| 2020 | |
| [24] | A Module for Introducing Ethics in AI: Detecting Bias in Language Models. . In Proceedings of the 10th Symposium on Educational Advances in Artificial Intelligence (EAAI), 2020. [slides] |
| [23] | Dugesia japonica is the best suited of three planarian species for high-throughput toxicology screening. . In Chemosphere, vol. 253, pp. 126718, 2020. [cached] |
| 2019 | |
| [22] | Lab Practicum For Bias In Algorithms. . 2019. |
| 2017 | |
| [21] | ACM-SIGBIO Undergraduate Research Highlight. . In ACM SIGBioinformatics Rec., ACM, vol. 7, no. 2, pp. 2:1–2:3, 2017. |
| [20] | Deep Residual Nets for Improved Alzheimer’s Diagnosis. . In Proceedings of the 8th ACM Conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB), 2017. [poster] |
| [19] | Identifying Parkinson’s Patients: A Functional Gradient Boosting Approach. . In Artificial Intelligence in Medicine (AIME), 2017. |
| 2016 | |
| [18] | Learning relational dependency networks for relation extraction. . In International Workshop on Statistical Relational AI (STARAI) at IJCAI, 2016. (arXiv:1607.00424[cs.AI]) [cached] |
| [17] | Learning relational dependency networks for relation extraction. . In Proceedings of the 26th International Conference on Inductive Logic Programming (ILP), 2016. [slides] |
| [16] | A Comparison of weak supervision methods for knowledge base construction. . In 5th Workshop on Automated Knowledge Base Construction (AKBC) at NAACL, 2016. [poster] |
| [15] | Deep Distant Supervision: Learning Statistical Relational Models for Weak Supervision in Natural Language Extraction. . Chapter in Solving Large Scale Learning Tasks. Challenges and Algorithms, Springer International Publishing, pp. 331–345, 2016. |
| 2015 | |
| [14] | Relational learning with expert advice. . In Proceedings of Text Analysis Conference (TAC) Workshop, 2015. |
| [13] | A comprehensive analysis of classification algorithms for cancer prediction from gene expression. . In Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB), pp. 525–526, 2015. [poster] |
| 2014 | |
| [12] | A support program for introductory CS courses that improves student performance and retains students from underrepresented groups. . In Proceedings of the 45th ACM Technical Symposium on Computer Science Education (SIGCSE), pp. 433–438, 2014. |
| [11] | A graphical model approach to ATLAS-free mining of MRI images. . In Proceedings of the 2014 SIAM International Conference on Data Mining (SDM), pp. 974–982, 2014. [poster] |
| 2013 | |
| [10] | Conditional random fields for brain tissue segmentation. . In Workshop on Machine Learning and Interpretation in NeuroImaging (MLINI) at NIPS, 2013. [poster] |
| 2012 | |
| [9] | Probabilistic ensembles for improved inference in protein-structure determination. . In Journal of Bioinformatics and Computational Biology, vol. 10, no. 01, pp. 1240009, 2012. (By invitation; PMID: 22809310) |
| [8] | Structural characterization of human UCH37. . In Proteins: Structure, Function, and Bioinformatics, Wiley Online Library, vol. 80, no. 2, pp. 649–654, 2012. |
| 2011 | |
| [7] | Techniques for Improved Probabilistic Inference in Protein-Structure Determination Via X-Ray Crystallography. . PhD thesis, University of Wisconsin at Madison, 2011. (Also appears as Technical report CS-TR-11-1703) [slides] |
| [6] | Probabilistic ensembles for improved inference in protein-structure determination. . In Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine (ACM-BCB), pp. 264–273, 2011. Invited for journal publication. [slides] [cached] |
| 2010 | |
| [5] | Guiding belief propagation using domain knowledge for protein-structure determination. . In Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology (ACM-BCB), pp. 285–294, 2010. Best Paper Award. [slides] [cached] |
| 2009 | |
| [4] | Spherical-harmonic decomposition for molecular recognition in electron-density maps. . In International Journal of Data Mining and Bioinformatics, Inderscience Publishers, vol. 3, no. 2, pp. 205–227, 2009. (PDF links to pre-print version) NIHMSID: NIHMS68171. PMCID: PMC2696052. |
| 2008 | |
| [3] | Machine learning in structural biology: Interpreting 3D protein images. . Chapter in Introduction to Machine Learning and Bioinformatics (S. Mitra, S. Datta, T. Perkins, G. Michailidis, eds.), CRC Press, pp. 237–276, 2008. |
| 2007 | |
| [2] | Creating protein models from electron-density maps using particle-filtering methods. . In Bioinformatics, Oxford Univ Press, vol. 23, no. 21, pp. 2851–2858, 2007. PMCID: PMC2567142 |
| [1] | Improved methods for template-matching in electron-density maps using spherical harmonics. . In IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 258–265, 2007. Invited for journal publication. [code/data] |