Kalie Knecht, PhD

Kalie Knecht, PhD

Kalie is an Applied Data Scientist working at the intersection of radiation detection, multimodal sensor fusion, robotics, and machine learning.

Posts by Collection

portfolio

publications

Evaluating 3D Gamma-ray Imaging Techniques for Distributed Sources at the Fukushima Daiichi Nuclear Power Station

Published in 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2020

Polaris-Lamp,a commercially available detector that has been integrated with contextual sensors, was hand-carried in a parking lot containing vehicles used during remediation efforts following the March 2011 Fukushima Daiichi Nuclear Power Station accident.

Recommended citation: K. Knecht et. al., "Evaluating 3D Gamma-ray Imaging Techniques for Distributed Sources at the Fukushima Daiichi Nuclear Power Station," in Proc. NSS/MIC, 2020, pp. 1-5. https://ieeexplore.ieee.org/abstract/document/9507840/

Polaris-LAMP: Multi-modal 3D Image Reconstruction with a Commercial Gamma-ray Imager

Published in IEEE Transactions on Nuclear Science, 2021

The Polaris-LAMP multi-modal 3D gamma-ray imager is a radiation mapping and imaging platform which uses a commercial-off-the-shelf detector integrated with a contextual sensor localization and mapping platform.

Recommended citation: J. Hecla and K. Knecht et. al.. "Polaris-LAMP: Multi-modal 3D Image Reconstruction with a Commercial Gamma-ray Imager" IEEE Trans. Nucl. Sci., vol. 68, no. 10, pp. 2539-2549, Oct. 2021, doi: 10.1109/TNS.2021.3110162. https://ieeexplore.ieee.org/abstract/document/9528363/

3D Compton Imaging of Distributed Sources around the Chernobyl Nuclear Power Plant

Published in 2021 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2021

Here, we present results employing Compton image reconstruction in combination with SDF of data that were collected over series of 20-50 minute dynamic measurements around Pripyat, a nearby town which has been abandoned since the accident in 1986 and in some locations within ChNPP.

Recommended citation: K. Knecht et. al., "3D Compton Imaging of Distributed Sources around the Chernobyl Nuclear Power Plant," in Proc. NSS/MIC, 2021, pp. 1-4. https://ieeexplore.ieee.org/abstract/document/9507840/

From the Field

Published in Berkeley Science Review Spring 2022, 2022

Late in the night on April 26, 1986, Chornobyl Nuclear Power Plant Unit 4 was scheduled for routine safety testing. Preparations for testing left the reactor in an unstable condition, resulting in a meltdown followed by explosions that destroyed the reactor building and released radioactive material for many days after.

Recommended citation: K. Knecht, "From the Field," in Proc. NSS/MIC, 2022.

Scene-Informed Optimization of Measurement Locations for Radiological Assessment

Published in 2022 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2022

Polaris-Lamp,a commercially available detector that has been integrated with contextual sensors, was hand-carried in a parking lot containing vehicles used during remediation efforts following the March 2011 Fukushima Daiichi Nuclear Power Station accident.

Recommended citation: K. Knecht et. al., "Scene-Informed Optimization of Measurement Locations for Radiological Assessment," in Proc. NSS/MIC, 2022.

Scene-Informed Optimal Measurement Positions for Quantitative Safeguards Measurement

Published in 2023 INMM & ESARDA Joint Annual Meeting, 2023

Portable radiation detection systems can be equipped with contextual sensors to allow free-moving 3D gammaray imaging through scene data fusion (SDF). While developed for free-moving measurements, SDF also has applications in cases that require multiple static measurements to generate quantitative 3D images, where the scene information can improve results. The scene information captured by these devices can be leveraged to determine optimal measurement positions for quantification measurements, such as in safeguards applications, where limited time is provided to quantify nuclear material present. In this work the scene information obtained from contextual sensors is used to construct a 3D voxel grid.

Recommended citation: K. Knecht et. al., "Scene-Informed Optimal Measurement Positions for Quantitative Safeguards Measurement," in Proc. INNM & ESARDA Joint Annual Meeting, 2023. https://resources.inmm.org/annual-meeting-proceedings/scene-informed-optimal-measurement-positions-quantitative-safeguards

Enhanced use of contextual data for quantitative Compton Imaging

Published in 2023 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2023

In this work the scene information obtained from contextual sensors is used to construct a 3D voxel grid. A 3D object of interest within this grid is selected by an operator either manually or automatically through an object detection machine learning framework. A number of potential measurement positions and orientations (poses) around this object of interest are identified, and the sensitivity to each of the object voxels from each of these poses is computed.

Recommended citation: K. Knecht et. al., "Enhanced use of contextual data for quantitative Compton Imaging," in Proc. NSS/MIC, 2023.

Enhanced use of contextual data for quantitative gamma-ray imaging in nuclear safeguards applications

Published in University of California, Berkeley Dissertation, 2025

In this work the scene information obtained from contextual sensors is used to construct a 3D voxel grid. A 3D object of interest within this grid is selected by an operator either manually or automatically through an object detection machine learning framework. A number of potential measurement positions and orientations (poses) around this object of interest are identified, and the sensitivity to each of the object voxels from each of these poses is computed.

Recommended citation: K. Knecht et. al., "Enhanced use of contextual data for quantitative gamma-ray imaging in nuclear safeguards applications," Dissertation No. 31297598, University of California, Berkeley, 2024. Available: https://escholarship.org/uc/item/3627r1jx.

talks

Evaluating 3D Gamma-ray Imaging Techniques for Distributed Sources at the Fukushima Daiichi Nuclear Power Station

Published:

Portable radiation detection systems can be equipped with contextual sensors to allow free-moving 3D gamma-ray imaging in a method called scene data fusion (SDF). The scene information provided by the contextual sensors can be used to enable 3D imaging and constrain image reconstruction to improve imaging accuracy and computational efficiency. SDF could be a useful tool in many applications, including radiation mapping for contamination remediation. To demonstrate this concept, Polaris-LAMP, a commercially available detector that has been integrated with contextual sensors, was operated in a parking lot of some of the vehicles that were used in the cleanup of the March 2011 Fukushima Daiichi Nuclear Power Station accident. Proximity mapping and Compton imaging techniques are applied to the data collected over a series of short measurements in this parking lot. These reconstruction techniques created accurate 3D maps of gamma-ray sources and successfully identified hot spot candidates on key features of vehicles in the parking lot, demonstrating the usefulness of SDF in radiation mapping of unknown distributed source environments.

3D Compton Imaging of Distributed Sources around the Chernobyl Nuclear Power Plant

Published:

Portable radiation detection systems can be equipped with contextual sensors to allow free-moving 3D gamma-ray imaging in a method called scene data fusion (SDF). The scene information provided by the contextual sensors can be used to enable 3D imaging and constrain image reconstruction to improve imaging accuracy and computational efficiency. SDF could be a useful tool in many applications, including radiation mapping for accident remediation. To demonstrate this concept, Polaris-LAMP, a commercially available detector that has been integrated with contextual sensors, was operated in and around the Chernobyl Nuclear Power Plant. Compton imaging techniques are applied to the data collected over a series of 20-50 minute dynamic measurements around Pripyat, a nearby town which has been abandoned since the accident. These reconstruction techniques created 3D maps of gamma-ray sources and successfully identified hot spot candidates on key features of the scenes investigated, demonstrating the usefulness of SDF in radiation mapping of unknown distributed source environments. The contextual data captured by Polaris-LAMP also generated interesting visual products of scenes around Pripyat.

Scene-informed Optimization of Measurement Locations for Radiological Assessments

Published:

Portable radiation detection systems can be equipped with contextual sensors to allow free-moving 3D gamma-ray imaging in a method called scene data fusion (SDF). The scene information provided by the contextual sensors can be used to enable 3D imaging and constrain image reconstruction to improve imaging accuracy and computational efficiency. While developed for free-moving measurements, SDF also has applications in cases that require multiple static measurements to generate 3D images, where the scene information can improve results. The scene information captured by these devices can be leveraged to determine optimal measurement positions for quantification measurements, such as in safeguards applications, where limited time is provided to quantify nuclear material present. In this work we are utilizing the 3D scene information obtained from an initial survey to create a measurement space that allows the determination of optimal positions and orientations (pose) of an instrument to assess radiological materials of interest. We will present our approach and results for performing an optimization to quantify properties of interest in low count rate environments and the minimization of associated uncertainties. %For quantification in low count rates, it is desired to have maximum and uniform sensitivity to the object of interest. Optimization techniques are developed to determine the measurement positions which best fulfill this criteria.

Scene-informed Optimal Measurement Positions for Quantitative Safeguards Measurements

Published:

Portable radiation detection systems can be equipped with contextual sensors to allow free-moving 3D gamma-ray imaging through scene data fusion (SDF). While developed for free-moving measurements, SDF also has applications in cases that require multiple static measurements to generate quantitative 3D images, where the scene information can improve results. The scene information captured by these devices can be leveraged to determine optimal measurement positions for quantification measurements, such as in safeguards applications, where limited time is provided to quantify nuclear material present.

Enhanced Use of Contextual Data for Quantitative Compton Imaging

Published:

Contextual sensors can be equipped to radiation detection systems to allow free-moving 3D gamma-ray imaging through scene data fusion. Scene data fusion captures relevant scene information to construct a 3D map of an environment, which can be used to constrain image reconstruction techniques. While developed to enable free-moving imaging measurements, scene data fusion also has applications in cases that require multiple static measurements to generate 3D images, where the scene information can improve results. One way we seek to further leverage contextual scene information is to use the 3D map to automatically identify the radiological object of interest in a scene, and then determine optimal measurement poses around that object for quantitative Compton imaging. We also seek to improve the use of contextual information by identifying materials present in an environment to inform attenuation estimates for intervening materials. We present the approach for further leveraging the contextual information, and the preliminary results of using an SDF-enabled gamma-ray imager to find optimal measurement positions for a distributed source scenario to produce quantitative Compton images with minimization of associated uncertainties.

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

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