Prashanth Reddy Duggirala

I'm a first year master's student majoring in Computer Science at University of California, Davis, where I plan to work on AI in general and computer vision in particular. I recently completed my B.Tech + M.Tech Dual Degree in Computer Engineering from IIITDM Kancheepuram, India. I love cars.

I'm currently working with the RUbiNet Lab, under the guidance of Prof. Sen-Ching Cheung and Prof. Chen-Nee Chuah as part of the ML-VIRSA project. Specifically, I'm working on Visual Saliency Prediction and autism spectrum disorder (ASD) diagnosis in children using a hybrid of technologies from Computer Vision and Deep Learning.

Email  /  Resume  /  GitHub  /  LinkedIn

Academic Objective

Exposure to applications of machine learning in the area of medicine and discussions with Ophthalmologists about potential applications of intelligent robots and sensor systems in the operation theatre has helped me realize how complex multimedia data is rapidly growing in the medical field. It has deeply influenced my determination to pursue research in applications of ML and computer vision in this area on the long term.


I have a keen interest in Computer Vision, Deep Learning and Blockchains. I have solved problems in the domains of Medical Diagnosis, Data Analytics, Sentiment Analysis, Time series prediction and also made a robot. You can find a detailed list of some of my research and projects here. The following is some of my research I want to publish:


Generative Adversarial Framework for Eye Image Synthesis and Gaze Estimation
[Report] [Slides]

Research and development of models to generate a large dataset of images with high diversity (e.g., in subjects, head pose, camera settings) and realism, while still maintaining granular control over the above attributes using Deep Convolutional GANs.


Gaze Direction Tracking in Infants
[Report] [Slides]

Development of Convolutional Neural Network based machine learning models for predicting eye-gaze direction. Additionally, development of approaches for 3D head pose estimation based on facial landmarks to determine yaw, roll and pitch from two dimensional images.


I have spent most of my summer breaks in the industry, working on exciting projects and trying to complement my knowledge from coursework with meaningful internships which gave me invaluable experience.


Machine Learning Intern/Research Fellow, Center for Innovation, L. V. Prasad Eye Institute, India (May 2018 - May 2019)

LVPEI Center for Innovation evolved out of LVP-MITRA program, a collaboration between L V Prasad Eye Institute and MIT Media Lab to build and deploy next generation of eye care technologies powered by AI.

I worked on a device called Pediatric Perimeter, a one-of-a-kind device to quantify visual field extent and developmental delays in infants. Specifically, my work was on video based eye gaze estimation of infants to automate the calculations of Visual Field Extent and Delay in reaction to light stimuli. Since it was to be used on infants, I developed machine learning algorithms for non-intrusive and pose-invariant eye-gaze estimation. Details in the Projects section.


Summer Intern, Leoforce Inc., India (June - July, 2017)

Worked with production database performance analysis and optimization team using MySQL server and Workbench. Monitored and profiled slow, unresponsive queries and stored procedures and improved their execution time so that the load on the server CPU is relieved and their application may become faster.


Summer Intern, OSI Systems Inc., India (May - July, 2016)

Worked with the Rapiscan team on AWK and Shell scripting languages with understanding of VB Script for text processing. Developed efficient algorithms for testing the baggage flow control in airport security screening machine systems and achieved a significant improvement in performance from before.


Teaching Assistant, IIITDM, India (2018 - 2019)

Worked as a Teaching Assistant for the courses listed below. I was responsible for curating course material, clarifying doubts on ML algorithms/techniques and the theory/logic behind the assignments along with conducting and evaluating assignments/examinations.

1. COM510 Machine Learning under Prof. Ganapati Panda (Spring 2019).
2. COM212 Database Systems under Prof. Munesh Singh (Spring 2019).
3. COM201 Programming and Data Structures under Prof. V Masilamani (Fall 2018).

Extra Curriculars

Organizer and Mentor to the winning team at Engineering The Eye 6, a one-of-a-kind, five day Health-Tech Hackathon conducted by LVPEI, one of the largest eye care networks in India.

Led a team that set up and maintained a large Hadoop cluster for distributed computing and scalable data mining purposes at a systems lab in the college.

Part of the team that Won first prize at Designception, an inter-college product design competition for an innovative conceptualization of portable sanitary napkin incinerator.

Won or was a finalist in numerous quiz competitions held at various inter-collegiate fests and main-quiz event winner at our college’s annual fest for two years in a row (2017-18).


Computer Vision - Machine learning - Deep Learning - TensorFlow - pyTorch - Predictive Data Analytics - CUDA - Python

Source code stolen from Jon Barron's website
Also, consider using my friend Kritika's fork of this page from whom I borrowed some ideas.