ScB., Chemical Physics, Brown University, 2007
MPhil, Theoretical Chemistry, University of Cambridge, 2008
PhD, Chemical Physics, Columbia University, 2013
Lawrence Distinguished Postdoctoral Fellow, LLNL, 20132016
Joined the Brown Chemistry Department in 2016
Yuan Liu, Minsik Cho, and Brenda Rubenstein Ab Initio Finite Temperature Auxiliary Field Quantum Monte Carlo. journal of chemical theory and computation. 2018; 
Rose, C., Reda, S., Rubenstein, B.M., and J. Rosenstein
Computing with Chemicals: Perceptrons Using Small Molecules.
2018;

Arcadia, C., Dombroski, A., Tann, H., Rosenstein, J., Kim, E., Rubenstein, B.M., and S. Reda
Parallelized Linear Classification with Volumetric Chemical Perceptrons.
2018;

Zhu H, Cai T, Que M, Song JP, Rubenstein BM, Wang Z, Chen O PressureInduced Phase Transformation and BandGap Engineering of Formamidinium Lead Iodide Perovskite Nanocrystals.. The journal of physical chemistry letters. 2018; 9 (15) : 41994205. 
Kim J, Baczewski AT, Beaudet TD, Benali A, Bennett MC, Berrill MA, Blunt NS, Borda EJL, Casula M, Ceperley DM, Chiesa S, Clark BK, Clay RC, Delaney KT, Dewing M, Esler KP, Hao H, Heinonen O, Kent PRC, Krogel JT, Kylänpää I, Li YW, Lopez MG, Luo Y, Malone FD, Martin RM, Mathuriya A, McMinis J, Melton CA, Mitas L, Morales MA, Neuscamman E, Parker WD, Pineda Flores SD, Romero NA, Rubenstein BM, Shea JAR, Shin H, Shulenburger L, Tillack AF, Townsend JP, Tubman NM, Van Der Goetz B, Vincent JE, Yang DC, Yang Y, Zhang S, Zhao L QMCPACK: an open source ab initio quantum Monte Carlo package for the electronic structure of atoms, molecules and solids.. Journal of Physics: Condensed Matter. 2018; 30 (19) : 195901. 
Advances in the Computational Sciences: Symposium in Honor of Dr. Berni Alder's 90th Birthday. 2017; 
Chang, C.C., Rubenstein, B.M., and M.A. MoralesSilva AuxiliaryField Based Trial Wave Functions in Quantum Monte Carlo Calculations . Physical Review B. 2016; 94 : 235144. 
B.M. Rubenstein Introduction to the Variational Monte Carlo Method in Quantum Chemistry and Physics. Springer. 2016; Variational Methods in Molecular Modeling : 285313. 
Rubenstein, B.M., Zhang, S., and D.R. Reichman AuxiliaryField Quantum Monte Carlo for BoseFermi Mixtures . Physical Review A. 2012; 86 : 053606. 
Rubenstein, B.M., Coluzza, I., and M.A. Miller Controlling the Folding and Binding of Proteins Using Polymer Brushes . Physical Review Letters . 2012; 108 : 208104. 
Rubenstein, B.M., Gubernatis, J.E., and J.D. Doll Comparative Monte Carlo Efficiency by Monte Carlo Analysis . Physical Review E. 2010; 82 : 036701. 
Rubenstein, B.M. and L.J. Kaufman The Role of Extracellular Matrix in Glioma Invasion: A Cellular Potts Model Approach. Biophysical Journal. 2008; 95 : 5661. 
For decades, quantum chemists have been forced to make an oftentimes humbling choice in their daytoday work: to use highly accurate, manybody methods that are too slow to apply to realistic quantum systems, or, to use faster onebody methods that are significantly less accurate. This fundamental compromise has glaringly limited the impact of quantum chemistry. Indeed, while most of modern experimental chemistry is focused upon synthesizing complex molecules and designing novel nano and bulk materials, most modern quantum chemistry techniques are hardpressed to even approach the scales necessary to answer many of the most pivotal experimental questions about these systems. The Rubenstein group is focused on developing electronic structure methods that are at once highly accurate and scale well with system size to help bridge this divide and enable theorydriven materials design. Other recurrent interests in the group revolve around molecular computing, quantum computing, computational biophysics, classical statistical mechanics, and computational linear algebra.
Of key interest to the group is the development and application of stochastic methods to meet the longstanding need for rigorous techniques capable of accessing experimentally relevant scales. Because they make careful use of random numbers, quantum Monte Carlo methods are not only highly accurate (they are the gold standard in much of condensed matter physics), but scale gracefully with system size. They can therefore address a wide variety of experimentally motivated questions inaccessible to equally accurate deterministic methods and be used to improve existing electronic structure methods including Density Functional Theory. Problems of primary interest to the group fall into three main categories:
Modeling of bulk transition metal oxides, transition metalbased nanoclusters, and organometallic frameworks. Electrons in transition metals occupy highly degenerate, stronglycorrelated d and f orbitals that are particularly difficult to model using onebody theories. The group’s recent advances developing stochastic techniques capable of modeling hundreds of electrons in hundreds of orbitals opens the door to simulating a variety of transition metalbased compounds and materials. Quantum Monte Carlo simulations of transition metal oxides will enable the high accuracy prediction of band gaps and high temperature, high pressure phase transitions, which will pave the way toward the development of more advanced photovoltaics as well as an improved understanding of the phase diagrams of complex solids.
Development of new methods capable of capturing relativistic effects, including spinorbit coupling, beyond the mean field level. Being able to properly model relativistic effects is critical to predicting the behavior of heavy elements including Se and Te, which comprise topological insulators and important semiconductors, and the lanthanides and actinides, which assume a pivotal role in the nuclear fuel cycle and exhibit intriguing volume collapse transitions in the bulk. Our group is currently exploiting quantum Monte Carlo’s unique ability to obtain the ground state wave functions of multicomponent Hamiltonians to explore the full hierarchy of relativistic Hamiltonians and their accuracy in quantum chemical calculations. These efforts will inform current experimental efforts underway at Brown and elsewhere.
Design and testing of finite temperature electronic approaches to model hot electrons and astrophysical conditions. Few electronic structure approaches are capable of modeling materials under conditions in which electrons are excited well above the ground state. This currently limits our understanding of photochemistry, plasma physics, and astrophysical processes such as star formation. Our group is developing density matrixbased methods that will enable the direct prediction of molecular behavior at high temperatures using both stochastic methods and more conventional finite temperature density functional theories.
Advances made in these directions will establish the foundations necessary for rigorous simulations of a variety of materials currently outside the scope of modernday exploration, dramatically expanding the predictive power of quantum chemical techniques. Students engaged in this work will develop a deep understanding of both quantum and statistical mechanics and will become familiar with modern high performance computing paradigms.
DOE Computational Chemical Science Research Center, "Bridging the Time Scale in Exascale Computing of Chemical Systems (CoI w/ Andrew Peterson, Franklin Goldsmith, Zachary Ulissi, Andrew Medford, and Matthew Willard)," 2018Present
NSF DMR, "Beyond DFT: Accurate Simulations of Low Dimensional Materials for Energy and Device Applications (PI w/ Can Ataca)," 2018Present
DARPA Molecular Informatics Program, "Chemical CPUs: Chemical Computational Processing via Ugi Reactions (PI w/ Jacob Rosenstein, Chris Rose, Peter Weber, Sherief Reda, Eunsuk Kim, Joseph Geiser, and Jason Sello)," 2017Present
NSF EPSCoR Program, "Genotypes to Phenoytpes (w/ Marty Ytreberg, Daniel Weinreich, Holly Wichman, others)," 20172021
XSEDE Computing Allocation, "Quantum Monte Carlo for Lattice Models and Materials," 2017Present
LLNL Laboratory Directed Research and Development GrantExploratory Research,“Quantum Simulations for Uncertainty Quantification (w/ Miguel MoralesSilva),” 2014Present
10th Annual LLNL Grand Challenge Tier 2 Computing Grant, “Transition Metals Done Right: An AFQMC Study of Transition Metal Oxide Phase Diagrams”, 2015Present
DOE BER Subsurface Biogeochemical Research Program, “Biogeochemical Processes at Femtomolar Concentrations and Nanometer Scales (w/ Annie Kersting, et al.),” 2015PresentYear  Degree  Institution 

2013  PhD  Columbia University 
2008  MPhil  University of Cambridge 
2007  ScB  Brown University 
DellIntel Young Investigator Award in Quantum Chemistry, 2018
Brown University Research Seed Award, 2017
Society for Science and the Public Advocate Award, 2017
Lawrence Distinguished Postdoctoral Fellowship, 20132016
National Science Foundation Graduate Research Fellowship, 20082013
Department of Energy Computational Science Graduate Fellowship, 20082012
Winston Churchill Foundation of America Fellowship to Cambridge, 20072008
Paul Cross Prize for Best Senior in Physical Chemistry (Brown), 2007
Leallyn B. Clapp Thesis Prize for Best Thesis in Physical Chemistry (Brown), 2007
Rhodes Scholarship Finalist (NJ/MA Region), 2006
Barry Goldwater Scholarship (NJ Region), 20062007
American Chemical Society
American Physical Society
Biophysical Society
Materials Research Society
CHEM 2010  Advanced Thermodynamics 