About

Hi! I am a PhD candidate at AIM lab - Harvard MGB and Editorial Board Trainee at Radiology: AI.

Previously, I was a Tech Consultant in AI&DL at Amazon Web Services (AWS)

Prior to joining AIM, I did my master's in Biomedical Computing at TU Munich. During my studies, I spent a year as a Visiting Scholar at Johns Hopkins University in ARCADE lab; worked as a Research Assistant at MITI in Klinikum Rechts de Isar; worked at ScintHealth (IFL Lab), and took part in MedInnovate Graduate Programm where VizCare was born. I did my Bachelor's degree in Computer Engineering at NTUU "KPI".

My primary research interests lie in computer-aided medical procedures and the application of deep learning in medicine. More broadly, I am intrigued by computer vision, machine learning, and image processing. Alongside my research, I am a passionate advocate for equitable educational opportunities and inclusive science communication, aiming to empower and uplift underrepresented communities.

Skills

  • Python
  • R
  • C#
  • Deep learning
  • Computer Vision
  • Medical Imaging
  • Statistics
  • AWS
  • MLOps
  • Slicer 3D
  • Unity
  • Organisation
  • Leadership
  • Collaboration

Selected Publications

You can find the full list on Google Scholar.

Automated temporalis muscle quantification and growth charts for children through adulthood

Anna Zapaishchykova, Kevin X. Liu, Anurag Saraf, Zezhong Ye, Paul J. Catalano, Viviana Benitez, Yashwanth Ravipati, Arnav Jain, Julia Huang, Hasaan Hayat, Jirapat Likitlersuang, Sridhar Vajapeyam, Rishi B. Chopra, Ariana M. Familiar, Ali Nabavidazeh, Raymond H. Mak, Adam C. Resnick, Sabine Mueller, Tabitha M. Cooney, Daphne A. Haas-Kogan, Tina Y. Poussaint, Hugo J.W.L. Aerts & Benjamin H. Kann

An Interpretable Approach to Automated Severity Scoring in Pelvic Trauma

Anna Zapaishchykova, David Dreizin, Zhaoshuo Li, Jie Ying Wu, Shahrooz Faghih Roohi, Mathias Unberath

Diffusion Deep Learning for Brain Age Prediction and Longitudinal Tracking in Children Through Adulthood

Anna Zapaishchykova, Divyanshu Tak, Zezhong Ye, Kevin X Liu, Jirapat Likitlersuang, Sridhar Vajapeyam, Rishi B Chopra, Jakob Seidlitz, Richard AI Bethlehem, Lifespan Brain Chart Consortium, Raymond H Mak, Sabine Mueller, Daphne A Haas-Kogan, Tina Y Poussaint, Hugo JWL Aerts, Benjamin H Kann

Boards, Advisory Committees, Professional Activity

• Radiology: Artificial Intelligence Trainee Editorial Board member

• MICCAI Student Board (MSB) 2023-2024 Executive Officer

• Reviewer for: Radiology: Artificial Intelligence, IEEE TMI, ML4H'23 & '24, Imaging Neuroscience, European Radiology, Biomarker Research, MICCAI'24, MICCAI Workshop on Deep Generative Models 2024, Journal of Open Source Software, BMC Medical Informatics and Decision Making

Honors & Awards

• Reviewer of the Year'24 - European Radiology

MICCAI 2023 Educational Challenge 3rd place winner: Preprocessing MRI in Python (Medium post)

• Brigham Research Institure Spotlight Award 2023 - Group Recognition

• PROMOS Scholarship award 2020

• Kaggle COVID-19 Dataset Award

Extras

Teach for Ukraine: Math Mentor & Volunteer 2024. A project to overcome educational losses and provide social-emotional support to children.

RSIPVision - Computer Vision News October 2024 an interview about Diffusion Models synthetic brain ageing

Science in the News 2024 invited talk "Tiny Patients, Big Solutions: How AI Helps Children with Brain Tumors"

AppCamps.de ClassChats Volunteer 2022: tech career talks for kids 5-9th grade

SegmentationReview, a tool for clinicians who need to quickly and efficiently review deep-learning generated segmentations; available in 3D Slicer extensions manager