Joshua Peter Ebenezer

Joshua Peter Ebenezer

Graduate Researcher and Assistant Director of LIVE

Laboratory for Image and Video Engineering (LIVE) at the University of Texas at Austin

Biography

I am a PhD student at the Laboratory for Image and Video Engineering at UT Austin, where I have also been serving as the Assistant Director since 2020. My advisor is Professor Alan Bovik. My research interests include video quality assessment, deep learning, and video processing. I received my B.Tech. from IIT Kharagpur, where I was awarded the Nilanjan Ganguly Memorial Award for the best undergraduate thesis and had the 3rd highest GPA in my graduating batch. My recent work has focused on video quality assessment for livestreamed high-motion videos, and I am currently working on quality assessment for HDR video. My work is sponsored by Amazon Prime Video.

For a complete list of my publications, please visit my Google Scholar page. You can find my CV here.

Being an academic is my vocation, and one that I enjoy immensely. I play the keyboard and the guitar occasionally. I love reading theology, history, philosophy, listening to music that stirs the soul, and getting to travel and experience different cultures and cuisines .

Interests

  • Video Quality Assessment
  • Deep Learning
  • Video Processing

Education

  • PhD in ECE, 2019 -

    UT Austin

  • B.Tech in ECE, 2019

    IIT Kharagpur

Experience

 
 
 
 
 

Assistant Director

Laboratory of Image and Video Engineering at UT Austin

Aug 2020 – Present Austin, Texas

Responsiblities include

  • Managing servers, equipment and resources for the lab.
  • Taking classes in case Dr. Bovik is away.
  • Representing the lab at meetings and conferences.
 
 
 
 
 

Applied Science Intern

Amazon Prime Video

May 2020 – Aug 2020 Seattle, WA
Developed a model to detect A/V Synchronization errors in tennis videos using audio and video ‘special event’ detectors built as deep learning networks.
 
 
 
 
 

Research Intern

Nanyang Technological University

May 2020 – Jul 2020 Singapore
Developed a deep-learning based system to segment cancerous regions of the skin.

Accomplishments

Engineering Graduate Fellowship

In recognition of outstanding academic record

Nilanjan Ganguly Memorial Award

Awarded for best undergraduate thesis in ECE

NTU-India Connect Scholarship

Funded intersnhip at NTU Singapore

DAAD-WISE Scholarship

Funded internship at TU Berlin (rejected as NTU-India Connect fell in the same period)

Goralal Syngal Memorial Award

Awarded for being in the top 3 in terms of GPA in the CS/ECE/EE departments

KVPY Fellowship

All India Rank 26 out of 100,000 aspirants. Awarded in recognition of scientific research potential

Projects

Video Quality Assessment using Space-Time chips

Developed a new feature space and algorithm for video quality.

FPGA implementation of fog-removal using anisotropic diffusion.

Implemented and optimized a fog-removal algorithm on an FPGA.

Deep learning for skin lesion segmentation

Proposed novel pre-processing techniques to improve identification of cancerous regions in the skin with deep learning.

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