Rashmi Tiwari
About Rashmi Tiwari
Rashmi Tiwari is a Data Scientist currently working at Cimpress India since 2023, with prior experience at Pushpak.ai and CSIR-CEERI. She specializes in deep learning architectures, large language models, and visual information processing.
Work at Cimpress
Rashmi Tiwari has been employed as a Data Scientist at Cimpress India since 2023. In this role, she works remotely and focuses on developing and optimizing deep learning architectures for real-time applications. Her responsibilities include leveraging cloud platforms and edge devices to enhance the performance of various data-driven projects.
Previous Experience at Pushpak.ai
Prior to her current position, Rashmi worked at Pushpak.ai as a Data Scientist from 2021 to 2023. During her tenure, she contributed to various machine learning initiatives, applying her expertise in deep learning and data analysis to solve complex problems in the field.
Research Background at CSIR-CEERI
Rashmi Tiwari began her career at CSIR-CEERI, where she held two positions. She served as a Research Trainee from 2018 to 2019 for 10 months and later as a Project Assistant-II from 2019 to 2020 for 9 months. In these roles, she gained valuable experience in research and development within the field of computer science.
Education and Expertise
Rashmi holds a Master of Technology (MTech) in Computer Science from the Central University of Rajasthan, where she studied from 2017 to 2019. She also earned a Bachelor of Technology (BTech) in Computer Science and Engineering from Chandra Shekhar Azad University of Agriculture & Technology. Her academic background supports her expertise in areas such as visual information processing, computer vision, and prompt engineering for machine learning models.
Specialization in Deep Learning and AI
Rashmi specializes in deep learning architectures and has a strong focus on benchmarking and fine-tuning large language models (LLMs). She is part of the Artwork Intelligence and Research (AIR) team, where she applies her skills in visual information processing and computer vision to advance AI technologies.