Dr. Masoumeh Javanbakhat | Digital Health | Best Researcher Award

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Dr. Masoumeh Javanbakhat | Digital Health | Best Researcher Award

Postdoctoral Researcher at Digital Health, Hasso Plattner Institute, Germany

Masoumeh Javanbakhat is a Postdoctoral Research Fellow at the Hasso-Plattner-Institute, specializing in Digital Health and Machine Learning. Her research focuses on applying machine learning techniques to digital health applications, with a particular interest in probabilistic AI, Bayesian deep learning, and modeling uncertainties in computer vision and medical images. Masoumeh’s work aims to improve healthcare outcomes through innovative technology and data analysis.

Professional Profiles:

Education:

Dr. Masoumeh Javanbakhat completed her Bachelor of Science in Applied Mathematics at Isfahan University, Iran, from 2005 to 2009. She pursued a Master of Science degree at Shahed University, Iran, from 2009 to 2012, focusing on Mathematics, with a thesis on combinatorial designs for key distribution in wireless sensor networks. Dr. Javanbakhat then completed her Ph.D. studies at Hakim Sabzevari University, Iran, from 2013 to 2018, under the guidance of Dr. Amir Hashemi, Dr. Leila Sharifan, and Prof. H. Michael Möller, with a thesis on the symbolic computation of H-bases, Gröbner bases, and minimal bases for syzygies. She collaborated as a Research Collaborator at Passau University, Germany, during 2017-2018, working on the numerical computation of H-bases. Currently, she is a Postdoctoral Research Fellow at the Hasso-Plattner-Institute in Potsdam, Germany, under the mentorship of Prof. Christoph Lippert, focusing on Probabilistic AI, Bayesian deep learning, and modeling uncertainties with applications in computer vision and medical images.

Honors:

Dr. Masoumeh Javanbakhat has received several honors throughout her academic career. She was awarded the Best PhD Graduate by the Faculty of Mathematics and Computer Science at Hakim Sabzevari University, Iran, in 2018. In 2017, she won the Award of University of Passau Research Collaboration from the Ministry of Science, Research, and Technology of Iran. Dr. Javanbakhat achieved a ranking of 1 out of 25 among Ph.D. students at Hakim Sabzevari University in 2018, demonstrating her academic excellence. During her Master’s studies at Shahed University, Iran, she was ranked 3 out of 20 among M.Sc. students in 2012. Similarly, during her Bachelor’s studies at Isfahan University, Iran, she was ranked 3 out of 20 among B.Sc. students in 2009. These honors reflect her outstanding academic performance and dedication to her field.

Academic Experience:

Dr. Masoumeh Javanbakhat has a strong background in academia, with experience both as a teacher and a researcher. From 2021 to 2023, she served as a Teaching Assistant for Mathematics for Machine Learning at the Hasso-Plattner-Institute. Prior to this, she worked as a Research Collaborator at the University of Passau, Germany, under the guidance of Prof. Tomas Sauer, from 2017 to 2018. Dr. Javanbakhat also has experience as an Instructor in Numerical Computation at Amin University from 2018 to 2019. She further enhanced her teaching skills as a Teaching Assistant for Computational Algebra at Isfahan University of Technology from 2018 to 2019, and for Basics of Algebra as well as Basics of Combinatorics at Shahed University from 2012 to 2013. Her academic experience demonstrates her dedication to both learning and teaching in the field of mathematics.
🔧 Programming: Python, MATLAB, Maple
💻 VSC & OS: Git, Linux, Unix
📊 Technical Skills: Data Analysis using Scikit-Learn, NumPy, Pandas, Matplotlib, Seaborn
🤖 Machine Learning: Supervised and Unsupervised Learning, Deep Learning, Computer Vision, Probabilistic AI, Bayesian Deep Learning, PyTorch, Weights and Biases
📚 Courses: Python, Deep Learning, Machine Learning, Probabilistic AI, AI for Medical Diagnosis
📜 Certifications: Hands-on Machine Learning with AWS and NVIDIA (In progress)
🧠 Soft Skills: Problem-solving, critical thinking, innovation, and creativity; Ability to deal with complexity and ambiguity; Communication and supervising

Publications:

  1. Key predistribution scheme for clustered hierarchical wireless sensor networks based on combinatorial designs
    1. Authors: M Javanbakht, H Erfani, HHS Javadi, P Daneshjoo
    2. Citations: 17
    3. Year: 2014
  2. Numerical computation of H-bases
    1. Authors: M Javanbakht, T Sauer
    2. Citations: 8
    3. Year: 2019
  3. On the construction of staggered linear bases
    1. Authors: A Hashemi, M Javanbakht
    2. Citations: 3
    3. Year: 2021
  4. On -Closed Graphs
    1. Authors: L Sharifan, M Javanbakht
    2. Citations: 3
    3. Year: 2017
  5. A probabilistic approach to self-supervised learning using cyclical stochastic gradient MCMC
    1. Authors: M Javanbakhat, C Lippert
    2. Citations: 1
    3. Year: 2023
  6. Computing H-bases via minimal bases for syzygy modules
    1. Authors: A Hashemi, M Javanbakht
    2. Citations: 1
    3. Year: 2020
  7. Algebraic invariants of certain projective monomial curves
    1. Authors: M Javanbakht, L Sharifan
    2. Citations: 1
    3. Year: 2019