Harvard Medical School Jacob Mayne Luber 10 Shattuck Street Boston, MA 02115 B jluber [at] g [dot] harvard [dot] edu Bioinformatics & Integrative Genomics Í scholar.harvard.edu/jluber

Education July Ph.D. Bioinformatics and Integrative Genomics (2021), Harvard University, 2016–Present Cambridge, MA, 02138. Division of Medical Sciences @ HMS / The Graduate School of Arts and Sciences @ Harvard 2012–2016 B.S. with Departmental Honors in Computer Science cum laude, Trinity University, San Antonio, TX. Trinity University Presidential Scholar Trinity University Mach Research Fellow President-Trinity University Chapter of Upsilon Pi Epsilon (honor fraternity of the Association for Computing Machinery) 2009-2012 High School Diploma, The Lawrenceville School, Lawrenceville, NJ.

Awards

Summer 2016 Function SIG (Formerly AFP)/ISMB Best Poster Award, International Society for Computational Biology.

An anonymous International Society for Computational Biology (ISCB) committee selected my talk/poster pairing "Predicting Functional Relationships In Osteoblasts" for the best poster award (tie for 1st place) on July 9th, 2016 at Function SIG (formally AFP) during The 24th Annual International Conference on Intelligent Systems for Molecular Biology (2016) out of a pool mainly comprised of junior faculty. Spring 2016 Trinity CS Department Senior Research Award, Trinity University.

"Outstanding Senior Research Award – not awarded every year, this honor is given to recognize that senior who has a particularly distinguished record of Computer Science research." Spring 2016 Mach Research Fellowship, Trinity University.

Annually, each academic department nominates one senior for the Mach, which recognizes outstanding undergraduate research achievement; of this candidate pool the Faculty Research Committee selects 5 recipients. I received the computer science department nomination and was one of the University wide recipients. Spring 2015 Trinity CS Department Junior Research Award, Trinity University.

"Outstanding Junior Research Award – not awarded every year, this honor is given to recognize that junior who has a particularly distinguished record of Computer Science research." Fall 2014 GCURS Best CS Research Talk, Rice University.

A panel comprised of Rice University CS faculty judged my talk at Rice’s annual undergrad- uate STEM conference to be the best talk in CS.

Research

September Gehlenborg Group (Upcoming), Harvard Medical School (Department of Biomed- 2016 – ical Informatics). January 2017 Upcoming PhD rotation project focusing on novel analysis of Hi-C data. http://gehlenborg.com/

July 2016 – Huttenhower Group, Harvard University TH Chan School of Public Health (De- Present partment of Biostatistics) & The Broad Institute of MIT and Harvard.

Current PhD rotation project focusing large scale machine learning problems in metagenomics and metatransciptomics. https://huttenhower.sph.harvard.edu/

Summer Bult Group, The Jackson Laboratory. 2015-June 2016 Research consisting of data mining and machine learning work to identify novel cancer biomarkers for the Patient Derived Xenograft project at JAX. I built a computational framework that uses statistically sound machine learning techniques to correlate drug response with genome based signatures in Triple Negative Breast Cancer Patient Derived Xenograft models. Through validation of predicted results, we evaluated models based on unsupervised clustering, a per tumor bayesian integration method, and a per gene multi-class support vector machine method. More recent work has focused on subtyping TNBC tumors. https://www.jax.org/research-and-faculty/research-labs/the-bult-lab

May 2014 – Hibbs Group, Trinity University (Department of Computer Science). June 2016 Work on large scale genomic data integration and machine learning (∼500B data points) in the context of finding new pathways that are related to osteoblast differentiation. Succesfully defended my honors undergraduate thesis "Improved Prediction of Mouse Pathways Related to Bone Maintenance Through Machine Learning Utilizing Diverse Genomic Data" in March 2016. http://www.cs.trinity.edu/ mhibbs/HibbsHome/Home.html

January 2015 Jiang Group, Trinity University (Department of Computer Science). – July 2016 Work on applying computational game theory to bayesian problem structuring techniques in computional biology. http://www.cs.trinity.edu/ xjiang/

August 2014 – Watson Group, Trinity University (Department of Economics). August 2015 Work on programming platform for simulating markets near wage equilibrium as well as work in computational game theory developing a meal prediction algorithm and user interface for Continuous Glucose Monitoring Systems that pairs a machine learning algorithm with models from behavioral economics. https://new.trinity.edu/faculty/elizabeth-watson Summer 2014 Center For Hellenic Studies, Harvard University.

Received an undergraduate research fellowship to study in residence at the Homer Multitext Seminar. Contributed work towards the publication of Iliad 12 in Harvard0s diplomatic Multitext edition of the Iliad, which is a project to combine multiple manuscripts of the Iliad and the marginal notes they contain into a set of XML files which are then parsed into a directed cyclic graph. Implemented an algorithm to perform optical character recognition on unusual 9th century Byzantine Greek ligatures that utilizes singular value decomposition and a support vector machine. http://chs.harvard.edu/CHS/article/display/1169 Code & Specific Project Information Detailed Research Overview, http://scholar.harvard.edu/jluber/research.

Poster & Slide Downloads, http://scholar.harvard.edu/jluber/presentations.

Software, http://scholar.harvard.edu/jluber/software-0.

Github, https://github.com/jacobluber.

Bitbucket, https://bitbucket.org/jluber/.

News, http://scholar.harvard.edu/jluber/news. Social Media Twitter, https://twitter.com/JacobLuber.

LinkedIn, https://www.linkedin.com/in/jacobluber. Relevant Coursework In Progress (Fall 2016) @ Harvard Medical School. Molecular Biology, Genetics, Bioinformatics & Integrative Genomics Seminar In Progress (Fall 2016) @ Massachusetts Institute of Technology. Quantitative Genomics Completed @ Trinity University. CS Honors Thesis, Linear Algebra, Compiler Engineering, Graphics, Game Design, Software Engineering, Thesis Readings, Analysis of Algorithms, Advanced Algorithms, Programming Languages, Artificial Intelligence, Special Topics in Computational Biology, Cloud Com- puting Seminar, Database Systems, Calculus,Theoretical Computer Science, Discrete Data Structures, Data Abstraction, Directed Studies in Economics, Directed Studies in Computer Science Completed @ The Jackson Laboratory. 2015 Short Course on Mammalian Genetics Proficiencies Languages and Technologies. Python (numpy, scipy, matplotlib), C++ (boost, Cilk Plus, icpc optimizations), C, C#, R (shiny server), Haskell, Scala, bash, MySQL, MIPS Assembly, LATEX, git, linux, gdb, Unity, processing, d3, cytoscape.js, AWS (EC2, load balancing, etc.), HPC (slurm, torque) Professional 2014 – Member, Association for Computing Machinery (ACM), http://www.acm. Present org/.

2015 – Member, International Society For Computational Biology (ISCB), https: Present //www.iscb.org/.

2016 – Exploratory Planning for ISCB Northeast Regional Student Group, http: Present //rsg.iscbsc.org/rsg. Papers, Conference Presentations, Posters, and Invited Talks 1 Jacob M. Luber, Joan Malcolm, Adam Lavertu, KB Choi, MA Hibbs, Joel H Graber, and Carol J Bult. Data Mining Diverse Compendia of Triple Negative Breast Cancer Samples for Improved Tumor Subtyping [POSTER]. International Conference on Intelligent Systems For Molecular Biology, July 2016. Orlando,FL.

2 Jacob M. Luber, Catherine Sharp, KB Choi, Cheryl Ackert-Bicknell, and MA Hibbs. Predicting Functional Relationships In Osteoblasts [TALK]. Function SIG, July 2016. Orlando, FL.

3 Jacob M. Luber, Catherine Sharp, KB Choi, Cheryl Ackert-Bicknell, and MA Hibbs. Predicting Functional Relationships In Osteoblasts [POSTER] . Function SIG, July 2016. Orlando, FL.

4 Jacob M. Luber. Improved Prediction of Mouse Pathways Related to Bone Maintenance Through Machine Learning Utilizing Diverse Genomic Data [INVITED LIGHTNING TALK]. Computational Systems for Integrative Genomics Workshop, April, 2016. Perelman School of Medicine, University of Pennsylvania. Philadelphia, PA.

5 Jacob M. Luber. Improved Prediction of Mouse Pathways Related to Bone Maintenance Through Machine Learning Utilizing Diverse Genomic Data [UNDERGRADUATE THE- SIS]. Trinity University CS Department Honors Undergraduate Thesis, March, 2016. Trinity University. San Antonio, TX.

6 Jacob M. Luber. Predicting pathways related to bone maintenence [talk]. Trinity University Biomath Seminar, October 2015. Trinity University. San Antonio, TX.

7 Jacob M. Luber and MA Hibbs. Methods for machine learning in functional genomics [talk]. Trinity University Math Majors Colloquium, September 2015. Trinity University. San Antonio, TX.

8 Jacob M. Luber, Joel Graber, and Carol J. Bult. Identifying genome signatures of drug response in patient derived xenografts (PDX): A machine learning approach [TALK]. The Jackson Laboratory Summer Student Symposium, August 2015. The Jackson Laboratory. Bar Harbor, ME.

9 Jacob M. Luber, Joel Graber, and Carol J. Bult. Identifying genome signatures of drug response in patient derived xenografts (PDX): A machine learning approach [MOUSEION PAPER]. The Jackson Laboratory Summer Student Symposium, August 2015. The Jackson Laboratory. Bar Harbor, ME.

10 Jacob M. Luber, AX Jiang, and MA Hibbs. Discerning Systematic Bias In S. cere- visiae Pathways Using Novel Bayesian Statistics Problem Structuring Methods [POSTER]. Joint International Conference on Intelligent Systems For Molecular Biology and European Conference on Computational Biology Student Council Symposium, July 2015. Dublin, Ireland.

11 Jacob M. Luber, Catherine Sharp, KB Choi, Cheryl Ackert-Bicknell, and MA Hibbs. A Context-Specific Machine Learning Method to Predict Novel Osteoporosis Related Pathways [POSTER]. Joint International Conference on Intelligent Systems For Molecular Biology and European Conference on Computational Biology, July 2015. Dublin, Ireland.

12 Jacob M. Luber, Catherine Sharp, KB Choi, Cheryl Ackert-Bicknell, and MA Hibbs. Identification of Osteoporosis-related Genes using Support Vector Machines [POSTER]. International Conference on Intelligent Biology and Medicine, December 2014. San Antonio, TX.

13 Jacob M. Luber, Catherine Sharp, KB Choi, Cheryl Ackert-Bicknell, and MA Hibbs. A Machine Learning Method for Prediction of Osteoporosis-Related Genes [TALK]. Gulf Coast Undergraduate Research Symposium, October 2014. Rice University. Houston, TX.

14 Jacob M. Luber. Support vector machine based learning techniques in functional genomics and computer vision [talk]. Computer Science Colloquium, November 2014. Trinity University. San Antonio, TX.

15 Jacob M. Luber. Machine learning techniques for optical character recognition of 9th century byzantine ligatures [talk]. Homer Multitext Seminar, July 2014. Harvard University Center For Hellenic Studies. Washington, DC.

16 Jacob M. Luber and MA Hibbs. Utilizing machine learning in computational biology and classics [talk]. Trinity University Summer Undergraduate Research Conference, July 2014. Trinity University. San Antonio, TX.

17 Jacob M. Luber. Software development for a bihormonal closed-loop bionic endocrine pancreas. Computer Science Colloquium, October 2013. Trinity University. San Antonio, TX.