Here is a link to my arXiv» page and a sortable list of articles on Google Scholar».

All my publications are sorted into the following categories:

- Machine Learning, Quantum Information, and Mathematical Physics
- Physics Education Research and Social Studies
- Media and Impact
- Other publications

Machine Learning, Quantum Information, and Mathematical Physics

- Amilson R. Fritsch, Shangjie Guo, Sophia M. Koh, I. B. Spielman, and
**Justyna P. Zwolak**,*Dark Solitons in Bose-Einstein Condensates: A Dataset for Many-body Physics Research*. arXiv:2205.09114 (2022). **Justyna P. Zwolak**and Jacob M. Taylor,*Colloquium: Advances in automation of quantum dot devices control*. arXiv:2112.09362 (2021).- Shangjie Guo, Sophia M. Koh, Amilson R. Fritsch, I. B. Spielman, and
**Justyna P. Zwolak**,*Combining machine learning with physics: A framework for tracking and sorting multiple dark solitons*. Phys. Rev. Research**4**(2): 023163 (2022). - Joshua Ziegler, Thomas McJunkin, E. S. Joseph, Sandesh S. Kalantre, Benjamin Harpt, D. E. Savage, M. G. Lagally, M. A. Eriksson, Jacob M. Taylor, and
**Justyna P. Zwolak**,*Toward Robust Autotuning of Noisy Quantum Dot Devices*. Phys. Rev. Applied**17**(2): 024069 (2022). - Brian J. Weber, Sandesh S. Kalantre, Thomas McJunkin, Jacob M. Taylor, and
**Justyna P. Zwolak**,*Theoretical bounds on data requirements for the ray-based classification*. SN Comp. Sci.**3**(1): 57 (2022). **Justyna P. Zwolak**, Thomas McJunkin, Sandesh S. Kalantre, Samuel F. Neyens, E. R. MacQuarrie, Mark A. Eriksson, and Jacob M. Taylor,*Ray-based framework for state identification in quantum dot devices*. PRX Quantum**2**(2): 020335 (2021).- Shangjie Guo, Amilson R. Fritsch, Craig Greenberg, Ian Spielman, and
**Justyna P. Zwolak**,*Machine-learning enhanced dark soliton detection in Bose-Einstein condensates*. Mach. Learn.: Sci. Technol.**2**(3): 035020 (2021). **Justyna P. Zwolak**, Sandesh S. Kalantre, Thomas McJunkin, Brian J. Weber, and Jacob M. Taylor,*Ray-based classification framework for high-dimensional data*. Proceedings of Third Workshop on Machine Learning and the Physical Sciences (NeurIPS 2020), Vancouver, Canada [December 11, 2020] (2020).**Justyna P. Zwolak**, Thomas McJunkin, Sandesh S. Kalantre, J. P. Dodson, E. R. MacQuarrie, D. E. Savage, M. G. Lagally, S. N. Coppersmith, Mark A. Eriksson, and Jacob M. Taylor,*Auto-tuning of double dot devices in situ with machine learning.*Phys. Rev. Applied**13**(3): 034075 (2020).- Featured as Editors’ Suggestion in
*Physical Review Applied*. - Featured in NIST News:
*To Tune Up Your Quantum Computer, Better Call an AI Mechanic: New paradigm for “auto-tuning” quantum bits could overcome major engineering hurdle.*(2020).

- Featured as Editors’ Suggestion in
- Sandesh S. Kalantre,
**Justyna P. Zwolak**, Stephen Ragole, Xingyao Wu, Neil M. Zimmerman, M. D. Stewart, and Jacob M. Taylor,*Machine Learning techniques for state recognition and auto-tuning in quantum dots.*npj Quantum Information**5**(6): 1–10 (2019). **Justyna P. Zwolak**, Sandesh S. Kalantre, Xingyao Wu, Stephen Ragole, and Jacob M. Taylor,*QFlow lite dataset: A machine-learning approach to the charge states in quantum dot experiments.*PLoS ONE**13**(10): e0205844 (2018).- Data is available at data.gov.
*QFlow lite*is available at github.com.

**Justyna P. Zwolak**and Dariusz Chruściński,*Recurrent construction of optimal entanglement witnesses for 2N qubit systems.*Phys. Rev. A**89**(5): 052314 (2014).**Justyna P. Zwolak**and Dariusz Chruściński,*New tools for investigating positive maps in matrix algebras.*Rep. Math. Phys.**71**(2): 163–175 (2013).- Spyridon Michalakis and
**Justyna Pytel**,*Stability of frustration-free systems.*Comm. Math. Phys.**322**(2): 277–302 (2013). - Dariusz Chruściński and
**Justyna Pytel**,*Optimal entanglement witnesses from generalized reduction and Robertson maps.*J. Phys. A: Math. Theor.**44**(16): 165304 (2011). - Dariusz Chruściński and
**Justyna Pytel**,*Constructing optimal entanglement witnesses. II. Witnessing entanglement in 4N x 4N systems.*Phys. Rev. A**82**(5): 052310 (2010). - Dariusz Chruściński,
**Justyna Pytel**, and Gniewomir Sarbicki,*Constructing new optimal entanglement witnesses.*Phys. Rev. A**80**(6): 062314 (2009).

Physics Education Research and Social Studies

- Robert P. Dalka and
**Justyna P. Zwolak**,*Restoring the structure: A modular analysis of ego-driven organizational networks*. arXiv:2201.01290 (2022). - Robert P. Dalka, Diana Sachmpazidi, Charles Henderson, and
**Justyna P. Zwolak**,*Network analysis approach to Likert-style surveys*. Phys. Rev. Phys. Educ. Res.**18**(2): 020113 (2022). - Eric A. Williams,
**Justyna P. Zwolak**, Remy Dou, and Eric Brewe, Linking engagement and performance: The social network analysis perspective. Phys. Rev. Phys. Educ. Res.**15**(2): 020150 (2019). - Remy Dou and
**Justyna P. Zwolak**,*Practitioner’s guide to social network analysis: Examining physics anxiety.*Phys. Rev. Phys. Educ. Res.**15**(2): 020105 (2019).- An invited article within the Quantitative Methods in PER: A Critical Examination Focused Collection.

- Emily M. Smith,
**Justyna P. Zwolak**, and Corinne A. Manogue,*Isolating approaches: How middle-division physics students coordinate forms and representations in complex algebra.*Phys. Rev. Phys. Educ. Res.**15**(1): 010138 (2019). - C. A. Hass, Florian Genz, Mary Bridget Kustusch, Pierre-P. A. Ouimet, Katarzyna Pomian, Eleanor C. Sayre, and
**Justyna P. Zwolak**,*Studying community development: A network analytical approach.*Proceedings of the Physics Education Research Conference 2018, Washington, DC [August 1-2, 2018], pp. 1–4 (2019). - Remy Dou, Eric Brewe, Geoff Potvin,
**Justyna P. Zwolak**, and Zahra Hazari,*Understanding the development of interest and self-efficacy in active-learning undergraduate physics courses.*Int. J. Sci. Educ.**40**(13): 1587–1605 (2018). **Justyna P. Zwolak**, Michael Zwolak, and Eric Brewe,*Educational commitment and social networking: The power of informal networks.*Phys. Rev. Phys. Educ. Res.**14**(1): 010131 (2018).- Featured as Editors’ Suggestion in
*Physical Review Physics Education Research*. - Featured as a Research Highlight in
*Nature Physics*: “Friendly persistence”,**14**: 528 (2018).

- Featured as Editors’ Suggestion in
**Justyna P. Zwolak**, Remy Dou, and Eric Brewe,*Student perceptions of the value of out-of-class interactions: Attitudes vs. Practice.*Proceedings of the Physics Education Research Conference 2017, Cincinnati, OH [July 26-27, 2017], pp. 480–483 (2018).- Eric Williams,
**Justyna P. Zwolak**and Eric Brewe,*Physics Major Engagement and Persistence: A Phenomenography Interview Study.*Proceedings of the Physics Education Research Conference 2017, Cincinnati, OH [July 26-27, 2017], pp. 436–439 (2018). - Katarzyna Pomian,
**Justyna P. Zwolak**, Eleanor Sayre, Scott Franklin, and Mary Bridgett Kustusch,*Using Social Network Analysis on classroom video data.*Proceedings of the Physics Education Research Conference 2017, Cincinnati, OH [July 26-27, 2017], pp. 316–319 (2018). **Justyna P. Zwolak**, Remy Dou, Eric A. Williams, and Eric Brewe,*Students’ network integration as a predictor of persistence in introductory physics courses.*Phys. Rev. Phys. Educ. Res.**13**(1): 010113 (2017).- Featured as Editor’s Choice in
*Science*: “The physics of social butterflies”,**356**: 282 (2017). - Featured in
*FIU News*: “To keep students interested in physics, have them interact” (May 15, 2017).

- Featured as Editor’s Choice in
- Remy Dou, Eric Brewe,
**Justyna P. Zwolak**, Geoff Potvin, Eric A. Williams, and Laird H. Kramer,*Beyond performance metrics: Examining a decrease in students’ physics self-efficacy through a social networks lens.*Phys. Rev. Phys. Educ. Res.**12**(2): 020124 (2016). **Justyna P. Zwolak**and Eric Brewe,*The impact of social integration on student persistence in introductory Modeling Instruction courses.*2015 Physics Education Research Conference Proceedings, College Park, MD [July 29-30, 2015], pp. 395–398 (2015).- Eric Williams, Eric Brewe,
**Justyna P. Zwolak**, and Remy Dou,*Understanding centrality: Investigating student outcomes within a classroom social network.*2015 Physics Education Research Conference Proceedings, College Park, MD [July 29-30, 2015], pp. 375–378 (2015). - Emily M. Smith,
**Justyna P. Zwolak**, and Corinne A. Manogue,*Student difficulties with complex numbers.*2015 Physics Education Research Conference Proceedings, College Park, MD [July 29-30, 2015], pp. 311–314 (2015). **Justyna P. Zwolak**and Corinne A. Manogue,*Assessing student reasoning in upper-division electricity and magnetism at Oregon State University**.*Phys. Rev. ST Phys. Educ. Res.**11**(2): 020125 (2015).- An invited article within the PER in Upper Division Physics Courses Focused Collection.

**Justyna P. Zwolak**and Corinne A. Manogue,*Revealing Differences Between Curricula Using the Colorado Upper-Division Electrostatics Diagnostic.*2014 Physics Education Research Conference Proceedings, Minneapolis, MN [July 30-31, 2014], pp. 295–298 (2015).**Justyna P. Zwolak**, Mary Bridget Kustusch, and Corinne A. Manogue,*Re-thinking the Rubric for Grading the CUE. The Superposition Principle.*2013 Physics Education Research Conference Proceedings, Portland, OR [July 17-18, 2013], pp. 385–388 (2014).

- Mary Theofanos and
**Justyna Zwolak**(May 16, 2021),*Diversity and Inclusivity at NIST*. Women in Standards News. **Justyna P. Zwolak**(June 2, 2020),*Ebb and Flow: Creating Quantum Dots Automatically With AI*. Taking Measure: Just a Standard Blog.

**Justyna P. Zwolak**, Automation of Experimental Quantum Dot Control. Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2021, pp. 24–27 (2022).- Judith Terrill,
**Justyna P. Zwolak**, James Filliben, and Jeffrey Bullard,*HydratiCA, In Situ Analysis, and Machine Learning*. Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2021, pp.82–83 (2022). **Justyna P. Zwolak**, I. B. Spielman, Sophia M. Koh, Shangjie Guo, Amilson R. Fritsch,*Combining Machine Learning with Physics: Enhanced Dark Soliton Detection in BECs*. Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2021, pp. 84–85 (2022).**Justyna P. Zwolak**, Sandesh S. Kalantre, Thomas McJunkin, Brian J. Weber, and Jacob M. Taylor,*Ray-based Classification Framework for Quantum Dot Devices*. Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2021, pp. 86–88 (2022).**Justyna P. Zwolak**, Zachary J. Grey, Joshua Ziegler, and Brian J. Weber,*Charge Field Decomposition and State Identification for Quantum Dot Data*. Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2021, pp. 88–90 (2022).- Joshua Ziegler,
**Justyna P. Zwolak**, Jacob M. Taylor, Thomas McJunkin, Sandesh Kalantre, E. S. Joseph, Benjamin Harpt, D. E. Savage, M. G. Lagally, and Mark A. Eriksson,*Noisy Quantum Dot Devices*. Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2021, pp. 90–92 (2022). - Joshua Ziegler and
**Justyna P. Zwolak**,*Physics-driven Tuning of Quantum Dot Charge States*. Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2021, pp. 92–93 (2022). **Justyna P. Zwolak**, Mary F. Theofanos, Jasmine Evans, and Sandra Spickard Prettyman,*Gender, Equity, and Inclusion Survey Study at NIST*. Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2021, pp. 134–135 (2022).**Justyna P. Zwolak**, Laura Espinal, and Camila Young,*Mapping and Analyzing Employee Networks through the NIST Interactions Survey*. Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2021, pp. 135–136 (2022).- Robert P. Dalka and
**Justyna P. Zwolak**,*Restoring Organizational Structure Using Projected Ego-Centric Networks*. Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2021, pp. 136–137 (2022). - Robert P. Dalka,
**Justyna P. Zwolak**, Diana Sachmpazidi, and Charles Henderson,*Physics Education Survey Validation Through a Network Analytic Approach*. Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2021, pp. 137–138 (2022). - Laura Espinal, Camila Young, and
**Justyna P. Zwolak**, Mapping employee networks through the NIST Interactions Survey. Natl. Inst. Stand. Technol. Interag. Intern. Rep. 8375 (2021). - Judith Terrill,
**Justyna P. Zwolak**, James Filliben, and Jeffrey Bullard,*HydratiCA, In Situ Analysis and Machine Learning*. Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2020, pp. 78–79 (2021). **Justyna P. Zwolak**, Sandesh S. Kalantre, Thomas McJunkin, Brian J. Weber, and Jacob M. Taylor,*Ray-based classification framework for quantum dot devices*. Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2020, pp. 79–81 (2021).- Zachary J. Grey,
**Justyna P. Zwolak**, Andrew M. Dienstfrey, Sandesh S. Kalantre, and Brian J. Weber,*Ray-Tracing Active Subspace Computations (R-TASC) for Quantum Dot Decompositions*. Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2020, pp. 81–83 (2021). **Justyna P. Zwolak**, Shangjie Guo, Amilson R. Fritsch, Craig Greenberg, and Ian B. Spielman,*Machine learning enhanced dark solitons detection in Bose-Einstein condensates*. Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2020, pp. 83–84 (2021).- Joshua Ziegler,
**Justyna P. Zwolak**, Jacob M. Taylor, Sandesh Kalantre, Thomas Mcjunkin, and Mark A. Eriksson,*Towards Robust Autotuning of Noisy Quantum Dot Devices*. Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2020, pp. 101–102 (2021). **Justyna P. Zwolak**, Mary F. Theofanos, Jasmine Evans, and Sandra Spickard Prettyman,*Gender, Equity and Inclusion Survey Study at the National Institute of Standards and Technology*. Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2020, pp. 129–130 (2021).**Justyna P. Zwolak**, Laura Espinal, and Camila Young,*Mapping and analyzing employee networks through the NIST Interactions Survey*. Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2020, pp. 130–131 (2021).- Mary F. Theofanos, Jasmine Evans,
**Justyna P. Zwolak**, and Sandra Spickard Prettyman,*Survey on Gender, Equity and Inclusion*. Natl. Inst. Stand. Technol. Interag. Intern. Rep. 8362 (2021). **Justyna P. Zwolak**,*Machine Learning for Experimental Quantum Dot Control*. Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2019, pp. 25–28 (2020).- Judith Terrill,
**Justyna P. Zwolak**, James Filliben, and Jeffrey Bullard,*HydratiCA, In Situ Analysis and Machine Learning*. Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2019, pp. 77–78 (2020). **Justyna P. Zwolak**, Justin Elenewski, Amilson R. Fritsch, and Ian B. Spielman,*Machine Learning Enhanced Dark Soliton Detection in Bose-Einstein Condensates*. Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2019, pp. 80–81 (2020).**Justyna P. Zwolak**and Remy Dou,*Practitioner’s Guide to Social Network Analysis for Education Researchers*. Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2019, pp. 119–120 (2020).**Justyna P. Zwolak**, Judith Terrill, and Aleksandra Słapik,*Computations in Physics: A Quest to Integrate Computer Methods in STEM Courses*. Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2019, pp. 120 (2020).**Justyna P. Zwolak**,*Machine Learning for Experimental Quantum Dot Control.*Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2018 », pp. 18–21 (2019).- Sandesh S. Kalantre,
**Justyna P. Zwolak**, Stephen Ragole, Xingyao Wu, Neil M. Zimmerman, M. D. Stewart, and Jacob M. Taylor,*Machine Learning Approach to Quantum Dot Experiments.*Applied and Computational Mathematics Division: Summary of Activities for Fiscal Year 2017 », pp. 87–88 (2018).