Monalisa Achalla
About Monalisa Achalla
Monalisa Achalla is a Computer Vision Engineer currently working at Packsize in Salt Lake County, Utah, and serves as a Research Assistant at Clarkson University Graduate School. She has a background in Electrical and Computer Engineering and has held various roles in technology and research, including positions at Deloitte India and NYISO.
Current Role at Packsize
Monalisa Achalla serves as a Computer Vision Engineer at Packsize, a position she has held since 2022. In this role, she focuses on optimizing object dimensioning systems through the application of advanced computer vision techniques. Her work involves conducting extensive testing and evaluation of various camera technologies to enhance accuracy and performance in packaging solutions.
Research Assistant Experience
Since 2019, Monalisa Achalla has been working as a Research Assistant at Clarkson University Graduate School. In this capacity, she engages in research activities that contribute to the field of computer vision. Her experience in academia complements her professional work, allowing her to apply theoretical knowledge to practical applications.
Previous Employment at Deloitte India
Monalisa Achalla worked at Deloitte India as a Business Technology Analyst from 2018 to 2019. During her tenure, she gained valuable experience in business technology solutions, which provided a foundation for her subsequent roles in computer vision and engineering.
Educational Background
Monalisa Achalla earned her Master's degree in Electrical and Computer Engineering from Clarkson University, where she studied from 2019 to 2021. Prior to this, she completed her Bachelor of Technology in Electronics and Communication at Vellore Institute of Technology from 2014 to 2018. Her educational background has equipped her with a strong foundation in engineering principles and technologies.
Technical Contributions and Projects
Monalisa Achalla has made significant contributions to the field of computer vision. She developed a robust detection model specifically for the packaging industry, capable of identifying and distinguishing fragile objects. Additionally, she created a comprehensive dataset for fragile and non-fragile objects, managing all stages from data extraction to labeling and processing. Her work includes implementing advanced techniques for manipulating, segmenting, and detecting point clouds to enhance object recognition and analysis.