Mentors: Oren Gurevitch <oren.gurevitch@mcgill.ca>, Maya Aderka <maya.aderka@mail.mcgill.ca>, Suresh Krishna <suresh.krishna@mcgill.ca>
Skill level: Advanced
Required skills: Fluency in Python/MATLAB. Familiarity with signal-processing algorithms and data-science/statistics. Familiarity with Slurm and working with clusters preferred. Basic web-development skills or interest in learning them will be useful.
Time commitment: Full time (350 hours)
Forum for discussion
About: Recent research has again begun to emphasize the close relationship between the temporal dynamics of heart-rate and blood-pressure with brain dynamics. The study of cardiovascular dynamics and brain dynamics uses a set of conceptually highly inter-related algorithms and software tools, that have yet to be brought together to take advantage of each other. Many projects currently use closed-source commercial software since the existing open-source software is not easy to use or poorly documented.
Aims: This project aims to implement software to jointly analyze brain and heart dynamics and integrate this software with existing packages as well as existing open datasets. A web platform will also be set up to facilitate web-based analysis.
Website: m2b3.com/BrainHeart
Tech keywords: Oscillations, brain heart interactions, health AI, time-series analysis, online portals
Subject: Interest in BrainHeart & Proposal Drafting
Dear Oren, Maya, and Suresh @suresh.krishna ,
I have been interested in this project since the day it was mentioned in the INCF GSOC-25 document. Currently, I have a signal processing subject in my semester at college, and I am highly motivated to work on this problem. I have experience working with Python, and we use MATLAB in our coursework, so I am quite familiar with it as well. I also have relevant web development experience, aligning with the key requirements mentioned in the project.
I am currently drafting a proposal for this project and will share it with you soon for feedback. Additionally, I am actively exploring the other technologies involved to strengthen my understanding.
To further demonstrate my skills, I am building an MVP for a personal project related to this domain. This project focuses on biomedical time-series analysis, specifically processing and visualizing heart rate and EEG data. The MVP includes:
- Signal preprocessing (filtering, normalization)
- Feature extraction (frequency components, statistical measures)
- Real-time visualization using Python (Matplotlib, Seaborn, Plotly)
- I also plan to explore Slurm-based processing to further align with the project’s scope.
This project directly aligns with the brain-heart interaction analysis required in the GSOC project.
By the time the GSOC period starts, I aim to gain further exposure to Slurm-based cluster computing, ensuring a smoother transition into the project.
I am excited about this opportunity and eager to contribute.
Looking forward to your insights!
Best regards,
Ritesh Singh
@riteshsingh - thank you for the interest. What you propose is along the right track. Looking forward to your proposal. Please send me a link to a Google Doc via DM when it is ready for feedback.
1 Like
@arnab1896 @PradeepGeorge @Mathew_Abrams - could one of you please update the description above to refer to oren.gurevitch@mail.mcgill.ca (rather than the address shown) and also the app link to GitHub - m2b3/BrainHeart ?
Thank you !
@suresh.krishna Thank you for your response!
I appreciate the opportunity to work on this project and will refine my proposal accordingly. Currently, for my individual project’s MVP, I am preprocessing and analyzing the CAP Sleep Database, which studies sleep disorders using EEG and ECG signals. This aligns with the project’s focus on biomedical time-series analysis.
I’ll share the Google Doc link via DM once it’s ready for feedback. Looking forward to your insights!