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Hassan 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
— Washington State University, School of Electrical Engineering and Computer Science, Pullman, WA, USA (and 4 more)
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2020 – today
- 2026
[c17]Atousa Jafari, Amir Hossein Hadipour, Muhammad Awais, Mohammadparsa Rostamzadehkhameneh, Hassan Ghasemzadeh Mohammadi, Marco Platzner:
CLAS: A Cross-Layer Approximate Synthesis Framework for LUT-Based DNN Accelerators. ARC 2026: 255-272
[c16]Muhammad Awais, Hassan Ghasemzadeh Mohammadi, Sayed Morteza Jawadi, Marco Platzner:
DP-MCTS: Deep Playout-Driven MCTS for Approximate Accelerator Design. DDECS 2026: 1-6
[i1]Atousa Jafari, Mahdi Taheri, Hassan Ghasemzadeh Mohammadi, Christian Herglotz, Marco Platzner:
Sensitivity-Guided Framework for Pruned and Quantized Reservoir Computing Accelerators. CoRR abs/2603.08737 (2026)- 2025
[j4]Muhammad Awais
, Hassan Ghasemzadeh Mohammadi, Marco Platzner
:
Design Space Exploration for Approximate Circuits via Checkpointing and DNN-Based Estimators. IEEE Trans. Very Large Scale Integr. Syst. 33(9): 2395-2405 (2025)
[j3]Atousa Jafari, Hassan Ghasemzadeh Mohammadi, Marco Platzner:
CRC: Compressed Reservoir Computing on FPGA via Joint HSIC LASSO-based Pruning and Quantization. WiPiEC Journal 11(1): 1-4 (2025)
[c15]Farjana Jalil, Muhammad Awais, Qazi Arbab Ahmed
, Hassan Ghasemzadeh Mohammadi, Thorsten Jungeblut
, Marco Platzner:
Deep&Wide: Achieving Area Efficiency in Scalable Approximate Accelerators. DSN-W 2025: 115-118
[c14]Muhammad Awais, Hassan Ghasemzadeh Mohammadi, Marco Platzner:
Swift Synthesis of Approximate Hardware Accelerators Using Generative Adversarial Networks. VLSI-SoC 2025: 1-5- 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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last updated on 2026-07-14 01:44 CEST by the dblp team
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