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Backpropagation-Free Learning: On the Emergence of Forward-Only Algorithms
Baichuan Huang , Alexander Ororbia , Amir Aminifar
paper /
cite
This survey paper provides a comprehensive overview to foster progress in BP-free learning in the context of emerging forward-only adaptation.
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BEFT: Bias-Efficient Fine-Tuning of Language Models in Low-Data Regimes
Baichuan Huang , Ananth Balashankar , Amir Aminifar
Accepted to ACL 2026 (Main Conference)
The 64th Annual Meeting of the Association for Computational Linguistics (Acceptance Rate: 19% )
paper /
Hugging Face BEFT /
Google Research Scholar Program 2025 /
code
We investigate the link between fine-tuning b q , b k , and b v with downstream performance. We find that fine-tuning b v in low-data regimes is sufficient; b k has no effect on improved expressiveness, whereas b q has a limited effect.
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TinyFoA: Memory Efficient Forward-Only Algorithm for On-Device Learning
Baichuan Huang , Amir Aminifar
Accepted to AAAI 2025
The 39th Annual AAAI Conference on Artificial Intelligence (Acceptance Rate: 23.4% )
paper /
code (... ⭐)/
poster/
ELLIS Poster in EurIPS
We propose a memory-efficient forward-only algorithm called TinyFoA, to reduce dynamic memory overhead in the training process.
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Binary Forward-Only Algorithms
Baichuan Huang , Amir Aminifar
Special Issue on "tinyML – The ecosystem for next generation ML systems" , 2025
IEEE Design & Test
paper /
code
We investigate and compare BP and forward-only algorithms in terms of binarization, finding that PEPITA and FF are more vulnerable to binary activations.
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Efficient On-Device Machine Learning with a Biologically-Plausible Forward-Only Algorithm
Baichuan Huang , Amir Aminifar
Accepted to MLSys 2025
The Eighth Annual Conference on Machine Learning and Systems (Acceptance Rate: 22% )
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artifacts available
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slides /
poster
We propose a biologically-plausible forward-only algorithm (Bio-FO), not only addressing the biological-implausibility issues associated with BP, but also outperforming the state-of-the-art forward-only algorithms.
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Energy-Aware Integrated Neural Architecture Search and Partitioning for Distributed Internet of Things (IoT)
Baichuan Huang , Azra Abtahi, Amir Aminifar
The inaugural issue of TCASAI , 2024
IEEE Transactions on Circuits and Systems for Artificial Intelligence
paper
We propose an energy-aware NAS framework for distributed IoT, aiming to search for distributed DNNs to maximize prediction performance subjected to Flash Memory (Flash), Random-access Memory (RAM), and energy constraints.
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LightFF: Lightweight Inference for Forward-Forward Algorithm
Amin Aminifar† , Baichuan Huang*† , Azra Abtahi, Amir Aminifar
(†equal contribution *corresponding author )
Accepted to ECAI 2024
The 27th European Conference on Artificial Intelligence (Acceptance Rate: 23% )
paper /
interactive demo /
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slides /
poster
We propose a lightweight inference scheme specifically designed for DNNs trained using the Forward-Forward algorithm ( Contributor to the Forward-Forward repository ... ⭐ ).
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EpilepsyNet: Interpretable Self-Supervised Seizure Detection for Low-Power Wearable Systems
Baichuan Huang , Renato Zanetti , Azra Abtahi Fahliani , David Atienza , Amir Aminifar
Accepted to AICAS 2023
IEEE 5th International Conference on Artificial Intelligence Circuits and Systems
paper /
slides
We propose the first interpretable self-supervised network for seizure detection without any need for real seizure data in training, which has comparable performance with supervised methods. (Contemporaneous and similar work of peers in AAAI2023)
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Lightweight Machine Learning for Seizure Detection on Wearable Devices
Baichuan Huang , Azra Abtahi Fahliani, Amir Aminifar
Top-5 Ranking in the Seizure Detection Challenge (Challenge Link )
Accepted to ICASSP 2023
IEEE International Conference on Acoustics, Speech, and Signal Processing
paper /
slides
We propose a lightweight machine-learning framework for real-time epilepsy monitoring on wearable devices (SensorDot of Byteflies ).
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M3 VSNet: Unsupervised Multi-metric Multi-view Stereo Network
Baichuan Huang , Hongwei Yi , Can Huang, Yijia He , Jingbin Liu, Xiao Liu
Accepted to ICIP 2021
IEEE International Conference on Image Processing
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code (... ⭐) /
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poster /
This method establishes the state-of-the-arts unsupervised MVS method and demonstrates the powerful generalization ability.
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A Survey of Simultaneous Localization and Mapping with an Envision in 6G Wireless Networks
Baichuan Huang , Jun Zhao , Jingbin Liu
Journal of Global Positioning Systems , 2021
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project (... ⭐)/
cite
The paper makes an overview in SLAM including Lidar SLAM, visual SLAM, and their fusion.
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A Robust Indoor Positioning Method based on Bluetooth Low Energy with Separate Channel Information
Baichuan Huang , Jingbin Liu, Wei Sun, Fan Yang
Sensors , 2019
paper
To improve the adaptability and robustness of the BLE positioning system, we propose making full use of the three separate channels instead of their combination.
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AOA Estimation Based on Channel State Information Extracted from WiFi with Double Antenna
Jingbin Liu, Baichuan Huang , Bin Zhang
Geomatics and Information Science of Wuhan University , 2018
paper
This paper uses two virtual antennas to realize the music algorithm (Angle of Arrival) based on channel state information (CSI).
Professional Service
Presentation: :
2026.04.27 : Speak at Perceptual Engineering: How can we engineer human perception? , AI Lund , Lund, Sweden
2025.12.02 : Poster Presentation at ELLIS UnConference in EurIPS, Copenhagen, Denmark
2025.09.23 : Panel at The Things Conference 2025 , Amsterdam, Netherlands
2025.05.14 : Oral and Poster Presentation at MLSys 2025 , Santa Clara, California, the USA
2025.02.28 : Poster Presentation at AAAI 2025 , Philadelphia, Pennsylvania, the USA
2024.10.21-10.24 : Oral Presentation and Outreach Activity at ECAI 2024 , Santiago de Compostela, Spain
2024.09.26 : Pitch Presentation at Politecnico di Milano , Milano, Italy
2024.09.24 : Pitch Presentation at University of Modena , Modena, Italy
2024.09.19-09.20 : Pitch and Poster Presentation in Engineering Health Fall meet 2024 , Helsingborg, Sweden
2023.10.24-10.27 : Poster and Workshop Presentation at Natural and Artificial Cognition II , AI Lund , Lund, Sweden
2023.09.29 : Poster Presentation at Schwarzman College of Computing , MIT , Boston, the USA
2023.06.11-06.13 : Oral Presentation at AICAS 2023 , Hangzhou, China
2023.06.04-06.10 : Oral Presentation at ICASSP 2023 , Rhodes Island, Greece
2021.09.19-09.22 : Oral Presentation at ICIP 2021 , Anchorage, Alaska, the USA (Hybrid)
Teaching Duty: :
2025 : Machine Learning for Internet of Things (IoT) (EITP40 ): Kaggle Competition , Invited Lecture (Efficient LLMs )
2024 : Machine Learning for Internet of Things (IoT) (EITP40 ): Kaggle Competition (Lab2 / Lab3 )
2023 : Machine Learning for Internet of Things (IoT) (EITP40 ): Kaggle Competition , supervision of students' project
2023-2024 : Signal Processing in Multimedia (EITA50 )
2022 : Machine Learning for Internet of Things (IoT) (EITP40 ): Kaggle Competition
Patents: :
A high quality precision panoramic imaging system and method based on the DSLR camera
An intelligent inspection robot and intelligent inspection method for underground pipelines
Grants: :
2025.05 : Research Stint Abroad from Wallenberg AI, Autonomous Systems and Software Program (WASP)
2025.03 : Travel Grants from The Royal Physiographic Society of Lund
Awards
2021.06 : Outstanding Graduates, issued by Wuhan University
2018-2021 : The First Prize Scholarship, issued by Wuhan University