cv
NeuroAI
Basics
Name | Ninad Aithal |
Label | Researcher |
reachninadaithal@gmail.com | |
Phone | +91-7795880966 |
Url | https://blackpearl006.github.io/ |
Summary | Machine learning researcher focused on neuroimaging, explainable AI, and topological data analysis, with publications in ISBI, ICPR, and MICCAI. |
Work
-
2024.08 - Present Project Associate, Vision and AI Lab
Indian Institute of Science
Working on explainable AI for brain age prediction in collaboration with Stanford Medicine and Centre for Brain Research.
- Deep learning-based biomarkers for brain aging
- Cross-population neuroimaging analysis
- Collaboration with Vinod Menon and Srikanth Ryali (Stanford Medicine)
Volunteer
-
2024.12 - 2024.12 India
Volunteer
Indian Conference on Computer Vision, Graphics and Image Processing
Assisted with organizing logistics and sessions during the national-level vision and AI conference.
- Volunteer at ICVGIP 2024
Education
-
2020.08 - 2024.05 Mangalore, India
B.Tech
Srinivas University Institute of Engineering and Technology
Robotics, AI and Machine Learning
- Thesis: MCI Detection using fMRI time series embeddings of Recurrence plots
-
2020.01 - 2024.09 Chennai, India
B.Sc
Indian Institute of Technology Madras
Data Science and Applications
- Deep Learning for Computer Vision
- Machine Learning
- Big Data & Biological Networks
Awards
- 2024.04.01
Dean’s Best Undergraduate Project Award
Srinivas University
Best project among 50+ submissions on Alzheimer’s detection using recurrence plots of fMRI data.
- 2020.08.01
Chairman’s Scholarship
Srinivas University
100% tuition waiver awarded to one student per department for academic excellence.
- 2023.11.01
Travel Grant
IEEE DHSR
Received funding to present research at IEEE Digital Health Symposium and Roundtable.
Certificates
Applications of Data Science in Healthcare | ||
IIT Madras | 2024-01-01 |
Understanding and Modeling EEG Data | ||
Chennai Mathematical Institute | 2023-07-01 |
Large Scale Brain Data Computing | ||
IIT Madras | 2023-05-01 |
Publications
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2024.07.01 Investigating Mild Cognitive Impairment through Persistent Homology
ICPR 2024
Used topological data analysis to explore brain dynamics for MCI classification.
-
2024.04.01 MCI Detection using fMRI time series embeddings of Recurrence plots
IEEE ISBI 2024
Presented novel methods to detect Mild Cognitive Impairment using recurrence plot-based embeddings from fMRI data.
Skills
Machine Learning & Neuroimaging | |
Python | |
PyTorch | |
Scikit-learn | |
Topological Data Analysis | |
FSL | |
Nilearn | |
Captum | |
SHAP | |
Git | |
Google Cloud Platform |
Languages
English | |
Fluent |
Kannada | |
Native speaker |
Hindi | |
Professional working proficiency |
Interests
Computational Neuroscience | |
Neurodegeneration | |
Alzheimer’s Disease | |
Brain Age Prediction | |
Functional MRI | |
DWI & Connectomics |
References
Prof. Neelam Sinha | |
Principal Investigator, Centre for Brain Research, IISc – Mentored multiple publications and conference abstracts with Ninad. |
Prof. Venkatesh Babu | |
Head, Vision and AI Lab, IISc – Currently supervising Ninad on explainable AI in brain aging research. |
Projects
- 2023.06 - 2023.10
NeuroLight
Efficient MR image preprocessing pipeline built with PyTorch Lightning for reproducible neuroimaging research.
- fMRI pipeline design
- Integrated with deep learning models