Mohak Chadha

Room No. 01.04.060

Boltzmannstr. 3.

Garching, 85748

My name is Mohak Chadha. I am a second-year PhD student at the Technical University of Munich (TUM) advised by Prof. Dr. Michael Gerndt. My research interests are in the domain of serverless, parallel, and high-performance computing.

Prior to starting my PhD, I completed my masters in Computer Science from TUM in 2020. During my masters, I worked at the Central Research and Technology (CRT) department at Airbus in Munich on two EU funded projects, i.e., Aramis 2. and COEMS..

Before my masters, I recieved my Bachelor’s in Computer Science and Master’s in Mathematics from Birla Institute of Technology and Science-Pilani in India. During that time, I interned at Nvidia, Center for Information Services and High Performance Computing, TU Dresden, and Central Electronics Engineering Research Institute, Pilani.

Contact

If you are interested in working with me, please send me an email. For students at TUM, looking for thesis topics please see here.

Recent News

Oct 28, 2021	Our Paper titled “FedLess: Secure and Scalable Federated Learning Using Serverless Computing” got accepted at IEEE BigData’21
Oct 26, 2021	Our Paper titled “ Estimating the Capacities of Function-as-a-Service Functions” got accepted at CloudAM@UCC’21
Oct 21, 2021	Our Paper titled “Towards Demystifying Intra-Function Parallelism in Serverless Computing” got accepted at WoSC@Middleware’21
Oct 12, 2021	Our Paper titled “Courier: Delivering Serverless Functions Within Heterogeneous FaaS Deployments” got accepted at IEEE/ACM UCC’21

Selected publications

BigData
FedLess: Secure and Scalable Federated Learning Using Serverless Computing

Grafberger, Andreas, Chadha, Mohak, Jindal, Anshul, Gu, Jianfeng, and Gerndt, Michael

In 2021 IEEE 9th International Conference on Big Data (IEEE BigData) 2021

Bib HTML
@inproceedings{fedless, author = {Grafberger, Andreas and Chadha, Mohak and Jindal, Anshul and Gu, Jianfeng and Gerndt, Michael}, booktitle = {2021 IEEE 9th International Conference on Big Data (IEEE BigData)}, title = {FedLess: Secure and Scalable Federated Learning Using Serverless Computing}, year = {2021}, volume = {}, number = {}, abbr = {BigData}, bibtex_show = {true}, html = {https://arxiv.org/pdf/2111.03396.pdf}, selected = {true} }

IEEE CLOUD

Architecture-Specific Performance Optimization of Compute-Intensive FaaS Functions

Chadha, Mohak, Jindal, Anshul, and Gerndt, Michael

In 2021 IEEE 14th International Conference on Cloud Computing (IEEE CLOUD) 2021

Bib HTML

@inproceedings{chadhaarchitecture,
  author = {Chadha, Mohak and Jindal, Anshul and Gerndt, Michael},
  booktitle = {2021 IEEE 14th International Conference on Cloud Computing (IEEE CLOUD)},
  title = {Architecture-Specific Performance Optimization of Compute-Intensive FaaS Functions},
  year = {2021},
  volume = {},
  number = {},
  abbr = {IEEE CLOUD},
  bibtex_show = {true},
  html = {https://arxiv.org/pdf/2107.10008.pdf},
  selected = {true}
}

IEEE/ACM UCC

Courier: Delivering Serverless Functions Within Heterogeneous FaaS Deployments

Jindal, Anshul, Frielinghaus, Julian, Chadha, Mohak, and Gerndt, Michael

In 2021 IEEE/ACM 14th International Conference on Utility and Cloud Computing (UCC) 2021

IC2E

DeepEdgeBench: Benchmarking Deep Neural Networks on Edge Devices

Baller, Patrick Stephan, Jindal, Anshul, Chadha, Mohak, and Gerndt, Michael

In 2021 IEEE 9th International Conference on Cloud Engineering (IC2E) 2021

Bib HTML

@inproceedings{deepedgebench,
  author = {Baller, Patrick Stephan and Jindal, Anshul and Chadha, Mohak and Gerndt, Michael},
  booktitle = {2021 IEEE 9th International Conference on Cloud Engineering (IC2E)},
  title = {DeepEdgeBench: Benchmarking Deep Neural Networks on Edge Devices},
  year = {2021},
  volume = {},
  number = {},
  abbr = {IC2E},
  bibtex_show = {true},
  html = {https://arxiv.org/pdf/2108.09457.pdf},
  selected = {true}
}

WoSC@Middleware

Towards Demystifying Intra-Function Parallelism in Serverless Computing

Kiener, Michael, Chadha, Mohak, and Gerndt, Michael

In Proceedings of the 2021 Seventh International Workshop on Serverless Computing 2021