CV

Theoretical and computational neuroscience, artificial intelligence, machine learning and data science.

09/2015-08/2020, Northeastern University, Ph. D. candidate in Physics
09/2011-06/2015, Lanzhou University, Cuiying Honors College, Bachelor of Science, Physics

06/2017-07/2017, Princeton University, Neurotechnologies for Analysis of Neural Dynamics summer course
07/2014-08/2014, The University of California, Berkeley, Summer School, Courses Taken: General Astronomy and Special Topics in History

05/2016-08/2020, Research Assistant, Neurogeometry Lab
06/2019-08/2019, Computational Biology/Data Science internship, Axcella Health
09/2015-04/2016, Teaching Assistant, Northeastern University, Introductory Physics Laboratory

Danke Zhang, Chi Zhang and Armen Stepanyants, Reconstructing connectome of the cortical column with biologically-constrained associative learning. (in preparation)
Chi Zhang, Danke Zhang, and Armen Stepanyants, Biologically inspired model of associative memory storage with noisy neurons and synapses. Submitted. Website: www.biorxiv.org/content/10.1101/583922v1 (in preparation)
Zhang, Danke, Chi Zhang, and Armen Stepanyants. "Robust associative learning is sufficient to explain the structural and dynamical properties of local cortical circuits." Journal of Neuroscience 39, no. 35 (2019): 6888-6904. Download
Yu, Lianchun, Chi Zhang, Liwei Liu, and Yuguo Yu. "Energy-efficient population coding constraints network size of a neuronal array system." Scientific Reports 6 (2016): 19369. Download
Chi Zhang, Liu Li-Wei, Wang Long-Fei, Yue Yuan, and Yu Lian-Chun. "Optimal Size for Maximal Energy Efficiency in Information Processing of Biological Systems Due to Bistability" Chinese Physics Letters 32, no. 11 (2015): 110501. Download

Danke Zhang, Chi Zhang and Armen Stepanyants. Reconstructing connectome of the cortical column with biologically-constrained associative learning. CNS2019, Barcelona, 2019. (Travel award)
Chi Zhang, Danke Zhang, and Armen Stepanyants. Fluctuations in neural activity are reflected in the structure of associative memory networks. COSYNE2019, Lisbon, Portugal, 2019. (Travel award)
Danke Zhang, Chi Zhang and Armen Stepanyants. Structural and dynamical properties of local cortical networks result from robust associative learning. CNS2018, Seattle, 2018. (Oral presentation, top 5%)
Danke Zhang, Chi Zhang and Armen Stepanyants. Order-to-chaos phase transition in recurrent networks operating at maximum capacity for storing sequences of network states, ICMNS2017, Boulder, 2017. (Oral presentation)
Chi Zhang, Danke Zhang, Armen Stepanyants. "Robustness to fluctuations in neural activity is reflected in the structure of critical associative memory networks." SfN, Washington, DC, November 2017.
Chi Zhang, Danke Zhang, Armen Stepanyants. "Structural and dynamic properties of neural networks with robust associative memory recall in the presence of fluctuations in neuron firing." International Conference on Mathematical Neuroscience, Boulder CO, May 2017.

Chi Zhang, Danke Zhang, Armen Stepanyants. "Robustness to fluctuations in neural activity is reflected in the structure of critical associative memory networks." Society for Neuroscience Annual Conference, Washington DC, Nov 2017.
Chi Zhang, Danke Zhang, Armen Stepanyants. "Structural properties of neural networks with robust associative memory recall in the presence of fluctuations in neuron firing." International Conference on Mathematical Neuroscience, Boulder CO, May 2017.

09/2019，CNS travel award
08/2019，Best graduate intern at Axcella Health
03/2019，Cosyne travel award
10/2014，First Class Scholarship and “Model Student” of LZU
04/2014，Honorable Mention, Mathematical Contest in Modeling/ Interdisciplinary Contest in Modeling
05/2013，Excellent Cadre of the Communist Youth League of LZU
12/2012，First Class Scholarship and “Model Student” of LZU
12/2011， “Outstanding Member” of the Student Union, LZU

Coding Languages: Python, Matlab, R, C++, html, CSS, javascript, Bash Script.
Machine Learning: SQL, Pandas, Scipy, Sklearn, Tensorflow, Keras, GPU computing.