Research Interests
Machine Learning, Representation Learning for Neuroscience, Deep Generative Learning for Neuroimaging Data, Cognitive Neuroscience, Data-driven Biomarker Discovery, Multimodal Learning, Network Neuroscience
BioSketch
Research
Latent graph encoding of multimodal neuroimaging features with generative AI architectures
2026
I. Batta*, Meenu Ajith*, Vince Calhoun | IEEE
Journal: 2026 33rd edition of the IEEE International Conference in Image Processing (ICIP)
Graph-based variational representation learning and reconstruction for multimodal neuroimaging data
2026
Meenu Ajith*, I. Batta*, Vince Calhoun | IEEE
Journal: 2026 60th IEEE Annual Asilomar Conference on Signals, Systems, and Computers Pages: (invited) ,
Conditioned Graph Reconstruction of Brain Functional Network Connectivity Reveals Interpretable Latent Axes of Sex and Fluid Intelligence
2026
I. Batta, Meenu Ajith, Vince Calhoun | Cold Spring Harbor Laboratory
Journal: bioRxiv Pages: 2026-02 ,
Default mode network functional connectivity as a transdiagnostic biomarker of cognitive function
2025
Vaibhav Tripathi, I. Batta, Andre Zamani, Daniel A Atad, Sneha KS Sheth, Jiahe Zhang, Tor D Wager, Susan Whitfield-Gabrieli, Lucina Q Uddin, Ruchika S Prakash, et al. | Elsevier
Journal: Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
The interplay between brain and behavior during development: A multisite effort to generate and share simulated datasets
2025
Neda Sadeghi, Isabelle F van der Velpen, Bradley T Baker, I. Batta, Kyle J Cahill, Sarah Genon, Ethan McCormick, L'e9a C Michel, Dustin Moraczewski, Masoud Seraji, et al. | Nature Publishing Group UK London
Journal: Scientific Data Pages: 473 , Volumes: 12 ,
Conditioned Graph Reconstruction of Brain Functional Network Connectivity Reveals Interpretable Latent Axes of Sex and Fluid Intelligence
2025
I. Batta*, Meenu Ajith*, Vince Calhoun | MIT Press
Journal: Network Neuroscience Pages: (under review) ,
A multimodal Neuroimaging-Based risk score for mild cognitive impairment
2024
Elaheh Zendehrouh, Mohammad SE Sendi, Anees Abrol, I. Batta, Reihaneh Hassanzadeh, Vince D Calhoun | Elsevier
Journal: NeuroImage: Clinical Pages: 103719 ,
Towards a multimodal neuroimaging-based risk score for mild cognitive impairment by combining clinical studies with a large (N> 37000) population-based study
2024
Elaheh Zendehrouh, Mohammad SE Sendi, Anees Abrol, I. Batta, Reihaneh Hassanzadeh, Vince Calhoun | Cold Spring Harbor Laboratory Preprints
Journal: medRxiv
Multimodal active subspace analysis for computing assessment oriented subspaces from neuroimaging data
2024
I. Batta, Anees Abrol, Vince D Calhoun, Alzheimer'92s Disease Neuroimaging Initiative, et al. | Elsevier
Journal: Journal of Neuroscience Methods Pages: 110109 , Volumes: 406 ,
Constrained Source-based Salience: Network-based Visualization of Deep Learning Neuroimaging Models
2024
I. Batta, Anees Abrol, Vince D Calhoun | IEEE
Journal: IEEE International Conference on Biomedical and Health Informatics (IEEE-BHI)
A Novel Deep Subspace Learning Framework to Automatically Uncover Assessment-Specific Independent Brain Networks
2024
I. Batta, Anees Abrol, Vince Calhoun | IEEE
Journal: 2024 58th Annual Conference on Information Sciences and Systems (CISS) Pages: 6-Jan ,
Searching Reproducible Brain Features using NeuroMark: Templates for Different Age Populations and Imaging Modalities
2024
Zening Fu, I. Batta, Lei Wu, Anees Abrol, Oktay Agcaoglu, Mustafa S Salman, Yuhui Du, Armin Iraji, Sarah Shultz, Jing Sui, et al. | Academic Press
Journal: NeuroImage Pages: 120617 , Volumes: 292 ,
ENIGMA-Meditation: Worldwide consortium for neuroscientific investigations of meditation practices
2024
Saampras Ganesan, Fernando A Barrios, I. Batta, Clemens CC Bauer, Todd S Braver, Judson A Brewer, Kirk Warren Brown, Rael Cahn, Joshua A Cain, Vince D Calhoun, et al. | Elsevier
Journal: Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
What do we really know about the interplay between brain, behavior, and cognition from childhood to early adulthood? An international group effort to generate and share simulated datasets.
2024
Neda Sadeghi, Isabelle Van Der Velpen, Bradley Baker, I. Batta, Sarah Genon, Ethan M McCormick, Lea Michel, Dustin Moraczewski, Jeffrey Bruce Morton, Masoud Seraji, et al. | OSF
Journal: OSF Preprints
A Multimodal Deep Learning Approach for Automated Detection and Characterization of Distinctly Salient Features of Alzheimers Disease
2023
I. Batta, Anees Abrol, Vince Calhoun | IEEE
Journal: 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI) Pages: 4-Jan ,
Building models of functional interactions among brain domains that encode varying information complexity: A schizophrenia case study
2022
I. Batta, Anees Abrol, Zening Fu, Adrian Preda, Theo GM van Erp, Vince D Calhoun | Springer US New York
Journal: Neuroinformatics Pages: 777-791 , Volumes: 20 ,
Learning active multimodal subspaces in the brain
2022
I. Batta, Anees Abrol, Zening Fu, Vince D Calhoun | IEEE
Journal: 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) Pages: 3822-3825 ,
SVR-based Multimodal Active Subspace Analysis for the Brain using Neuroimaging Data
2022
I. Batta, Anees Abrol, Vince D Calhoun, Alzheimer'92s Disease Neuroimaging Initiative | Cold Spring Harbor Laboratory
Journal: bioRxiv Pages: 2022-07 ,
Neuroimaging PheWAS (phenome-wide association study): a free cloud-computing platform for big-data, brain-wide imaging association studies
2021
Lu Zhao*, I. Batta*, William Matloff, Caroline O'92Driscoll, Samuel Hobel, Arthur W Toga | Springer US
Journal: Neuroinformatics Pages: 285-303 , Volumes: 19 ,
A Multimodal Learning Framework to Study Varying Information Complexity in Structural and Functional Sub-Domains in Schizophrenia
2021
I. Batta, Anees Abrol, Zening Fu, Vince Calhoun | IEEE
Journal: 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI) Pages: 994-998 ,
A weighted network analysis framework for the hourglass effect'97And its application in the C. elegans connectome
2021
I. Batta, Qihang Yao, Kaeser M Sabrin, Constantine Dovrolis | Public Library of Science San Francisco, CA USA
Journal: PLOS ONE Pages: e0249846 , Volumes: 16 ,
Uncovering Active Structural Subspaces Associated with Changes in Indicators for Alzheimer'92s Disease
2021
I. Batta, Anees Abrol, Vince Calhoun | IEEE
Journal: 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) Pages: 3948-3951 ,
Parity is associated with cognitive function and brain age in both females and males
2020
Kaida Ning, Lu Zhao, Meredith Franklin, Will Matloff, I. Batta, Nibal Arzouni, Fengzhu Sun, Arthur W Toga | Nature Publishing Group UK London
Journal: Scientific Reports Pages: 6100 , Volumes: 10 ,
Varying Information Complexity in Functional Domain Interactions in Schizophrenia
2020
I. Batta, Anees Abrol, Zening Fu, Vince Calhoun | IEEE
Journal: 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE) Pages: 1042-1047 ,
Regularized topological data analysis for extraction of coherent brain regions
2019
I. Batta, Nicolas Honnorat, Christos Davatzikos | SPIE
Journal: SPIE Medical Imaging 2019: Image Processing Pages: 131-136 , Volumes: 10949 ,
Teaching Engagements
Miscellaneous
I am currently a faculty member (assistant professor) at the Mehta Family School of Data Science and Artificial Intelligence (MFSDSAI), Indian Institute of Technology Roorkee (IITR). My research lies at the intersection of machine learning and neuroscience, with a focus on developing interpretable representation learning methods for high-dimensional multimodal neuroimaging data to uncover biologically meaningful signatures of brain disorders and cognitive function.
Before joining IIT Roorkee, I was a postdoctoral research associate at the tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), GSU/GAtech/Emory, Atlanta, USA. I completed my Ph.D. in Electrical and Computer Engineering at the Georgia Institute of Technology (Georgia Tech), USA in 2023, advised by Dr. Vince Calhoun. Prior to my graduate studies, I received a dual degree (B.Tech. and M.Tech.) in Computer Science and Engineering from the Indian Institute of Technology Delhi (IIT Delhi) in 2017.
My work has introduced a suite of novel frameworks spanning active subspace learning, deep learning-based interpretation, and conditional generative modeling, aimed at ensuring both predictive performance as well as neurobiological interpretability in brain imaging studies.
If you are interested in working with me, please drop me an email highlighting your experience, interests and any proposed ideas.
