I am a postdoctoral researcher at Memorial Sloan Kettering Cancer Center’s Department of Medical Physics. With my advisors, Dr. Allen Tannenbaum & Dr. Joseph Deasy, I’m researching machine learning and graph analysis methods with applications in cancer. I enjoy working in sync with clinicians and biologists to go after pragmatic unsolved questions.

While the focus of my research remains creating novel computer vision and machine learning methods, I have applied those tools to a variety of problems. Selected publications below are organized by application topic.

The full list of publications can be found on Google Scholar. Curriculum vitae is here.

Newest publication – Multiple Myeloma & Graph Analysis

Using Ollivier-Ricci curvature (a measure of network robustness), we identified 118 genes previously unassociated with MM that identify a high risk subtype.

A.K. Simhal, K.H. Maclachlan, R. Elkin, J. Zhu, L. Norton, J.O. Deasy, J.H. Oh, S.Z. Usmani, A. Tannenbaum. “Gene interaction network analysis in multiple myeloma detects complex immune dysregulation associated with shorter survival.” 2023. bioRxiv.

Graph Analysis & Diffusion Tensor MRI

These papers were the first to use a measure of network robustness, Ollivier-Ricci curvature, to analyze DTI images of children with ASD. The papers showed the differences in brain connectivity before and after a stem cell transfusion.

A. K. Simhal, K. L. H. Carpenter, J. Kurtzberg, A. Song, A. Tannenbaum, L. Zhang, G. Sapiro, G. Dawson. “Changes in the geometry and robustness of diffusion tensor imaging net- works: secondary analysis from a randomized controlled trial of young autistic children receiving an umbilical cord blood infusion.” 2022. Frontiers in Psychiatry.

A. K. Simhal, K. L. H. Carpenter, S. Nadeem, J. Kurtzberg, A. Song, A. Tannenbaum, G. Sapiro, G. Dawson. “Measuring robustness of brain networks in autism spectrum disorder with Ricci curvature.” 2020. Scientific Reports.

Cervical Cancer & Machine Learning (SVM models)

We developed an image processing pipeline to automate detections of various cervical lesions taken via a pocket colposcope.

M. N. Asiedu, A. K. Simhal, U. Chaudhary, J. L. Mueller, C. T. Lam, J. W. Schmitt, G. Vene- gas, G. Sapiro, and N. Ramanujam. “Development of algorithms for automated detection of cervical pre-cancers with a low-cost, point-of-care, pocket colposcope.” 2018. IEEE Transactions on Biomedical Engineering.

M. N. Asiedu, A. K. Simhal, C. T. Lam, J. Mueller, U. Chaudhary, J. W. Schmitt, G. Sapiro, and N. Ramanujam. “Image processing and machine learning techniques to automate diag- nosis of lugol’s iodine cervigrams for a low-cost point-of-care digital colposcope.” 2018. Optics and Biophotonics in Low-Resource Settings IV. Volume 10485. International Society for Optics and Photonics.

Autism Spectrum Disorders & Random Forest Models

The first paper uses random forest (RF) models to figure what helps kids with ASD successfully complete MRI scans. The second uses RF to model survey data to examine what helped kids with ASD through the COVID-19 pandemic.

A. K. Simhal, J. O. A. Filho, P. Segura, J. Cloud, E. Petkova, R. Gallagher, F. X. Castellanos, S. Col- combe, M. P. Milham, A. D. Martino. “Predicting multiscan MRI outcomes in children with neurodevelopmental conditions following MRI simulator training.” 2021. Developmental Cognitive Neuroscience.

B. Vibert, …, A. K. Simhal, …, A. D. Martino. “CRISIS AFAR: An International Collaborative Study of the Impact of the COVID-19 Pandemic on Youth with Autism and Neurodevelopmental Conditions.” 2023. Molecular Autism.

Synapse Biology & Image Processing

This trio of papers presents a novel unsupervised method for synapse detection. The method, designed for array tomography, detects and characterizes synapses and astrocytes in mouse brain tissue. The method was used to examine synaptic differences in mouse models of fragile X syndrome, a type of ASD. I’ve presented this work at various meetings and multiple labs have adapted the methodology into their pipelines.

A. K. Simhal, Y. Zuo, M. M. Perez, D. V. Madison, G. Sapiro, and K. D. Micheva. “Multifaceted changes in synaptic composition and astrocytic involvement in a mouse model of fragile x syndrome.” 2019. Scientific Reports.

A. K. Simhal, B. Gong, J. S. Trimmer, R. J. Weinberg, S. J. Smith, G. Sapiro, and K. D. Micheva. “A computational synaptic antibody characterization tool for array tomography.” 12, 2018. Frontiers in Neuroanatomy.

A. K. Simhal, C. Aguerrebere, F. Collman, J. T. Vogelstein, K. D. Micheva, R. J. Weinberg, S. J. Smith, and G. Sapiro. “Probabilistic fluorescence-based synapse detection.” 2017. PLoS Computational Biology.

Published software tools

• Ollivier-Ricci curvature for brain connectivity analysis (MATLAB)
• Probabilistic synapse detection (MATLAB)
• Probabilistic synapse detection (Python)
• Synaptic antibody characterization tool (Python)

Posters

Posters that I’ve presented at conferences can be found here. A full list of conference presentations is listed on my CV.