BIMSA > Thomas Tulu
Postdoc Thomas Tulu

Group: Statistics, Probability and Data Science

Office: A3-4-103

Email: thomaswetere@bimsa.cn

Research Field: Data Science

CV

Biography

Dr Thomas Wetere Tulu received his PhD from Harbin Institute of Technology(HIT) in Engineering Mathematics and worked at City University of Hong Kong(Hong Kong), Yildiz Technical University(Turkey), University of Macau(Macau), China CDC(Beijing), Addis Ababa University(Ethiopia), Addis Ababa Science & Technology University(Ethiopia) and Mekelle University(Ethiopia). His favorite quote is: " It is only through mathematics that we can thoroughly understand what true science is." - Augustus Comte

Research Interest

  • Biomathematics
  • Machine Learning
  • Bioinformatics
  • Optimization
  • High Performance Computing(HPC)
  • Biostatistics
  • Data Science

Education Experience

  • 2014 - 2017      Harbin Institute of Technology,      Engineering Mathematics,      Ph.D
  • 2009 - 2011      Addis Ababa University,      Computational Data Science,      M.Sc.
  • 2002 - 2006      Mekelle University,      Mathematics,      Bachelor

Work Experience

  • 2024 -      Tsinghua University, BIMSA,      Postdoctoral Research Fellow
  • 2022 - 2023      City University of Hong Kong,      Postdoctoral Research Fellow
  • 2020 - 2022      University of Macau,      Postdoctoral Research Fellow
  • 2018 -      Addis Ababa University,      Assistant professor
  • 2006 - 2014      Mekelle University,      Lecturer

Honors and Awards

  • 2022      City University of Hong Kong Postdoctoral Fellowship winner
  • 2020      UM Macao Research Fellowship & UM Research Associateship UM Macao Talent programme winner, University of Macau
  • 2018      Talented Young Scientist Program (TYSP) winner
  • 2017      TUBITAK Research Fellowship winner, Yildiz Technical University(Turkey)
  • 2017      Outstanding International Student Award, Harbin Institute of Technology(HIT)
  • 2015      CAS-TWAS Fellowship Winner

Publication

  • [1] Thomas Wetere Tulu, Tsz Kin Wan, Chun Hei Wu, Ching Long Chan, Peter Yat Ming Woo, Cee Zhung Steven Tseng, Asmir Vodencarevic, Cristina Menni , Kei Hang Katie Chan, Machine Learning-Based Prediction of COVID-19 Mortality Using Immunological and Metabolic Biomarkers, BMC Digital Health(2023)
  • [2] Tsz Kin Wan, Rui Xuan Huang, Thomas Wetere Tulu, Jun Dong Liu, Asmir Vodencarevic, Chi Wah Wong, Kei Hang Katie Chan, Identifying predictors of COVID-19 mortality using machine learning, Life Journal(2022)
  • [3] Thomas, Ieng Tak Leong, Zunyou Wu, Modeling and Predicting Corona Contagion Dynamics in China, USA, Brazil & Ethiopia, Journal of Applied Mathematics and Statistics(2020)
  • [4] Thomas Wetere Tulu , Tian Boping, Mathematical Modeling, analysis and Simulation of Epidemics, Bulletin of Iranian Mathematical society(2017)
  • [5] Thomas Wetere Tulu, Tian Boping, Zunyou Wu, Modeling the effects of quarantine and vaccination on Ebola Epidemics, Advances in difference equations, Springer(2017)
  • [6] Thomas Wetere Tulu, Tian Boping, Zunyou Wu, Mathematical Modeling, analysis and Markov Chain Monte Carlo Simulation of Ebola Epidemics, Results in Physics(2017)

 

Update Time: 2025-04-14 17:08:49