PDF: CV_Lynn

Education:

• University of Pennsylvania, Philadelphia, PA

• Swarthmore College, Swarthmore, PA

Research experience:

Research Interests: Statistical mechanics, information theory, computational neuroscience, cognitive science, network science

• Princeton University and City University of New York, Center for the Physics of Biological Function

• University of Pennsylvania, Departments of Bioengineering & Electrical and Systems Engineering

• University of Pennsylvania, Department of Electrical and Systems Engineering

• Fermi National Laboratory, Accelerator Physics Center

• University of Texas, Austin, Institute for Computational Engineering and Sciences

• Swarthmore College, Department of Physics and Astronomy

Grants & awards:

• James S. McDonnell Foundation Postdoctoral Fellowship. 2020.

• Complexity Postdoctoral Fellowship at the Santa Fe Institute. 2020 (declined for JSMF Fellowship).

• Sackler Colloquium Travel Award. 2019.

• APS Division of Biological Physics (DBIO) Shirley Chan Student Travel Grant. 2019.

• President Gutmann Leadership Award, University of Pennsylvania. 2018.

• School of Arts and Sciences Graduate Student Government (SASgov) Travel Grant. 2018.

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

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

• 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.

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

• Werner Teutsch Memorial Prize, University of Pennsylvania. 2015.

• High Honors in Physics, Swarthmore College. 2014.

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

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

Invited talks:

• Christakis Group, Yale University. February, 2024.

• Function and emergence of irreversibility in neural systems. CCN Junior Theoretical Neuroscientists Symposium, Flatiron Institute. June, 2023.

• Emergence and function of irreversibility in neural systems. From Non-equilibrium Physics to Life Sciences. Rome, Italy, April, 2023. | YouTube

• Statistical physics of brain network function and structure. Department of Cognitive Science, University of California, San Diego. February, 2023.

• Emergent scale-free networks. Network Science Institute, Northeastern University. February, 2023.

• Statistical physics of brain network function and structure. School of Engineering, Brown University. February, 2023.

• Statistical physics of emergence and dynamics in neural systems. Department of Physics and QBio Institute, Yale University. February, 2023. | YouTube

• Human learning and information processing with complex networks. Lombrozo Group, Princeton University. December, 2022.

• Energy, function, and irreversibility in the brain. The thermodynamics of natural & artificial computational systems, Santa Fe Institute. August, 2022.

• Emergence of irreversibility and heavy-tailed connectivity in neuronal networks. Institute of Neuroscience, University of Oregon. August, 2022.

• Heavy-tailed neuronal connectivity arises from Hebbian self-organization. Shine Group, University of Sydney. July, 2022.

• Emergence and function of irreversibility in neural systems. Centre for Eudaimonia and Human Flourishing, University of Oxford. June, 2022.

• Structure and stochastic thermodynamics of brain networks. The future of the thermodynamics of computation, Santa Fe Institute. November, 2021. | YouTube

• Broken detailed balance and entropy production in neural systems. Dynamics of the off-equilibrium brain, Santa Fe Institute. July, 2021.

• Compressibility of complex networks. Networks seminar, University of Oxford. February, 2021.

• Compressibility of complex networks. DCIST, Army Research Lab, University of Pennsylvania. January, 2021.

• Non-equilibrium dynamics and entropy production in the human brain. Sporns and Betzel Groups, Indiana University. June, 2020.

• Human learning and information processing in complex networks. Swarthmore College. February, 2020. | YouTube 1 | YouTube 2

• The statistical mechanics of human behavior. Princeton-CUNY Center for the Physics of Biological Function. January, 2020.

• Quantifying how humans learn and receive information from communication networks. Army Research Lab Visit, University of Pennsylvania. January, 2020.

• The statistical mechanics of human behavior. Santa Fe Institute. January, 2020.

• Human learning and information processing with complex networks. Poeppel Group, New York University. December, 2019.

• Human information processing in complex networks. Computational Linguistics Seminar, University of Pennsylvania. October, 2019.

• Human information processing in complex networks. Computational Neuroscience Initiative, University of Pennsylvania. September, 2019.

• Human information processing in complex networks. Plotkin Group, University of Pennsylvania. July, 2019.

• Influence Maximization in Ising Networks. Sompolinsky Group, Center for Brain Science, Harvard University. February, 2017.

• Simulation of Channeling Radiation in Diamond. Fermi National Laboratory. August, 2013.

Contributed talks:

• Heavy-tailed neuronal connectivity arises from Hebbian self-organization. APS March Meeting. Las Vegas, NV, March, 2023.

• Decomposing the arrow of time in interacting systems. Workshop on Stochastic Thermodynamics III. June, 2022. | YouTube

• Decomposing the arrow of time in interacting systems. APS March Meeting. Chicago, IL, March, 2022.

• Compressibility of complex networks. CompleNet. May, 2021.

• Human information processing in complex networks. APS March Meeting. March, 2021.

• Structure from noise: Mental errors yield abstract representations of events. APS March Meeting. Boston, MA, March, 2019.

• Structure from noise: Mental errors yield abstract representations of events. Conference on Complex Systems. Thessaloniki, Greece, September, 2018.

• Surges of collective human activity emerges from simple pairwise correlations. Conference on Complex Systems. Thessaloniki, Greece, September, 2018.

• Surges of collective human activity emerges from simple pairwise correlations. CompleNet. Boston, MA, March, 2018.

• Surges of collective human activity emerges from simple pairwise correlations. APS March Meeting. Los Angeles, CA, March, 2018.

• Maximizing Activity in Ising Networks via the TAP Approximation. Association for the Advancement of Artificial Intelligence. New Orleans, LA, February, 2018.

• Influence Maximization in Ising Networks. APS March Meeting. New Orleans, LA, March, 2017.

Refereed posters:

• Exactly solvable statistical physics model of large neuronal populations. COSYNE. Montreal, Canada, March, 2023.

• Heavy-tailed connectivity arises from Hebbian self-organization. COSYNE. Lisbon, Portugal, March, 2022.

• Human information processing in complex networks. Interdisciplinary Advances in Statistical Learning. San Sebastian, Spain, June, 2019.

• Structure from noise: Mental errors yield abstract representations of events. Context & Episodic Memory Symposium. Philadelphia, PA, May, 2019.

• Human information processing in complex networks. Sackler Colloquium: Brain Produces Mind by Modeling. Irvine, CA, May, 2019.

• Structure from noise: Mental errors yield abstract representations of events. Emory Theoretical Biophysics Workshop. Atlanta, GA, January, 2019.

• Structure from noise: Mental errors yield abstract representations of events. Conference on Cognitive and Computational Neuroscience. Philadelphia, PA, September, 2018.

• Maximizing Influence in an Ising Network: A Mean-Field Optimal Solution. Advances in Neural Information Processing Systems. Barcelona, Spain, December, 2016.

Teaching experience:

• Guest Lecturer:

  • Network Neuroscience, Department of Bioengineering, University of Pennsylvania. Fall 2019.

  • Network Neuroscience, Department of Bioengineering, University of Pennsylvania. Fall 2017.

• Teaching Assistant:

  • Biophysics, Department of Physics, Princeton University. Spring 2021.

  • Networked Life, Department of Networked and Social Systems Engineering, University of Pennsylvania. Fall 2015.

  • Principles II (Electricity & Magnetism), Department of Physics and Astronomy, University of Pennsylvania. Spring 2015.

  • Principles I (Classical Mechanics), Department of Physics and Astronomy, University of Pennsylvania. Fall 2014.

Academic service:

• Organization:

  • Chair of focus session “Statistical mechanics of the brain”, APS March Meeting, 2023.

  • Co-organizer of “The thermodynamics of natural & artificial computational systems”, Santa Fe Institute, 2022.

  • Co-organizer of “The future of the thermodynamics of computation”, Santa Fe Institute, 2021.

  • Organizing committee for CPBF Symposia, City University of New York, 2020 - Present.

  • Organizing committee for Biophysics Seminar Series, Princeton University, 2020 - Present.

• Reviewer: Physical Review Letters, Science Advances, Journal of Neuroscience, NeurIPS, NeuroImage, Communications Physics, Scientific Reports, Physical Review Research, Progress in Neurobiology, Entropy (reviewer board), Journal of Complex Networks, Neuroscience Letters, Network Science, Chaos, Collective Intelligence, IEEE CDC.