My Research Team
Post-doctoral researcher
07/2020–present
TU Delft, The Netherlands
Project: Synthetic tabular data generation via generative adversarial networks
PhD student
09/2020–present
TU Delft, The Netherlands
Project: Adversarial learning
PhD student
S.Ghiassi@tudelft.nl
02/2019–present
TU Delft, The Netherlands
Project: Robust machine learning systems
PhD student
08/2020–present
TU Delft, The Netherlands
Project: Federated learning
(Co-supervise with Stefanie Rosss)
PhD student
09/2021–present
TU Delft, The Netherlands
Project: Federated learning
(Co-supervise with Jeremie Decouchant)
PhD student
06/2021- present
TU Delft, The Netherlands
Project: Neural network based topology optimization
(Co-supervise with Miguel Bessa)
TU Delft Master, Bachelor and Interns.
I supervise a large number of master thesis and bachelor thesis students, covering a wide range of topics in distributed machine learning systems. I also recruit them as summer interns in my lab or startup.
To know the cool stuffs my students do, check out the DIS group website and Generatrix .
I am always interested in hiring motivated students!
N. Ramashan
03/2017–12/2017
Project: Cloud-based security service
R. Birke
01/2012–06/2017
Project: Datacenter discovery and cognitive threat intelligence platform
M. Ghassi
02/2019–present
TU Delft, The Netherlands
Project: Robust machine learning systems
Affiliated Postdoctoral Fellows @IBM Research
N. Ramashan
03/2017–12/2017
Project: Cloud-based security service
R. Birke
01/2012–06/2017
Project: Datacenter discovery and cognitive threat intelligence platform
PhD Student Co-Advisory Role @IBM Research
H. Zhang
09/2017–04/2018
Co-adviser of Dapprox
Swiss Federal Institute of Technology (ETH), Switzerland
Project: Distributed lower-precision machine learning
H. Sun
01/2016–11/2016
Co-adviser of LoadOpt
University of Lugano, Switzerland
Project: Trading-off accuracy and latency on big data processing platforms
A. Rosa
10/2013–04/2016
Co-adviser of LoadOpt
University of Lugano, Switzerland
Project: Characterizing and predicting failures of big data applications
PhD Intern Mentor @IBM Research
S. Cerf
07–11/2018
University of Grenoble, France
Project: Robust learning against noisy data
N. Ramashan
08–12/2016
KTH Royal Institute of Technology, Sweden
Project: Optimizing tail latency for in-memory data store
J. Xue
08–12/2015
College of William and Mary, USA
Project: Proactive datacenter ticket management using approximate time series prediction
S. Spicuglia
03/2014–08/2015
University of Lugano, Switzerland
Project: Resource and overload management for big data platforms
C. Wang
06–10/2014
Pennsylvania State University, USA
Project: Pricing design for co-located cloud tenants
D. Cavada
09/2013–08/2014
Bogazici University, Turkey
Project: Energy-aware scheduling design for datacenter (became her thesis dissertation)
A. Podzimek
08/2012–04/2013
Charles University, Czech Republic
Project: Partial load benchmarking (became his thesis dissertation)
D. Ansaloni
09/2010–04/2011
University of Lugano, Switzerland
Project: Consolidating workloads on multicore systems
Master Student Co-Advisory Role @IBM Research
J. Vallone
09/2014–06/2015
Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland
Master thesis: Contention detection by throttling: a black-box on-line approach
Y. Yin
02–07/2014
Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland
Master thesis: Optimizing energy, locality and priority in a MapReduce cluster