About Dr. B

Welcome! I am a data scientist and researcher involved into the design, development and analysis of machine learning algorithms into solving real-world problems in the context of Responsible AI. I am also an educator teaching graduate level breadth courses and under-graduate level technical elective courses covering machine learning, deep learning, reinforcement learning and Bioinformatics. In the computer science department, I run the Machine Learning Laboratory (ML Lab) where I supervise a bunch of undergraduate, MS and PhD students who are working on several collaborative research projects to make a positive difference in the community we live in.

I earned my Ph.D in Computer Science and Engineering from the University of Texas at Arlington in 2016, my M.S. and B.S. both in Computer Science and Engineering from University of Dhaka in 2009 and 2008 respectively. My schoarly works have been published in MLWA, IEEE/ACM TCBB, BMC Medical Genomics, NetMAHIB, JBCB, BMC Bioinformatics other outlets. Although many of the published works cover problem in genomic, transcriptomic and proteomic domains, later I expanded my research problem area into several other fields including education, human development, cybersecurity, NLP and NLU, medical imaging with the help of a few amazing collaborators and colleagues at CU Denver.


Currently, I’m looking for a competitive graduate student to investigate Data-blind machine learning paradigm. If you are interested, send me an email at [email protected]

  • Current PhD Students
  • Current MS Students
    • Srivani Inturi
  • Graduated PhD Students
    • Dr. Javier Pastorino
      • Dissertation title: Training Machine Learning Models in Various Oblivious Settings
        • Cite as: “Gonzalez, J. A. P. (2022). Training Machine Learning Models in Various Oblivious Settings (Doctoral dissertation, University of Colorado at Denver).” [ ProQuest ]
      • First job: Assistant Prof, CSE@CU Denver
  • Graduated MS Students
    • James Theiring
      • MS thesis: Bias Mitigation in Visual Models through Split-model regularization: A case study in online class participants’ Engagement classification. (Fall 2022)
      • First job: IPS Strategic Capital as Data Science Specialist.
    • Rory Flynn
      • MS thesis: Predicting Autism Spectrum Disorder from Genome-wide Association data with Genetic Balancing Generative Adversarial Network (Fall 2020)
    • Zhelin Yu
      • MS research + courses: Tumor Segmentation (Fall 2020)
      • First employment after graduation: Oracle
    • Nathan Justice
      • MS thesis: Identification of Metastatic tissue in Histopathologic scans of lymph node sections. (Spring 2020)
      • First job: Amazon (training specialist)
    • Jian Peng
      • MS thesis: 3D CNN data integration platform for ADHD detection (Fall 2019)
      • First job: founding partner of the startup called InHouse.
    • Mohammed Mahdi
      • MS thesis: Protein Phosphorylation Site Prediction using Deep Learning approach (Fall 2018)
      • First job: Research scientist at the Ministry of Education, Iraq.