About Me

About-me

Revathy Venkataramanan

Graduate Research Assistant

I am a Ph.D. student from the University of South Carolina, advised by Dr.Amit Sheth. Currently, I am working on food computation models that involves multi-modal learning, process modelling, knowledge infused learning and explainability. This work involves building a cooking simulator that imitates the real-world cooking process to understand the impact of the cooking methods over ingredients. This cooking simulator is being extended for explainable meal recommendation system for chronic health conditions. The recommendation utilizes external knowledge to explain and reason its recommendation choices. I am also working on utilizing cooking and flavour context to find alternate set of ingredients for a given recipe which can also be an added feature to the recommendation system. As a team, we are also working on developing a mobile application to estimate carbohydrate content from food images for type-1 diabetes patients.


AREAS OF INTEREST

Multimodal learning, Process modeling, Computer Vision, Natual Language Processing, Deep learning, Precision Nutrition, AI for Personalized Health, Internet of Things


Name: Revathy Venkataramanan

Phone: +1-937-929-9384

Education: PhD Computer Science

Email: first_name[at]email.sc.edu

Address: 429 Horizon-I, 541 Main St, Columbia, SC - 29201

Nationality: Indian

Design & Code

My Skills

Python, Java

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90%

Scikit Learn, Matlab, OpenCV

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70%

Material Design, Semantic UI

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70%

Windows, Linux, Mac OS

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75%

Tensorflow, Numpy, Keras

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80%

Android Programming

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90%

Elasticsearch, MySQL

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75%

Object detection, CNN

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80%

Alma Mater

Education

Aug 2019 - Present

PhD in Computer Science

University of South Carolina | Columbia, USA

GPA 4.0/4.0

Aug 2016 - Apr 2019

MS in Computer Science

Wright State University | Dayton, OH

GPA 3.66/4.0

Sep 2012 - Apr 2016

BE in Computer Science and Engineering

RMD ENgineeing College | Chennai, India

CGPA 8.48/10

Where I work(ed)

Experience

May 2021 - Aug 2021

Deep Learning Intern

Appzen, SanJose, California 95002, USA

Designed and developed a document generation model for invoices that employs controlled randomisation by studying existing probability distribution. Built a deep learning model to extract key-value pairs from the invoice document through self-supervised learning approach.

Aug 2019 - Present

Graduate Research Assistant

AI Institute, University of South Carolina, Columbia, SC

Building a personalized explainable diet recommendation model by utilizing various knowledge sources. Working on infusing knowledge into process modelling to enhance the representation learning of deep learning models. Developing a nutrition chatbot to track and recommend meals for type-1 diabetes, hypertension, and for the general population.

Jan 2017 - Jul 2019

Graduate Research Assistant

Knoesis Research Center, Wright State University
Dayton, OH, USA

Designed a food image to nutrition framework to monitor diet for obese and bariatric surgery patients. Analyzed real asthma patients’ data to identify personalized triggers.

Dec 2013 - Jan 2014

Android Developer Intern

Nua Trans Media, Chennai, India

Developed an android app “XNGNotes” where students can trade used books and notes.

What I Love To Do

My Projects

mHealth app to estimate Carbohydrate Contents for Type-1 Diabetes| Team Project | Aug 2021 - Present

A multi modal approach to monitor diet, recommend meals and promote healthy eating habits NOURICH is an android app developed to monitor the individual’s dietary patterns and their weight and assist them in making informed decisions about food choices to maintain a healthier weight. The app can recognize food images, log them and recommend meal based on user’s health condition and preferences

kHealth Asthma | Team Project | Jan 2017 - April 2019

A semantic multi-sensory approach to personalize asthma management in children

Contributions:

Analyzed 100 patients data to identify and rank their triggers causing asthma symptoms. Developed API’s for data analysis involved in the design and testing of the dashboard (link:) Funded by NIH. Grant Number

kHealth Bariatrics | Team Project | May 2017 - Jul 2019

A multi sensory approach to support patients for post surgical behaviour

Contributions:

1) Designed the system architecture 2) Developed an android app to monitor patient’s diet and emotional well being 3) Validated the IoT sensors required for the project

Let's See My Works

My Publication

Determination of Personalized Asthma Triggers From Multimodal Sensing and a Mobile App: Observational Study

Revathy Venkataramanan, Krishnaprasad Thirunarayan, Utkarshani Jamini, Dipesh Kadariya, Hong Yung Yip, Maninder Kalra, Amit Sheth.
Published in: JMIR Pediatrics & Parenting 2019;2(1):e14300 DOI: 10.2196/14300

How Is My Child Asthma? Digital Phenotype and Actionable Insights for Pediatric Asthma

Utkarshani Jaimini, Krishnaprasad Thirunarayan, Maninder Kalra, Revathy Venkataramanan, Dipesh Kadariya, Amit Sheth.
Published in: JMIR Pediatrics & Parenting 2018;1(2):e11988, DOI: 10.2196/11988.

kBot: Knowledge-enabled Personalized Chatbot for Asthma Self-Management

Dipesh Kadariya, Revathy Venkataramanan, Hong Yung Yip, Maninder Kalra, Krishnaprasad Thirunarayan, Amit Sheth.
Published in: IEEE SMARTSYS Workshop on Smart Service Systems (SMARTCOMP 2019). IEEE, 2019

Knowledge-Enabled Personalized Dashboard for Asthma Management in Children

Vaikunth Sridharan, Revathy Venkataramanan, Dipesh Kadariya, Krishnaprasad Thirunarayan, Amit Sheth, Maninder Kalra.
Published in: Annals of Allergy, Asthma & Immunology 121.5 (2018): S42. (Poster)

Feasibility of Recording Sleep Quality And Sleep Duration Using Fitbit in Children with Asthma

Amit Sheth, Hong Yung Yip, Utkarshani Jaimini, Dipesh Kadariya, Vaikunth Sridharan, Revathy Venkataramanan, Tanvi Banerjee, Krishnaprasad Thirunarayan, Maninder Kalra.
Published in: 32nd Annual Meeting of the Associated Professional Sleep Societies (SLEEP), 2-6 June 2018, Baltimore, MD. (Poster)

A Multisensory Approach to Monitor Bariatric Patient’s Postsurgical Behavior and Lessen Weight Recidivism

Sarah Sohail, Joon Shim, Revathy Venkataramanan, Utkarshani Jaimini, Dene Berman, Priti Parikh, Amit Sheth.
Published in: Obesity Week 2017. 34th ASMBS Annual Meeting; 2017 Oct 29- Nov 2; Washington D.C. (Poster)

Correlating Multimodal Signals with Asthma Control in Children Using kHealth Personalized Digital Health System

Amit Sheth, Tanvi Banerjee, Utkarshani Jaimini, Dipesh Kadariya, Vaikunth Sridharan, Krishnaprasad Thirunarayan, Revathy Venkataramanan, Hong Yung Yip, Maninder Kalra.
Published in: American Thoracic Society (ATS) International Conference. (Poster)

Mentors

REFERENCES

Prof. Amit Sheth, Director- AI Institue

University of South Carolina, Columbia, SC, 29201, USA.

Prof. Biplav Srivastava, AI Institute

University of South Carolina, Columbia, SC, 29201 USA.

Get In Touch

Contact Me

Address

429 Horizon-I, 541 Main St,
Columbia, SC - 29201

Email

first_name[at]email.sc.edu

Call Me

+1 937-929-9384

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