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update stomps profile page (including orcid) #221

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Sep 9, 2023
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update stomps profile page (including orcid) #221

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43 changes: 37 additions & 6 deletions community/people/js/index.md
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Expand Up @@ -5,25 +5,56 @@ image: stomps.jpg
role: PhD Candidate
email:
- [email protected]
room: "434 Engineering Research Building"
address: "1500 Engineering Dr"
google_map: "https://www.google.com/maps/place/Engineering+Dr,+Madison,+WI+53706/@43.0722638,-89.4132024,17z/data=!4m5!3m4!1s0x8807acc6ec542427:0x8e97163cfd1719a0!8m2!3d43.0722638!4d-89.4110137"
city_state_zip: "Madison, WI 53706"
room: "Oak Ridge National Laboratory"
address: "1 Bethel Valley Road"
google_map: "https://goo.gl/maps/TEF15a3HJ7wUUeba9"
city_state_zip: "Oak Ridge, TN 37831"
services:
email: [email protected]
github: stompsjo
linkedin: jordan-stomps-556912b8
orcid: 0000-0001-7811-4479
scholar: TD8qHhkAAAAJ&hl
---

## Biography

Jordan’s research focuses on machine learning applications to nuclear
nonproliferation. In particular, he is using gamma radiation measurements
collected for the NNSA NA-22 Multi-Informatics for Nuclear Operations
Scenarios testbed at Oak Ridge National Laboratory to train models
capable of detecting shielded radiological material transfers.
State-of-the-art artificial intelligence techniques require large volumes
of labeled data to train a successful model. Characterizing radiation
data often involves manual analysis by subject-matter experts which is
time consuming, resource intensive, and unfeasible for leveraging machine
learning. Jordan is addressing this by using semi-supervised machine
learning to utilize labeled and unlabeled radiation measurements to design
models that can be used for more informed decisions and resource
efficiency in nuclear security. His research is supported by the NNSA
Consortium for Enabling Technology and Innovation (ETI) under the
computer and engineering sciences for nonproliferation thrust. Originally
from Detroit, Jordan spends his free time gardening and cooking with his
wife, daughter, and dog.

For more information on recent research, please review [this publication](https://www.mdpi.com/2673-4362/4/3/32).

## Research Interests


* Gen. IV Nuclear Reactors
* Computational Modeling Methods
* Semi-Supervised Machine Learning
* Nuclear Nonproliferation
* Artificial Intelligence
* Data Science and Analysis
* Fuel Cycle Analysis
* Scientific Computing
* Radiation Detection
* Anomaly Detection

## Education


* University of Wisconsin, Madison, WI [PhD. Graduate Student, Nuclear Engineering & Engineering Physics]
* University of Wisconsin, Madison, WI [M.S. Nuclear Engineering & Engineering Physics, 2021]
* Michigan State University, East Lansing, MI [BS Physics, 2019]