Ali Zoljodi received his B.Sc. degree from the Kerman University of Bahonar (2016) and the M.Sc. degree from the Shiraz University of Technology (2019), both in Software Engineering. He has some experience in Evolutionary based Deep Neural Network Optimization.
He is a member of the AutoDeep project at Mälardalen University, and he is working on the robust development of computer vision algorithms for autonomous driving applications.
3DLaneNAS: Neural Architecture Search for Accurate and Light-Weight 3D Lane Detection (Sep 2022) Ali Zoljodi, Mohammad Loni, Sadegh Abadijou , Mina Alibeigi , Masoud Daneshtalab ICANN2022: 31st International Conference on Artificial Neural Networks (ICANN2022)
FastStereoNet: A Fast Neural Architecture Search for Improving the Inference of Disparity Estimation on Resource-Limited Platforms (Nov 2021) Mohammad Loni, Ali Zoljodi, Amin Majd , Byung Hoon Ahn , Masoud Daneshtalab, Mikael Sjödin, Hadi Esmaeilzadeh IEEE Transactions on Systems, Man, and Cybernetics: Systems (SMCS)
DenseDisp: Resource-Aware Disparity Map Estimation by Compressing Siamese Neural Architecture (Jul 2020) Mohammad Loni, Ali Zoljodi, Amin Majd , Masoud Daneshtalab, Mikael Sjödin, Ben Juurlink , Reza Akbari IEEE WORLD CONGRESS ON COMPUTATIONAL INTELLIGENCE (WCCI) 2020 (IEEE WCCI)
DeepMaker: A Multi-Objective Optimization Framework for Deep Neural Networks in Embedded Systems (Jan 2020) Mohammad Loni, Sima Sinaei, Ali Zoljodi, Masoud Daneshtalab, Mikael Sjödin Elsevier journal of Microprocessors and Microsystems (MICPRO)
NeuroPower: Designing Energy Efﬁcient Convolutional Neural Network Architecture for Embedded Systems (Sep 2019) Mohammad Loni, Ali Zoljodi, Sima Sinaei, Masoud Daneshtalab, Mikael Sjödin The 28th International Conference on Artificial Neural Networks (ICANN 2019)