Experience

Atlas AI

• United States
• Technology, Information and Internet
• 1 - 100 Employee

• Machine Learning Engineer

  • Jul 2021 - Present



Greenstand

• United States
• Environmental Services
• 1 - 100 Employee

• Machine Learning Engineer

  • Jul 2020 - Jun 2021

  - Developing an algorithm to automate the identification of 200,00+ plant images uploaded by users, to help eliminate the need for numerous hours of manual annotation.- Adopted a Bilinear CNN model with orderless pooling for fine grained visual recognition in order to realize an accuracy of 85%.- Implementing computer vision algorithms to enable the model to predict previously unseen plant species.Technolgies Used: Python, TensorFlow, OpenCV, Amazon Sagemaker, Amazon S3 - Developing an algorithm to automate the identification of 200,00+ plant images uploaded by users, to help eliminate the need for numerous hours of manual annotation.- Adopted a Bilinear CNN model with orderless pooling for fine grained visual recognition in order to realize an accuracy of 85%.- Implementing computer vision algorithms to enable the model to predict previously unseen plant species.Technolgies Used: Python, TensorFlow, OpenCV, Amazon Sagemaker, Amazon S3



Intelligent Information Systems Research Laboratory

• Graduate Researcher

  • Aug 2019 - Jun 2020

  - Designed a system to recognize human emotions by extracting keypoints and spatiotemporal features from in-the-wild video clips.- Implemented a Convolutional LSTM network for video classification and performed emsembling, achieving results comparable to the current state-of-the-art while significantly lowering the computational complexity.Technologies Used: Python, PyTorch, OpenCV, numpy, pandas - Designed a system to recognize human emotions by extracting keypoints and spatiotemporal features from in-the-wild video clips.- Implemented a Convolutional LSTM network for video classification and performed emsembling, achieving results comparable to the current state-of-the-art while significantly lowering the computational complexity.Technologies Used: Python, PyTorch, OpenCV, numpy, pandas



Penn State University

• United States
• Higher Education
• 700 & Above Employee

• Graduate Learning Assistant

  • Jan 2020 - May 2020

  CSE 583: Pattern Recognition and Machine Learning - Assisted graduate students in the coursework by holding office hours and answering questions on a discussion forum. - Handled grading of homeworks, programming assignments and projects done in MATLAB and Python.

• Grading Assistant

  • Aug 2019 - Dec 2019

  EE 310 Electronic Circuit Design I - Graded weekly homeworks and tests.



Council of Scientific and Industrial Research

• Research Services
• 200 - 300 Employee

• Research Intern

  • May 2017 - Jul 2017

  Modeled a system to predict the performance of a receiver based on properties of the transmitted signal and the environmental conditions. Used the results of the predictive analysis to train the system to select appropriate signal processing techniques in order to achieve required receiver performance. Modeled a system to predict the performance of a receiver based on properties of the transmitted signal and the environmental conditions. Used the results of the predictive analysis to train the system to select appropriate signal processing techniques in order to achieve required receiver performance.