Eric J. Ma

Email | 857-209-1375 | LinkedIn | GitHub | Personal Website | North Quincy, MA


Skills

  • Languages and Tools: Python, HTML, CSS, bash scripting, git, Illustrator, Indesign, Photoshop
  • Packages: Pandas, PyMC3 (Bayesian statistics), Flask, scikit-learn, scikit-image, Keras, NetworkX, Mesa
  • ML/Stats: Network science, variational autoencoders, random forests, Bayesian inference, graphical models, agent-based models
  • Life Sciences: Microbiology, virology, biochemistry, molecular biology

Experience

Novartis Institutes for Biomedical Research (NIBR), Investigator II, Cambridge MA

September 2018-Present

  • Investigator in the Scientific Data Analysis (SDA) team reporting to Holger Hoefling.
  • Led an initiative to characterize the performance of message passing neural networks.
  • Developed a hierarchical Bayesian 4-parameter dose response model to aid project team in compound selection.
  • Co-hosted a machine learning session with Sivakumar Gowrisankar at the internal Data in Drug Discovery Day (D4).
  • Co-organized an internal course with Yuan Wang and Laszlo Urban on machine learning for NIBR colleagues in the Pre-Clinical Safety (PCS) department.
  • Led a deep learning workshop at our NIBR Shanghai office.
  • Currently developing a deep Bayesian optimization pipeline to accelerate protein engineering cycles.

Novartis Institutes for Biomedical Research (NIBR), Investigator I, Cambridge MA

September 2017-Present

  • Investigator in the Scientific Data Analysis (SDA) team reporting to Mark Borowsky.
  • Performed internal consulting projects and expanded the SDA Statistical Learning initiative with colleagues.
  • Developed parameterized Bayesian agent-based models of internal project portfolio for scenario planning purposes, using PyMC3 and Mesa.
  • Authored custom deep learning package to train graph convolutional neural networks to predict structural determinants of RNA cutting, with one paper currently in writing.
  • Assisted in mentoring two interns, Stacy Meichle (Computer Aided Drug Discovery) and Fritz Lekschas (SDA).

Insight Data Science, Health Data Science Fellow, Boston MA

June 2017-August 2017

  • Built Flu Forecaster, a machine learning-powered system that forecasts flu sequences six months out, to better prepare for manufacturing of vaccine strains.
  • Implemented a variational autoencoder (deep learning model) to learn a continuous representation of 14,455 influenza hemagglutinin protein sequences, and trained a Gaussian process model on the continuous representation to predict new flu sequences.
  • Developed interactive blog post using Flask and Bootstrap, and deployed to Heroku and GitHub.
  • Led peer workshops on web development, deep learning and code style.

Massachusetts Institute of Technology, ScD Candidate, Cambridge MA

August 2011-May 2017

  • Developed a scalable, network-based phylogenetic heuristic algorithm for detecting reassortant influenza viruses using 18,632 fully sequenced virus genomes that improved our capacity to detect reassortment events by two orders of magnitude.
  • The algorithm was used in a lead-author study (published in PNAS) providing systematic evidence that genome shuffling is important for host switching, and a co-authored study (published in Ecology Letters) that showed that reassortment is a strategy for viral gene persistence in wild animal reservoirs.
  • Contributed reproducible data analysis for colleagues through fluorescent image quantification and genomic analysis in studies that refuted binding properties of novel influenza viruses.
  • Performed Bayesian statistical modelling for colleagues testing the efficacy of phone sterilization tools.
  • Delivered tutorials and talks on Network Analysis and Bayesian statistical methods at annual Python conferences, including PyCon, SciPy, and PyData.

The University of British Columbia, Undergraduate Researcher, Vancouver BC

June 2006-May 2010

  • Investigated the role of T cells in intestinal inflammation and fibrosis in a Salmonella typhimurium-induced model of gut inflammation, leading to First Prize Poster (Rising Stars of Research 2008) and Best Talk (Multidisciplinary Undergraduate Research Conference 2009) awards.
  • Co-founded the first UBC International Genetically Engineered Machines (iGEM) team, where we achieved a Gold status standing in our first year of competition.
  • Served as a Peer Academic Coach, guiding first- and second-year students towards academic success through building good habits on learning strategies and time management.

Education

Sc.D., Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge MA

August 2011-May 2017

B.Sc., Integrated Sciences, The University of British Columbia, Cambridge MA

June 2006-May 2010


Publications

  • Long-term colonization dynamics of Enterococcus faecalis in implanted devices in research macaques. Applied and Environmental Microbiology (2018). [link]
  • Evaluation of 6 Methods for Aerobic Bacterial Sanitization of Smartphones. Journal of the American Association for Laboratory Animal Science (2018). [link]
  • Evaluation of 6 Methods for Aerobic Bacterial Sanitization of Smartphones. Journal of the American Association for Laboratory Animal Science (2017). [link]
  • Reassortment of influenza A viruses in wild birds in Alaska before H5 clade 2.3. 4.4 outbreaks. Emerging Infectious Diseases (2017). [link]
  • A real-time surveillance dashboard for monitoring viral phenotype from sequence. International Journal of Infectious Diseases (2016). [link]
  • Evidence of seasonality in a host-pathogen system: Influenza across the annual cycle of wild birds. Integrative and Comparative Biology (2016). [link]
  • A point mutation in the polymerase protein PB2 allows a reassortant H9N2 influenza isolate of wild-bird origin to replicate in human cells. Infection, Genetics and Evolution (2016). [link]
  • New England harbor seal H3N8 influenza virus retains avian-like receptor specificity. Scientific Reports (2016). [link]
  • Ecosystem interactions underlie the spread of avian influenza a viruses with pandemic potential. PLOS Pathogens (2016). [link]
  • Transmission of influenza reflects seasonality of wild birds across the annual cycle. Ecology Letters (2016). [link]
  • Reticulate evolution is favored in influenza niche switching. PNAS (2016). [link]
  • Genetic characterization of a rare H12N3 avian influenza virus isolated from a green-winged teal in Japan. Virus Genes (2015). [link]