Lead

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Associate Professor
Lydia Y. Chen
lydiaychen@ieee.org

Postdocs

Zilong Zhao
Z.Zhao-8@tudelft.nl

Ph.D. Students

Masoud Ghiassi
S.Ghiassi@tudelft.nl
Taraneh Younesian
T.Younesian@tudelft.nl
Hao Li
H.Li-9@tudelft.nl   
Jiyue Huang
J.Huang-4@tudelft.nl
Chi Hong
C.Hong@tudelft.nl  


Visiting Ph.D students

Name University Topic
Isabelly Rocha University of Neuchatel Resource managment for deep neural networks clusters
Nathaniel Morris Ohio State University Computational sprinting
Rania Talbi INSA-Lyon Attacks on federated learning systems


Master Thesis Students and Interns

Name Master/Intern Thesis/Project
Robert Konig Master 21 De-biasing multi-label problems
Erwin van Thiel Master 21 Adversarial example for multi-label problems
Izaak Cornelis Master 21 Federated learrning on non-IID data
Aditya Kunar Master 21 GAN-based synthetic tabular data generator
Zhiyue Zhang Master 21 Disparity seeding for maximizing information spread on social networks
Bart Cox Master 20 Efficient multiple DNNs inference on edge devices
Shikhar Deve Master 20 Multi-fidelity hyper-parameter tuning for machine learning algorithms
Victor Wernet Intern 20 Distributed generative adversarial networks
Jeroen Galjaard Intern 20 Scheduling algorithms for multiple DNNs inference on edges
Hans Brouwer Intern 20 Pipetuning hyper- and system parameters for DNN clusters


Bachelor Thesis Students

Name Year Thesis
Ben Provan-Bessell 2021 Text-to-Comic Generative Adversarial Network
Maciej Styczeń 2021 Automated Text-Image Comic Dataset Construction
Bartlomiej Kotlicki 2021 HaarCNN: Detection and Recognition of Comic Strip Characters with Deep
Darwin Morris 2021 Synthesizing Comics via Conditional Generative Adversarial Networks
Krzysztof Garbowicz 2021 DilBERT^2: Humor Detection and Sentiment Analysis of Comic Texts Using Fune-Tuned BERT Models
Cosmin Pene 2021 Multi-Label Gold Asymmetric Loss Correction with Single-Label Regulators
Mark Basting 2021 Multi-AL: Robust Active learning for Multi-label Classifier
Johnathan Rozen 2021 Robust Multi-label Active Learning for Missing Labels
Jan-Mark Dannenberg 2021 Time Series Synthesis using Generative Adversarial Networks
Pepijn te Marvelde 2021 Differentially Private GAN for Time Series
Marcus Plesner 2021 FeTGAN: Federated Time-Series Generative Adversarial Network
Auke Schaap 2021 Time Series Synthesis Using GANs - A take on DoppelGANger
Jeroen Galjaard 2020 Mema: Fast Inference of Multiple Deep Models
Hans Brouwer 2020 Modeling Inference Time of Deep Neural Networks on Memory-constrained Systems
Wouter van Lil 2020 Analysis of the effect of caching convolutional network layers on resource constraint devices
Simon Tulling 2020 Offline Compression of Convolutional Neural Networks on Edge Devices
Khalid El Haji, Noah Posner, Haka Ilbaş, Sergen Karpuz, and Victor Wernet 2020 Synthetic Waste Generator for Classification Training
Dennis Böhm, Dylan Franken, Govert de Gans, Bas Musters, and Bram van Kooten 2020 TAM 2.0
Simon Barendsem, and Jorick Spitzen 2019 Job containerization and orchestration to reduce TTC and operational costs