Md. Rezaul Karim, M.Sc.
Contact Information
| Address: |
Lehrstuhl Informatik 5 6014, Ground floor, building: E2 Ahornstr. 55 52056 Aachen DE |
| Phone: | +49 241 80 21501 |
| Fax: | +49 241 80 22321 |
| Email: | rezaul.karim@fit.fraunhofer.de |
I am a Scientist at Fraunhofer FIT. I am also a Ph.D. researcher at RWTH Aachen University. I am working towards developing a distributed knowledge pipeline with linked data infrastructure and deep neural networks for biomedical informatics.
I have a MSc in Computer Engineering from the Kyung Hee University, Korea, and a BSc in Computer Engineering from the University of Dhaka, Bangladesh. I have 8 years of experience in the area of research and software developments with practical knowledge on software development process and life cycle with a strong working knowledge of algorithms and data structure.
Before joining Fraunhofer FIT, I worked at Insight Centre for Data Analytics, Ireland as a Researcher. Before that I worked at Samsung Electronics as a Lead Engineer for 3 years with Global Samsung R&D centers in India, Korea, Vietnam, and Turkey. Previously, I worked as a Research Assistant at the Kyung Hee University, Korea, as an R&D Engineer with BMTech21 Worldwide, Korea. Also, I worked with i2SoftTechnology, Dhaka, Bangladesh as a Software Engineer.
Research interests:
• Machine Learning & Deep Learning
• Semantic Web & Linked Data
• Bioinformatics
• Big data
Specialization:
• Programming languages: C/C++/Java/R/Python/Scala
• Big data technologies: Spark, Hadoop, Zeppelin
• Sreaming: Spark Structured Streaming, Apache Flink
• Deep & machine learning: R, Scikit-learn, Spark ML, Keras, TensorFlow, DeepLearning4j, H2O
• Linux: System programming & shell scripting
• Samantic Web Technologies: OWL, RDF, SPARQL, Jena Fuseki, Virtuoso TDB
• Cloud services: Amazon AWS, Digital Ocean
• Virtualization technology: Docker
• Version control: Git, Perforce
• RDBMS/Database: Oracle Certified Associate, MySQL, PostgreSQL, MongoDB, NoSQL
• Web programming: PHP, MySQL, HTML5, CSS3, JavaScript
GitHub: https://github.com/rezacsedu
Current Teaching
Past Teaching
Theses
- Deep Learning-based Knee Osteoarthritis Diagnosis from Radiographs and Magnetic Resonance Images (2019)
- Implementation of Clinical Decision Support Services to Detect Drug Interactions using Clinical Quality Language (2019)
- Using Deep Neural Networks and Copy Number Variations for Cancer Detection (2018)
- Analysis of Breast Cancer Genomic Data with Multimodal Deep Belief Network ()
- Optimizing Mining Maximal Frequent Patterns with MFPAS ()
Publications
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A Distributed Analytics Platform to Execute FHIR-based Phenotyping Algorithms
Md. Rezaul Karim, Binh-Phi Nguyen, Lukas Zimmermann, Toralf Kirsten, Matthias Löbe, Frank Meineke, Holger Stenzhorn, Oliver Kohlbacher, Stefan Decker, Oya Beyan
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Schema Extraction for Privacy Preserving Processing of Sensitive Data
Lars Gleim, Md. Rezaul Karim, Lukas Zimmermann, Oliver Kohlbacher, Holger Stenzhorn, Stefan Decker, Oya Beyan
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Cancer Risk and Type Prediction Based on Copy Number Variations with LSTM and Deep Belief Networks
Md. Rezaul Karim, Md Ashiqur Rahman, Stefan Decker, Oya Beyan
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Mining maximal frequent patterns in transactional databases and dynamic data streams: A spark-based approach
Md. Rezaul Karim, Michael Cochez, Oya Beyan, Chowdhury Farhan Ahmed, Stefan Decker
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Towards a FAIR Sharing of Scientific Experiments: Improving Discoverability and Reusability of Dielectric Measurements of Biological Tissues
Md. Rezaul Karim, Matthias Heinrichs, Lars Gleim, Michael Cochez, Emily Porter, Alessandra La Gioia, Saqib Salahuddin, Martin O'Halloran, Stefan Decker, Oya Beyan
Professorship for Christoph Quix 