About

Keerthi Suresh is a Research and Development Engineer at Konica Minolta, Inc. with a passion for setting and achieving impactful goals. She recently graduated from IIT Madras, the best engineering institute in India according to the MHRD, Government of India, and has a versatile range of experiences in entrepreneurship, research, and educational content creation. Keerthi's explorations have taken her from case study experiences in Australia to research in Japan to educational content creation in Kerala, each of which has helped her learn more about what makes the world tick. At Konica Minolta, Keerthi is developing a digital scheduling and visualization system for High Street Printers, analyzing customer needs through Customer Journey Mapping and User Story Mapping. She is continuously improving the prototype through feedback using Agile Development techniques and keeping track of team progress through meticulously planned scrum meetings. Keerthi started from scratch and became able to execute full-stack development, demonstrating her ability to learn quickly and adapt to new challenges. In the past, Keerthi has participated in intensive workshops that teach how to conceive, develop, and validate innovative business ideas. She has also worked as a Research Intern at the Australian National University, where she used machine learning approaches to find the optimal constellation for a new splitting receiver architecture. Keerthi conducted simulations to determine the correlation between different component noise factors and constellations and plotted Signal to Noise Ratio (SNR) v/s Symbol Error Rate (SER) for different splitting ratios to conclude that deep learning is reliable to determine message-to-symbol mappings. Keerthi's educational background includes a Bachelor's degree in Electrical Engineering from IIT and a Master of Business Administration (MBA) from Quantic School of Business and Technology, which she will complete in December 2021. Her tech stack includes skills in research, deep learning, and machine learning, and she has 0.51 years of relevant experience. Keerthi's persistent drive to conquer mountains one step at a time makes her a valuable asset to any team.