Binghamton Researcher Studied Genetic Rheumatoid Factors

A Binghamton University PhD candidate is using artificial intelligence to investigate the genes behind rheumatic diseases.

Updated on Oct. 13, 2026 in Arthritis

A close-up, high-detail photograph of glowing fiber-optic strands creating a complex, interwoven network of blue light. — Binghamton University PhD candidate Neda Amiri Rad is utilizing advanced computational modeling to map the genetic origins of rheumatoid arthritis. AI Illustration. Upload story photo >

Neda Amiri Rad, a PhD candidate at Binghamton University, has dedicated her research to analyzing the genetic foundations of autoimmune conditions. Her work leverages artificial intelligence and network science to better understand the development of complex rheumatic diseases.

Why it matters

Amiri Rad conducts this critical research in memory of her mother, who passed away in 2018 due to complications from rheumatoid arthritis. Her study aims to provide deeper insights into the underlying causes of a disease that continues to impact millions of people globally.

According to 2021 data, 17.9 million people were living with rheumatoid arthritis worldwide. The research focus remains on the intersection of medicine and computational analysis to address these high global figures.

The players

Neda Amiri Rad

Neda Amiri Rad is an industrial and systems engineering PhD candidate at Binghamton University who utilizes AI and network science for medical research.

Binghamton University

Binghamton University is a public research institution in New York that provides institutional support and mentorship for advanced academic studies.

The details

Amiri Rad, who previously earned engineering degrees in Iran, utilizes computational modeling to map gene interactions related to autoimmune health. She is currently working within the industrial and systems engineering department at Binghamton University, supported by faculty mentorship.

Amiri Rad's mother died in 2018.
In 2021, 17.9 million people lived with rheumatoid arthritis worldwide.

The Big Picture

This research follows a pattern set by the intersection of AI and network science in genomics, applying computational rigor to characterize complex autoimmune pathways.

While this is currently academic research, the application of AI to gene mapping could eventually lead to more targeted diagnostic tools for autoimmune patients. These advancements aim to improve long-term outcomes for those currently living with chronic rheumatic conditions.

The takeaway

This work highlights the increasing role of computational engineering in solving complex biological mysteries. Readers can look toward advancements in AI-driven medicine as key milestones in modern efforts to manage autoimmune health.