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Alfred Farris

Assistant Professor of Physics

photo of Alfred Farris

Contact

770.784.4578

Education

AA| Oxford College of Emory University| 2011

BS| Emory University| 2013

PhD| University of Georgia| 2019

Accomplishments

Phi Beta Kappa Recognition for Excellent Teaching; Emory University (2021).

William P. Cummings Award for Excellence as a Student and Teacher; Department of Physics and Astronomy, University of Georgia (2019).

Sean M. Kirkpatrick Award for Outstanding Achievement in Graduate Research; Department of Physics and Astronomy, University of Georgia (2018).

Excellence in Teaching Award; The Center for Teaching and Learning and The Graduate School, University of Georgia (2018).

Advanced Short Term Research Fellowship; Oak Ridge National Laboratory (2017, 2018).

APS - SBF Travel Grant; American Physical Society (2017).

Future Faculty Program Fellow; The Center for Teaching and Learning, University of Georgia (2016-2017).

Outstanding Teaching Assistant Award; The Center for Teaching and Learning, University of Georgia (2016).

Publications

  • "Wang-Landau Algorithm and its Extensions", Challenges and Advances in Computational Chemistry and Physics: Generalized-Ensemble Algorithms -- Ideas and Applications (Edited by Yuji Sugita and Yuko Okamoto), A. C. K. Farris and D. P. Landau, Springer, In preparation (2023).
  • "Wang-Landau Sampling of Lattice Multiblock Copolymers", R. F. Bull, A. C. K. Farris, and D. P. Landau, J. Chem. Phys. 159, 104903 (2023).
  • A Student's Guide to Rotational Motion, E. Seitaridou and A. C. K. Farris, Cambridge University Press (2023).
  • "A First Look at Structural Properties of Long HP Model Sequences", A. C. K. Farris and D. P. Landau, J. Phys. Conf. Ser. 2207, 012002 (2022).
  • "Effects of Lattice Constraints in Coarse-Grained Protein Models", A. C. K. Farris, D. T. Seaton, and D. P. Landau, J. Chem. Phys. 154, 084903 (2021). 
  • "Replica Exchange Wang-Landau Sampling of Long HP Model Sequences", A. C. K. Farris and D. P. Landau, Physica A 569, 125778 (2021). 
  • "A First Look at Lattice Effects in Coarse-Grained Protein Models via Wang-Landau Simulations", A. C. K. Farris, D. T. Seaton and D. P. Landau, J. Phys. Conf. Ser. 1290, 012019 (2019).
  • "Crambin Homologues in the H0P Lattice Protein Model", Z. Zhang, A. C. K. Farris, G. Shi, T. Wüst, and D. P. Landau, J. Phys. Conf. Ser. 1290, 012018 (2019).
  • "Statistical Physics Meets Biochemistry: Wang-Landau Sampling of the HP Model of Protein Folding", A. C. K. Farris, T. Wüst, and D. P. Landau, Am. J. Phys., 87, 4 (2019). [Editors' Pick]
  • "Histogram-Free Multicanonical Monte Carlo Sampling to Calculate the Density of States", A. C. K. Farris, Y. W. Li, and M. Eisenbach, Comput. Phys. Commun., 235, 297-304 (2019).
  • "The Role of Chain-Stiffness in Lattice Protein Models: A Replica-Exchange Wang-Landau Study", A. C. K. Farris, G. Shi, T. Wüst, and D. P. Landau, J. Chem. Phys. 149, 125101 (2018).
  • "Effects of Stiffness on Low Energy States in a Lattice Protein Model for Crambin", A. C. K. Farris, G. Shi, T. Wüst, and D. P. Landau, J. Phys.: Conf. Ser. 1012, 012008 (2018).
  • "Folding in a semi-flexible lattice model for Crambin", G. Shi, A. C. K. Farris, T. Wüst, and D. P. Landau, J. Phys.: Conf. Ser. 686, 012001 (2016).
  • "Renormalization group solution of the Chutes & Ladder model", L. A. Ball, A. C. K. Farris, and S. Boettcher, Physica A 421, 171-179 (2015).

Presentations

* Denotes presentation by undergraduate research student

  • *"Wang-Landau Sampling of Lattice Multiblock Copolymers". American Physical Society March Meeting. Online. Mar. 2023
  • * "Quantifying Thermodynamic Properties of Texts Using Jaynes' Principle of Maximum Entropy”. American Physical Society March Meeting. Las Vegas, NV. Mar. 2023
  • "Wang-Landau Sampling of Lattice Multiblock Copolymers". Center for Simulational Physics 36th Annual Workshop, University of Georgia. Feb. 2023
  • * "Wang-Landau Sampling of Lattice Multiblock Copolymers". IUPAP Conference on Computational Physics. Online. Aug. 2022
  • * "Identifying Bacterial Strains Using Image Analysis”. Summer Oxford Research Scholars Symposium. Oxford, GA. Aug. 2022
  • * "Quantifying Patterns of Sound Units in Languages Using Maximum Entropy”. Summer Oxford Research Scholars Symposium. Oxford, GA. Aug. 2022
  • * "Quantifying Patterns of Sound Units in Languages Using Maximum Entropy”. Oxford Research Scholars Symposium. Oxford, GA. Apr. 2022
  • * "Quantifying Patterns of Sound Units in Languages Using Maximum Entropy”. American Physical Society March Meeting. Chicago, IL. Mar. 2022
  • "A First Look at Structural Properties of Long HP Model Sequences”. American Physical Society March Meeting. Chicago, IL. Mar. 2022
  • "A First Look at Structural Properties of Long HP Model Sequences”. Center for Simulational Physics 35th Annual Workshop, University of Georgia (Online). Feb. 2022
  • * "Quantifying Languages Using Computational Statistical Physics: Examining the Energies of Words". Summer Oxford Research Scholars Symposium. Online. Aug. 2021
  • "Replica Exchange Wang-Landau Sampling of Long HP Lattice Protein Sequences".  IUPAP Conference on Computational Physics. Online. Aug. 2021
  • "Effects of Lattice Constraints in Coarse-Grained Protein Models: A Wang-Landau Study". American Physical Society March Meeting. Online. Mar. 2021
  • "Effects of Lattice Constraints in Coarse-Grained Protein Models: A Wang-Landau Study". Center for Simulational Physics 33rd Annual Workshop, University of Georgia. Feb. 2020
  • “Statistical Physics Meets Biochemistry: Monte Carlo Simulations of Coarse-Grained Protein Models”. Bioengineering Seminar, University of Georgia. Apr. 2019
  • "Removing Lattice Constraints from Lattice Protein Models: A Wang-Landau Study”. American Physical Society March Meeting. Boston, MA. Mar. 2019
  • "Effects of Lattice Constraints in the HP Lattice Protein Model”. Center for Simulational Physics 32nd Annual Workshop, University of Georgia. Feb. 2019
  • "An Improved Multicanonical Monte Carlo Algorithm for the Basis Expansion of the Density of States”. IUPAP Conference on Computational Physics. Davis, CA. Aug. 2018
  • "Investigating Protein Folding via Monte Carlo Simulations and Statistical Physics”. West Coast University School of Pharmacy. Los Angeles, CA. Mar. 2018
  • “Monte Carlo Simulations of Coarse-Grained Protein Models for Crambin”. American Physical Society March Meeting. Los Angeles, CA. Mar. 2018
  • "Wang-Landau Simulations of Coarse-Grained Protein Models for Crambin”. Center for Simulational Physics 31st Annual Workshop, University of Georgia. Feb. 2018
  • “Exploring Effects of Rigidity in a Semi-flexible Lattice Model for Crambin: A REWL Study”. 9th Brazilian Meeting on Simulational Physics. Natal, Brazil. Aug. 2017
  • “Replica-Exchange Wang-Landau Simulations of a Semi-flexible H0P Lattice Protein Model for Crambin”. American Physical Society March Meeting. New Orleans, LA. Mar. 2017
  • “The Lab in Col-LAB-oration: Group and Problem-based Learning in the STEM Classroom”. Teaching Assistant Workshop Symposium, University of Georgia. Feb. 2017
  • "Introduction to Laboratory Teaching”. Teaching Assistant Orientation, University of Georgia. Aug. 2016

Research Interests

My research involves using high performance computers and Monte Carlo simulations to study problems in statistical physics. 

Research Interest 1 (Physics in Language): Application of techniques from computational statistical physics to study patterns in language. Specifically, the emergence of new words in languages, how languages progress over time, and the similarities and differences between the use of language across different forms of media.

Research Interest 2 (Physics in Biochemistry): Computer simulations offer a viable route to study the protein folding process, but even still, there are many questions regarding the “best” model resolution and simulational framework. This project involves using state of the art Monte Carlo methods from computational statistical physics, such as Wang-Landau and Multicanonical sampling, to explore differrent coarse-grained models and study the folding behavior of these model proteins and polymers.

Research Interest 3 (Algorithm Development): Development of new, extended ensemble Monte Carlo algorithms for use in computational statistical physics. Specifically, the development of simulational frameworks that may prove particularly useful for systems with continuous state variables. 

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