EDUCATION:

University of Pennsylvania, Philadelphia, PA
Ph.D. in Physics
GPA: 4.0
Advisors: Danielle S. Bassett & Daniel D. Lee
Expected 2019

Swarthmore College, Swarthmore, PA
B.A. in Physics with High Honors
B.A. in Mathematics
2014

 

RESEARCH EXPERIENCE:

Research Interests: Statistical mechanics of complex systems, behavioral network science, dynamical systems, control theory, machine learning

University of Pennsylvania, Departments of Bioengineering & Electrical and Systems Engineering
Graduate Research Assistant with Prof. Danielle S. Bassett
2017 – Present

University of Pennsylvania, Department of Electrical and Systems Engineering
Graduate Research Assistant with Prof. Daniel D. Lee
2015 – Present

Fermi National Laboratory, Accelerator Physics Center
Lee Teng Fellow in Accelerator Science and Engineering with Dr. Tanaji Sen
2013 – 2014

University of Texas, Austin, Institute for Computational Engineering and Sciences
Moncrief Undergraduate Intern with Prof. Dmitrii E. Makarov
2012

Swarthmore College, Department of Physics and Astronomy
Undergraduate Research Assistant with Prof. John Boccio
2011 – 2012

 

PUBLICATIONS:

Christopher W. Lynn, Lia Papadopoulos, Daniel D. Lee, and Danielle S. Bassett. Surges of collective human activity emerge from simple pairwise correlations. In Press. (arxiv.org/abs/1803.00118)

Christopher W. Lynn and Daniel D. Lee. Maximizing Activity in Ising Networks via the TAP Approximation. Association for the Advancement of Artificial Intelligence (AAAI). 2018. (arxiv.org/abs/1803.00110)

Christopher W. Lynn and Daniel D. Lee. Statistical Mechanics of Influence Maximization with Thermal Noise. EPL (Europhysics Letters) 117.6: 66001. 2017.

Christopher W. Lynn and Daniel D. Lee. Maximizing Influence in an Ising Network: A Mean-Field Optimal Solution. Advances in Neural Information Processing Systems (NIPS). 2016. (arxiv.org/abs/1608.06850)

Tanaji Sen and Christopher LynnSpectral Brilliance of Channeling Radiation at the ASTA Photoinjector. Journal of Modern Physics A 29.30: 1450179. 2014.

Ben Blomberg, Daniel Mihalcea, Harsha Panuganti, Philippe Piot, Charles Brau, Bo Choi, William Gabella, Borislav Ivanov, Marcus Mendenhall, Christopher Lynn, Tanaji Sen, Wolfgang Wagner. Planned High-brightness Channeling Radiation Experiment at Fermilab’s Advanced Superconducting Test Accelerator. International Particle Accelerator Conference (IPAC). 2014.

 

PRESENTATIONS:

Christopher W. Lynn, Lia Papadopoulos, Daniel D. Lee, and Danielle S. Bassett. Collective human activity emerges from simple pairwise interactions. CompleNet. Boston, MA, March, 2018.

Christopher W. Lynn, Lia Papadopoulos, Daniel D. Lee, and Danielle S. Bassett. Collective human activity emerges from simple pairwise interactions. APS March Meeting. Los Angeles, CA, March, 2018.

Christopher W. Lynn and Daniel D. Lee. Maximizing Activity in Ising Networks via the TAP Approximation. Association for the Advancement of Artificial Intelligence (AAAI). New Orleans, LA, February, 2018.

Christopher W. Lynn and Daniel D. Lee. Influence Maximization in Ising Networks. APS March Meeting. New Orleans, LA, March, 2017.

Christopher W. Lynn and Daniel D. Lee. Influence Maximization in Ising Networks. Center for Brain Science, Harvard University. Cambridge, MA, February, 2017.

Christopher W. Lynn and Daniel D. Lee. Maximizing Influence in and Ising Network: A Mean-Field Optimal Solution. Advances in Neural Information Processing Systems (NIPS). Barcelona, Spain, December, 2016.

Christopher W. Lynn and Tanaji Set. Simulation of Channeling Radiation in Diamond. Advanced Superconducting Test Accelerator, Fermi National Laboratory. Batavia, IL, August, 2013.

 

GRANTS & AWARDS:

Graduate and Professional Student Assembly (GAPSA) Research Student Travel Grant. 2018.

American Physical Society (APS) Group on Statistical & Nonlinear Physics (GSNP) Student Speaker Award Winner. 2018.

American Physical Society (APS) Division of Condensed Matter Physics (DCMP) Graduate Student Travel Award. 2018.

Association for the Advancement of Artificial Intelligence (AAAI) Student Scholarship. 2018.

STEM Pop Talks Competition Winner, University of Pennsylvania. 2017.
Best research talk among science and engineering graduate students and postdocs, as voted by a nonscientific audience.

Advances in Neural Information Processing Systems (NIPS) Graduate Travel Award. 2016.

Werner Teutsch Memorial Prize, University of Pennsylvania. 2015.
Awarded to the first-year physics graduate student who shows the most promise for outstanding achievement in research.

High Honors in Physics, Swarthmore College. 2014.
Awarded to students who exhibit excellence in Oxford-style written and oral examinations as part of the Honors Program at Swarthmore College.

Lee Teng Fellowship in Accelerator Science and Engineering, Fermi National Laboratory. 2013.

Moncrief Undergraduate Internship, University of Texas at Austin. 2012.

 

TEACHING EXPERIENCE:

Guest Lecturer, University of Pennsylvania:

Network Neuroscience, Department of Bioengineering. Fall 2017.

Teaching Assistant, University of Pennsylvania:

Networked Life, Department of Networked and Social Systems Engineering. Fall 2015.
Principles II (Electricity & Magnetism), Department of Physics and Astronomy. Spring 2015.
Principles I (Classical Mechanics), Department of Physics and Astronomy. Fall 2014.

 

ACADEMIC & COMMUNITY SERVICE:

Referee:

IEEE Conference on Decision and Control (CDC). 2017.
Advances in Neural Information Processing Systems (NIPS). 2016.

Founder & Organizer:

“Whiskey Seminar Series,” University of Pennsylvania. 2015 – Present.
A casual weekly forum for physics graduate students and postdocs to develop their presentation skills by giving talks about their research.

Volunteer Instructor:

Discovery Summer Camp at the Franklin Institute, Philadelphia, PA. 2015 – Present.
Collaborate with other science graduate students to plan and teach weekly workshops for children, with the goal of sparking interest in science and developing critical thinking skills.

Member:

Association for the Advancement of Artificial Intelligence. 2017 – Present.
American Physical Society. 2016 – Present.

 

CLASSES:

Adv Theoretical Phys: Intro to Renormalization (PHYS-696), Spring 2017.

Distributed Dynamical Systems (ESE-635), Fall 2016.

Computational Learning Theory (CIS-625), Spring 2016.

Advanced Statistical Mechanics (PHYS-612), Spring 2016.

Machine Learning (CIS-520), Fall 2015.

General Relativity (PHYS-503), Fall 2015.

Electromagnetic Phenomena (PHYS-516), Spring 2015.

Intro to Condensed Matter Physics (PHYS-518), Spring 2015.

Quantum Mechanics II (PHYS-532), Spring 2015.

Solid State Theory II (PHYS-662), Spring 2015.

Quantum Mechanics I (PHYS-531), Fall 2014.

Intro to Field Theory (PHYS-601), Fall 2014.

Statistical Mechanics (PHYS-611), Fall 2014.

 

PDF: Resume_Lynn

Skip to toolbar