Soda Hall

Berkeley, CA

Hello. I'm

Varun Shenoy

I am a senior at Cupertino High School pursuing a career at the crossroads of computer science, electronics engineering, and healthcare. I strive to build compelling products, design clean user experiences, and learn about new technologies. My current research focus is applying cutting-edge machine learning technologies to the frontlines of healthcare.



MEDIA COVERAGE OF MY WORK

EXPERIENCES

Researcher
Stanford University | School of Medicine

Collaborating with Stanford Radiology to develop a web tool for automating radiology tasks utilizing deep learning and computer vision (paid position).


August 2018 - Present


Research Intern
Berkeley Artificial Intelligence Research

Applying computer vision to medical imaging. Designing deep neural networks for object detection in medical images and researching domain adaptation techniques for medical image synthesis.


Summer 2018


Data Scientist
Palo Alto Veterans Affairs Hospital

Currently collaborating with medical professionals to develop an automated method for assessing postoperative wounds using artificial intelligence.


June 2017 - Present


Secretary-Webmaster
Cupertino FBLA

2018 - Currently developing a new informative website for the chapter at tinofbla.org.

2017 - Led 250+ members in the competitive events offered by the FBLA-PBL organization, from business law to graphic design to e-business.


August 2015 - Present


Eagle Scout
Troop 407, Cupertino, CA

Eagle Scout with Silver Palm from Troop 407 from Cupertino with over 40 merit badges, from Fishing to Electronics. Inducted into the Order of the Arrow, the Boy Scout honor society.


August 2011 - Present


Online Editor
The Prospector

Redesigning and improving the online side of Cupertino High School's student-run publication at chsprospector.com.


August 2017 - Present


Link Crew Leader
Cupertino Link Crew

Selected to help freshman learn about Cupertino High School and provide support as an upperclassman mentor.


August 2017, August 2018


App Developer
Apple App Store

Building mobile applications for the App Store to solve a wide variety of problems. Currently have over 20,000 downloads for all my apps combined from users all over the world. Attended WWDC in 2016, 2017, and 2018 on scholarship.


August 2015 - Present


Curriculum Developer
TechLab Education

Developed comprehensive iOS curriculum for TechLab Education covering everything from basic Swift programming to web queries and Firebase. Taught iOS students a variety of concepts, from maps to database management.


Summer 2016


Webmaster
Cupertino Speech & Debate

Award winning parliamentary debater and extemporaneous speaker. Designed and built tinosd.org for Cupertino High School Speech & Debate. Competed in the Varsity division for both events.


August 2016 - June 2017


FEATURED PROJECTS

Theia
Automated Wound Assessment from a Smartphone

Theia is a deep learning based system for automated postoperative wound assessment with a convolutional neural network based backend and iOS frontend. It has won multiple awards at a variety of venues.


Summit
Embedded News Summarization using Machine Learning

Summit is an iOS app that summarizes the daily news. It helps busy people read the news in a matter of seconds. It has over 13,000 downloads and won me a Apple Scholarship to the World Wide Developer Conference in 2016. It also won the 2017 Congressional App Challenge in the CA-17 (Silicon Valley) district.


Dermyx
Skin Lesion Diagnosis via Deep Learning

Dermyx uses machine learning for bring rapid melanoma diagnosis on a desktop and mobile app. Dermyx was the only high school based team, competing against university medical and CS students, at Stanford health++ 2016. Dermyx won the Global Oncology Grand Prize.


Biosnap
Providing Intelligence to "Dumb" and Inexpensive Medical Monitors

Biosnap enables you to capture medical monitor data with a picture and store it automatically in your Health app swiftly without the usage of the mobile keyboard. With Biosnap, there's no reason to buy an expensive internet-connected medical monitor or maintain a log of measured biomarkers.


Agora
Fundraising for Clubs Made Simple

Agora is a mobile application that enables clubs on campus to raise money by holding digital yard sales. It was built for the Future Business Leaders of America (FBLA) 2017 Mobile Application Development competition, winning 1st place in California and 2nd place at Nationals.


RESEARCH
Deepwound: Automated Postoperative Wound Assessment and Surgical Site Surveillance through Convolutional Neural Networks

The incidence of postoperative wound infections after lower extremity bypass can be as high as 10%-20%. An automated method of diagnosing wound complications would serve to limit the expense of time and money from hospitals, doctors, insurers, and patients. The algorithmic classification of wound images, due to variability in the appearance of wound sites, is a challenge. Deep convolutional neural networks (CNNs), a subgroup of artificial neural networks that exhibit great promise in the analysis of of visual imagery, may be leveraged to categorize surgical site wounds. We present Deepwound, a multi-label CNN trained to classify wound images with image pixels and labels as the sole inputs.

Varun Shenoy, Elizabeth Foster, Lauren Aalami, Bakar Majeed, Oliver Aalami (2018)
Oral Presentation at the 2018 Surgical Infection Society Annual Meeting (Top 10 Papers)
Patent pending under US 62/670,970
Utilizing Smartphone-Based Machine Learning in Medical Monitor Data Collection: Seven Segment Digit Recognition

Biometric measurements captured from medical devices, such as blood pressure gauges, glucose monitors, and weighing scales, are essential to tracking a patient's health. Trends in these measurements can accurately track diabetes, cardiovascular issues, and assist medication management for patients. Currently, patients record their results and date of measurement in a physical notebook. It may be weeks before a doctor sees a patient’s records and can assess the health of the patient. This research presents a mobile application that enables users to capture medical monitor data and send it to their doctor swiftly using HealthKit. A key contribution of this paper is a robust engine that can recognized digits from medical monitors with an accuracy of 98.2%.

Varun Shenoy, Oliver Aalami (2017)
Oral Presentation at the 2017 American Medical Informatics Association Annual Symposium
A Machine Learning Model for Essay Grading via Random Forest Ensembles and Lexical Feature Extraction through Natural Language Processing

Written assignments provide a greater degree of assessment on the student’s depth of the subject matter and promote deep cognitive analysis. Often, the same essay prompts are recycled year after year. The cultivation of manual data from essays on the same prompt year after year can help teachers create a rapid, autonomous method to grade essays through the fields of statistics and machine learning. This research proposes a novel automated method to grade essays for syntactical correctness through training a machine learning model. The final model was able to achieve a quadratic weighted kappa score of 0.96 across all essay sets, a near perfect agreement with the human rater. Therefore, this research represents a near human-level accuracy in essay scoring.

Varun Shenoy (2016)

SELECT AWARDS & HONORS
DEVELOPMENT

WWDC Scholarship 2018

Apple Inc.

1st Place

2018 California FBLA State Leadership Conference

Coding & Programming

Recognized as a Young Innovator to Watch

Consumer Electronics Show 2018

for Theia

2nd Place

FBLA Nationals 2017 (Anaheim, CA)

Mobile Application Development

WWDC Scholarship 2017

Apple Inc.

1st Place

2017 California FBLA State Leadership Conference

Mobile Application Development

Overall Winner

2017 Congressional App Challenge

California's 17th District (Silicon Valley)

Global Oncology Grand Prize

health++ 2016

for Dermyx

WWDC Scholarship 2016

Apple Inc.

1st Place

2016 California FBLA State Leadership Conference

Computer Game & Simulation Programming

Most Appealing App Design

2016 Congressional App Challenge

California's 17th District (Silicon Valley)

RESEARCH

2nd Place in Posters

National JSHS 2018

Computer Science + Math

Top 10 Abstracts

Surgical Infection Society Annual Meeting 2018

for Deepwound

3rd ACM Student Prize

Synopsys Science Fair 2018

for Deepwound

1st Prize, Morgan Lewis

Synopsys Science Fair 2018

for Deepwound

3rd Place

Northern California + Nevada JSHS 2018


CONTACT ME