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Kingsford, C. School of Computer Science

I. CURRICULUM VITAE

CARLETON KINGSFORD

EDUCATION Ph.D. in Computer Science (advisor: Mona Singh) Princeton University 2005 M.A. in Computer Science Princeton University 2002 B.S. in Computer Science (second major: Mathematics) Duke University 2000

EMPLOYMENT 2019 – Present Professor, Computational Biology Department, School of Computer Science, Carnegie Mellon University. (Courtesy appointment Department of Biological Sciences.) 2016 – 2019 Associate Professor (with tenure), Computational Biology Department, School of Computer Science, Carnegie Mellon University. (Courtesy appointment Department of Biological Sciences.) 2012 – 2016 Associate Professor (without tenure), Computational Biology Department (formerly the Lane Center for Computational Biology), School of Computer Science, Carnegie Mellon University. 2007 – 2012 Assistant Professor, Computer Science Department, University of Maryland, College Park (Courtesy appointments in Institute for Advanced Computer Studies, Applied Mathematics & Statistics, Biological Sciences Graduate Program, and Department of Bioengineering) 2005 – 2007 Postdoctoral Fellow, Steven L. Salzberg Group, Center for Bioinformatics and Computational Biology, University of Maryland, College Park

II. PUBLICATION LIST H-index: 26

CHAPTERS IN BOOKS 1. P. Spealman, H. Wang, G.E. May, C. Kingsford, and C.J. McManus. Exploring

ribosome positioning on translating transcripts with ribosome profiling. Methods in Molecular Biology, Springer (2015).

2. H. Lee and C. Kingsford. Accurate assembly and typing of HLA using a graph-guided assembler Kourami. HLA Typing: Methods and Protocols, Sebastian Boegel, editor. (2018).

REFEREED JOURNAL PAPERS – PUBLISHED


1. B. Chazelle, C. Kingsford, and M. Singh. A semidefinite programming approach to side-chain positioning with new rounding strategies. INFORMS Journal on Computing, Special Issue on Computational Molecular Biology / Bioinformatics, 16:380-392 (2004). [Cited ≥ 91 times; Conference version appeared as: The side-chain positioning problem: a semidefinite programming formulation with new rounding schemes. In Proceedings of ACM FCRC 2003, Principles of Computing and Knowledge: Paris Kanellakis Memorial Workshop, pages 86-94 (2003).]

2. C. Kingsford, B. Chazelle, and M. Singh. Solving and analyzing side-chain positioning problems using linear and integer programming. Bioinformatics 21:1028-1039 (2005). [Cited ≥ 184 times.]

3. C. Kingsford, K. Ayanbule, and S. Salzberg. Rapid, accurate, computational discovery

of Rho-independent transcription terminators illuminates their relationship to DNA uptake. Genome Biology 8:R22 (2007). [Cited ≥ 346 times.]

4. S. L. Salzberg, C. Kingsford, G. Cattoli, D. J. Spiro, D. A. Janies, M. Mehrez Aly, I. H.

Brown, E. Couacy-Hymann, G. Mario De Mia, D.H. Dung, A. Guercio, T. Joannis, A. S. Maken Ali, A. Osmani, I. Padalino, M. D. Saad, V. Savic, N. A. Sengamalay, S. Yingst, J. Zaborsky, O. Zorman-Rojs, E. Ghedin, and I. Capua. Genome analysis linking recent European and African influenza (H5N1) viruses. Emerging Infectious Diseases 13(5):713-718 (2007). [Cited ≥ 199 times.]

5. C. Kingsford, A. Delcher, and S. L. Salzberg. A unified model explaining the offsets of overlapping and near-overlapping prokaryotic genes. Molecular Biology and Evolution 24:2091-2098 (2007).

6. C. Kingsford and S. L. Salzberg. What are decision trees? (Review), Nature

Biotechnology 26(9):1011-1013 (2008). [Cited ≥ 140 times.] 7. S. Navlakha, M. C. Schatz, and C. Kingsford. Revealing biological modules using graph

summarization. Journal of Computational Biology 16(2):253-264 (2009). [Presented at RECOMB-SB/RG satellite conference, 2008; cited ≥ 75 times.]

8. C. Kingsford†, N. Nagarajan†, and S. Salzberg. 2009 Swine-Origin Influenza A (H1N1)

resembles previous influenza isolates. PLoS ONE 4(7):e6402 (2009). †First two authors contributed equally; C.K. corresponding author. [Cited ≥ 68 times.]

9. S. Navlakha, J. White, N. Nagarajan, M. Pop, and C. Kingsford. Finding biologically

accurate clusterings in hierarchical decompositions using the variation of information. Journal of Computational Biology 17(3):503-516 (2010). [Conference version appeared in Proceedings of 13th Annual International Conference on Research in Computational Molecular Biology (RECOMB), pages 400-418 (2009).]

10. C. Kingsford, M. Schatz, M. Pop. Assembly complexity of prokaryotic genomes using

short reads. BMC Bioinformatics 11:21 (2010). [Designated highly accessed; top-10 most-viewed articles Jan/Feb 2010; top-10 cited article in BMC Bioinformatics for 2010; cited ≥ 102 times.]

11. S. Navlakha and C. Kingsford. The power of protein interaction networks for associating

diseases with genes. Bioinformatics 26 (8):1057-1063 (2010). [Recommended by the Faculty of 1000 (http://f1000.com/3314959); cited ≥ 255 times.]

12. J. White, S. Navlakha, N. Nagarajan, C. Kingsford, and M. Pop. Alignment and

clustering of phylogenetic markers – implications for microbial diversity studies. BMC


Bioinformatics 11:152 (2010). [Designated highly accessed by the journal; cited ≥ 73 times.]

13. C. Kingsford, E. Zaslavsky, and M. Singh. A cost-aggregating integer linear program for

motif finding. Journal of Discrete Algorithms 9(4):326-334 (2011). [Conference version appeared as: A compact mathematical programming formulation for DNA motif finding. In Proceedings of the 17th Annual Symposium on Combinatorial Pattern Matching, LNCS 4009, pages 233-245 (2006).]

14. N. Nagarajan and C. Kingsford. GiRaF: Robust, computational identification of

influenza reassortments via graph mining. Nucleic Acids Research 39(6):e34 (2011). [Cited ≥ 39 times.]

15. G. Marçais and C. Kingsford. A fast, lock-free approach for efficient parallel counting of

occurrences of k-mers. Bioinformatics 27(6):764-770 (2011). [Cited ≥ 650 times.] 16. D. R. Kelley and C. Kingsford. Extracting between-pathway models from E-MAP

interactions using expected graph compression. Journal of Computational Biology 18(3):379-390 (2011). [Conference version appeared in Proceedings of the 14th Annual International Conference on Research in Computational Molecular Biology (RECOMB), pages 248-262 (2010).]

17. S. Navlakha and C. Kingsford. Network archaeology: Uncovering ancient networks

from present-day interactions. PLoS Computational Biology 7(4):e1001119. [Selected for oral presentation at the RECOMB-Systems Biology satellite conference, 2010; cited ≥ 57 times.]

18. J. Wetzel, C. Kingsford, and M. Pop. Assessing the benefits of using mate-pairs to

resolve repeats in de novo short-read prokaryotic assemblies. BMC Bioinformatics 12:95, 2011. [Cited ≥ 53 times. Designated “Highly Accessed” by the journal.]

19. R. Patro, E. Sefer, J. Malin, G. Marcais, S. Navlakha, and C. Kingsford. Parsimonious reconstruction of network evolution. Algorithms for Molecular Biology 7:25 (2012). [Conference version appeared in Proceedings of the 11th Workshop on Algorithms in Bioinformatics (WABI), pages 237-249 (2011).]

20. R. Patro and C. Kingsford. Global network alignment using multiscale spectral

signatures. Bioinformatics 28(23):3105-3114 (2012). [Cited ≥ 104 times.] 21. G. Duggal and C. Kingsford. Graph rigidity reveals well-constrained regions of

chromosome conformation embeddings. BMC Bioinformatics 13:241 (2012). 22. D. Filippova, A. Gadani, C. Kingsford. Coral: an integrated suite of visualizations for

comparing clusterings. BMC Bioinformatics 13:276 (2012). [Designated “Highly Accessed” by the journal.]

23. G. Duggal, R. Patro, E. Sefer, H. Wang, D. Filippova, S. Khuller and C. Kingsford.

Resolving spatial inconsistencies in chromosome conformation measurements. Algorithms for Molecular Biology 8:8 (2013). [Conference version appeared as: Resolving spatial inconsistencies in chromosome conformation data. In Proceedings of 12th Annual Workshop on Algorithms in Bioinformatics (WABI), pp 288-300, 2012.]

24. G. Duggal, H. Wang, and C. Kingsford. Higher-order chromatin domains link eQTLs

with the expression of far-away genes. Nucleic Acids Research 42(1):87-96 (2014).


25. R. Patro, S. M. Mount, and C. Kingsford. Sailfish enables alignment-free isoform quantification from RNA-seq reads using lightweight algorithms. Nature Biotechnology 32:462-464 (2014). [Cited ≥ 270 times.]

26. D. Filippova, R. Patro, G. Duggal, and C. Kingsford. Identification of alternative

topological domains in chromatin. Algorithms for Molecular Biology 9:14 (2014). [Cited ≥ 79 times; Designated “Highly Accessed” by the journal. Conference version appeared as: Multiscale identification of topological domains in chromatin. In Proceedings of Workshop on Algorithms in Bioinformatics (WABI), pages 300-312 (2013).]

27. H. Xin, J. Greth, J. Emmons, G. Pekhimenko, C. Kingsford, C. Alkan, and O. Mutlu.

Shifted Hamming Distance: A fast and accurate SIMD-friendly filter for local alignment in read mapping. Bioinformatics 31(10):1553-60 (2015).

28. C. Kingsford and R. Patro. Compression of short-read sequences using path encoding.

Bioinformatics 31(12):1920-1928 (2015). http://dx.doi.org/10.1093/bioinformatics/btv071

29. R. Patro and C. Kingsford. Data-dependent bucketing improves reference-free

compression of sequencing reads. Bioinformatics 31(17):2770-2777 (2015). http://dx.doi.org/10.1093/bioinformatics/btv248

30. Hongyi Xin, Richard Zhu, Sunny Nahar, John Emmons, Gennady Pekhimenko, Carl

Kingsford, Can Alkan and Onur Mutlu. Optimal seed solver: Optimizing seed selection in read mapping. Bioinformatics 32(11):1632-1642 (2016). http://dx.doi.org/10.1093/bioinformatics/btv670 [ePub ahead of print.]

31. E. Sefer and C. Kingsford. Diffusion Archaeology for Diffusion Progression History

Reconstruction. Knowledge and Information Systems, pages 1-25, 2015 (Journal version of ICDM 2014 paper.)

32. B. Solomon and C. Kingsford. Fast search of thousands of short-read sequencing

experiments. Nature Biotechnology 34:300–302 (2016)

33. H. Wang, J. McManus, and C. Kingsford. Isoform-level ribosome occupancy estimation guided by transcript abundance with Ribomap. Bioinformatics 32(12):1880-1882 (2016). http://dx.doi.org/10.1093/bioinformatics/btw085 [ePub ahead of print.]

34. R. Patro†, R. Norel†, R. J. Prill, J. Saez-Rodriguez, P. Lorenz, F. Steinbeck, B. Ziems,

M. Lustrek, N. Barbarini, A. Tiengo, R. Bellazzi, H.-J. Thiesen, G. Stolovitzky and C. Kingsford. A computational method for designing diverse linear epitopes including citrullinated peptides with desired binding affinities to intravenous immunoglobulin. BMC Bioinformatics 17:155 (2016). † joint first authors. [The method described won first place in the DREAM5 Challenge 1 competition at the RECOMB Systems Biology satellite conference, 2010.]

35. E. Sefer, G. Duggal, and C. Kingsford. Deconvolution of ensemble chromatin

interaction data reveals the latent mixing structures in cell subpopulations. Journal of Computational Biology 23(6):425-38 (2016). First appeared in Proceedings of the 19th Annual International Conference on Research in Computational Molecular Biology (RECOMB), pages 293-308 (2015).

36. H. Karathia, C. Kingsford, M. Girvan and S. Hannenhalli. A pathway-centric view of

spatial proximity in the 3D nucleome across cell lines. Scientific Reports http://dx.doi.org/10.1101/017087.


37. N. Sauerwald†, S. Zhang†, C. Kingsford, and Ivet Bahar. Chromosomal dynamics predicted by an elastic network model explains genome-wide accessibility and long-range couplings. Nuc. Acids Res., 45(7):3663-3673 (2017). Pre-print available at http://dx.doi.org/10.1101/08118.

38. R. Patro, G. Duggal, M. I Love, R. A Irizarry, C. Kingsford. Salmon provides accurate,

fast, and bias-aware transcript expression estimates using dual-phase inference. Nature Methods 14:417-419 (2017) doi: http://dx.doi.org/10.1101/021592 (pre-print cited ≥ 37 times; manuscript cited ≥ 354 times).

39. Yaron Orenstein§, David Pellow§, Guillaume Marçais, Ron Shamir†, and Carl

Kingsford†. Designing small universal k-mer hitting sets for improved analysis of high-throughput sequencing. PLoS Computational Biology, 13(10): e1005777, 2017. (Workshop version appeared as “Compact Universal k-mer Hitting Sets” in Proceedings of WABI, pages 257-268, 2016). †joint corresponding authors; §contributed equally. https://doi.org/10.1371/journal.pcbi.1005777

40. Mingfu Shao and Carl Kingsford. Accurate assembly of transcripts through phase-

preserving graph decomposition. Nature Biotechnology 35:1167–1169 (2017) http://dx.doi.org/10.1038/nbt.4020

41. Mingfu Shao and Carl Kingsford. Theory and A Heuristic for the Minimum Path Flow

Decomposition Problem. IEEE Transactions on Computational Biology and Bioinformatics 16(2):658-670. (Conference version first appeared as Mingfu Shao and Carl Kingsford. Efficient Heuristic for Decomposing a Flow with Minimum Number of Paths. In RECOMB-seq, 2017. doi: http://dx.doi.org/10.1101/087759)

42. H. Lee and C. Kingsford. Kourami: Graph-Guided Assembly for Novel HLA Allele

Discovery. Genome Biology 19:16, 2018. https://doi.org/10.1186/s13059-018-1388-2

43. Hao Wang, Carl Kingsford, and C. Joel McManus. Using the Ribodeblur pipeline to recover A-sites from yeast ribosome profiling data. Methods 137:67-70, 2018.

44. C. Ma, M. Shao, and C. Kingsford. SQUID: Transcriptomic structural variation

Detection from RNA-seq. Genome Biology 19:52, 2018. https://doi.org/10.1186/s13059-018-1421-5

45. Guillaume Marçais, Brad Solomon, Rob Patro, Carl Kingsford (2019). Sketching and

Sublinear Data Structures in Genomics. Annual Review of Biomedical Data Science, 2:93-118. http://www.annualreviews.org/eprint/SAEEJ5IATHJDK3ES4YST/full/10.1146/annurev-biodatasci-072018-021156

46. Laura H. Tung, Mingfu Shao, Carl Kingsford (2019). Quantifying the Benefit Offered

by Transcript Assembly with Scallop-LR on Single-Molecule Long Reads. To appear Genome Biology (bioRxiv. [https://doi.org/10.1101/632703])

47. Cong Ma, Carl Kingsford (2019). Detecting anomalies in RNA-seq quantification. Cell

Systems 9:1-11. (pre-print. https://doi.org/10.1101/541714)

48. Natalie Sauerwald, Akshat Singhal, Carl Kingsford (2018). Analysis of the structural variability of topologically associated domains as revealed by Hi-C. Nuc Acids Res Genomics and Bioinformatics 2(1):iqz008 (2020) [pre-print: https://doi.org/10.1101/498972]


49. HuMAP Consortium (2019). The human body at cellular resolution: the NIH Human Biomolecular Atlas Program. Nature 574:187-192 (2019).

REFEREED CONFERENCE/WORKSHOP PAPERS 1. J. H. Reif, T. H. LaBean, M. Pirrung, V. S. Rana, B. Guo, C. Kingsford, and G. S.

Wickham. Experimental construction of very large scale DNA databases with associative search capability. In Proceedings of the Seventh International Meeting on DNA Based Computers, pages 231-247 (2001). [Cited ≥ 78 times.]

2. N. Nagarajan and C. Kingsford. Uncovering genomic reassortments among infuenza

strains by enumerating maximal bicliques. In Proceedings of IEEE International Conference on Bioinformatics and Biomedicine, pages 223-230 (2008).

3. G. Lapizco-Encinas, C. Kingsford, and J. Reggia. A cooperative combinatorial particle

swarm optimization for side-chain packing. In Proceedings of IEEE Swarm Intelligence Symposium (SIS), part of the IEEE Symposium Series on Computational Intelligence, pages 22-29 (2009).

4. S. Navlakha and C. Kingsford. Exploring biological network dynamics with ensembles

of graph partitionings. Pacific Symposium on Biocomputing (PSB), pages 166-177 (2010).

5. G. Lapizco-Encinas, C. Kingsford and J. Reggia. Particle swarm optimization for

multimodal combinatorial problems and its application to protein design. In Proceedings of IEEE Congress on Evolutionary Computation (CEC), pages 1-8 (2010).

6. G. Duggal, S. Navlakha, M. Girvan, C. Kingsford. Uncovering many views of biological

networks using ensembles of near-optimal partitions. In Proceedings of MultiClust: 1st International Workshop on Discovering, Summarizing, and Using Multiple Clusterings, KDD (2010). [Available at: http://eecs.oregonstate.edu/research/multiclust/nearopttrees-2.pdf]

7. E. Sefer and C. Kingsford. Metric labeling and semi-metric embedding for protein annotation prediction. In Proceedings of 15th Annual International Conference on Research in Computational Molecular Biology (RECOMB), pages 392-407 (2011).

8. R. Patro†, G. Duggal†, E. Sefer, H. Wang, D. Filippova, and C. Kingsford. The missing

models: A data-driven approach for learning how networks grow. In Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pages 42-50 (2012). †First two authors contributed equally.

9. D. Filippova, M. Fitzgerald, C. Kingsford, F. Benadon. Dynamic exploration of

recording sessions between jazz musicians over time. In Proceedings of International Conference on Social Computing (SocialCom), pages 368-376 (2012).

10. R. Patro and C. Kingsford. Predicting protein interactions via parsimonious network

history inference. In 21st Annual Conference on Intelligent Systems for Molecular Biology (ISMB) and Bioinformatics 29(13):i237-i246 (2013).

11. H. Wang, G. Duggal, R. Patro, M. Girvan, S. Hannenhalli, and C. Kingsford.

Topological properties of chromosome conformation graphs reflect spatial proximities within chromatin. In Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics (BCB), pages 306-315 (2013).


12. E. Sefer and C. Kingsford. Diffusion archaeology for diffusion progression history

reconstruction. In Proceedings of IEEE International Conference on Data Mining (ICDM), pages 530-539 (2014).

13. E. Sefer and C. Kingsford. Convex risk minimization to infer networks from

probabilistic diffusion data at multiple scales. In Proceedings of IEEE International Conference on Data Engineering (ICDE), pages 663-674 (2015).

14. E. Sefer and C. Kingsford. Semi-nonparametric modeling of topological domain

formation from epigenetic data. In Proceedings of Workshop on Algorithms in Bioinformatics (WABI), pages 148-161 (2015).

15. D. Filippova and C. Kingsford. Rapid separable compression enables fast analyses of

sequence alignments. In Proceedings of ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), pages 194-201 (2015).

16. D. Pellow, D. Filippova, and C. Kingsford. Improving Bloom filter performance on

sequence data using k-mer Bloom filters. In Proceedings of the 20th Annual International Conference on Research in Computational Molecular Biology (RECOMB), 2016.

17. H. Wang, J. C. McManus, and C. Kingsford. Accurate Recovery of Ribosome Positions

Reveals Slow Translation of Wobble-Pairing Codons in Yeast. In Proceedings of the 20th Annual International Conference on Research in Computational Molecular Biology (RECOMB), 2016.

18. N. Gupta, K. Sanjeev, T. Wall, C. Kingsford, R. Patro. Efficient Index Maintenance

Under Dynamic Genome Modification. In RECOMB-seq Satellite Workshop, 2016. http://arxiv.org/abs/1604.03132

19. B. Solomon and C. Kingsford. Improved Search of Large Transcriptomic Sequencing

Databases Using Split Sequence Bloom Trees. In RECOMB 2017: Research in Computational Molecular Biology, pages 257-271, 2017. Profiled with a blurb in Cell Systems (Sep. 2017). [Journal version in J. Comp. Biology.]

20. G. Marçais, D. Pellow, D. Bork, Y. Orenstein, R. Shamir, C. Kingsford. Improving the

performance of minimizers and winnowing schemes. In Proceedings of ISMB and Bioinformatics 33(14):i110-117, 2017.

21. G. Marçais, D. DeBlasio, C. Kingsford. Asymptotically optimal minimizers schemes. In

In Proceedings of ISMB 2018. Bioinformatics 34(13):i13-i22, 2018. (Preprint: https://www.biorxiv.org/content/early/2018/01/30/256156)

22. N. Sauerwald and C. Kingsford. Quantifying the similarity of topological domains

across normal and cancer human cell types. In Proceedings of ISMB 2018, Bioinformatics 34(13):i475–i483, 2018.

23. Guillaume Marçais, Dan DeBlasio, Prashant Pandey, Carl Kingsford (2019). Locality

sensitive hashing for the edit distance. In Proceedings of ISMB 2019.

24. Quang Minh Hoàng, Nghia Hoang, Bryan Low, Carl Kingsford (2019). Collective Model Fusion for Multiple Black-Box Experts. In Proceedings of ICML 2019.


25. Yutong Qiu, Cong Ma, Han Xie, Carl Kingsford (2019). Detecting Transcriptomic Structural Variants in Heterogeneous Contexts via the Multiple Compatible Arrangements Problem. In Proceedings of WABI 2019.

26. Dan DeBlasio, Fiyinfoluwa Gbosibo, Carl Kingsford, Guillaume Marcais (2019).

Practical universal k-mer sets for minimizer schemes. In Proceedings of ACM-BCB 2019. [Best student paper award.]

27. Hongyi Xin, Mingfu Shao, Carl Kingsford (2019). Context-Aware Seeds for Read

Mapping. In Proceedings of WABI 2019.

28. Natalie Sauerwald, Yihang Shen, Carl Kingsford (2019). Topological data analysis reveals principles of chromosome structure throughout cellular differentiation. In Proceedings of WABI 2019. [Preprint: https://doi.org/10.1101/540716]

29. Dan DeBlasio, Kwanho Kim, Carl Kingsford (2019). More accurate transcript assembly

via parameter advising. In Proceedings of the 2019 ICML Workshop on Computational Biology. [Preprint: https://doi.org/10.1101/342865]

OTHER PUBLICATIONS

1. C. Kingsford. Computational Approaches to Problems in Protein Structure and Function, Ph.D. Dissertation, Department of Computer Science, Princeton University, August 2005.

2. C. Kingsford and G. Marçais. A synthesis for exactly 3-edge-connected graphs. http://arxiv.org/abs/0905.1053 [Authors are alphabetized.]

3. C. Kingsford. Review of “Complex Social Networks” by Fernando Vega-Redondo. ACM SIGACT News 41(1):29-31, 2011.

4. C. Kingsford. Teaching Computation to Biologists. (Book Review). Computing in Science & Engineering. 18(1):4-5 (2016).

5. Farhad Hormozdiari, Fereydoun Hormozdiari, Carl Kingsford, Paul Medvedev, Raheleh Salari, Fabio Vandin. RECOMB Over the Last 10 Years. Invited to Proceedings of the 20th Annual International Conference on Research in Computational Molecular Biology (RECOMB)

PRE-PRINTS

1. Scott A Keith, Rory Eutsey, Heewook Lee, Brad Solomon, Stacie Oliver, Carl Kingsford, N Luisa Hiller, Brooke M McCartney (2019). Identification of Microbiota-Induced Gene Expression Changes in the Drosophila melanogaster Head. BioRxiv. https://doi.org/10.1101/561043

2. Avi Srivastava, Laraib Malik, Mohsen Zakeri, Hirak Sarkar, Charlotte Soneson, Michael

I Love, Carl Kingsford, Rob Patro (2019). Alignment and mapping methodology influence transcript abundance estimation. bioRxiv. [https://www.biorxiv.org/content/10.1101/657874v1]

3. Vaibhav Rajan, Carl Kingsford, Xiuwei Zhang (2019). Maximum Likelihood

Reconstruction of Ancestral Networks by Integer Linear Programming. bioRxiv. [https://www.biorxiv.org/content/10.1101/574814v1]


4. Maria-Florina Balcan, Dan DeBlasio, Travis Dick, Carl Kingsford, Tuomas Sandholm,

Ellen Vitercik (2019). How much data is sufficient to learn high-performing algorithms? arXiv:1908.02894 cs.LG.

5. Cong Ma, Hongyu Zheng, Carl Kingsford (2019). Finding ranges of optimal transcript expression quantification in cases of non-identifiability. bioRxiv. https://www.biorxiv.org/content/10.1101/2019.12.13.875625v1

6. Cong Ma, Carl Kingsford (2019). Estimating mutual information under measurement error. bioRxiv 852384. https://www.biorxiv.org/content/10.1101/852384v1

7. Natalie Sauerwald, Carl Kingsford (2019). A statistical method for identifying consistently important features across samples. BioRxiv. https://biorxiv.org/cgi/content/short/833624v1

SOFTWARE ARTIFACTS 1. SCPLP. Ampl models for side-chain positioning.

⟨http://compbio.cs.princeton.edu/scplp⟩ 2. TransTermHP. Software system for the discovery of Rho-independent termination

signals in bacterial genomes. ⟨http://transterm.cbcb.umd.edu⟩ 3. VI-Cut. Software to find clusters that optimally match partially known labels.

⟨http://cbcb.umd.edu/VICut/⟩ 4. GIRAF. A computational method for reassortment detection.

⟨http://cbcb.umd.edu/software/giraf⟩

5. ModuTree. Clustering with partial cluster label information. ⟨http://www.cs.cmu.edu/~ckingsf/software/modutree/⟩

6. JELLYFISH. A fast, parallel k-mer counter. ⟨http://cbcb.umd.edu/software/jellyfish⟩ 7. PARANA. Parsimonious reconstruction of ancestral interaction networks.

⟨http://www.cs.cmu.edu/~ckingsf/software/parana/⟩

8. GHOST. Global alignment of biological networks via spectral signatures. ⟨http://www.cs.cmu.edu/~ckingsf/software/ghost/⟩

9. STARFISH. Software to identify rigid components in chromosome conformation

capture data. ⟨http://www.cs.cmu.edu/~ckingsf/software/starfish/⟩ 10. CORAL. An integrated suite of visualizations for comparing clusterings.

⟨http://cbcb.umd.edu/kingsford-group/coral/⟩

11. Map of Jazz Musicians: web application to explore recorded collaborations between jazz musicians. ⟨http://mapofjazz.com⟩

12. PARANA2. Parsimonious reconstruction of ancestral interaction networks by summing

over histories. ⟨http://www.cs.cmu.edu/~ckingsf/software/parana2/⟩ 13. Armatus. Multi-resolution domain calling software for chromosome conformation

capture interaction matrices. ⟨https://github.com/kingsfordgroup/armatus⟩


14. SAILFISH. Fast transcript abundance quantification from RNA-seq.

⟨http://www.cs.cmu.edu/~ckingsf/sailfish⟩

15. DHREC: Diffusion archeology to predict past diffusion history from several snapshots. ⟨http://www.cs.cmu.edu/~ckingsf/software/dhrec/code.html⟩

16. CORMIN: Software to infer contact networks from diffusion data.

⟨http://www.cs.cmu.edu/~ckingsf/software/cormin/code.html⟩

17. PathEnc. Compression of short-read sequences using path encoding. ⟨http://www.cs.cmu.edu/~ckingsf/software/pathenc⟩

18. MINCE: bucketing-based reference-free compression.

⟨http://www.cs.cmu.edu/~ckingsf/software/mince/⟩

19. Ribomap: Isoform-level ribosome occupancy estimation guided by transcript abundance. ⟨http://www.cs.cmu.edu/~ckingsf/software/ribomap/⟩

20. Sequence Bloom Trees: fast search of thousands of short-read sequencing collections.

⟨http://www.cs.cmu.edu/~ckingsf/software/bloomtree/⟩

21. 3CDE: Software for the deconvolution of Hi-C matrices from mixed populations of cells. ⟨http://www.cs.cmu.edu/~ckingsf/research/3cde/code.html⟩

22. Referee: compression of sequence alignment files. ⟨https://github.com/Kingsford-

Group/referee⟩

23. SALMON: Fast, accurate software for RNA-seq expression quantification ⟨http://combine-lab.github.io/salmon/⟩

24. SQUID: Transcriptomic structural variation detection from RNA-seq.

⟨https://github.com/Kingsford-Group/squid⟩

25. SCALLOP: improved transcript assembly. ⟨https://github.com/Kingsford-Group/scallop⟩

26. Kourami: Graph-guided assembly for novel HLA allele discovery.

⟨https://github.com/Kingsford-Group/kourami⟩

VIDEO PRODUCTIONS 1. R. Patro, G. Duggal, E. Sefer, H. Wang, D. Filippova, and C. Kingsford. The Missing

Models Teaser Video. [Won best video at KDD 2012.]

III. EVIDENCE OF EXTERNAL REPUTATION

CITATIONS AND AWARDS § Duke University Dean's List (various semesters), 1997-2000. § Outstanding Undergraduate Teaching Assistant, Computer Science Department, Duke

University, 1999. § Graduated magna cum laude, 2000. § DIMACS Summer Support Award ($1,000), 2004. § Named one of 30 “Tomorrow's PIs” by Genome Technology Magazine, December 2008.


§ University of Maryland Computer Science Department “CS Teaching Excellence Award for Professor” ($500 research funds), 2010.

§ NSF CAREER award, 2011. § Alfred P. Sloan Research Fellowship in Computational and Evolutionary Molecular

Biology, 2012. § Gordon and Betty Moore Data-Driven Discovery Investigator Competition, 2014 - $1.5

million (14 awarded out of 1095 applicants). § Invited to be a “long-term participant” of the “Algorithmic Challenges in Genomics”

semester-long program at the Simons Institute for the Theory of Computing at Berkeley, Spring 2016.

INVITED TALKS

§ The side-chain positioning problem. DIMACS Workshop on Geometric Optimization, Piscataway, NJ, May 19, 2003.

§ Uncovering Reassortments Among Influenza Strains by Enumerating Maximal Bicliques. INFORMS Annual Meeting, Washington, D.C., October 13, 2008.

§ The Power of Interaction Networks for Identifying Disease-related Genes. University of

Maryland / NIH National Cancer Institute Systems Biology Collaboration Workshop. January 26, 2010.

§ Clustering Uncertain Biological Networks. Network Dynamics 2010. April 9, 2010.

§ Clustering Uncertain Biological Networks. Workshop of the Partnership for Cancer

Technology at NIH. June 15, 2010.

§ Analyzing protein-protein interactions for annotation prediction. American Chemical Society Mid-Atlantic Regional Meeting (MARM). May, 23, 2011.

§ Network Archaeology: Uncovering Ancient Networks from Present-day Interactions.

INFORMS Annual Meeting, Charlotte, NC, 2011.

§ Graph-theoretic Approaches for Testing Embeddability and Spatial Functional Enrichment in Chromosome Conformation Data. Pac. Symp. Biocomp., Hawaii, Jan. 2012.

§ Network Archaeology: Uncovering Ancient Networks from Present-day Interactions. IMA

workshop Network Links: Connecting Social, Communication, and Biological Network Analysis, University of Minnesota, Mar. 2012.

§ Network Archaeology: Uncovering Ancient Networks from Present-Day Interactions.

ISMB 2012 highlights track talk.

§ Network Archaeology: Uncovering Ancient Networks from Present-day Interactions. SIAM Conference on Discrete Mathematics, Halifax, Nova Scotia, 2012

§ Computational Challenges Comprehending Chromosome Conformation Capture

Constraints, 13th INFORMS Computing Society Conference, 2013

§ Modeling the Evolution of Networks. Systems Biology: Networks, Cold Spring Harbor, NY, 2013.

§ Detection of Alternative Domains in Chromosome Conformation Capture Data. Highlights


talk at ACM-BCB, 2015.

§ How fast do ribosomes move? RECOMB Satellite Conference on Bioinformatics Education, HHMI Chevy Chase campus, November 2015.

§ Featured speaker at CMU President’s Global Advisory Council annual meeting, October

2016.

§ Speaker at Distinguished Seminar Series at Institute for Computational Medicine at Johns Hopkins University, Dec 3, 2019.

SEMINARS & COLLOQUIA

§ Solving side-chain positioning problems using mathematical programming. Sandia National Laboratories, Albuquerque, NM. August 10, 2004.

§ Exploring protein structure using mathematical programming. Industrial Affiliates Day, Princeton, NJ, September 30, 2004.

§ Modeling problems in biology using linear and integer programming. Program in Integrative Information, Computer and Application Sciences, Princeton, NJ. March 28, 2005.

§ Combinatorially optimal side-chain positioning using integer programming. Barry Honig lab, Columbia, New York, NY. April 27, 2005.

§ Combinatorially optimal side-chain positioning using integer programming. David Baker lab, U. Washington, Seattle, WA. May 2, 2005.

§ Combinatorially optimal side-chain positioning using integer programming. Mark Gerstein group, Yale University. May 9, 2005.

§ Combinatorially optimal side-chain positioning using integer programming. George Church lab, Harvard Medical School, Boston, MA. May 19, 2005.

§ Combinatorially optimal side-chain positioning using integer programming. Steven Salzberg group, The Institute for Genome Research, Rockville, MD. May 24, 2005.

§ Prediction of Transcription Terminators in Prokaryotes. Program in Integrative Information, Computer and Application Sciences, Princeton, NJ. February 28, 2007.

§ Transcription Terminators, DNA Uptake, and Overlapping Genes. Lambda Lunch Seminar, National Institutes of Health, Bethesda, MD. December 18, 2008.

§ Extracting Better Biological Modules from Interaction Networks. U. Pittsburgh & CMU Joint Computational Biology Seminar, Pittsburgh, PA. February 13, 2009.

§ Protein Annotation Prediction by Clustering Within Interaction Networks. University of Delaware. April 15, 2009.

§ Protein Annotation Prediction by Clustering Within Interaction Networks. University of


Maryland, Baltimore County (UMBC), Baltimore, MD. June 23, 2009.

§ Protein Annotation Prediction by Clustering Within Interaction Networks. NCBI, NIH, Bethesda, MD. July 14, 2009.

§ Network Archaeology: Uncovering Ancient Networks from Present-day Interactions. J. Craig Venter Institute, Rockville, MD, 2011.

§ Two computational challenges in evolution: Influenza reassortment detection & Reconstruction of ancestral protein interactions. Campbell & Company, Baltimore, Maryland. Feb. 2012.

§ RNA-seq expression estimates need not take longer than a cup of coffee. University of

Maryland. May 2013.

§ RNA-seq expression estimates need not take longer than a cup of coffee. Penn State University. November 2013.

§ RNA-seq expression estimates need not take longer than a cup of coffee. Texas Tech.

October 2014.

§ Accurate, fast, and model-aware transcript expression quantification with Salmon. Simons Institute; Workshop on Regulatory Genomics and Epigenomics, March 2016.

§ The Experiment Discovery Problem: Methods for Searching Large Databases of

Sequencing Experiments. Univ of California, San Diego. February 1, 2017.

§ The Experiment Discovery Problem: Methods for Searching Large Databases of Sequencing Experiments. Department of Biomedical Informatics, University of Pittsburgh. February 10, 2017.

IV. EXTERNAL PROFESSIONAL ACTIVITIES CONFERENCE AND WORKSHOP COMMITTEES

§ 2008 INFORMS Annual Meeting, Session organizer, Bioinformatics cluster. § 2008 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Program

committee, area co-chair and session chair. § 2009 Brazilian Symposium on Bioinformatics (BSB), Program committee. § 2009 Computational Systems Bioinformatics Conference (CSB), Program committee. § 2009 Workshop on Algorithms in Bioinformatics (WABI), Program committee. § 2009 Pacific Symposium on Biocomputing (PSB), Reviewer. § 2010 Workshop on Algorithms in Bioinformatics (WABI), Program committee. § 2010 2nd Annual International Conference on Bioinformatics and Computational Biology

(BICOB), Program committee. § 2010 Brazilian Symposium on Bioinformatics (BSB), Program committee. § 2010 Intelligent Systems for Molecular Biology (ISMB), Program committee. § 2010 Pacific Symposium on Biocomputing (PSB), Reviewer. § 2011 Workshop on Algorithms in Bioinformatics (WABI), Program committee. § 2011 ACM Conference on Bioinformatics, Computational Biology and Biomedicine

(BCB), Program committee. § 2011 Intelligent Systems for Molecular Biology (ISMB), Late-breaking research

committee. § 2011 Pacific Symposium on Biocomputing (PSB), Reviewer.


§ 2012 Workshop on Algorithms in Bioinformatics (WABI), Program committee. § 2012 ACM Conference on Bioinformatics, Computational Biology and Biomedicine

(BCB), Program committee. § 2012 Intelligent Systems for Molecular Biology (ISMB), Program Area Co-chair (area:

protein interactions and networks). § 2012 SIAM Conference on Discrete Mathematics, Session organizer, Bioinformatics

cluster (Halifax, Nova Scotia). § 2012 IEEE Symposium on Biological Data Visualization (BioVis), Program committee. § 2013 Workshop on Algorithms in Bioinformatics (WABI), Program committee. § 2013 ACM Conference on Bioinformatics, Computational Biology and Biomedicine

(BCB), Program committee. § 2013 Intelligent Systems for Molecular Biology (ISMB), Program committee. § 2013 IEEE Symposium on Biological Data Visualization (BioVis), Program committee. § 2014 Workshop on Algorithms in Bioinformatics (WABI), Program committee. § 2014 ACM Conference on Bioinformatics, Computational Biology and Biomedicine

(BCB), Program committee. § 2014 Intelligent Systems for Molecular Biology (ISMB), Program committee. § 2014 HitSeq (ISMB satellite), Program committee. § 2014 RECOMB, Program committee, Poster track chair, Local organization committee. § 2015 Workshop on Algorithms in Bioinformatics (WABI), Program committee. § 2015 ACM Conference on Bioinformatics, Computational Biology and Biomedicine

(BCB), Program committee. § 2015 Intelligent Systems for Molecular Biology (ISMB), Program committee. § 2015 RECOMB, Program committee. § 2015 HitSeq (ISMB satellite), Program committee. § 2015 ACM-BCB Tutorial session, Co-organizer. § 2016 4th SIAM Workshop on Network Science, Program committee. § 2016 Intelligent Systems for Molecular Biology (ISMB), Program committee (area:

Comparative Genomics and Proteomics). § 2016 RECOMB-SEQ satellite workshop, Co-chair § 2016 Workshop on Algorithms in Bioinformatics (WABI), Program committee. § 2016 RECOMB, Program committee. § 2017 RECOMB, Program committee. § 2017 RECOMB-Seq, Program committee. § 2017 WABI, Program committee. § 2017 ISMB, Program committee, “HitSeq” track. § 2017 RECOMB-CCB, Program committee. § 2018 WABI, Program committee. § 2018 ISMB, Area Co-Chair, Area: Comparative and Functional Genomics. § 2018 RECOMB Computational Cancer Biology, Program Committee. § 2018 RECOMB-Seq, Program committee. § 2018 FAB (Future of Algorithms in Biology), Founder, Co-organizer § 2019 ISMB, Area Co-Chair, Area: Comparative and Functional Genomics. § 2019 WABI, Program committee. § 2019 Workshop on Automated Algorithm Design, TTI-C, Co-organizer. § 2020 RECOMB, Program committee. § 2020 WABI Co-chair, Program committee. § 2020 ISMB Area Co-chair, Program committee.

MEMBERSHIPS IN PROFESSIONAL SOCIETIES

§ International Society for Computational Biology (ISCB), member, 2008-present § Association for Computing Machinery (ACM), member, 2013-present


EDITORIAL BOARD MEMBERSHIPS

§ PLoS Computational Biology, Guest Associate Editor, 2007. § PLoS ONE, Academic Editor, 2008-2016.

REVIEWING ACTIVITIES (NON-PROGRAM COMMITTEES, PARTIAL LIST)

§ Genome Biology § Genome Research § BMC Bioinformatics § ICALP 2008 § Molecular Biology and Evolution § Nature Biotechnology § Nature Methods § Bioinformatics Journal § IEEE Transactions on Knowledge and Data Engineering § Journal of Combinatorial Optimization § PLoS Computational Biology § ISAAC § Nucleic Acids Research § BMC Systems Biology § Journal of the Royal Society Interface § Theoretical Computer Science § Pattern Recognition Letters § IEEE Computer § Cell Systems § Genes, Genomes, Genetics § IEEE Transactions on Computational Biology and Bioinformatics

REVIEWING ACTIVITIES FOR FUNDING AGENCIES

§ Member of over 7 NSF review panels § Member of NIH ad hoc review panel for R15 applications § Ad hoc member, GCAT NIH Study Section, Fall 2013, Fall 2014, Fall 2016, Winter 2018 § Ad hoc member, BDMA NIH Study Section, Winter, 2017 § Reviewer, DOE Office of Science Graduate Student Research (DOE SCGSR), 2015


VI. EVIDENCE OF TEACHING PERFORMANCE

COURSES TAUGHT AT CARNEGIE MELLON § 02-251 Great Ideas in Computational Biology (co-taught with Phillip Compeau) § 15-451 Algorithms (co-taught with Daniel Sleator) § 02-701 CPCB Journal Club § 02-201/601 Programming for Scientists § 02-613/15-351/15-650 Algorithms and Advanced Data Structures § 02-713/02-513 Algorithms and Data Structures for Scientists § 02-714/02-514 String Algorithms § 03-513 Biological Data Integration Practicum (co-taught with Joel McManus)

COURSES TAUGHT OUTSIDE CARNEGIE MELLON § CMSC 858S Computational Genomics, University of Maryland, College Park § CMSC 423 Bioinformatics, University of Maryland, College Park § CMSC 858M Computational Evolutionary Dynamics, University of Maryland, College

Park § BISI 648a,b Team-taught Graduate Bioinformatics Courses, University of Maryland,

College Park § CMSC 858L Network Algorithms for Biology, University of Maryland, College Park § CMSC 451 Algorithm Design and Analysis, University of Maryland, College Park


§ CMSC 858L Graphs and Networks in Computational Biology, University of Maryland, College Park

§ CMSC 420 Data Structures, University of Maryland, College Park

VII. CONTRIBUTIONS TO EDUCATION

CURRICULUM DESIGN § CMU 02-215 Great Ideas in Computational Biology – This new course teaches

computational biology from a computational and algorithmic perspective. Introduces genomics, network biology, protein structure, and other applications. Joint with Phillip Compeau.

§ CMU 02-201/02-601 Programming for Scientists - This new course teaches programming to advanced students who lack strong programming experience. Focus is on programming concepts and coursework consists of many programming projects.

§ CMU 02-714/02-514 String Algorithms - Developed new course exploring modern

string algorithms, and particularly their application in computational biology.

§ CMU 02-713/02-513 Algorithms and Data Structures for Scientists - Developed this course to teach advanced algorithmic design techniques to MS students who do not necessarily have a strong background in computer science. The course covers the algorithmic design techniques of greedy algorithms, divide-and-conquer, dynamic programming, linear programming, network flow, A*. Splay trees, heaps, and union-find data structures and the theory of NP-completeness are also covered. Converted to 15-351 beginning Fall 2014.

§ UMD CMSC858L Graphs and Networks in Computational Biology - Developed this

new advanced graduate-level course exploring the use of graphs and graph algorithms to model biology and biological problems. Introduced computer science graduate students to the relevant biology. This course was merged with other content to become CMSC 702 Computational Systems Biology), which began being offered in Spring 2012.

§ UMD CMSC858M Computational Evolutionary Dynamics - Developed this new

graduate-level course presenting computational models and problems associated with systems that change over time. Inferring past states of a system (e.g. interaction network, genome sequence) and predicting future states of similar systems.

§ UMD CMSC858S Computational Genomics - Developed this new graduate-level

course covering computational techniques associated with analysis of genomics data. Included sequence alignment algorithms, alignment statistics, phylogenetic reconstruction, exact string matching, suffix arrays and trees, multiple sequence alignment, genome assembly, the Burrows-Wheeler transform, Hidden Markov Models, and gene finding.

LECTURE NOTES AND COURSE MATERIALS § UMD CMSC 423: Extensive bioinformatics lecture slides

http://www.cs.cmu.edu/~ckingsf/bioinfo-lectures/ § 02-613, 15-351, 15-650: Extensive algorithms lecture slides

http://www.cs.cmu.edu/~ckingsf/class/02713/lectures.html § 02-201: assignments and autograders for 10 assignments

OTHER


§ Seminar for high-school students, Andrew's Leap, CMU (“Understanding the Genome: Traveling Salespeople, Evening Strolls, and Logic Puzzles”), July 2014 & July 2015.

§ Instructor, Johns Hopkins CTY program (hosted at CMU), Fall 2013. § Co-organizer, 2011 CBCB Summer Internship program that hosted 3 undergraduate

interns. § Co-organizer, 2010 CBCB Summer Internship program that hosted 6 undergraduate and

high-school interns. § Co-organizer, 2009 CBCB Summer Internship program that hosted 4 undergraduate and

high-school interns. § Mentored high-school student in project to investigate geographical distribution of

influenza (Summer 2007). § Co-organizer, summer seminar series on computational approaches for drug design,

Program in Integrative Information, Computer and Application Sciences, Princeton, NJ, 2004. Sought to bridge gap between academics and industry.

§ Mentored high-school student in project to computationally predict disulfide bonds in protein structures (Summer 2003).

§ Tepper MBA capstone faculty mentor (Spring 2017) for Ryan Swick (with Bill Scherlis and Chris Langmead).

§ Spoke at Fox Chapel High School about genomics (November 2017). § Spoke at Fox Chapel High School about genomics (October 2018).

VIII. STUDENT ADVISING

CURRENT PHD STUDENTS Cong Ma (CPCB)

§ 2015 § Anomaly Detection in Gene Expression

Natalie Sauerwald (CPCB)

§ 2015 § Relating Genome 3D Structure to Function

Daniel Bork

§ 2016 § TBD

Hongyu Zheng (CPCB) § 2017 § TBD

Laura Tung (CPCB)

§ 2017 § TBD

Yutong Qiu (CPCB)

§ 2018 § TBD

Yiheng Shen (CPCB)

§ 2018 § TBD


Minh Hoang (CSD) § 2018 § Genomic Feature Selection

Mohsen Ferdoesi (CPCB; joint with Hosein Mohimani)

§ 2018 § TBD

COMPLETED PHD STUDENTS Bradley Solomon

§ Started: 2013 § Algorithms and Analysis of Large-Scale Data Sets

Hongyi Xin

§ “Methods for Reducing Unnecessary Computation on False Mappings in Read Mapping” (Advised informally since 2014; formal advisor since 2017)

§ February 2018. Hao Wang

§ Computational methods for exploring gene regulation mechanisms using high throughput sequencing data, 2009 – September 2015.

§ Scientist, Roche Darya Filippova

§ “Algorithms for identification, visualization, and compression of prominent substructures in biological data”, July 23, 2015.

§ Scientist, Roche; now Scientist, GRAIL Emre Sefer

§ “Inferring and Analyzing the Present and the Past of Networks from Limited Information”, February 19, 2015

§ Postdoc, Bar-Joseph group, Carnegie Mellon University; now Goldman Sachs Geet Duggal

§ “Algorithms for identifying compact regions of chromatin and their relationship to gene regulation”, December 5, 2014

§ Scientist, DNAnexus Robert Patro

§ “Computationally Comparing Biological Networks and Reconstructing Their Evolution”, July 13, 2012

§ Assistant Professor, Stony Brook University Guillaume Marçais

§ “Genome Assembly Techniques”, July 25, 2011 § Project Scientist, Carnegie Mellon University § Co-advisor James York

Saket Navlakha

§ “Algorithms to Explore the Structure and Evolution of Biological Networks”, October 29, 2010

§ Assistant Professor, Salk Institute for Biological Studies Grecia Lapizco-Encinas


§ “Cooperative Particle Swarm Optimization for Combinatorial Problems”, August 27, 2009 § Senior Data Scientist at LivingSocial § Co-advisor Jim Reggia

POSTDOCTORAL MENTORING

• Dr. Guillaume Marçais, Project Scientist (Current)

• Dr. Prashant Pandey, Postdoc (Postdoc at Berkeley)

• Dr. Heewook Lee, Lane Fellow (Assistant Professor, Arizona State University, Summer 2019)

• Dr. Dan DeBlasio, Lane Fellow (Assistant Professor, University of Texas, El-Paso, Summer 2019)

• Dr. Mingfu Shao, Lane Fellow (Assistant Professor, Penn State University)

• Dr. Rob Patro, Postdoc (Assistant Professor, Stony Brook University)

• Dr. Jeremy Bellay, Postdoc (UMD)

FORMER MASTERS STUDENTS Kwanho Kim, MSCB

§ Analyzing the Influence of Assessment Metrics on Automated Transcript Assembly Parameter Selection, 2014-2019

§ The Broad Institute Timothy Wall

§ Graduated 2017 David Pellow, LTI

§ Candidate genomic origins of the Pre-Implantation Factor (PIF), 2014-2015 § Currently a Ph.D. student with Ron Shamir, TAU

Qian Wan, MSCB

§ Accurate Search of SRA Human RNA-Seq Experiments by Tissue and Cell Type, 2014-2015

§ Affymetrix (Eureka Genotyping branch)

UNDERGRADUATE SENIOR THESES AND RESEARCH PROJECTS Nicholas Jacobs

§ Visualizing Geographical Locations of Influenza Genomes, 2007 Joshua Wetzel

§ Genome Assembly Complexity, 2009 Kris Samala

§ Predicting Evolution of Influenza, 2009


Rachel Blythe

§ Graph-based Detection of Genetic Reassortment and Rearrangement, 2010

Megan Riordan § Graph Clustering and Visualization, 2010

Aashish Gadani

§ Graph Clustering and Visualization, 2010 Cara Treglio

§ Generating ensembles of chromosome structures, 2011-2012 Christina Brant

• Interface design for clinical genomic expert Kevin Au

• Speeding up biological network alignment, 2014 David Lindenbaum

• Speeding up biological network alignment, 2014 Brandon Price

• Implementing machine learning methods for clinical genomics, 2014 Fiyinfoluwa Gbosibo

• Finding sparse universal hitting sets for long k-mers, 2017 Raymond Song

• Using GPUs to speed up expression quantification, 2018

M.S. OR PH.D. THESIS COMMITTEE SERVICE Adam Lee

§ A Framework for Discovering Meaningful Associations in the Annotated Life Sciences Web, 2008

Ben Langmead

§ Algorithms and High Performance Computing Approaches for Sequencing-Based Comparative Genomics, 2009

Cole Trapnell

• Transcript Assembly and Abundance Estimation with High-Throughput RNA Sequencing, 2010

Adam Phillippy

§ Whole-Genome Sequence Analysis for Pathogen Detection and Diagnostics, 2010 Louis Licamale

§ Knowledge Discovery from Gene Expression Data: Novel Methods for Similarity Search, Signature Detection, and Confounder Correction, 2011

Sergy Koren


§ Genome Assembly: Novel Applications by Harnessing Emerging Sequencing Technologies and Graph Algorithms, 2012

Kawther Abdilleh

§ Patterns of gene expression and gene network evolution in Drosophila, 2010–2013 Ted Gibbons

§ Scaling Up Comparative Dinoflagellate Genomics, 2010–present David Kelley

§ Computational Methods to Improve Genome Assembly and Gene Prediction, 2011 Vinodh Rajapaksi

§ Data Representation for Learning and Information Fusion in Bioinformatics, 2011 Daehwan Kim

§ RNA-Sequencing Analysis: Read Alignment and Discovery Reconstruction of Fusion Transcripts, 2011

Pieter Spealman

• Evolution of translational regulation, 2013-present Md Ahsanur Rahman

• Reverse Engineering Hypergraphs from Network Ensembles, 2013-2015 Yizhu Lin

• High-throughput Probing of Human LncRNA Structure, 2013-present David Farrow

• Analysis of the Determinants of Influenza Evolution through Application of Large-Scale and Long-Term Simulation, 2013-2016

Ayshwarya Subramanian

• Inferring tumor evolution using computational phylogenetics, 2014 Salim Akhter Chowdhury

§ Algorithms to Reconstruct Evolutionary Models of Tumor Progression, 2014 Jing Xiang (machine learning, DAP committee)

• An integrated approach to validating ChIP-Seq using A* Lasso for Sparse Bayesian Network Learning, 2014-2017

Andrej Savol

• Spectral Approaches for Identifying Kinetic Features in Molecular Dynamics Simulations of Globular Proteins, 2015

Charlotte Darby (MS Thesis Committee)

• 2016 Kelvin Liu

• TDB, 2017 She Zhang

• TDB, 2017


IX. UNIVERSITY SERVICE

SCHOOL AND DEPARTMENT SERVICE AND COMMITTEE WORK – CARNEGIE MELLON UNIVERSITY • Chair, 10th Anniversary Celebration Conference, Computational Biology Department, 2018-

2019 • Member, Dean Search Committee, School of Computer Science, 2018-2019 • Chair, Faculty Search Committee, Computational Biology, 2018-2019 • Chief Science Officer, Center for Machine Learning and Health, 2017-Present • Co-Associate Director, Joint CMU-Pitt Ph.D. Program in Computational Biology (CPCB),

2015-Present • Member, SCS Council, 2015-Present • TCS Hall Design Committee Chair, Spring 2018 • CPCB Journal Club Instructor, Spring 2017, Spring 2018 • Faculty Mentor: Xu, Compeau, Kim, Mohmani • Co-Director, Masters in Computational Biology Program, 2012-2014 • Co-Chair, Admissions committee, CPCB Ph.D. program, 2015, 2016 • Chair, Faculty search committee, Lane Center / Comp. Biol. Department, 2014–2015 • Member, Faculty search committee, Comp. Biol. Department, 2015–2016; 2017–2018 • Co-Director, Clinical Genomics Expert Project, 2013–2015 • Member, Admissions committee, CPCB Ph.D. program, 2014

SCHOOL AND DEPARTMENT SERVICE AND COMMITTEE WORK – UNIVERSITY OF MARYLAND, COLLEGE PARK • Chair, Computational biology faculty search committee, 2007-2008. • Organizer, Undergraduate Grad School / Research Workshop (2008-2010). • Co-organizer, CS Friday Faculty Lunch (2008-2009). • Middle States dissertation defense evaluation committee (2008-2009). • Judge, High-school programming contest (Spring 2009). • Middle States Evaluation of Writing Skills Committee (Fall 2009). • Judge & problem designer, High-school programming contest (Spring 2010). • Judge & problem designer, High-school programming contest (Spring 2011). • UMIACS Appointments, Promotions, and Tenure (APT) Committee (2011-2012). • Admissions Committee, Computational Biology, Bioinformatics, and Genomics (CBBG)

concentration of Biological Sciences Ph.D. program (2011-2012).

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