The Applied Nuclear Physics Program at Lawrence Berkeley Lab: Advancing Radiation Detection Techniques through Coupling with Computer and Robotics Technologies

brianquiter
SPEAKER:

Dr. Brian Quiter

Staff Applied Physicist/Engineer and Deputy Program Head of the Applied Nuclear Physics Program

DATE/TIME:
MON, 01/29/2024 - 3:00PM TO 4:00PM
LOCATION:
3105 ETCHEVERRY HALL

Abstract:

Researchers in the Applied Nuclear Physics (ANP) program at Lawrence Berkeley National Laboratory have focused on developing new radiation detectors and radiation detection methods to solve problems related to mitigating the effects of nuclear disasters, preventing nuclear proliferation, enhancing nuclear security, and improving nuclear medicine. The new methods involve inducing and observing more esoteric signatures in a target medium, creating new radiation detectors to provide better information about distributions of radioactive material, and developing software and techniques to take advantage of the additional information these detection systems generate. This talk focuses on combining radiation detectors with robotics technologies to enable Scene Data Fusion (SDF) and the algorithmic work ANP has done to further improve the SDF technique for various applications.

Bio:

Dr. Quiter was educated at the University of California, Berkeley. He received his B.S. in Bio-Nuclear Engineering in 2003, his M.S. in 2005 for work related to the activation of neutrinoless double beta decay relevant materials, and his Ph.D. degree in Nuclear Engineering in 2010. Throughout his schooling, Dr. Quiter studied physics of, instrumentation for, and modeling of problems related to nuclear security applications such as nuclear detection problems, passive and active interrogation of intermodal cargo, pre-and post-detonation nuclear forensics, and nuclear safeguards. His Ph.D. thesis was entitled “Nuclear Resonance Fluorescence for Radioactive Materials Assay”. Dr. Quiter joined LBNL in August of 2010, was promoted to staff scientist in 2014 and Deputy Program Head of the Applied Nuclear Physics program in 2019. He has extensive experience modeling radiation transport and radiation detectors, coupling radiation sensors with robotics technologies, planning and performing radiological measurements in uncontrolled environments, and managing the vast and complicated data that multi-sensor systems can produce. Dr. Quiter leads a research portfolio comprising over a dozen scientists and engineers and maintains collaborations with academia, industry, and numerous other government laboratories.  

New Staff Announcement: Amanda Gill

New Staff Announcement: Amanda Gill

January 26, 2024

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The UC Berkeley Nuclear Engineering Department is excited to announce our new Student Services Advisor Amanda Gill.

For the past seven years, Amanda has served as the Associate Director for the Evening & Weekend MBA Program at the Haas School of Business. There, Amanda excelled in areas of academic advising, project & curricular management, and program leadership, ensuring smooth operations and an enriching experience for approximately 300 graduate students at any given time. Prior to joining Haas, Amanda served as a Program Coordinator for the UC Berkeley Extension.

Her many years of service are rife with acknowledgement for the exceptional work she's done guiding students. In addition to numerous Spot Awards, Amanda received an Outstanding Team Advising award in December 2016 and Outstanding Advisor award in December 2022, both of which were bestowed by the UC Berkeley Excellence in Advising Awards program. Amanda also received the Haas Outstanding Staff Award in May 2023.

Amanda's ties to Cal go back further than her close to 12 years as a staff member, having earned both a Bachelor of Arts in English and Master of Arts in Global Studies from UC Berkeley.

When Amanda isn't doing great work for the university and its students, she's an avid traveler, with visits to over 35 countries and all seven continents (most recently Antarctica in December 2022).

Constrained Bayesian Optimization of Experiments

Daniel Siefman
Daniel Siefman
SPEAKER:

Daniel Siefman

Assistant Professor 

DATE/TIME:
MON, 01/22/2024 - 3:00PM TO 4:00PM
LOCATION:
3105 ETCHEVERRY HALL

Abstract:

Engineering and research projects often involve optimizing a variable with respect to input parameters while respecting a constraint. For example, this might be optimizing the power production of a reactor by changing fuel parameters while maintaining a power peaking factor below a certain threshold. The design process can involve expensive modeling or physical experimentation, where the expense may be a combination of time, cost, manpower, or materials. Constrained Bayesian Optimization is a machine learning framework to optimize an engineered system while minimizing iterations of the resource intensive model or experiment. This seminar introduces the algorithm and shows its application to designing integral experiments for nuclear data validation, criticality safety, and advanced reactor neutronics mockups.

Bio:

Daniel Siefman became an assistant professor in the Nuclear Engineering Department in 2024. His research interests include critical and subcritical experiments and methods, nuclear data validation and adjustment, computational methods in radiation transport, neutron noise, reactor dosimetry, design optimization and safety analysis of nuclear reactors with machine learning, and nuclear power plant decommissioning. Daniel received a bachelor’s degree in Nuclear Engineering from the University of Florida in 2013, masters degrees in Nuclear Engineering from the École polytechnique fédérale de Lausanne (EPFL) and from ETH Zurich in 2015, and a PhD in Nuclear Engineering from EPFL in 2019. From 2019 to 2023, he was a staff scientist in the Nuclear Criticality Safety Division at Lawrence Livermore Laboratory supporting R&D efforts in integral experiments, nuclear data validation, radiation transport, neutron noise, and diagnostics for nuclear emergency response.

Spring 2024 Colloquium

Spring 2024 Colloquium Archive

Towards Scientific AI for the simulation and optimization of complex systems

April 15, 2024

DATE/TIME: MON, 04/15/2024 – 3:00PM TO 4:00PM LOCATION: 3106 ETCHEVERRY HALL SPEAKER: Raphael Pestourie Professor, Georgia Tech, School of Computational Science and Engineering Abstract: Complex systems are hard to simulate …

Emission Tomography: From Grayscale to Colorful Images One More Time

April 8, 2024

DATE/TIME: MON, 04/08/2024 – 3:00PM TO 4:00PM LOCATION: 3106 ETCHEVERRY HALL SPEAKER: Ling-Jian Meng, Ph.D Professor Department of Nuclear, Plasma, and Radiological Engineering, Department of Bioengineering, and Beckman Institute of …

High-field HTS stellarators with liquid metal walls

April 1, 2024

SPEAKER: Francesco Volpe Founder, CEO, CTO Renaissance Fusion DATE/TIME: MON, 04/01/2024 – 3:00PM TO 4:00PM LOCATION: 3106 ETCHEVERRY HALL Abstract: French- and Swiss-based startup Renaissance Fusion strives to build a …

eVinci Technology and the Potential of Microreactors

March 18, 2024

SPEAKER: Zach McDaniel Director, Partnerships and Grants DATE/TIME: MON, 03/18/2024 – 3:00PM TO 4:00PM LOCATION: 3106 ETCHEVERRY HALL Abstract: Westinghouse is developing the eVinci™ microreactor to revolutionize how cost-competitive, carbon-free …

Chasing the Light: What More We Can Learn from the X-ray and Tissue Interactions

March 11, 2024

SPEAKER: Dr. Ke Sheng Professor and Vice Chair of Medical Physics Department of Radiation Oncology DATE/TIME: MON, 03/11/2024 – 3:00PM TO 4:00PM LOCATION: 3106 ETCHEVERRY HALL Abstract: Traditional medical physics …

Advanced Reactors Overview at the Idaho National Laboratory

March 4, 2024

SPEAKER: Youssef A. Ballout Division Director, Reactor Systems Design & Analysis DATE/TIME: MON, 03/04/2024 – 3:00PM TO 4:00PM LOCATION: 3106 ETCHEVERRY HALL Abstract: Dr. Youssef Ballout will discuss the historical …

Adam Cunha

Brachytherapy State of the Art and Future Directions

February 26, 2024

SPEAKER: J. Adam M. Cunha Assistant Professor  DATE/TIME: MON, 02/26/2024 – 3:00PM TO 4:00PM LOCATION: 3106 ETCHEVERRY HALL Abstract: Radiation has been used for the treatment of cancer for over …

The Applied Nuclear Physics Program at Lawrence Berkeley Lab: Advancing Radiation Detection Techniques through Coupling with Computer and Robotics Technologies

January 29, 2024

SPEAKER: Dr. Brian Quiter Staff Applied Physicist/Engineer and Deputy Program Head of the Applied Nuclear Physics Program DATE/TIME: MON, 01/29/2024 – 3:00PM TO 4:00PM LOCATION: 3105 ETCHEVERRY HALL Abstract: Researchers …

Daniel Siefman

Constrained Bayesian Optimization of Experiments

January 22, 2024

SPEAKER: Daniel Siefman Assistant Professor  DATE/TIME: MON, 01/22/2024 – 3:00PM TO 4:00PM LOCATION: 3105 ETCHEVERRY HALL Abstract: Engineering and research projects often involve optimizing a variable with respect to input …

New Faculty Announcement: Daniel Siefman

Daniel Siefman

New Faculty Announcement: Daniel Siefman

January 10, 2024

Daniel Siefman
The UC Berkeley Nuclear Engineering Department is pleased to announce new assistant professor Daniel Siefman.
His research interests include critical and subcritical experiments and methods, nuclear data validation and adjustment, computational methods in radiation transport, neutron noise, reactor dosimetry, design optimization and safety analysis of nuclear reactors with machine learning, and nuclear power plant decommissioning.  Daniel received a bachelor’s degree in Nuclear Engineering from the University of Florida in 2013, masters degrees in Nuclear Engineering from the École polytechnique fédérale de Lausanne (EPFL) and from ETH Zurich in 2015, and a PhD in Nuclear Engineering from EPFL in 2019. From 2019 to 2023, he was a staff scientist in the Nuclear Criticality Safety Division at Lawrence Livermore Laboratory supporting R&D efforts in integral experiments, nuclear data validation, radiation transport, neutron noise, and diagnostics for nuclear emergency response.

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