Experience

TechGirlz

• United States
• Non-profit Organizations
• 1 - 100 Employee

• Teen Advisory Board

  • Sep 2022 - Present

  Teen Advisory Board Member * Mission is to show young girls possibilities in Technology and Science and develop a love for Technology * TechGirlz workshops: Python, Introductory courses in AI * Working on creating Introductory Machine Learning Course for middle school girls * Moderated Apache Spark Panel at the Women in Tech Summit (WITS) Teen Advisory Board Member * Mission is to show young girls possibilities in Technology and Science and develop a love for Technology * TechGirlz workshops: Python, Introductory courses in AI * Working on creating Introductory Machine Learning Course for middle school girls * Moderated Apache Spark Panel at the Women in Tech Summit (WITS)



Prevent Cyber Bullying Project

• Freshman High School Student

  • Feb 2023 - Present

  Preventing Cyber Bullying: * Created a website using Python and HTML to help users, expand their knowledge about Cyber Bullying, expand the glossary of Cyber bullying terminology, and a place to verify the usage of any objectionable language and get suggestions for an inclusive and safe language to prevent Cyber Bullying. * Search - A simple search against a glossary of Cyber Bullying terms that will be educative for the users to understand the meaning of some of the Cyberbullying terms * Add a new Cyber Bullying Term - An add button that leads the user to a new form that enables them to add a new acronym/word and definition * Recommender (In progress) - Integration with KINDLY API (UNICEF) that uses AI/ML to verify any phrase for offensive intent that can recommend a kinder alternative. A text area that takes a few sentences as input that can be verified against the KINDLY API for validation or an alternate more safe and inclusive phrase. Show less



Pnuemonia Diagnosis using ML/AI

• Freshman High School Student

  • Feb 2023 - Present

  Pneumonia Diagnosis: As a part of a team of high schoolers, I am currently scoping the project and identifying the problem space. * Pneumonia is an inflammatory condition in the lungs that can be caused due to both viral or bacterial infection. * The inflammation on the air sacs can be seen clearly using X-Rays. X-Ray images, when trained using Dense or Convolutional Neural Networks can detect the inflamed regions clearly and classify Pneumonia over non-Pneumonia X-Rays. * For training Pneumonia detection, public datasets can be used that have labelled pneumonia and non-pneumonia images. Python based pipelines can be used for model inference purposes to classify any new test image reducing the dependency on manual analysis. Confusion Matrix, ROC Curve and AUC Curve's can be used as evaluation metrics to assess the performance of the classifier. Show less



Albert Einstein College of Medicine

• United States
• Higher Education
• 700 & Above Employee

• Freshman High School Student

  • Feb 2023 - Present

  Accepted by Dr. Tim Q Duong, PhD for research in the field of AI/Medicine - Currently identifying projects to work on. * Professor and Vice Chair for Research, Radiology, * Assoc Director in Integrative Imaging & Data Science, Center for Health & Data Innovation * Albert Einstein College of Medicine and Montefiore Medical Center Accepted by Dr. Tim Q Duong, PhD for research in the field of AI/Medicine - Currently identifying projects to work on. * Professor and Vice Chair for Research, Radiology, * Assoc Director in Integrative Imaging & Data Science, Center for Health & Data Innovation * Albert Einstein College of Medicine and Montefiore Medical Center



CARDIOMYOPATHY DETECTION USING ML AND AI

• Freshman High School Student

  • Jul 2022 - Present

  * Inspired by the loss of a grandfather to late detection of heart disease. Late Detection of heart disease is one of the biggest causes of death and as result, any technological advancements in this space would be hugely impactful to many families across the world. * Working with a team of 4 high schoolers to detect heart disease earlier than other monitoring systems can, using AI and ML * Using ECG Technology, detection of Cardiomyopathy, Tachycardia, Bradycardia, and other types of arrhythmia through Machine Learning and Artificial Intelligence years earlier. * Connecting with several major cardiology researchers and universities to collect relevant data Show less