology in Computer Science and is set to graduate in 2024. She has a strong background in problem-solving and data structures and algorithms using C++. She also has experience in Frontend Web Development using HTML, CSS, and JavaScript. Meha is proficient in Python and has worked with various libraries like OpenCV, TensorFlow, Keras, NumPy, Pandas, and Matplotlib. Meha has an impressive track record of achievements and experiences in the field of technology. She was chosen by Google as one of the top 55 women across various Asia Pacific countries out of 15K+ applicants based on her excellence in technology, academics, computer science, leadership, and upliftment of minorities in Computer Science. She was also selected for a one-month long mentorship by Microsoft, where she built a face recognition system that detected seven different emotions and suggested songs, movies, and books accordingly. Furthermore, Meha was among the top 60 women in tech chosen by LinkedIn for placement-related guidance. She has also worked on building a metaverse shopping environment and an autonomous bot on Gazebo using ROS, OpenCV, and Python. Meha has been awarded several scholarships, including 100% scholarships to attend the prestigious Grace Hopper Celebration & Harvard WeCode Conference '22 and to pursue a course and certification in Linux. She has also worked at SAWO Labs, where she contributed to technical documentation, built projects integrating SAWO, and helped solve community doubts. Meha co-founded a community aimed at providing financial literacy to freshers, free of cost, which has over 200 mentees as of now. Currently, Meha works as a Mentor at codess.cafe, where she mentors 2nd and 3rd-year girls for placement preparation, takes mock interviews, guides and upskills them in a way to contribute to the community. She has also worked as a Teaching Assistant at Coding Blocks and as a Microsoft Engage at Microsoft, where she built a CNN-based face recognition system that detected human emotions in real-time using camera live feed. Her tech stack includes software engineering, Python, web development, Keras, computer vision, Pandas, JavaScript, frontend, CNN, and Flask. Overall, Meha is a highly motivated and skilled individual who is dedicated to making a positive impact in the field of technology.