Dr. Jeffrey Robinson

Non-Tenure Track

Universities at Shady Grove

College of Natural and Mathematical Sciences

About

Robinson is a UMBC alumni, then worked at TIGR/JCVI for 8 years as Research Associate. He then attended Dartmouth College for his PhD in Biological Sciences from the Molecular and Cellular Biology program. He performed his postdoctoral research at NIH, studying RNA-expression and spatial transcriptomics in digestive disease model system. Most recently, Robinson has developed the curriculum of the Translational Life Science Technology (TLST) Bioinformatics Track, where he teaches upper level courses in bioinformatics, biostatistics, machine learning, and flow cytometry.

Research interests

Computational Genomics, Extremophiles, Evolutionary Biology

Teaching interests

​Genomics, Bioinformatics, Evolutionary Biology, Machine Learning, Experiential Education

Education

  • Ph D, Biological Sciences — Dartmouth College (2014)
    microRNA in Porifera: Evolution of a Molecular Mechanism in Sponges
  • MS, Biotechnology — Johns Hopkins University (2008)
  • BS, Biological Sciences — UMBC (1999)

Publications

  • VCFgenerator 2024 GitHub.com Jeffrey Robinson, Nhi Luu, Lloyd Jones, Jan Le, Gina Hwang
  • OmicsVMconfigure 2023 GitHub.com Jeffrey Robinson, Nhi Luu

Presentations

  • Register with GIGA-NCBI BioProject and utilize the GIGAGoaT Resources. 2023 Global Invertebrate Genomics Alliance - V (GIGA V) · Global Invertebrate Genomics Alliance (GIGA) · Oral Presentation

Grants and Contracts

  • BIO220099: Automated computational workflow for genomewide variation analysis focusing on extremophile adaptations of Halophilic Archaea. 2024 NSF · Grant · Funded
  • BIO220099: Computational workflows for analysis of microbial halophile genomes and microbiomes. 2024 NSF · Grant · Funded
  • MCB200044: Bioinformatics Training for Applications in Translational and Molecular Biosciences 2023 NSF · Grant · Funded
  • MCB200044: Bioinformatics Training for Applications in Translational and Molecular Biosciences 2023 NSF · Grant · Funded

Research in Progress

  • Modelling miRNA-mRNA regulatory networks using a Graph Convolutional Neural Network (GCN) Framework 2015 Scholarly · On-Going

Courses Taught

  • Machine Learning Applications for Translational Bioinformatics BTEC 423 · Spring 2024
  • Statistics for Translational Life Science BTEC 350 · Spring 2024
  • Software Applications in the Life Sciences BTEC 330 · Spring 2024