Jennifer Tour Chayes
Jennifer Tour Chayes is Associate Provost of the
Division of Computing, Data Science, and Society
and Dean of the
School of Information
at the
University of California, Berkeley,
where she is also Professor of Electrical Engineering and Computer Sciences, Mathematics, Statistics, and Information.
She is deeply committed to increasing racial and gender diversity in science, technology, engineering, and mathematics (STEM).
Chayes’ research areas include phase transitions in computer science, structural and dynamical properties of networks
including graph algorithms, and applications of machine learning. She is one of the inventors of the field of graphons,
which are widely used for the machine learning of largescale networks. Her prior work in the modeling and analysis of
random, dynamically growing graphs, is used to model the internet, the World Wide Web, and social and economic networks.
Her more recent work focuses on machine learning, including applications in cancer immunotherapy, ethical decisionmaking,
and climate change. She is the coauthor of more than 150 scientific papers and the coinventor of 30 patents.
Prior to joining UC Berkeley in 2020, Chayes worked at Microsoft Research for 23 years. She was Technical Fellow and
Managing Director of Microsoft Research New England in Cambridge, Massachusetts, which she cofounded in 2008, Microsoft
Research New York City, which she cofounded in 2012, and Microsoft Research Montreal, which she cofounded in 2017.
Chayes developed Microsoft Research laboratories into worldrenowned multidisciplinary centers, bringing together
computer scientists, mathematicians, physicists, social scientists, and biologists. Chayes cofounded the Theory
Group at Microsoft Research and was Research Area Manager for Mathematics, Theoretical Computer Science, and Cryptography.
Among her contributions to Microsoft technologies are the development of methods to analyze the structure and behavior of
various networks, the design of auction algorithms, and the design and analysis of various business models for the online world.
Before working at Microsoft, Chayes was Professor of Mathematics at UCLA.
She has received numerous awards for leadership and scientific contributions, including the Anita Borg
Institute Women of Vision Leadership Award, the Society for Industrial and Applied Mathematics’ (SIAM) John
von Neumann Lecture Award, the Association for Computing Machinery’s (ACM) Distinguished Service Award, and
honorary doctorates from Bard College and Leiden University. Chayes is a member of the American Academy of
Arts and Sciences and the National Academy of Sciences. She is a fellow of the American Association for the
Advancement of Science, the American Mathematical Society, the Association of Computing Machinery, the
Association of Women in Mathematics, and the Fields Institute.
Chayes is a member of numerous advisory boards and steering and oversight committees, including the UC
Center for DataDriven Insights and Innovation, the UC Health Governance Task Force, Massachusetts Institute
of Technology’s (MIT) Institute for Data, Systems, and Society and Schwarzman College of Computing, Harvard
University’s Institute for Applied and Computational Science, the Howard Hughes Medical Institute (HHMI)
Janelia Campus, the International Centre for Theoretical Sciences in Bangalore, India, the Center for Minorities
and People with Disabilities in IT, the Systems and Machine Learning conference, the Climate Change AI initiative,
and the National Science Foundation’s (NSF) Institute for AI and Fundamental Interactions. She is also a member of
the selection committee for the VinFuture Prize.
She received a bachelor’s degree in biology and physics from Wesleyan University – graduating first in her class –
and earned her Ph.D. in mathematical physics at Princeton. She completed her postdoctoral work in mathematics
and physics at Harvard and Cornell.
Chayes is married to Christian Borgs, her primary scientific
collaborator and Professor of Electrical Engineering and Computer Sciences at UC Berkeley.
For more details, download the detailed CV
here.
Selected Publications
Graph Limits, Graphons and Nonparametric Network Models

Counting graph homomorphisms
(with C. Borgs, L. Lovasz, V. Sos, B. Szegedy and K. Vesztergombi)
in Topics in Discrete Mathematics (eds. M. Klazar, J. Kratochvil, M. Loebl, J. Matousek, R. Thomas, P. Valtr),
315371, Springer (2006). 

Graph limits and parameter testing
(with C. Borgs, L. Lovasz, V. Sos, B. Szegedy and K. Vesztergombi)
Proceedings of the 38rd Annual ACM Symposium on the Theory of Computing (STOC),
261270 (2006).


Convergent sequences of dense graphs I: Subgraph frequencies,
metric properties and testing
(with C. Borgs, L. Lovasz, V. Sos, and K. Vesztergombi)
Advances in Math. 219, 18011851 (2008).


Convergent sequences of dense graphs II: Multiway cuts and statistical physics
(with C. Borgs, L. Lovasz, V. Sos, and K. Vesztergombi)
Ann. of Math. 176, 151219 (2012).


Moments of twovariable functions and the uniqueness of graph limits
(with C. Borgs and L. Lovasz)
GAFA 19, 15971619 (2010).


Limits of randomly grown graph sequences
(with C. Borgs, L. Lovasz, V. Sos, K. Veszterbombi)
Eur. J. Comb. 32, 985999 (2011).


Left and right convergence of graphs with bounded degree
(with C. Borgs, J. Kahn, L. Lovasz)
Random Struct. Alg. 42, 128 (2013).


Asymptotic behavior and distributional limits of preferential attachment graphs
(with N. Berger, C. Borgs, A. Saberi) Ann. Probab. 42(1), 140 (2014).


Convergent sequences of sparse graphs: A large deviations approach
(with C. Borgs, and D. Gamarnik) Random Struct. Alg. 51, 5289 (2017). 

An L^{p} theory of sparse graph convergence I:
limits, sparse random graph models, and power law distributions
(with C. Borgs, H. Cohn and Y. Zhao).
Trans. Amer. Math. Soc. 372, 3019–3062 (2019).


An L^{p} theory of sparse graph convergence II:
LD convergence, quotients, and right convergence
(with C. Borgs, H. Cohn and Y. Zhao)
Annals of Prob. 45, 337396 (2018). 

Graphons: a nonparametric method to model, estimate, and design
algorithms for massive networks
(with C. Borgs).
Proceedings of the 18th ACM Conference on Economics and Computation (EC’17), 665–672, (2017). 

Sparse exchangeable graphs and their limits via graphon processes
(with C. Borgs, H. Cohn and N. Holden)
Journal of Machine Learning Research 18 (210), 171 (2018). 

Sampling perspectives on sparse exchangeable graphs
(with C. Borgs, H. Cohn, V. Veitch). Annals of Prob. 47 (5), 27542800 (2019). 

Identifiability for graphexes and the weak kernel metric
(with C. Borgs, H. Cohn, L. M. Lovasz).
In: I. Brny, G. Katona, A. Sali, Attila (Eds.),
Building Bridges II  Mathematics of Laszlo Lovasz. Bolyai Society Mathematical Studies, Vol. 28, 29–157 (2020).


Limits of sparse conguration models and beyond: graphexes and multigraphexes
(with C. Borgs, S. Dhara, and S. Sen). Preprint (2019). 

A correction to Kallenberg's theorem for jointly exchangeable random measures
(with C. Borgs, S. Dhara, and S. Sen). Preprint (2019). 

A large deviation principle for block models
(with C. Borgs, J. Gaudio, S. Petti and S. Sen). Preprint (2020). 
Mechanism Design, Social Choice and Recommendation Systems

Multiunit auctions with budgetconstrained bidders
(with C. Borgs, N. Immorlica, M. Mahdian and A. Saberi)
Proceedings of the 6th ACM Conference on Electronic Commerce (EC), 4451 (2005). 

Bid optimization in online advertisement auctions
(with C. Borgs, O. Etesami, N. Immorlica and M. Mahdian)
2^{nd} Workshop on Sponsored Search Auctions (2006) and
Proceedings of the 16th international conference on World Wide Web (WWW), 531540 (2007). 

The myth of the folk theorem
(with C. Borgs, N. Immorlica, A. Kalai, V. Mirrokni
and C. Papadimitriou)
Proceedings of the 40th Annual ACM Symposium on the Theory of Computing (STOC)
(2008).


Trustbased recommendation systems: An axiomatic approach
(with R. Andersen, C. Borgs, U.Feige, A. Flaxman, A. Kalai, V. Mirrokni and M. Tennenholtz)
Proceedings of the 17th international conference on World Wide Web (WWW),
199208 (2008).


A novel approach to propagating distrust
(with C. Borgs, A. Kalai, A. Malekiany, M. Tennenholtz)
Proceedings of the 6th International Workshop on Internet and Network Economics
(WINE) 87105 (2010).


Gametheoretic models of information overload in social networks
(with C. Borgs, B. Karrer, B. Meeder, R. Ravi, R. Reagans and A. Sayedi)
Proceedings of the 7th Workshop on Algorithms and Models for the Web Graph (WAW) 146161 (2010).


Fast convergence of natural bargaining dynamics in exchange
networks
(with Y. Kanoria, M. Bayati, C. Borgs and A. Montanari)
Proceedings of the 22nd ACMSIAM Symposium on Discrete Algorithm (SODA) 15181537 (2011).


The hitchhiker's guide to affiliation networks: A gametheoretic approach
(with C. Borgs, J. Ding and B. Lucier)
Proceedings of the 2nd Symposium on
Innovations in Computer Science (ICS) 389400 (2011).


Pricing and queuing
(with C. Borgs, S. Doroudi, M. HarcholBalter, K. Xu)
SIGMETRICS Performance Evaluation Review 40(3): 7173 (2012).


Priority pricing in queues with a continuous distribution of customer valuations
(with S. Doroudi, M. Akan, M. HarcholBalter, J. Karp, C. Borgs)
CMU technical report CMUCS13109 (2013).


The optimal admission threshold in observable
queues with state dependent pricing
(with C. Borgs, S. Doroudi, M. HarcholBalter, K. Xu)
Probability in the Engineering and Informational Sciences 28, 101110 (2014). 

Optimal multiperiod pricing with service guarantees
(with O. Candogan,
C. Borgs, I. Lobel, and H. Nazerzadeh) Management Science 60, 17921811 (2014).


Bargaining dynamics in exchange networks
(with M. Bayati, C. Borgs,
Y. Kanoria and A. Montanari) J. Econ. Theory 156, 417454 (2015).


An axiomatic approach to community detection
(with C. Borgs, A. Marple, and S.H. Teng)
Proceedings of the 2016 ACM Conference on Innovations in Theoretical Computer Science (ITCS '16), 135146
(2016).


Thy friend is my friend: iterative collaborative filtering for sparse matrix estimation
(with C. Borgs, C.E. Lee, D.Shah).
Advances in Neural Information Processing Systems (NIPS) 30, 4718–4729, (2017). 

Iterative collaborative filtering for sparse matrix estimation
(with C. Borgs, C.E. Lee, D.Shah). Preprint (2017). 
Machine Learning, Estimation and Responsible AI

Statistical mechanics of Steiner trees
(with M. Bayati, A. Braunstein, A. Ramezanpour, and R. Zecchina)
Physical Review Letters 101, 037208 14 (2008), reprinted in
Virtual Journal of Biological Physics Research 16, August 1 (2008).


BeliefPropagation for weighted bmatchings on arbitrary graphs and its relation to linear programs with integer solutions
(with M. Bayati, C. Borgs and R. Zecchina)
SIAM Journal of Discrete Mathematics, 25, 9891011 (2011).


Private graphon estimation for sparse graphs
(with C. Borgs and A. Smith)
Advances in Neural Information Processing Systems (NIPS) 28, 13691377 (2015). 

Full version of the above paper. 

Consistent nonparametric estimation for heavytailed sparse graphs
(with C. Borgs, H. Cohn and S. Ganguly)
preprint (2015). 

Unreasonable effectiveness of learning neural networks: From accessible states and robust ensembles to basic algorithmic schemes
(with C. Baldassi, C. Borgs, A. Ingrosso, C. Lucibello, L. Saglietti, and R. Zecchina).
Proceedings of the National Academy of Sciences
(PNAS) 113, E7655–E7662 (2016).


EntropySGD: biasing gradient descent into wide valleys
(P. Chaudhari, A. Choromanska, S. Soatto, Y. LeCun,
C. Baldassi, C. Borgs, J.T. Chayes, L. Sagun and R. Zecchina).
International Conference on Learning Representations (ICLR), 119 (2017).


Revealing network structure, condentially: improved rates for node
private graphon estimation
(with C. Borgs, A. Smith, I. Zadik).
Proceedings of the 59 th Annual IEEE Symposium on Foundations of Computer Science (FOCS),
533543 (2018).


Bias in bios: a case study of semantic representation
bias in a highstakes setting
(M. DeArteaga, A. Romanov, H. Wallach, J. Chayes, C. Borgs, A. Chouldechova,
S. Geyik, K. Kenthapadi, A. Kalai).
Proceedings of the 2nd Conference on Fairness,
Accountability, and Transparency (FAT* '19), 120128 (2019). 

What’s in a name? Reducing bias in bios without access to
protected attributes.
(A. Romanov, M. DeArteaga, H. Wallach, J. Chayes, C. Borgs, A. Chouldechova, S.
Geyik, K. Kenthapadi, A. Kalai). Proceedings of the 16th
Annual Conference of the North American Chapter
of the Association for Computational Linguistics (NAACL '19). Best Paper Award. 

Algorithmic greenlining: an approach to increase diversity
(with C. Borgs, N. Haghtalab, A. Kalai and E. Vitercik). AIII / ACM Conference on Artificial
Intelligence, Ethics and Society (AIES) ), 69–76 (2019). 

The disparate equilibria of algorithmic decisionmaking when individuals
invest rationally
(L. Liu, A. Wilson, N. Haghtalab, A. Kalai, C. Borgs, and J.T.
Chayes). Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (FAT* '20), 381–391 (2020). 
Computational Biology

A multifactorial model of T Cell expansion and durable clinical benefit
in response to a PDL1 inhibitor
(M. Leiserson, V. Syrgkanis, A. Gilson, M. Dudik, S. Gillett, J. Chayes,
C. Borgs, D.F. Bajorin, J. Rosenberg, S. Funt, A. Snyder,
L. Mackey).
Preprint (2018).


Finding undetected protein associations in cell signaling by belief propagation
(with M. BaillyBechet, C. Borgs, A. Braunstein, A.Dagkessamanskaia,
J. Francois, and R. Zecchina). Proceedings of the National Academy of Sciences
(PNAS) 108, 882887 (2011).


Simultaneous reconstruction of multiple signaling pathways via the
prizecollecting Steiner forest problem
(N.Tuncbag, A.Braunstein, A.Pagnani, S.C.Huang, J.Chayes, C.Borgs, R.Zecchina, E.Fraenkel),
16th Annual International Conference on Research in Computational Molecular Biology (RECOMB), 287  301 (2012)
and Journal of Computational Biology 20, 124136 (2013). 

Sharing information to reconstruct patientspecific pathways in heterogeneous diseases
(A. Gitter, A. Braunstein, A. Pagnani, C. Baldassi, C. Borgs, J. Chayes, R. Zecchina, E. Fraenkel).
Proceedings of the Pacific Symposium on Biocomputing (PSB), 3950 (2014).

Processes on Networks and Graph Algorithms

On the spread of viruses on the Internet
(with N. Berger, C. Borgs and A. Saberi)
Proceedings of the 16th ACMSIAM Symposium on Discrete Algorithm (SODA), 301310 (2005). 

Local computation of pagerank contributions
(with R. Andersen, C. Borgs, J.
Hopcroft, V. Mirrokni and S. Teng)
Proceedings of the 5th Workshop on Algorithms and Models for
the Web Graph (WAW), 150165 (2007).


Robust PageRank and locally computable spam detection features
(with R. Andersen, C. Borgs, J. E. Hopcroft, K. Jain, V.S. Mirrokni and S.H. Teng)
AIRWeb 2008, 6976 (2008).


On the stability of web crawling and web search
(with R. Andersen, C. Borgs, J. E. Hopcroft, V.S. Mirrokni and S.H. Teng)
ISAAC 2008, 680691 (2008).


How to distribute antidote to control epidemics
(with C. Borgs, A. Ganesh, and A. Saberi)
Random Struct. Algorithms 37, 204222 (2010).


We know who you followed last summer: inferring social link creation
times in twitter
(with B. Meeder, B. Karrer, A. Sayedi, R. Ravi and C. Borgs) Proceedings of the 20th International World Wide Web Conference
(WWW), 517526 (2011).


A sublinear time algorithm for PageRank computations
(with M. Brautbar, C. Borgs and S.H. Teng)
Proceedings of the 9th Workshop
on Algorithms and Models for the Web Graph (WAW), 4153 (2012).


The power of local information in social networks
(with M. Brautbar, C. Borgs, S. Khanna, B. Lucier)
Proceedings of the 8th International Workshop on Internet and Network Economics
(WINE), 406  419 (2012). 

Finding endogenously formed communities
(with M.F. Balcan, M. Braverman, C. Borgs and S.H. Teng)
24th Annual ACMSIAM Symposium on Discrete Algorithm (SODA), 767783 (2013). 

Multiscale matrix sampling and sublineartime PageRank
(with M. Brautbar, C. Borgs and S.H. Teng)
Internet Mathematics 10, 2048 (2014).


Maximizing social influence in nearly optimal time
(with M. Brautbar, C. Borgs and B. Lucier)
Proceedings of the 25nd Annual ACMSIAM Symposium on Discrete Algorithm (SODA),
946957 (2014).

Network Modeling and Graph Theory

Directed scalefree graphs
(with B. Bollobas, C. Borgs and O. Riordan)
Proceedings of the 14th Annual ACMSIAM Symposium on Discrete Algorithms (SODA),
132139 (2003).


Degree distribution of the FKP network model
(with N. Berger, B. Bollobas, C. Borgs and O. Riordan)
Proceedings of the 30th International Colloquium on Automata, Languages and
Programming (ICALP), 725738, Lecture Notes in Computer Science 2719 (2003).


Exploring the community structure of newsgroups
(with C. Borgs, M. Mahdian and A. Saberi)
Proceedings of the 10th ACM SIGKDD International Conference on
Knowledge, Discovery and Data Mining (KKD), 783787 (2004).


Newsgroup cluster data referred to in the above paper.


Competitioninduced preferential attachment
(with N. Berger, C. Borgs, R. D'Souza and R. D. Kleinberg)
Proceedings of the 31st International Colloquium on Automata, Languages and
Programming (ICALP), 208221, Lecture Notes in Computer Science 3142 (2004) 

Degree distribution of competitioninduced preferential attachment
graphs
(with N. Berger, C. Borgs, R. D'Souza and R. D. Kleinberg)
Combinatorics, Probability and Computing 14, 697721 (2005). 

Emergence of tempered preferential attachment from optimization
(with N. Berger, C. Borgs, R. D'Souza and R. D. Kleinberg)
Proceedings of the National Academy of Sciences (PNAS) 104, 61126117 (2007),
cover article. 

Fitting the WHOIS Internet data A short note with technical
details left out in the above paper.


First to market is not Everything: An analysis of preferential
attachment with fitness
(with C. Borgs, C. Daskalakis and S.Roch)
Proceedings of the 39th annual ACM Symposium on the Theory of Computing (STOC), 135144 (2007). 
Phase Transitions in Combinatorics
and Computer Science

Uniform boundedness of crossing probabilities implies hyperscaling
(with C. Borgs, H. Kesten and J. Spencer)
Random Structures and Algorithms 15, 368413 (1999).


The birth of the infinite cluster: Finitesize scaling in percolation
(with C. Borgs, H. Kesten and J. Spencer)
Communications in Mathematical Physics 224, 153204 (2001).


The scaling window of the 2SAT transition
(with B. Bollobas, C. Borgs, J.H. Kim and D.B. Wilson)
Random Structures and Algorithms 18, 201256 (2001).


Sharp threshold and scaling window for the integer partitioning problem
(with C. Borgs and B. Pittel)
Proceedings of the 33rd annual ACM Symposium on the Theory of Computing (STOC), 330336 (2001).


Phase transition and finitesize scaling for the integer partitioning problem
(with C. Borgs and B. Pittel)
Random Structures and Algorithms 19, 247288 (2001).


Constrained integer partitions
(with C. Borgs, S. Mertens and B. Pittel)
Proceedings of the 6th Latin American Symposium on Theoretical Informatics
(LATIN), 5968, Lecture Notes in Computer Science 2976 (2004).


Phase diagram for the constrained integer partitioning problem
(with C. Borgs, S. Mertens and B. Pittel)
Random Structures and Algorithms 24, 315380 (2004).


Random subgraphs of finite graphs: I. The scaling window
under the triangle condition
(with C. Borgs, R. van der Hofstad, G. Slade and J. Spencer)
Random Structures and Algorithms 27, 137184 (2005). 

Random subgraphs of finite graphs: II. The lace expansion
and the triangle condition
(with C. Borgs, R. van der Hofstad, G. Slade and J. Spencer)
Annals of Probability 33, 18861944 (2005). 

Random subgraphs of finite graphs: III. The phase transition
for the ncube
(with C. Borgs, R. van der Hofstad, G. Slade and J. Spencer)
Combinatorica 26, 395410 (2006). 

The KestenStigum reconstruction bound is tight for roughly symmetric
binary channels
(with C. Borgs, E. Mossel and S. Roch)
47th Annual IEEE Symposium on Foundations of Computer Science (FOCS),
518530 (2006).


Proof of the local REM conjecture for number partitioning I: Constant
energy scales
(with C. Borgs, S. Mertens and C. Nair)
Random Structures and Algorithms 34, 217240 (2009). 

Proof of the local REM conjecture for number partitioning II: Growing
energy scales
(with C. Borgs, S. Mertens and C. Nair)
Random Structures and Algorithms 34, 241284 (2009). 

Percolation on dense graph sequences
(with B. Bollobas, C. Borgs and O. Riordan)
Ann. Probab. 38, 150183 (2010).

Monte Carlo Markov Chains and Approximation Algorithms

Torpid mixing of some Monte Carlo Markov Chain algorithms in statistical physics
(with C. Borgs, A. Frieze, J.H. Kim, P. Tetali, E. Vigoda and V. Vu)
Proceedings of the 40th Annual Symposium on Foundations of Computer Science (FOCS),
218229 (1999).


On the sampling problem for Hcolorings on the hypercubic lattice
(with C. Borgs, M. Dyer and P. Tetali)
in Graphs, Morphisms and Statistical Physics (eds. J Nesetril and P Winkler),
DIMACS Series in Discrete Mathematics and Theoretical Computer Science 63,
1328, American Mathematical Society (2004). 

Tight bounds for mixing of the SwendsenWang algorithm at the Potts transition point
(with C. Borgs and P. Tetali)
Probab. Theory Relat. Fields 152, 509  557 (2012).


Efficient sampling and counting algorithms for the Potts model on Z^{d} at all temperatures
(with J. T. Chayes, T. Helmuth, W. Perkins and P. Tetali). Proceedings of the 52nd Annual Symposium on Theory of Computing (STOC),
738751 (2020).

Zeros of Complex Partition Functions and LeeYang Theory

Gibbs states of graphical representations of the Potts model with external fields
(with M. Biskup, C. Borgs and R. Kotecky)
Journal of Mathematical Physics 41, 11701210 (2000).


General theory of LeeYang zeros in models with firstorder phase transitions
(with M. Biskup, C. Borgs, L. Kleinwaks and R. Kotecky)
Physical Review Letters 84, 47944797 (2000).


Partition function zeros at firstorder phase transitions: A general analysis
(with M. Biskup, C. Borgs, L. Kleinwaks and R. Kotecky)
Communications in Mathematical Physics 251, 79131 (2004). 

Partition function zeros at firstorder phase transitions:
PiorogovSinai theory
(with M. Biskup, C. Borgs and R. Kotecky)
Journal of Statistical Physics 116, 97155 (2004).
