Researcher ML in Healthcare, PhD Candidate, Data Scientist.
PhD Candidate, Computer Science and Machine Learning
2021-now Hasso Plattner Institute
As a PhD candidate at the HPI, I am working on a project aimed at developing a predictive approach to detecting complications after surgeries in collaboration with Berlin’s biggest hospital, the Charité. The challenge I face is to combine multiple data sources and employ different AI/ML techniques to get a risk assessment for doctors to increase the survival rate.
- Master Theses: Hendrik Schmidt, 2022-2023: Benchmarking Model-agnostic Multi-source Supervised Domain Adaptation for Clinical Prediction on ICU Data and YAIB.
- Master Project: Alisher Turubayev, Anna Shopova, Fabian Lange, Mahmut Kamalak, Paul Mattes, and Victoria Ayvasky, 2022-2023: Deep Learning Data Generation for Medical Prediction Systems.
- Course: Statistics in Healthcare, 2022, 2023: Grading and Supervision of final presentation and report.
- Invited talk at ETH Zürich Biomedical Informatics group about Yet another ICU Benchmark.
Double Master in Data Science
2019-2021 EIT Digital Master School, TU Eindhoven & TU Berlin, with Honours
The EIT Digital Master programme is a selective double degree Master of Science focused on combining technical knowledge and innovation at two renowned European Technical Universities. I studied at Eindhoven University of Technology in the period of 2019-2020 and at the Technical University of Berlin during 2020-2021. This programme includes a minor in entrepreneurship and innovation and is supported by the European Institute of Innovation and Technology (which is part of the EU).
- GPA – 8.5 [4.0/4.0] (Cum Laude) 151 ECTS
- Thesis “A Semi-automated Training Data Generation Approach with the Human-in-the-Loop.” at the Database Systems and Information Management Group of TU Berlin
- Awarded the EIT Digital Excellence Scholarship
- Participant of the Honors Academy at TU/e: Honours programme of 20 ECTS for Personal Leadership
- Including courses: Advanced Algorithms, Cloud Computing, Discrete Event Systems, Speech Analysis, Scalable Data Science, Statistical Learning Theory, Advanced Statistics, Visualization, Data Mining, Data Engineering, Process Mining and Technology Entrepreneurship
- With Innovation Space Project in interdisciplinary team for Signify (Philips Lighting), Cyclomedia and the TU/e Intelligent Lighting Institute
- Selected for the Semi-Professional Race Rowing team at E.S.R Thêta
Bachelor of Computer Science
2016-2019 Utrecht University, with Honours
During my time at Utrecht University, I have developed skills for problem solving and reasoning. I have taken many different courses in Computer Science and other disciplines.
- GPA – 8.28, [4.0/4.0] (Cum Laude) 218.5 ECTS
- Descartes Honours Programme (30 ECTS): Focused on broad academic development through lectures from prominent figures in society and projects with students from other disciplines
- Minor in Mathematics
- Including courses: Data Analysis and Retrieval, Algorithms, Intelligent Systems, Computational Intelligence, Optimisation & Complexity, Concurrency, Graphics, Functional Programming and Data-structures
- Bachelor software project in automated medical reporting with semantic interpretation
- Commissioned by the Care2Report project (Department of Computer Science, Utrecht University)
- Supervised a group of 10 computer science students
- Co-author of the “The Care2Report System: Automated Medical Reporting as an Integrated Solution to Reduce Administrative Burden in Healthcare” paper, written with the department of Computer Science, presented at the HICSS-53 conference.
Preporatory Scientific Education
Utrechts Stedelijk Gymnasium
This classical school (est. 1474) has offered a high standard of education to prepare me for university. I graduated with the Nature and Technology and Nature and Health profiles. I participated in the Robotics club and took Cambridge English Proficiency classes. Along with that I took Economics, German, Latin, Greek and Art history.
See my Google Scholar profile for a comprehensive list
- R. van de Water, H. Schmidt, P. Elbers, P. Thoral, B. Arnrich, and P. Rockenschaub, ‘Yet Another ICU Benchmark: A Flexible Multi-Center Framework for Clinical ML’. arXiv, Jun. 08, 2023. Available: http://arxiv.org/abs/2306.05109 (under review at NeurIPS Dataset and Benchmarks Track 2023)
- A. Winter, R. van de Water et al., Advancing Preoperative Outcome Prediction: A Comparative Analysis of Machine Learning and ISEG Risk Score for Predicting 90-Day Mortality after Esophagectomy, 2023 (under review at JAMA Surgery)
- O. Konak, R. van de Water et al., ‘HARE: Unifying the Human Activity Recognition Engineering Workflow’, (Under review at IEEE SENSORS JOURNAL 2023)
- O. Konak, A. Wischmann, R. van de Water, and B. Arnrich, ‘A Real-time Human Pose Estimation Approach for Optimal Sensor Placement in Sensor-based Human Activity Recognition’. arXiv, Jul. 06, 2023. doi: 10.48550/arXiv.2307.02906. (under review at iWOAR 2023)
- R. van de Water, F. Ventura, Z. Kaoudi, J.-A. Quiané-Ruiz, and V. Markl, ‘Farming your ML-based query optimizer’s food’, in 2022 IEEE 38th international conference on data engineering (ICDE), 2022, pp. 3186–3189. (Best demo award 2022)
- R. van de Water, F. Ventura, Z. Kaoudi, J. Quiane-Ruiz, and V. Markl, ‘Farm your ML-based query optimizer’s Food!–Human-Guided training data generation–’, presented at the Conference on Innovative Data Systems Research (CIDR), 2022.
- L. Maas, M. Geurtsen, F. Nouwt, S. Schouten, R. van de Water, S. van Dulmen, F. Dalpiaz, K. van Deemter, S. Brinkkemper ‘The Care2Report system: automated medical reporting as an integrated solution to reduce administrative burden in healthcare’, in Information technology in healthcare: IT architectures and implementations in healthcare environments, Hawaii International Conference on System Sciences (HICSS), 2020.
Best Demonstration Paper Award at ICDE
Received “Best Demonstration” Award from IEEE International Conference on Data Engineering (ICDE) 2022. Elaboration of the jury: “The award committee members have chosen your demonstration unanimously both based on the relevance of the problem, the high potential of the proposed approach and the excellent presentation.” More information here, video here.
Finalist at the Bionnale Speed Lecture Award
I was a finalist at the Bionnale 2022 Speed Lecture Award. Here I presented my doctoral research topic with the topic: “Dr. Droid and the Curious Case of Complication Prevention”. The presentation focused on communicating the possibilities and challenges of predicting post-surgery complications using hetereogeneous patient data. The presentation was recorded and can be viewed here
Honors Academy Master
Selected for the Honors Academy Master: a program consisting of 20 ECTS where you orient yourself in your professional career and choose your own program of professional development.
EIT Digital Excellence Scholarship
Awarded the highest scholarship for the selective Dual Degree MSc Data Science (with minor in entrepreneurship) at the TU Eindhoven and TU Berlin.
Research Assistent at the Hasso Plattner Institute Digital Health Center
Responsible for supervising Master Theses, Master Projects and grading of individual students. Performing Scientific Data Analysis and Data Engineering for the Charité Academic Hospital.
Research Assistent at German Institute of Artificial Intelligence (DFKI)
Worked on the Agora project, an open platform bringing together data, algorithms, models and computational resources.
Ambassador of the EIT Digital Master School
Representative of my Master School where I organise events, answer questions from prospective students and represent the master school in several capacities.
Education assistant for the Science Faculty of Utrecht University
Reviewed and graded code, diagrams and documentation. I developed teaching and organisational skills.
- Managed a class of 60 students and assisted with their practical assignments
- Supervised finals with 300 participants
Organisation committee study excursion
Organised an educational exchange to Sofia of the Descartes Honours Programme
- Organised educational activities for 35 students and 3 supervisors
- Developed parts of the programme curriculum and managed university funds
Machine learning, Statistics, Linear algebra, Statistical learning, Software
SCRUM, Scientific & Creative writing, Scientific presenting, Entrepreneurial pitching, Design Thinking, Chairing meetings, Leading teams
🎲 Miscellaneous Education
- UX Design Certificate, 2020-2021, TechLabs Digital Shaper Program
- Big Data Analytics Summer School, 2020, KTH Royal Institute of Technology
- Education Assistant Training, 2018, Faculty of Social Sciences, Utrecht University
- Academic Writing Training, 2018, Skills Lab, Utrecht University
- Dutch - Native
- English - Fluently - Cambridge University (2016) CPE CEFR C2 level
- German - Professional - TU Berlin (2021) CEFR C1 level
- 🖼️Galleries and art history
- 🚴♂️Race biking
- 🎸Playing guitar and drums