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I’m Sweta Priyadarshi

Awarded GHC'2020 ECE Scholarship Featured as "Women in AI" by Carnegie Mellon University Awarded Best Presentation award at IRC-ICCV 2020 Conference Deep Learning Enthusiast Machine Learning Enthusiast Vision Enthusiast Multimodal Enthusiast
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Sweta
Priyadarshi

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ABOUT ME

I am Sweta Priyadarshi, a budding deep learning enthusiast. I would define myself as someone who loves learning and is passionate about innovation. I am a graduate student at Carnegie Mellon University, doing my masters in Electrical and computer engineering. I hold expertise in deep learning algorithms, machine learning algorithms, vision, language processing, speech processing and multimodal machine learning. Explore my website and do leave a comment what you liked about it the most.😊

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EXPERIENCE

  • Machine Learning Software Engineer

    DEKA R&D, Autonomous Robotics
    Feb 2021 - Ongoing

    Developed and deploying models for 3D object detection for Fedex delivery bots.

  • Graduate Research Assistant

    Carnegie Mellon University, Biometrics Center, Cylab
    Sept 2019 - Dec 2020

    Developed models for object detection (semantic segmentation, classification, object tracking and detection), also worked on OCR Development for price tags for Bossonova bots.

  • Graduate Teaching Assistant

    Carnegie Mellon University
    Aug 2020 - Dec 2020

    18793 - Image and video Processing Teaching Assistant. Mentoring, doubt clarification related to the assignments & projects and grading are cruical part of the responsibility.

  • Deep Learning Intern

    Nvidia
    May 2020 - Aug 2020

    Implemented and obtained novel algorithm for task loss balancing for Multi-tasking networks among tasks for scene understanding on NYUv2 and Taskonomy dataset, considering positive and negative knowledge transfer among tasks. Implemented branching methods to balance different tasks in multi-task networks.

  • Graduate Research Assistant

    Carnegie Mellon University, AiPEX Lab
    Jan 2020-May 2020

    Embedded physiological signals using GAN in the synthetically generated videos to diversify the dataset for motion-robust, non-contact heart rate estimation, project funded by BMGF.

  • Research Associate

    IIT Bombay - NCPRE Lab
    Sept 2018-June 2019

    Worked on various deep learning models, to aid the solar domain. Major contribution from algorithm perspective were deblurring of images(using DL models), object detection, pattern recognition and detection.

  • Operations Engineer

    Amazon
    April 2018-Sept 2018

    Worked on optimization and automation of processing equipment and green energy sourcing for power requirement (pan India) Amazon.

  • Research Intern

    IIT Bombay - NCPRE Lab
    Jan 2018 - April 2018

    Developed and proposed a device that can detect panel temperature as a function of time and keep saving all the dataset on the cloud server. The proposed device is 100 times cheaper than the existing system to capture module temperature and is robust and easy to use. Due to its nature of being inexpensive, it can be deployed for large scale PV plant temperature monitoring.

  • Design Engineer Intern

    Changzhou Xingyu Automotive Lighting Systems Co., Ltd
    May 2017 - July 2017

    Devised a RGB driver module to be employed in car lighting system.

  • Summer Intern

    Tata Steel
    May 2016 - June 2016

    Breakdown survey and Thermal Power Plant Overview: Summer '16 Tata Steel Pvt. Ltd., West Bokaro Div., India.

SKILL

Deep Learning 95%
Machine Learning 95%
Computer Vision 95%
Speech & Language Modelling 92%
Data Science 92%
Python (Programming Language) 95%
MATLAB 90%
C++ 85%
SQL 80%
Pytorch 95%
Pyspark 95%
Keras 93%
Tensorflow 85%

QUOTES



LOCATION

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