About Me
Hey there! I'm Manash. I'm currently in my third year of graduate school at the University of Houston pursuing my PhD in Developmental, Cognitive, and Behavioral Neuroscience. In short, I'm interested in creating software solutions and algorithms that make behavioral research more accessible, efficient, and reproducible. I developed and currently maintain several open-source tools for data pre-processing and analysis. Outside of academics, I love video games, everything Gundam/Gunpla, and hanging out with my 11-year old pup Holly.
Development
I love computer science. I use my knowledge to develop free and open-source tools that allow researchers to easily pre-process data. I'm most fluent in MATLAB, but also proficient in C/C++, Python, R, and JavaScript.
Data Analysis
I leverage a diverse array of statistical and computational tools to gain deep insights into data. I'm knowledgable in simple statistical techniques like N-way-ANOVAs, A/B testing, and linear mixed effects models as well as more complex techniques like unsupervised and deep learning.
Pipeline Design
I use a variety of tools and methodologies, including Python and MATLAB for ETL/ELT, to design and implement efficient data processing pipelines for behavioral research, working with high-density behavioral and physiological data, among other data types.
Projects
Reconstructing Gaze in the Real World: A Proof of Concept
Using markerless pose estimation and projective geometry to effectively create a unitary representation of the human body and gaze as it exists within the 3-dimensional environment. Presented at DCBN Brown Bag Seminar 2026.
(Write-up Coming Soon)Multimodal Physiological States Underlie Infant Visual Attention
Using K-Means clustering and probability density distributions to understand how heart rate, respiration rate, and body movement interact during moments of low gaze velocity. Presented at MindBrainBody Symposium 2026.
View PosterCaregiver Prosody is Contingent on Infant Sustained Visual Attention
Using linear modeling, time-series clustering, and time-series bootstrap permutation tests to understand the function of infant-directed speech. Presented at the IEEE International Conference of Development and Learning (ICDL) 2025.
View PosterTonaFlow: A Free and Open Source Software for ECG Pre-Processing
A simple-to-use GUI-based software for wavelet-based filtering, artifact removal, R-peak detection, and calculation of heart-rate from raw electrocardiogram (ECG) signals.
View ProjectBoids
My implementation of "Boids" using P5.js. A flocking simulation demonstrating emergent behavior from simple behavioral rules.
View ProjectPublications
J.I. Borjon, M.K. Sahoo, K.D. Rhodes, R. Lipschutz, & J.R. Bick, Recognizability and timing of infant vocalizations relate to fluctuations in heart rate, Proc. Natl. Acad. Sci. U.S.A. 121 (52) e2419650121, https://doi.org/10.1073/pnas.2419650121 (2024).
Alviar, C., Sahoo, M., Edwards, L. A., Jones, W., Klin, A., & Lense, M. (2023). Infant-directed song potentiates infants' selective attention to adults' mouths over the first year of life. Developmental Science, 26, e13359. https://doi.org/10.1111/desc.13359
Bambha, V. P., Franklin, B. E., Sahoo, M., Le, G. X., Dubois, B. E., Martinez, D., … Borjon, J. I. (2026). Toward a biologically grounded understanding of autonomic function in developmental science. Neuroscience & Biobehavioral Reviews, 191, 106984. https://doi.org/10.1016/j.neubiorev.2026.106984