Research
Publications
Peer-reviewed work spanning network science, link prediction, machine learning, data stream classification, computational genetics, and autonomous music composition. Ph.D. research conducted under Nitesh Chawla at the University of Notre Dame.
Journal Publications
Journal of the American Dental Association, 2019
Clinical predictors of persistent TMD in people with first-onset TMD: a prospective case-control studyMeloto C.B., Slade G.D., Lichtenwalter R.N., Bair E., Rathnayaka N., Diatchenko L., Dubner R., Greenspan J.D., Maixner W., Fillingim R.B., and Ohrbach R.
Human Molecular Genetics, 2019
A study in scarlet: MC1R as the main predictor of red hair and exemplar of the flip-flop effectZorina-Lichtenwalter K., Lichtenwalter R.N., Zaykin D.D., Parisien M., Gravel S., Bortsov A., and Diatchenko L.
Pain, 2018
Human pain genetics database: a resource dedicated to human pain genetics researchMeloto C.B., Benavides R., Lichtenwalter R.N., Wen X., Tugarinov N., Zorina-Lichtenwalter K., Chabot-Doré A.J., Piltonen M.H., Cattaneo S., Verma V., Klares R. 3rd, Khoury S., Parisien M., Diatchenko L.
Proceedings of the 21st European Conference on Advances in Databases and Information Systems, 2017
Genotypic data in relational databases: efficient storage and rapid retrievalLichtenwalter R.N., Zorina-Lichtenwalter K., and Diatchenko L.
Knowledge and Information Systems, 2015
Evaluating link prediction methodsYang Y. and Lichtenwalter R.N. and Chawla N.V.
Springer Plus, 2014
Vertex collocation profiles: theory, computation and resultsLichtenwalter R.N. and Chawla, N.V.
Physical Review Letters E, 2012
Range-limited centrality measures in complex networksErcsey-Ravasz M., Lichtenwalter R.N., Chawla N.V. and Toroczkai Z.
Social Network Analysis and Mining, 2012
Supervised methods for multi-relational link predictionDavis D., Lichtenwalter R., and Chawla N.V.
Journal of Machine Learning Research, 2011
LPmade: Link prediction made easyLichtenwalter R.N. and Chawla N.V.
Journal of Intelligent Systems, 2010
A machine learning approach to autonomous music compositionLichtenwalter R.N. and Chawla N.V.
LNCS: New Frontiers in Applied Data Mining, 2009
Learning to classify data streams with imbalanced class distributionsLichtenwalter R.N. and Chawla N.V.
Conference Publications
Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, 2012
Link prediction: fair and effective evaluationLichtenwalter R.N. and Chawla N.V.
Proceedings of the International Conference on World Wide Web, 2012
Vertex collocation profiles: Subgraph counting for link analysis and predictionLichtenwalter R.N. and Chawla N.V.
Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, 2011
DisNet: A framework for distributed graph computationLichtenwalter R.N. and Chawla N.V.
Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, 2011
Multi-relational link prediction in heterogeneous information networksDavis D. and Lichtenwalter R. and Chawla N.V.
Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2010
New perspectives and methods in link predictionLichtenwalter R.N. and Lussier J.T. and Chawla N.V.
Proceedings of the Indian International Conference on Artificial Intelligence, 2009
Applying learning algorithms to music generationLichtenwalter R.N. and Lichtenwalter K. and Chawla N.V.
Proceedings of the PAKDD Conference, 2009
Adaptive methods for classification in arbitrarily imbalanced and drifting data streamsLichtenwalter R.N. and Chawla N.V.
Proceedings of the IEEE International Symposium on Parallel and Distributed Processing, 2008
Data mining on the grid for the gridChawla N.V., Thain D., Lichtenwalter R.N., and Cieslak D.A.