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ORCIDHassan Ghasemzadeh Mohammadi
Person information
- affiliation: Paderborn University, Department of Computer Science, Germany
- affiliation (PhD 2016): École Polytechnique Fédérale de Lausanne (EPFL), Integrated Systems Lab (ISL), Switzerland
- affiliation: Sharif University of Technology, Department of Computer Engineering, Tehran, Iran
Other persons with the same name
- Hassan Ghasemzadeh 0001
![[0000-0002-1844-1416]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-1844-1416")
— Washington State University, School of Electrical Engineering and Computer Science, Pullman, WA, USA (and 4 more)
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2020 – today
- 2024
[c13]Muhammad Awais, Hassan Ghasemzadeh Mohammadi, Marco Platzner:
DeepApprox: Rapid Deep Learning based Design Space Exploration of Approximate Circuits via Check-pointing. ISVLSI 2024: 88-93- 2021
- [c12]Muhammad Awais, Hassan Ghasemzadeh Mohammadi, Marco Platzner:
LDAX: A Learning-based Fast Design Space Exploration Framework for Approximate Circuit Synthesis. ACM Great Lakes Symposium on VLSI 2021: 27-32 - [c11]Hassan Ghasemzadeh Mohammadi, Felix Paul Jentzsch, Maurice Kuschel, Rahil Arshad, Sneha Rautmare, Suraj Manjunatha, Marco Platzner, Alexander Boschmann, Dirk Schollbach:
FLight: FPGA Acceleration of Lightweight DNN Model Inference in Industrial Analytics. PKDD/ECML Workshops (1) 2021: 351-362 - 2020
- [c10]Hassan Ghasemzadeh Mohammadi, Rahil Arshad, Sneha Rautmare, Suraj Manjunatha, Maurice Kuschel, Felix Paul Jentzsch, Marco Platzner, Alexander Boschmann, Dirk Schollbach:
DeepWind: An Accurate Wind Turbine Condition Monitoring Framework via Deep Learning on Embedded Platforms. ETFA 2020: 1431-1434 - [c9]Muhammad Awais, Hassan Ghasemzadeh Mohammadi, Marco Platzner:
A Hybrid Synthesis Methodology for Approximate Circuits. ACM Great Lakes Symposium on VLSI 2020: 421-426
2010 – 2019
- 2019
- [c8]Linus Witschen, Hassan Ghasemzadeh Mohammadi, Matthias Artmann, Marco Platzner:
Jump Search: A Fast Technique for the Synthesis of Approximate Circuits. ACM Great Lakes Symposium on VLSI 2019: 153-158 - 2018
- [c7]Muhammad Awais, Hassan Ghasemzadeh Mohammadi, Marco Platzner:
An MCTS-based Framework for Synthesis of Approximate Circuits. VLSI-SoC 2018: 219-224 - 2016
- [b1]Hassan Ghasemzadeh Mohammadi:
Robustness Analysis of Controllable-Polarity Silicon Nanowire Devices and Circuits. EPFL, Switzerland, 2016 - [j2]Hassan Ghasemzadeh Mohammadi, Pierre-Emmanuel Gaillardon, Jian Zhang, Giovanni De Micheli, Ernesto Sánchez, Matteo Sonza Reorda:
A Fault-Tolerant Ripple-Carry Adder with Controllable-Polarity Transistors. ACM J. Emerg. Technol. Comput. Syst. 13(2): 16:1-16:13 (2016) - [j1]Hassan Ghasemzadeh Mohammadi, Pierre-Emmanuel Gaillardon, Giovanni De Micheli:
Efficient Statistical Parameter Selection for Nonlinear Modeling of Process/Performance Variation. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 35(12): 1995-2007 (2016) - 2015
- [c6]Hassan Ghasemzadeh Mohammadi, Pierre-Emmanuel Gaillardon, Giovanni De Micheli:
Fault modeling in controllable polarity silicon nanowire circuits. DATE 2015: 453-458 - [c5]Hassan Ghasemzadeh, Pierre-Emmanuel Gaillardon, J. Zhang, Giovanni De Micheli, Ernesto Sánchez, Matteo Sonza Reorda:
On the Design of a Fault Tolerant Ripple-Carry Adder with Controllable-Polarity Transistors. ISVLSI 2015: 491-496 - 2014
- [c4]Hassan Ghasemzadeh Mohammadi, Pierre-Emmanuel Gaillardon, Majid Yazdani, Giovanni De Micheli:
Fast process variation analysis in nano-scaled technologies using column-wise sparse parameter selection. NANOARCH 2014: 163-168 - 2013
- [c3]Hassan Ghasemzadeh Mohammadi, Pierre-Emmanuel Gaillardon, Majid Yazdani, Giovanni De Micheli:
A fast TCAD-based methodology for Variation analysis of emerging nano-devices. DFTS 2013: 83-88 - [c2]Pierre-Emmanuel Gaillardon, Hassan Ghasemzadeh, Giovanni De Micheli:
Vertically-stacked silicon nanowire transistors with controllable polarity: A robustness study. LATW 2013: 1-6 - 2010
- [c1]Mehrdad Khatir, Hassan Ghasemzadeh Mohammadi, Alireza Ejlali:
Sub-threshold charge recovery circuits. ICCD 2010: 138-144
Coauthor Index
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