Hello, I am Priyanka Moorthy.

Machine Learning Engineer | Software Engineering | MS in AI @ SJSU

About Me

I am currently pursuing my Masters's in Artificial Intelligence from SJSU and will graduate this May’23. I am looking for Full-time and Internships opportunities for both Software Engineer and Software Engineer in ML roles. Prior to my Master’s, I worked as a Software Engineer for nearly 2 years, where I had the opportunity to develop end-to-end applications in a fast-paced environment.

✉️ : priyankamoorthycit@gmail.com

Projects


Computer Vision

Butterfly

Pix2Pix on Butterfly data

GAN network for image translation from line art to colored butterfly images with a Pix2Pix Architecture. Achieved discriminator and generator loss of 0.91 and 1.23 respectively.

Read More
Butterfly

Mask-RCNN on Nuclie data

Image segmentation model built using Mask-RCNN architecture on nuclei data to perform object detection and segementation masks on nuclei in images. Achieved a mean average precision of 0.73.

Read More
Butterfly

Continuous Sign Language Recognition

Working on implementing a modified SAM-SLR framework for continous sign language recognition in realtime as part of my Master's project

Read More

Natural Language Processing

feature visualization

Abstractive Summarization

Scraped thousands of movie records including plot line and storyline features from the IMDB website using BeautifulSoup. Performed data cleaning, removed stop words, applied PorterStemmer to stem words. Fine-tuned a Pegasus model that follows a Self-Supervised Objective.

Read More
Butterfly

Sentiment Analysis on Amazon reviews

Data preprocessing, word embedding, and experimental analysis of sentiment classification on amazon reviews data by implementing FNN, CNN, LSTM, and distillBERT models.

Read More

Machine Learning and Data Mining

Butterfly

EDA on College Majors Data

Performed data cleaning, Exploratory Data Analysis and mined answers from data for proposed research questions

Read More
feature visualization

Using T-SNE to visualize high-dimensional data on outfit images

Data Collection, Visualize features extracted by ResNet101 network using t-SNE

Read More
feature visualization

Deep-Q Learning on Continuous Mountain Car

Implemented a sequential Deep-Q Learning on Open AI’s continuous mountain car environment that converges in 1643 episodes with 12 hidden dimensions.

Read More
feature visualization

Lo-Fi Music Generation

Trained a LSTM model on Lo-Fi style music data to generate similar music.

Read More