Dr. Andreas Henschel
Dr. Andreas Henschel Associate Professor
Teaching Areas
Research Interests

Associate Professor, Department of Electrical Engineering and Computer Science

Dr. Andreas Henschel earned his M.Sc. and Ph.D. in Computer Science from the Technical University of Dresden (Germany), in 2002 and 2008, respectively. He joined Masdar Institute as a Post-doctoral researcher in 2009. In 2011, he became Assistant Professor at Masdar Institute, UAE.  He spent one year at the Massachusetts Institute of Technology MIT), USA as a Visiting Scholar.

Dr. Henschel he has published more than 50 peer reviewed journal papers and conference publications, mainly on the topics of Bioinformatics and Artificial Intelligence, which is also central to his teaching activities since 2012.

As of 2019, he has graduated six Master's students and one Ph.D. student as main supervisor. His research focus is on Genomic Data Science and Bioinformatics,  which are at the intersection of health care and AI/Data Science in the Khalifa University research ecosystem.

In his capacity as Bioinformatics project leader of the Khalifa University Center for Biotechnology, he is currently heading the UAE population stratification analysis using large scale data, the creation of large scale Whole Genome Sequencing pipelines and the development of Bioinformatics tools used for  Microbiome and Genetic data generated by internal collaborators (focus on Histocompatibility genes) and external collaborators (focus on Pancreatic ductal adenocarcinoma).

He is currently engaged in an ADEK-funded project to predict CRISPR activity using Deep Neural Networks and Transfer Learning techniques.

Amongst other internal and external professional committee services such as Editorial Board participation, Dr. Henschel serves as the chair of the graduate student admission committee since Fall 2017.

  • Ph.D., Computer Science, Technical University of Dresden (Germany), 2008
  • M.Sc., Computer Science, Technical University of Dresden (Germany),  2002
Teaching Areas
  • Algorithms in Bioinformatics
  • Techniques in Artificial Intelligence
  • Bioinformatics and Computational Biology
  • Machine Learning
  • Genomic Data Science
  • Discrete Math for Computer Science
Research Interests
  • Microbiome informatics
  • Machine learning for big data genetics/genomics, genotype-phenotype prediction
  • Genome analysis for next-generation sequencing
  • Deep learning particularly transfer learning for sequential data