Jasin Machkour
Member of the Robust Data Science Group at the Institute of Telecommunications, TU Darmstadt.
Contact
jasin.machkour@tu-...
work +49 6151 16-22531
Work
S3|06 29
Merckstr. 25
64283
Darmstadt
Links
Office Hours: Upon request
Bio
Jasin received the B.Sc. degree in Industrial Engineering and the M.Sc. degree in Electrical Engineering and Information Technology with a major in Communication and Sensor Technology from Technische Universität Darmstadt (TU Darmstadt) in 2016 and 2019, respectively.
He spent one year of his master’s studies (2016/2017) at the Department of Electrical and Computer Engineering of the University of Illinois at Urbana-Champaign (USA).
His bachelor’s and master’s theses deal with robust and adaptive regression for linear and sparse models and robust and adaptive statistical learning for high-dimensional data, respectively.
In September 2019, he started his doctoral studies at TU Darmstadt. From September 2019 until February 2020 and from May 2023 until August 2023, he visited Prof. Daniel P. Palomar at The Hong Kong University of Science and Technology. From May 2022 until July 2022, he visited Prof. Frédéric Pascal at Université Paris-Saclay (CentraleSupélec). In 2022, he completed the Statistical Genomics Summer Course at University of Oxford.
Jasin is a founding member of the EURASIP Student Committee and represents the area Theoretical and Methodological Trends in Signal Processing (TMTSP).
Research
Jasin’s research interests lie in the broad field that is often called statistical learning, machine learning, data science, or statistical signal processing. He is particularly interested in developing methods/algorithms for large-scale and high-dimensional learning tasks with provable statistical properties.
The following topics are of great interest to him:
- Sparse regression in high-dimensional settings
- False discovery rate (FDR) control in variable/feature selection
- Methods for genome-wide association studies (GWAS)
- Parallel computing on high-performance computing (HPC) clusters.
| Fabian Scheidt | Robust and Computationally Efficient Statistical Learning in High-Dimensional Data: The T-Rex Selector | Master's Thesis | 03/2023 |
| Marie Flohr | Reproducibility Analysis of Discoveries in Genome-Wide Association Studies Using Variable Selection Methods for High-Dimensional Data | Bachelor's Thesis | 12/2022 |
|
Simon Tien (co-supervision with Michael Muma) |
Development of High-Dimensional Learning Methods for Genome-Wide Association Studies | Master's Thesis | 06/2022 |
|
Lisa Dawel (co-supervision with Michael Muma) |
Development and Analysis of Sparse High-Dimensional Ensemble Learning Methods | Master's Thesis | 12/2021 |
| Pertami Kunz | Robust Variable Selection and False Discovery Rate Control for High-Dimensional Regression Models Using Knockoffs | Master's Thesis | 02/2021 |
| Qiang Zhao | Robust Error Control for High-Dimensional Variable Selection based on the Stability Selection Method | Master's Thesis | 01/2021 |
| Group of three Master's students | Python vs. R: Benchmarking the computational performance of the Terminating Random Experiments (T-Rex) Method | RSP Seminar | 07/2022 |
| Group of four Master's students | HIV Dataset Case-Study C – Same Features but Different Responses | RSP Seminar | 02/2022 |
| Individual project (Master's student) | Integrating Robust Loss Functions Into Deep Learning | RSP Seminar | 02/2021 |
| Individual project (Master's student) | Robust Reconstruction of Biomedical Images in the Presence of Outliers | RSP Seminar | 02/2021 |
| Individual project (Master's student) | HIV Dataset Case-Study B – What Types of Outliers are More Severe? | RSP Seminar | 02/2021 |
| Group of two Master's students | Dependent Data Bootstrap | ATISSP Seminar | 02/2021 |
| Group of two Master's students | Hypotheses Testing With The Bootstrap and Signal Detection | ATISSP Seminar | 02/2021 |
| Group of two Master's students | Applications of The Bootstrap | ATISSP Seminar | 02/2021 |
Teaching
Robust and Biomedical Signal Processing (RSP Seminar) – WS 2020/21 & WS 2021/22
Medizintechnisches Praktikum – WS 2021/22
Praktikum Kommunikationstechnik und Sensorsysteme – SS 2021 & WS 2021/22
Advanced Topics in Statistical Signal Processing (ATISSP) – WS 2020/21
Publications
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