Kia Ghods

I am a second-year undergraduate at Princeton University , studying math + cs. I am broadly interested in the intersection of machine learning and cognitive science.

I am a researcher in Princeton's Neuroscience of Cognitive Control Lab , where I work on developing computational cognitive science approaches to understanding large vision and language models.

At Princeton, I am Head Editor of the Newsletter & Staff Writer for The Daily Princetonian, Outreach Officer for Princeton's ACM chapter, Officer of AI@Princeton, and a member/co-organizer of various machine learning related reading groups.

Outside of academics, I am an avid fan of both playing and watching basketball and tennis. I also enjoy reading, writing, and am learning the piano.

You can reach me at [x] at princeton dot edu where [x] = kia.ghods

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Research

My research has spanned a variety of fields, including applied mathematics, computational cognitive science, and drug discovery. Below is a list of papers and projects highlighting my prior research.

Understanding the Limits of Vision Language Models Through the Lens of the Binding Problem

Validation of a Multi-Strain HIV Within-Host Model with AIDS Clinical Studies

We validated a HIV within-host model using two data sets and found it to be structurally identifiable, estimating that the average time for a resistant strain to emerge is 844 days. In the unique patient case, all parameters except the mutation rate were practically identifiable.

Modeling the interplay between albumin-globulin metabolism and HIV infection

HIV infection is a significant public health issue, and while the role of nutrition, particularly albumin and globulin, in HIV progression is recognized, no mathematical models have previously described their interaction with the virus. In this paper, we present a model that accurately describes this interaction, revealing that albumin and globulin do not impact the infection rate or immune response, and identify that better data could improve our understanding of these dynamics. I presented this work at various venues, most notably at The Global Health Leaders Conference at Johns Hopkins University (2022).

Development of covalent binders of c-Myc mRNA

I synthesized covalent binders to target cancer-linked c-Myc RNA and repeated genetic patterns (i.e. r(CAG) expansion). This work was presented at the Max Planck Florida Institute for Neuroscience .