IMS Directory Listing

Natnael T Hamda
  • Title
    • Postdoctoral Scholar
  • Division Physical & Biological Sciences Division
  • Department
    • Institute of Marine Sciences
    • IMS-National Marine Fisheries Services at Long Marine Lab
  • Phone
    831-420-3900
  • Email
  • Office Location
    • 250 Natural Bridges, 067
    • NMFS/LML
  • Mail Stop NMFS

Summary of Expertise

Dr. Hamda has significant research and work experience in the application of machine learning and AI-driven technologies in biomedical research; in climate science and manufacturing industries. He is skilled in applied mathematics and advanced probabilistic programming inference techniques. His recent works focus on the integration of deep learning and AI for curating, analyzing and downstream analysis of Next Generation Sequence (NGS) data. He is also skilled and experienced in building knowledge graph-based Database system for end-to-end data integration and feature engineering of unstructured ‘Big Data’. Dr. Hamda holds MSc. in Biochemical Engineering in computing, Ph.D. in Bioinformatics and Theoretical Biology from Vrije University, Amsterdam, Netherlands and Ph.D. in Modelling from Jagiellonian University, Poland.

Research Interests

Machine Learning, AI, Deep Learning, Cancer research, climate change

Biography, Education and Training

Dr. Hamda has significant research and work experience in the application of machine learning and AI-driven technologies in biomedical research; in climate science and manufacturing industries. He is skilled in applied mathematics and advanced probabilistic programming inference techniques. His recent works focus on the integration of deep learning and AI for curating, analyzing and downstream analysis of Next Generation Sequence (NGS) data. He is also skilled and experienced in building knowledge graph-based Database system for end-to-end data integration and feature engineering of unstructured ‘Big Data’. Dr. Hamda holds MSc. in Biochemical Engineering in computing, Ph.D. in Bioinformatics and Theoretical Biology from Vrije University, Amsterdam, Netherlands and Ph.D. in Modelling from Jagiellonian University, Poland.

Honors, Awards and Grants

  • Abstract on “Unsupervised ML based multivariate time-series classification for animal behavioral studies” selected and featured at Society Integrative and Comparative Biology (SICB) 2018 Annual Meeting
  • Best poster award as early researcher career, The International Society for Ecological Modelling Global Conference (ISEM 2017), September 2017, Jeju, South Korea.
  • Certificate of merit as a best lecturer, Addis Ababa University, 2010
  • Winner of four Scholarship awards for M.Sc. and Ph.D. studies
  • Winner of the Ethiopian Science and Technology best MSc Student Award (2008) for showing academic excellence and research potential.

Teaching Interests

Bioinformatics, Machine Learning, Deep Learning, AI