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PAVEL CHVYKOV

Physics and Complexity Science researcher
Machine Learning professional
Mindfulness practitioner and explorer

Image by Yuhan Du

PH.D. RESEARCH AT MIT (2013-20)

How do structures self-organize in our complex world? Or are we just good at finding subtle patterns in the chaos?

In my work I explored both these possibilities using tools from dynamical systems theory, statistical mechanics, and information theory, as well as experiments with robotic swarms. See this blog post for an overview, and my research page for more details.

[Adviser: Jeremy England]

Highlight: my research was featured in Science Magazine as a breakthrough in our understanding of self-organization

WORK AT GENERAL MOTORS (2021- )

Researching ways to coordinate Machine Learning models and align their performance with company's goals

The operations of a company as large as GM naturally forms a complex ecosystem of many interacting parts. The emergent collective properties of such systems are often hard to anticipate. I research ways to leverage Machine Learning tools to understand, predict, and optimize company-wide patterns, and to study the feedback effects ML has on this ecosystem.

Image by Stefan Rodriguez
Network

CURRENT RESEARCH INTERESTS

The "paradoxes" of out-of-equilibrium interaction networks

I am interested in understanding how the social fabric of our lives emerges from the network structure of our interactions. It seems that common misconceptions and social issues can arise from faulty assumptions about this network (like equilibrium or ergodicity). 

I use networks of Machine Learning algorithms as a fruitful proxy for social networks with regard to these questions. 

 
 

OTHER INTERESTS

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OUTREACH AND TEACHING

Whether helping to develop and teach at a program in Applied Math in Senegal, assisting graduate physics courses at MIT, or developing and running new demos with the MIT museum based on Tadashi's "Math Toys" - teaching and mentoring has been an integral part of my scientific journey.

Lately, my work at GM gave me new opportunities to share the big-picture perspective provided by complexity science with my colleagues and the broader company - giving invited lectures, starting a seminar series, and speaking at internal conferences. 

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BLOG OF SCIENTIFIC BRAINSTORMING

This is my creative outlet for big ideas, unrealized research projects, and near-scientific speculations about various aspects of life, universe, and the scientific endeavour. 

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TRAVEL

I have been traveling on-and-off since 2008 - whether by working and studying in different countries, going to conferences and workshops, or being a digital nomad. I am a minimalist and enjoy living out of a carry-on backpack for years at a time. I find that travel keeps me real about fundamental truths I can believe about the world, and culture-specific opinions that quickly break down in other contexts. 

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MINDFULNESS AND MENTAL HEALTH

Our reality arises in the interaction between the inner and the outer. Having made understanding of "the outer" my profession, I have then been digging into understanding "the inner" over the last 5 years. I have come to appreciate that this research is no less profound or elegant than physics. I have completed many courses in various mindfulness traditions, such as Vipassana, Non-Violent Communication, Circling, Radical Honesty, and Tantra Yoga, and have taught workshops in some of them.

My deeper interest here is to bring more of the rationalist approach and the scientific method into these practices to help de-segregate science and spirituality. 

Check out some of my blog posts on this, e.g. this one

 

BRIEF BACKGROUND

  • B.Sc.: University of Michigan, U.S. - Physics and Math, with experimental work on laser systems and condensed matter 

    • 1 year study-abroad at Oxford University, U.K.

  • M.Sc: Perimeter Institute, Canada - Theoretical physics, thesis on asymptotically safe quantum gravity

  • Gap-year: teaching at a master’s program in applied math in Senegal

  • Ph.D. + 1 year post-doc: Massachusetts Institute of Technology, U.S., thesis "On typicality and adaptation in driven dynamical systems"

  • Machine Learning scientist at General Motors: understanding and predicting behavior of GM's logistics network; AI alignment