Prof. Dr.-Ing. Bert Arnrich

Bjarne Pfitzner

Research Assistant, PhD Candidate

Phone: +49-(0)331 5509-1374

Room: G-2.1.12

Email: bjarne.pfitzner(at)hpi.de


Personal Information

  • Since Nov. 2018: Research Assistant and PhD Candidate at HPI
  • 2014 - 2018: Computing (M.Eng.) at Imperial College London (Integrated Master's Degree)
  • 2017: Software Engineering Intern at Accenture Plc in Bonn

Research Interests

  • Privacy-Preserving Machine Learning
    • Federated Learning
    • Fully-Decentralised Learning
  • Differential Privacy
  • Generative Models
  • Distributed Ledger Technologies

Teaching Activities

Project Supervision

Winter Term 2022/23Master ProjectDeep Learning Data Generation for Medical Prediction Systems
Summer Term    2021Master ProjectForecasting Alarms in Intensive Care Units
Winter Term 2020/21Master ProjectPreventive Maintenance for Patients


Thesis Supervision

2021Joceline ZieglerPrivacy-Preserving Classification of X-Ray Images in a Federated Learning Setting
2020Lando LöperPersonalised Sensor-Based OCD Detection Using Federated Learning
2020Lina KohlsAnonymization of Fitness Data for Scientific Research
2020Julian BaumannSecurity Analysis of a Platform for the Collection and Evaluation of Health Data




  • Differentially-Private Federated Learning with Non-IID Data For Surgical Risk Prediction. Pfitzner, Bjarne; Maurer, Max M.; Winter, Axel; Riepe, Christoph; Sauer, Igor M.; van de Water, Robin; Arnrich, Bert in Preprint (2024).


  • Predictive Alarm Prevention by Forecasting Threshold Alarms at the Intensive Care Unit. Chromik, Jonas; Pfitzner, Bjarne; Ihde, Nina; Michaelis, Marius; Schmidt, Denise; Klopfenstein, Sophie Anne Ines; Poncette, Akira-Sebastian; Balzer, Felix; Arnrich, Bert in Biomedical Engineering Systems and Technologies, A. C. A. Roque, D. Gracanin, R. Lorenz, A. Tsanas, N. Bier, A. Fred, H. Gamboa (reds.) (2023). (Vol. 1814) 215–236.
  • Federated Learning for Activity Recognition: A System Level Perspective. Kalabakov, Stefan; Jovanovski, Borche; Denkovski, Daniel; Rakovic, Valentin; Pfitzner, Bjarne; Konak, Orhan; Arnrich, Bert; Gjoreski, Hristijan in IEEE Access (2023). 11 64442–64457.


  • Computational Approaches to Alleviate Alarm Fatigue in Intensive Care Medicine: A Systematic Literature Review. Chromik, Jonas; Klopfenstein, Sophie Anne Ines; Pfitzner, Bjarne; Sinno, Zeena-Carola; Arnrich, Bert; Balzer, Felix; Poncette, Akira-Sebastian in Frontiers in Digital Health (2022). 4
  • Extracting Alarm Events from the MIMIC-III Clinical Database. Chromik., Jonas; Pfitzner., Bjarne; Ihde., Nina; Michaelis., Marius; Schmidt., Denise; Klopfenstein., Sophie; Poncette., Akira-Sebastian; Balzer., Felix; Arnrich., Bert (2022). 328–335.
  • Forecasting Thresholds Alarms in Medical Patient Monitors using Time Series Models. Chromik., Jonas; Pfitzner., Bjarne; Ihde., Nina; Michaelis., Marius; Schmidt., Denise; Klopfenstein., Sophie; Poncette., Akira-Sebastian; Balzer., Felix; Arnrich., Bert (2022). 26–34.
  • Defending against Reconstruction Attacks through Differentially Private Federated Learning for Classification of Heterogeneous Chest X-ray Data. Ziegler, Joceline; Pfitzner, Bjarne; Schulz, Heinrich; Saalbach, Axel; Arnrich, Bert in Sensors, (F. Marulli; L. Verde, reds.) (2022). 22(14)
  • DPD-fVAE: Synthetic Data Generation Using Federated Variational Autoencoders With Differentially-Private Decoder Pfitzner, Bjarne; Arnrich, Bert (2022).


  • Perioperative Risk Assessment in Pancreatic Surgery Using Machine Learning. Pfitzner, Bjarne; Chromik, Jonas; Brabender, Rachel; Fischer, Eric; Kromer, Alexander; Winter, Axel; Moosburner, Simon; Sauer, Igor M.; Malinka, Thomas; Pratschke, Johann; Arnrich, Bert; Maurer, Max M. (2021). 2211–2214.
  • Implicit Model Specialization through Dag-Based Decentralized Federated Learning. Beilharz, Jossekin; Pfitzner, Bjarne; Schmid, Robert; Geppert, Paul; Arnrich, Bert; Polze, Andreas in Middleware ’21 (2021). 310–322.
  • Sensor-Based Obsessive-Compulsive Disorder Detection With Personalised Federated Learning. Kirsten, Kristina; Pfitzner, Bjarne; Löper, Lando; Arnrich, Bert (2021). 333–339.
  • Differentially Private Federated Learning for Anomaly Detection in EHealth Networks. Cholakoska, Ana; Pfitzner, Bjarne; Gjoreski, Hristijan; Rakovic, Valentin; Arnrich, Bert; Kalendar, Marija in UbiComp ’21 (2021). 514–518.
  • Data Augmentation of Kinematic Time-Series From Rehabilitation Exercises Using GANs. Albert, Justin; Glöckner, Pawel; Pfitzner, Bjarne; Arnrich, Bert (2021). 1–6.


  • Tangle Ledger for Decentralized Learning. Schmid, R.; Pfitzner, B.; Beilharz, J.; Arnrich, B.; Polze, A. (2020). 852–859.
  • Federated Learning in a Medical Context: A Systematic Literature Review. Pfitzner, Bjarne; Steckhan, Nico; Arnrich, Bert in ACM Transactions on Internet Technology (TOIT) Special Issue on Security and Privacy of Medical Data for Smart Healthcare (2020).


  • Poisoning Attacks with Generative Adversarial Nets. Muñoz-González, Luis; Pfitzner, Bjarne; Russo, Matteo; Carnerero-Cano, Javier; Lupu, Emil C (2019).
  • Unobtrusive Measurement of Blood Pressure During Lifestyle Interventions. Morassi Sasso, Ariane; Datta, Suparno; Pfitzner, Bjarne; Zhou, Lin; Steckhan, Nico; Boettinger, Erwin; Arnrich, Bert (2019).