Office: 218 Cramer Hall, NMT |

email: ramyaa at cs dot nmt dot edu |

phone: 575 835 5949 |

Fall office hours: Wed 2-3, The 1-2 (or by appt - email me) |

My primary fields of research are Theory of computation (and complexity) and Logic, focusing on implicit complexity (relating logical complexity of concepts to computational, resource-based complexity), especially on emerging models of computation, such as stream computation, biological neural networks etc. My secondary research area is Artificial Intelligence, focusing on machine learning.

The field of implicit complexity relates conceptual complexity to resource-based complexity. One advantage of conceptual complexity definitions is that they are logical, and do not refer to a particular machine model or resource, and so are easily adaptable to new and emerging models of computation. My past and current research has been the study of conceptual complexity, and their relation to resource-based complexity classes over different data models. I plan to continue this study for emerging models of computation, especially where a computational model is yet to be defined in rigorous, mathematical detail, such as biologically realistic neural networks, DNA computation, probabilistic computation etc.

I am also interested in using machine learning /data mining techniques to solve real-world problems. Further, I am interested in advancements in neural networks - especially biologically inspired developments.

- Aranda D, Towler A, Ramyaa R, and Kuo R.
*Designing an Educational Game for Teaching Foundational Concepts in Propositional Logic.*2019, E-learn - Ramyaa R, Hosseini O, Krishnan GP and Krishnan S.
*Phenotyping Women Based on Dietary Macronutrients, Physical Activity and Body Weight Using Machine-Learning Tools.*2019. Nutrients 11 (7). - Krishnan GP*, Tadros T*, Ramyaa R, Bazhenov M.
*Biologically inspired sleep algorithm for artificial neural networks. 2019*. arXiv:1908.02240. *Equal first author. - Tadros T, {Krishnan GP}, Ramyaa R, Bazhenov M.
*Biologically inspired sleep algorithm for increased generalization and adversarial robustness in deep neural networks.*Accepted in ICLR 2020. Link - Ramyaa R, Das K, Marru S.
*Aggregating Ensemble Weather Predictions for Rainfall Prediction.*ICMLC 2018 conference proceedings. - Buss S, and Ramyaa R.
*Short refutations for the equivalence-chain principle for constant-depth formulas.*Under review in Mathematical Logic Quarterly. - Leivant D, and Ramyaa R.
*The computational contents of ramified corecurrence.*selected for Foundations of Software Science and Computation Structures (FoSSaCS) conference, 2015. - Danner N, Licata DR, Ramyaa.
*Denotational cost semantics for functional languages with inductive types.*ICFP 2015: 140-151 - Danner N, Licata DR, Ramyaa.
*Denotational cost semantics for functional languages with inductive types.*arXiv:1506.01949. Link - Ramyaa R, and Leivant D.
*Ramified Lazy Corecursion and Logspace*. Logic and Computational Complexity. Vienna, 2014. - Hofmann M, Ramyaa R, and Sch\öpp U.
*Pure pointer programs and tree isomorphism. Foundations of Software Science and Computation Structures.*Foundations of Software Science and Computation Structures (FOSSCS), 2013. Springer Berlin Heidelberg. PDF - Verma A, Ramyaa R, Singh R, Marru S.
*Validating distance decay through agent based modeling*, Special Issue of Security Informatics (SI) on Computational Criminology 2012. PDF - Ramyaa R, Leivant D. Ramified Corecurrence and Logspace, Electr. Notes Th. CS. 276%: 247-261 (2011). PDF
- Leivant D, Ramyaa R,/Implicit complexity for coinductive data: a characterization of corecurrence/,DICE 2011: 1-14. PDF
- Ramyaa R, Leivant D,
*Feasible Functions over Co-inductive Data*, WoLLIC 2010: 191-203. PDF - Verma A, Ramyaa R, Singh R, and Marru S./Rationalizing police patrol beats using Voronoi Tessellations/. ACM SIGKDD Workshop on Intelligence and Security Informatics, 2010.
- McClendon RW, Hoogenboom G, Jain A, Ramyaa R, Smith B.
*Temperature prediction for Frost Prediction*, Proc. of the 2005 Southeast Regional Vegetable Conference. GA, 2005. P. 97. - Ramyaa R, He C, Rasheed K. Using Machine Learning Techniques for Stylometry, IC-AI 2004. PDF
- Potter WD, Ramyaa, Li J, Ghent J, Twardus D, Thistle H. STP: An Aerial Spray Treatment Planning System, Proc. of the IEEE SoutheastCon 2002, pp. 300-305, Columbia, SC. PDF

- ACM SAC 2018 IoT Track SRC program
- Program Committee DICE 2016.
- STACS (Symposium on Theoretical Aspects of Computer Science) for 2014, 2015.
- LICS (Logic In Computer Science) for 2013, 2015.

- Fall 2015 - Foundations of Computer Science
- Spring 2015 - Formal Languages and Automata

- Theory of Computation, NMT, fall 2017
- Foundations of computation (discrete mathematics), NMT, fall 2017
- Automata and Formal Languages, NMT, spring 2016
- Foundations of computation (discrete mathematics), NMT, fall 2015
- Introduction to Artificial Intelligence, Wesleyan University, spring 2015.
- Introduction to programming for non-majors (with python), Wesleyan University, fall 2014.
- Introduction to programming for non-majors (with python), Wesleyan University, fall and spring 2013.