Curriculm Vitea

EDUCATION

Michigan State University

MAY 2018 - July 2023

Erskine College

AUGUST 2014 - MAY 2018


TEACHING AND MENTORING EXPERIENCE

Assistant Professor of Physics

AUGUST 2023-PRESENT

Responsible for teaching classes and supervising labs for the physics major and minor as well as the data science major and minor. Classes taught include General Physics II, Machine Learning and Neural Networks, Quantum Mechanics, and Data Acquisition, as well as General Physics I and General Physics II laboratory courses.

Visiting Researcher-Center for Computing in Science Education

SEPTEMBER 2022-DECEMBER 2022

Collaborated with physics education researchers at the Center for Computing in Science Education (CCSE) at the University of Oslo in Oslo, Norway.

Classical Mechanics Graduate Teaching Assistant

JANUARY 2021-MAY 2021 || JANUARY 2022-May 2022

Assisted with all aspects of teaching classical mechanics.  This included acting as a facilitator and instructor during class and holding office hours, in addition to writing and grading homework and exams.  Additionally, in the Spring of 2022, aiding in curriculum development to transition the class to a half-flipped and hybrid classroom format.

Undergraduate Research Mentor

MAY 2021-DECEMBER 2021 || MAY 2022 - PRESENT

Mentor and supervise undergraduates as they perform research projects in nuclear many-body theory.  I have currently mentored seven undergraduates from Michigan State University and two students from the National Science Foundation's Research Experience for Undergraduates program.

INSIGHT Program Instructor

JUNE 2021

Designed and taught a one-week intensive class on scientific Python for the Institute for Nuclear Science to Inspire the Next Generation of a Highly Trained Workforce (INSIGHT) program at FRIB, a program for minorities and underrepresented students majoring in physics at historically minority colleges across the nation.

Introductory Mechanics Graduate Teaching Assistant

JANUARY 2021-MAY 2021

Held nine office hours per week to assist students with their assignments and understanding of the subject.

P-Cubed and EMP-Cubed Graduate Teaching Assistant

AUGUST 2018- DECEMBER 2020

Assisted with all aspects of teaching P-Cubed and EMP-Cubed, flipped format classrooms for introductory mechanics and electricity and magnetism, respectively.  This included acting as a facilitator during class and holding office hours, in addition to writing and grading exams.

Chemistry and Physics Lab Assistant

August 2015-MAY 2018

Assisted with the preparation, clean-up, and instruction of chemistry and physics labs, ranging from introductory to advanced level in addition to performing general laboratory maintenance. 

Supplemental Instruction Leader

AUGUST 2015-MAY 2015

Aided students by holding twice-weekly sessions to review the material covered in class and to assist with homework problems.  Was assigned to General Chemistry I and II, General Physics I and II, Introduction to Statistics, and Calculus I.

PUBLICATIONS


SERVICE

American Physics Society Topical Group on Data Science (GDS)

FEBRUARY 2022 - PRESENT

RESEARCH EXPERIENCE

Improving the Accuracy of Infinite Matter Calculations with Machine Learning, Relatistic Potentials, and Three-Body Forces

FEBRUARY 2023-JUNE 2023

Worked to improve the accuracy of coupled cluster calculations of infinite matter by including realistic nuclear interactions, three-body forces to allow for coupled cluster triples calculations, and using machine learning to accelerate the convergence of calculations with respect to the number of single-particle states and the number of particles.  This work was performed as part of the DOE SCGSR fellowship (awarded September 2022).

Applications of Machine Learning to Studies of Infinite Nuclear Matter

MAY 2018-JULY 2023

Developed machine learning software and write many-body physics codes which will improve the ability to study infinite nuclear matter from a theoretical perspective.  Many-body methods of interest are many-body perturbation theory, coupled-cluster theory, and the in-medium similarity renormalization group.

Solving Many-Body Methods with Deep Learning and Cloud Computing

OCTOBER 2019-MAY 2020

Performed as part of the Michigan State University Cloud Computing Fellowship.  Used virtual machines on Microsoft’s Azure cloud computer to drastically decrease the run time needed to perform hyperparameter tuning on machine learning algorithms with many-body applications.

Rotational Analysis of Beryllium Isotopes with JISP16 and Daejeon16 Interactions

MAY 2017 - JULY 2017

Performed as part of the Research Experience for Undergraduates (REU) program.  Wrote scripts and performed data analysis on the output of nuclear many-body codes to compare the performance of two different interactions when studying the nucleus of several isotopes of beryllium.

Determination of the Aluminum Background Signal in the Qweak Experiment

MAY 2016 - AUGUST 2016

Performed as part of the Research Experience for Undergraduates (REU) program. Wrote scripts and performed data analysis in an attempt to remove a source of experimental error from the data generated by the Qweak experiment which ran at Jefferson National Laboratory.

Parallelization of the Method of Feasible Directions

MARCH 2017 - MAY 2018

Parallelized an implementation of the method of feasible directions, an optimization code.  Compared the performance of the serial and parallel versions of the code on a small cluster of computers.

Water Purification Abilities of Titania Photocatalyst

JANUARY 2016 - MAY 2018

Analyzed the ability of titania nanoparticles to degrade common agricultural antibiotics when exposed to direct sunlight.  The titania nanoparticles were adhered to UV-transparent acrylic and the degradation of the antibiotics was analyzed using high-performance liquid chromatography.  

VOLUNTEER EXPERIENCE

Social Media Coordinator for the American Physic Society's Topical Group for Data Science (APS GDS)

AUGUST 2022 - PRESENT

Instructor for the Due West Robotics Club

NOVEMBER 2016-MAY 2017

Taught middle school and high school-aged members of the Due West Robotics Club electronics and programming through the use of Arduino microcontrollers.

AWARDS, SCHOLARSHIPS, AND FELLOWSHIPS

U.S. Department of Energy (DOE) Office of Science Graduate Student Research Fellowship (SCGSR)

A highly competitive and prestigious award that provides recipients with funding to complete part of their thesis research at a DOE national laboratory under the supervision of a DOE scientist.  My award allowed by to complete part of my thesis research at Oak Ridge National Laboratory under the supervision of Dr. Gustav Jansen.

Colleges' Online Learning Academy (COLA) Fellowship

Recipients are provided with funding for the development of online learning resources which will be incorporated into classes at Michigan State University.  I created a literature review of digital textbooks and explored creating digital textbooks with a software called Jupyter Books.

Data Science Community of Practice (DSECOP) Fellowship

Recipients are provided with funding for the development of modules that introduce data science and machine learning into standard physics classrooms.  I created two modules that can be used to incorporate machine learning into undergraduate physics classes: Solving Differential Equations with Neural Networks, which introduces students in a classical mechanics course to neural networks, and The Machine Learning Workflow, which introduces students in introductory mechanics laboratory classes to the machine learning workflow through linear regression.  Both of these modules are avaliable at: https://github.com/GDS-Education-Community-of-Practice/DSECOP.

Outstanding Graduate Student: Graduate TA Award, Advanced Course

Awarded to teaching assistants in advanced physics classes.  Recipients are chosen by the professors of the classes.

National Science Foundation Graduate Research Fellowship Honorable Mention 

Cloud Computing Fellowship

Awarded to fifteen Michigan State University graduate students with funding to pursue an investigation into the use of cloud computing in thesis research projects. HERE

Outstanding Graduate Student: Graduate TA Award, Introductory Course

Awarded to teaching assistants in introductory physics classes.  Recipients are chosen by the professors of the classes.

Dr. Everett Askins Sloan Outstanding Senior Award

Awarded to the most outstanding senior in the physical sciences.

Faculty Endowed Scholarship

Awarded to the most promising student from the junior class.

WORKSHOPS

Association for American Physics Teachers First Year Teaching Institute (FTI)

NOVEMBER 2023

The purpose of this institute is to provide new physics faculty members with the skills and knowledge needed to build authentic styles of teaching. Topics covered include active learning and teaching, and reflective teaching, among other topics.

Data Science Education Community of Practices (DSECOP) June Workshop

JUNE 2022

Sponsored by the University of Maryland and the American Physics Society DSECOP division.  The topic of the workshop was “Data Science Education in Physics Curriculum”.  Involved lectures on integrating data science and machine learning into physics classes of all levels.

Oslo Physics Education Research Summer Institute

JUNE 2022

Sponsored by the University of Oslo’s Center for Computing in Science Education.  Involved talks and workshops related to many current topics in physics education research including integrating computation in physics classes and upper-level physics instruction

Certification in College Teaching Institute

MAY 2021

Sponsored by Michigan State University Graduate School.  Involved a lecture component, group discussions, and written assignments.  Covered topics such as curriculum development, teaching philosophies, and teaching portfolios.

ECT* TALENT School: Machine Learning Applied to Nuclear Physics: Experiment and Theory

JUNE 2020

Sponsored by the European Center for Theoretical Studies in Nuclear Physics and Related Areas.  Involved a lecture component and hands-on programming sessions.  Covered many topics in machine learning that can be applied in the physical sciences.

FRIB Theory Alliance Summer School on Machine Learning Applied to Nuclear Physics

MAY 2019

Sponsored by the Facility for Rare Isotope Beams.  Involved a lecture component and hands-on programming sessions.  Covered many topics in machine learning that can be applied in the physical sciences.

SKILLS

Education

Physics

Programming

SELECTED PRESENTATIONS

Using Bayesian Machine Learning to Extend the Range of Ab-Initio Many-Body Calculations for Infinite Matter Systems

MARCH 2024, Abstract Submitted

Extending the Range of Nuclear Many-Body Calculations with Bayesian Machine Learning

NOVEMBER 2023

Nuclear Physics as an Interdisciplinary Field

NOVEMBER 2023

Introduction to Data Science Libraries

JUNE 2023

Application of Machine Learning to Studies of Infinite Nuclear Matter

OCTOBER 2022

Machine Learning in the Undergraduate Physics Curriculum

OCTOBER 2022

Application of Machine Learning to Studies of Infinite Nuclear Matter

September 2022

Using Neural Networks to Solve Differential Equations in Classical Mechanics

JUNE 2022

Better Support for Students in Classical Mechanics Through a Flipped Classroom and Hybrid Approach

JUNE 2022

Application of Kernel Ridge Regression to Predict Energies of Many-Body Systems

MAY 2022

Better Support for Students in Classical Mechanics Through a Flipped Classroom Approach

MARCH 2022

Application of Machine Learning to Studies of Infinite Nuclear Matter

OCTOBER 2021

Coupled Cluster Theory Applied to Infinite Matter: A Review and Initial Results

APRIL 2021

An Introduction to Cloud Computing for Physicists

APRIL 2021

Deep Learning and the Many-Body Problem

NOVEMBER 2019

Parallelization of the Method of Feasible Directions

MARCH 2018

Iron-Modified TiO2 for the photocatalytic degradation of tetracycline and tylosin

MARCH 2018

Rotational Analysis of Beryllium Isotopes Using JISP16 and Daejeon16 Interactions

OCTOBER 2017

Determination of the Aluminum Background Signal in the Qweak Experiment

APRIL 2017

Determination of the Aluminum Background Signal in the Qweak Experiment

OCTOBER 2016

REFERENCES

Morten Hjorth-Jensen

THESIS ADVISOR


Johannes Pollanen

FORMER TEACHING SUPERVISOR, THESIS COMMITTEE MEMBER


Joel Boyd

FORMER RESEARCH ADVISOR


A downloadable PDF copy of my CV is avaliable here.