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
-
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