Sina Jamalzadegan

Postdoctoral Scholar · UC Santa Cruz Genomics Institute

Sina Jamalzadegan, Ph.D.

I work on AI for biosensing, and that phrase has to carry two halves that usually sit in different buildings. The materials half decides what can be measured at all: liquid metals, plasmonic nanoparticles, flexible substrates. The biology half decides what a measurement means: CRISPR, RNA, organoids, genomes. I build the model layer that carries a signal from one half to the other, and I have peer-reviewed work on both sides of it.

Chemical engineer by training, now at a genomics institute. The through-line across every project is the same question: how do you take a signal that is noisy, low-cost, and field-deployable, and make it trustworthy enough to act on?

The wearable behind that question caught tomato spotted wilt virus four days after infection, before any visible symptom. Science Advances, 2023, covered by The Wall Street Journal, Nature Food, and Nature Plants.

Sina Jamalzadegan

News

  1. Jun 2026Received the James K. Ferrell Outstanding Ph.D. Graduate Award from the NC State Department of Chemical and Biomolecular Engineering. Announcement
  2. Jul 2026First paper from my postdoc at UC Santa Cruz: Virtual Brain Organoids, under review at Trends Open (Cell Press).
  3. May 2026From Sensor to Solution: Grounded LLM Interfaces for Equitable, Smartphone-Based Pathogen Surveillance published in Frontiers in Sensors. DOI
  4. Mar 2026Started as a postdoctoral scholar at the UC Santa Cruz Genomics Institute, working on AI and high-performance computing for genomics.
  5. Jan 2026Contributed to Humanity's Last Exam, a 2,500-question expert benchmark for AI, published in Nature. DOI

All news and press coverage

Research

Five connected threads. Each one is a different attack on the same problem: closing the gap between what a cheap sensor physically measures and what a person actually needs to decide.

From Sensor to Solution: biosensor inputs pass through a grounded multimodal LLM and a quality-control stage, then route to retest, refer, or report.
01AI agents for biosensing. A measurement is not a decision. Grounded models read raw sensor output, check it against a version-controlled knowledge base rather than against what the model remembers, and return retest, refer, or report.
HueBase AI pipeline: literature intelligence, a unified dye-analyte-solvent feature space, an XGBoost engine, and a dye-by-solvent probability matrix.
02AI-guided sensor discovery. HueBase AI predicts how an analyte and a dye will interact before anyone makes anything, narrowing a library of thousands to a handful worth synthesizing. Sensor design becomes a search problem instead of a screen.
Adaptive liquid metal technologies: EGaIn branching into plasmonics, laser-tunable infrared emissivity, and soft biosensors.
03AI for materials discovery. How the plasmonic resonance of EGaIn nanoparticles shifts with shape and size, computed across the space rather than measured at a few points. The output is a design map, not a single device.
Plant VOC Intelligence: needle-based vegetable phenotyping, a leaf-clip wearable, and smartphone colorimetric disease detection feeding a shared AI layer.
04Wearable sensors for plant and human health. A leaf-mounted patch, a needle probe, and a smartphone-read colorimetric array all feed one model layer. The patch behind this line caught tomato spotted wilt virus four days after infection, well ahead of any visible symptom.
CRISPR diagnostics: Cas12 and Cas13 collateral cleavage feeding point-of-care, pathogen, food-safety, environmental, agricultural, and biomarker applications.
05CRISPR and smartphone molecular diagnostics. Cas12 and Cas13 collateral cleavage used as a detection primitive, then carried out of the lab: no thermocycler, no plate reader, no trained operator, and attomolar sensitivity for HIV-1 read on a phone camera.
01 AI agents for biosensing 02 AI-guided sensor discovery 03 AI for materials discovery 04 Wearable sensors for plant and human health 05 CRISPR and smartphone molecular diagnostics

Read the research in full

Selected publications

The paper the rest of the work is built on, three journal covers, and the current first-author work.

  1. G. Lee, O. Hossain, S. Jamalzadegan, Y. Liu, H. Wang, A. C. Saville, T. Shymanovich, R. Paul, D. Rotenberg, A. E. Whitfield, J. B. Ristaino, Y. Zhu, and Q. Wei. Abaxial Leaf Surface-Mounted Multimodal Wearable Sensor for Continuous Plant Physiology Monitoring. Science Advances, 2023, 9(4), eade2232. DOI Covered by The Wall Street Journal, Nature Food, Nature Plants, NC State News
  2. S. Jamalzadegan, J. Xu, Y. Shen, B. Mativenga, M. Li, M. Zare, A. Penumudy, Z. Hetzler, Y. Zhu, and Q. Wei. Advancing Wearable VOC Sensors: A Roadmap for Sustainable Agriculture and Real-Time Plant Health Monitoring. Chemical & Biomedical Engineering Journal, 2025, 2, 460–474. DOI Cover
  3. S. Jamalzadegan, M. Zare, M. J. Dickens, F. Schenk, A. Velayati, M. Yarema, M. D. Dickey, and Q. Wei. Shape and Size-Dependent Surface Plasmonic Resonances of Liquid Metal Alloy (EGaIn) Nanoparticles. Nanoscale, 2025, 17, 22819–22833. DOI Cover
  4. M. Bagi, S. Jamalzadegan, A. Steksova, and Q. Wei. CRISPR-Cas Based Platforms for RNA Detection: Fundamentals and Applications. Chemical Communications, 2025, 61, 13571–13600. DOI Cover
  5. S. Jamalzadegan, A. Penumudy, M. Eghbali, S. Moghaddam, M. F. Hamedani, and Q. Wei. From Sensor to Solution: Grounded LLM Interfaces for Equitable, Smartphone-Based Pathogen Surveillance. Frontiers in Sensors, 2026, 7, 1826260. DOI

All publications and preprints

Get in touch

I am looking for collaborators on AI agents for biosensing and on AI-enhanced computational biology, chemistry, and materials, co-authors for perspectives and reviews in those fields, and seminar invitations.

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What I am looking for, in detail