Welcome! I am currently a postdoctoral researcher at Laboratoire Albert Fert, CNRS, Thales in France, working with Julie Grollier. I am mainly working on developing novel algorithms for unsupervised/self-supervised learning in neural networks, aiming to enhance their ability to discover hidden patterns in data without the need for labeled inputs. More importantly, the developed learning rule is intended to not only enhance the efficiency of neural networks but also align closely with the learning mechanisms observed in the human brain (so called bio-plausible learning rules, i.e., learning rules that alternate from backpropogation). Check about my research details: Research.
Before my postdoc, my academic journey began with a PhD at Université Paris-Saclay and Beihang University, where I was fortunate to be co-supervised by Damien Querlioz and Dafiné Ravelosona at Center for Nanoscience and Nanotechnology (C2N). My fascination with AI took root during a research project at C2N, where I delved into the intricate world of modeling time-series data. This data came from an exciting source: experimental spintronic nano-devices (tiny, cutting-edge components used in the field of electronics). My task involved using them for spoken digit recognition with reservoir computing (check my posts for more info: What and Why reservoir computing, Memory and Nonlinearity in Reservoir Computing).
In pursuit of creating a digital counterpart to the physical setup of these devices, I utilized a sophisticated deep learning method known as neural ordinary differential equations. This approach allowed me to predict future data trends with exceptional accuracy and computational efficiency. The success of this project was not only a personal milestone but also a recognized achievement, leading to a publication in Nature Communications and earning the distinction of being selected as an Editor’s highlight. Moreover, the methodology I developed proved versatile, extending its application to other dynamic physical systems. This adaptability was demonstrated in another project, where it was used to uncover experimental data, with these findings too being published in Nature Communications.
During my PhD, I also had the invaluable opportunity to intern at Huawei’s AI lab. There, my focus shifted to industrial data, employing the hidden Markov method for time series modeling. Additionally, I contributed to enhancing deep learning models, specifically in generating realistic face images and videos, and aligning face images for various business applications, including customer service in banks and virtual streaming platforms.
Outside from my professional career, I also enjoy drawing, painting, cooking, sports (running, hiking, skiining, etc.), listening to podcasts, and also recording my thoughts either during research or in my life—>Posts
Recent news/experience
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2024.06 I presented my poster entitled “Contrastive Forward Forward Algorithm” International Conference on Neuromorphic Computing and Engineering (ICNCE-2024) in Aachen, Germany.
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2023.10 I attended the International conference on neuromorphic, natural and physical computing (NNPC 2023) in Hanover, Germany.
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2023.06 Our work of “Experimental demonstration of a skyrmion-enhanced strain-mediated physical reservoir computing system” was published in Nature communications!
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2022.11 I gave an oral presentation at IEEE MMM conference in Minneapolis, USA. My talk was also selected as a finalist for the Best student presentation award!
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2022.09 I started my six-months internship as a research scientist at AI lab of Huawei Technology in Beijing, China.
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2022.02 Our work of “Forecasting the outcome of spintronic experiments with neural ordinary differential equations” was published in Nature communications!
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2019.10 I won the Best poster award at 4th International workshop on Spintronic Memory and Logic, SML at Beihang University, China. I was also furtunate to be awarded by the physicist of the 2007 Nobel Prize winner, Albert Fert!
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2019.06 I attened IEEE magnetics Summer school with full scholarship in Virgina, USA.
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2019.01 I gave an oral presentation at IEEE Joint-MMM conference in DC, USA.
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2018.05 I gave an oral presentation at IEEE INTERMAG conference in Singapore.
Publications
Please see my Google Scholar or Researchgate page.