We are the Distributed Learning Systems Lab at the Distributed Systems Section, EWI faculty, TU Delft. We working on a wide variety of research problems in distributed machine learning systems, and developing cutting edge AI technology for industry. Check our start-up spin-off, Generatrix.

Our lab is supported by TU Delft, Aegon, ABB Research, Swiss National Science Foundation (SNSF), and Dutch National Science Foundation (NWO).


  • [12/21] Our paper, “Lightweight and Accurate DNN-based Anomaly Detection at Edge" , is accpted in IEEE Transactions on Parallel and Distribution Computing
  • [12/21] Our paper, “EdgeTuner: Fast Scheduling Algorithm Tuning for Dynamic Edge-Cloud Workloads and Resources" , is accpted in IEEE INFOCOM22
  • [11/21] Our paper, “Locality Sensitive Hash Aggregated Nonlinear Neighborhood MatrixFactorization for Online Sparse Big Data Analysis" , is accpted in ACM Transactions on Data Science
  • [10/21] Lydia will serve TPC track co-chair of CCGRID22 .
  • [09/21] Our paper, CTAB-GAN: Effective Table Data Synthesizing , is accpted in ACML21
  • [09/21] Our paper, QActor: On-line Active Learning for Noisy Labeled Stream Data , is accpted in ACML21
  • [08/21] Our paper, LegoDNN: Block-grained Scaling of Deep Neural Networks for Mobile Vision , is accepted in MobiCom21
  • [08/21] Our paper, Federated Learning with Heterogeneity-Aware Probabilistic Synchronous Parallel on Edge , is accepted in IEEE Transactions on Service Computing
  • [08/21] Our paper, Disparity seeding , is accepted in CIKM21
  • [07/21] Lydia will serve TPC co-chair of BDCAT21 .
  • [08/21] Lydia will serve TPC Sigmetrics21 .
  • [07/21] The Generatrix team enters the semi-final of The European Social Innovation Competition !
  • [07/21] We graduate 13 bachelor students on broad topics of synthesizing comics, privacy preserving time-series synthesizing, and robust multi-label learning.
  • [07/21] Our paper on differential privacy for sparse tensor factorization is accepted in IEEE Transactions on Industrial Informatics
  • [05/21] Our PerCom'21 papre is invited for a special issuee of Pervasive and Mobile Computing Journal.
  • [05/21] Our paper, LABELNET: Recovering Noisy Labels, is accepted in IJCNN
  • [03/21] Our paper on differential private deep learning at edges is acceptedd in IEEE Transactions on Parallel and Distributed Computing
  • [02/21] Our paper, Enhancing Robustness of On-line Learning Models on Highly Noisy Data, is accepted in IEEE Transactions on Dependable and Secure Computing
  • [01/21] Our paper, Online Label Aggregation: A Variational Bayesian Approach, is accepted inWWW21
  • [01/21] Our two papers on Multiple Inference of Deep Models on Edge will appear in PerCom21
  • [12/20] We just received a NWO take-off grant for our project, "Tabular Data Synthesizer"
  • [12/20] Our paper on Practical Analysis of Replication-Based Systems will appear in INFOCOM2021
  • [11/20] Our paper, Courier: Real-Time Optimal Batch Size Prediction for Latency SLOs in BigDL, will appear in ICPE21
  • [11/20] Our paper on federated learnnig at heterogeneous platform will appear in AI/ML special issue of TPDS
  • [11/20] Our paper on stochastic optimization for parallel sparse Tucker decomposition will appear in AI/ML special issue of TPDS
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