I am currently a Ph.D. candidate at the Chalmers University and
expect to graduate at the end of May 2022.
I perform empirical studies on IoT devices:
- Embedded Devices (ARM cortex M)
- TinyML (CMSIS-NN, TensorFlow Micro)
- Deep Learning Quantization (PyTorch, Tensorflow)
- Blockchain (Hyperledger, Ethereum)
Performance of deep neural networks on low-power IoT devices - CPS-IoTBench '21
TinyEVM: Off-Chain Smart Contracts on Low-Power IoT Devices - 40th IEEE International Conference on Distributed Computing Systems (2020)
IoTLogBlock: Recording Off-line Transactions of Low-Power IoT Devices Using a Blockchain - 44th Annual IEEE Conference on Local Computer Networks (2019)
Performance of Secure Boot in Embedded Systems - IEEE International Conference on Distributed Computing in Sensor Systems (2019).
