Download Mariia’s Resume
Download Mariia’s CV

Education

Ph.D in Biomedical Engineering, George Washington University
B.S. in Biomedical Engineering, University of Minnesota - Twin Cities

Work experience

Machine Learning Engineer – ORISE Fellow | FDA | Washington DC| June 2022 - Present

• Contributing to the development of an open-source deep unsupervised learning library (DomId)
• Developed three deep learning algorithms for conditional and contextual identification hidden subgroups in the digital pathology datasets assisting in bias reduction
• Performed regulatory science research to assess the generalizability of ML models, which resulted in multiple scientific publications at top-tier ML conferences
• Received “Outstanding Young Researcher” award (LinkedIn post)

Researcher | George Washington University | Washington DC| September 2019 - December 2023

• Developed deep generative models (VAEs, DDPMs) to detect abnormal brain connectivity, which reduced sex-related bias compared to existing solutions
• Contributed to the development of a state-of-the-art robust multimodal emotion recognition system using Generative Pre-trained Transformer (GPT), WaveRNN, and FaceNet+RNN
• Implemented explainable AI algorithms for EEG signals for early diagnosis of dementia with 80% confidence 
• Designed an AI-based robotic system for stroke detection that can be scaled up for in-hospital use

Teaching Assistant | George Washington University | Washington DC | September 2019 – May 2022

• Guided 8 - 10 team projects through the process of engineering medical devices for real* world clients
• Introduced students to principles of SCRUM project management, product development, and customer discovery
• Assisted students with Python, SolidWorks, 3D printing, microcontrollers, circuit design, and digital signal processing
• Recieved “Outstandin Teaching” award (LinkedIn post)

Biomedical Engineering Intern | InSitu Technologies Inc | St. Paul, MN | February 2019 – May 2019

• Performed experiments to aid the design and development of new products for treatment of aneurysms
• Automated process of statistical analysis of test data which reduced data processing time by 10 hours/week
• Wrote and executed process validation protocols and technical reports

Research Assistant | University of Minnesota | Minneapolis, MN | September 2018 – December 2018

• Analyzed the magnetoencephalography (MEG) data from patients with Parkinson’s disease
• Applied traditional machine learning algorithms (LDA, SVM, linear regression) to uncover the correlation between measured brain activity and changes in a behavioral task

Math Teaching Assistant | University of Minnesota | Minneapolis, MN | January 2016 – May 2019

• Organized and led weekly recitations sessions for ~60 students/semester for pre* calculus, calculus classes
• Graded homework, exams, quizzes and reported statistics of students’ performance
• Hosted office hours and appointment based tutoring sessions

Skills

Programing Languages and Software: Python, MATLAB, Mathematica, SolidWorks, LaTex, Altium Designer
Tools and Libraries: PyTorch, Tensorflow, Keras, Sklearn, Git, Scikit-learn, OpenCV, Pandas, Numpy, Scipy

Publications

Sidulova, Mariia, and Chung Hyuk Park. “Conditional Variational Autoencoder for Functional Connectivity Analysis of Autism Spectrum Disorder Functional Magnetic Resonance Imaging Data: A Comparative Study.” Bioengineering 10.10 (2023): 1209.

Sidulova, Mariia, Xudong Sun, and Alexej Gossmann. “Deep Unsupervised Clustering for Conditional Identification of Subgroups Within a Digital Pathology Image Set.” MICCAI, 2023.

Xie, Baijun, Mariia Sidulova, and Chung Hyuk Park. “Robust multimodal emotion recognition from conversation with transformer-based crossmodality fusion.” Sensors 21.14 (2021): 4913.

Sidulova, Mariia, Nina Nehme, and Chung Huyk Park. “Towards Explainable Image Analysis for Alzheimer’s Disease and Mild Cognitive Impairment Diagnosis.” 2021 IEEE Applied Imagery Pattern Recognition Workshop (AIPR). IEEE, 2021.

Sidulova, Mariia, Ria Kim, and Chung Hyuk Park. “Cerebrovascular Event Detection Robotic System: Rob Bitt.” 2020 8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob). IEEE, 2020. (Best Student Paper Award Nominee)

Sidulova, Mariia, and Chung Hyuk Park. “Towards Explainable Diagnosis of Alzheimer’s.”

Sidulova, Mariia, et al. “Musical Intervention: A Case Study on Longitudinal Analysis with Mixed Initiative Child-Robot Interaction.”

Presentations

MICCAI Conference | Vancouver | October 2023
“Deep Unsupervised Clustering for Conditional Identification of Subgroups Within a Digital Pathology Image Set”

IEEE ICRA Conference | Philladephia, PA | May 2022
“A Case Study on Longitudinal Analysis with Mixed Initiative Child-Robot Interaction.”

IEEE AIPR Conference | Virtual | October 2021
“Explainable Artificial Intelligence (XAI) for Alzheimer’s Disease (AD) and Mild Cognitive Impairment (MCI) Detection from EEG signals.”

IEEE BioRob Conference | Columbia University (Virtual) | Fall 2020
“Cerebrovascular Event Detection Robotic System: Rob Bitt.”

IROS Conference | Las Vegas (Virtual)| Fall 2020
“Towards Explainable Diagnosis of Alzheimer’s.”

GW New Venture Competition 2020 | GWU | Spring 2020
Mariia Sidulova, Ria Kim. Rob Bitt. (Semifinalist)

IMPACT Symposium | Mayo Clinic | Spring 2018
Karena Lin, Clairice Pearce, Mariia Sidulova “IL-6 Release During Febrile Hyperthermia Leads to HLHS Through Canonical Wnt Signaling”

Service and leadership

• Volunteer for ArtReach Program
• President of Russian Speaking Student Association at University of Minnesota