Shanshan Qin

Shanshan Qin

Postdoctoral Fellow in Computational and Theoretical Neuroscience

Harvard University

About me

I am a postdoctoral researcher at the Harvard John A. Paulson School of Engineering and Applied Sciences. I am interested in a broad spectrum of questions in computational and theoretical neuroscience. My research aims to elucidate the principles underlying neural computation and cognition. Specifically, my research addresses questions like: 1) how does the brain efficiently sense and represent external world? 2) How does the brain organize and update memories to support adaptive behavior and life-long learning? 3)How does the brain solve computational problems at the algorithmic level? Answers to these questions will have broad implications, such as shedding light on treating neurodegenerative diseases and psychiatric disorders. I earned my PhD in condensed matter physics from Peking University. During my PhD, I explored various problems at the interface between physics and biology. I was advised by Dr. Chao Tang and Dr. Yuhai Tu at Center for Quantitative Biology. Before that, I studied physics at Central China Normal University at Wuhan. I also enjoy badminton, swimming, hiking, cooking, Chinese calligraphy, watching movies and reading.


  • Theoretical and Computational Neuroscience
  • Quantiative and Systems Biology
  • Physics of life


  • PhD in Condensed Matter Physics, 2019

    Peking University, Beijing, China

  • BS in physics, 2012

    Central China Normal University, Wuhan, China



Internal state dependent olfactory behavior

Animal exhibit distinct behavior that dependent their internal states even for the same sensory input. Drosophila larva responds different to odors when starved compared with fed. This internal state dependent oflactory behavior is controled by a topdown feedback to antennal lobe circuit.

Biologically plausible supervised learning algorithm

Biologically plausible networks models with noisy synaptic update explain the widely observed representational drift.

Early-warning signals of critical transition - effect of extrinsic noise

We extend previous theory to investigate how the interplay of extrinsic noise and intrinsic noise affects early-warning signals near critical transitions.

Odor representation in C. elegans

Multineuronal imaging of the odor responses in C. elegans and decoding analysis revealed a distinct organization compared with insects and mamammlians.

Optimal nonlinear compressed sensing in olfactory periphery

To achieve efficient coding of odor information in an array of nonlinear olfactory receptors, the odor-receptor sensitivity matrix must be sparse. This sparsity depends on the statistics of environmental odors. We used analytical calclation and extensive numerical simulation to study the optimal sensitivity matrix for recptors with and without spontaneous (background) activity.

Representational drift

Biologically plausible networks models with noisy synaptic update explain the widely observed representational drift.

Short-term plasticity in early olfactory information processing

We built a circuit model of the first olfactory information processing center of fruit fly, which incorporates key features of neuron-neuron interactions such as short-term plasticity and presynaptic inhibition.


Coordinated drift of receptive fields in Hebbian/anti-Hebbian network models during noisy representation learning

Recent experiments have revealed that neural population codes in many brain areas continuously change even when animals have fully …

Drifting neuronal representations: Bug or feature?

The brain displays a remarkable ability to sustain stable memories, allowing animals to execute precise behaviors or recall stimulus …

Functional imaging and quantification of multi-neuronal olfactory responses in C. elegans

Many animals perceive odorant molecules by collecting information from ensembles of olfactory neurons. Each neuron employs receptors …

Cell-to-cell variability in inducible Caspase9-mediated cell death

iCasp9 suicide gene has been widely used as a promising killing strategy in various cell therapies. However, different cells show …

Short-Term Plasticity Regulates Both Divisive Normalization and Adaptive Responses in Drosophila Olfactory System

In Drosophila, olfactory information received by olfactory receptor neurons (ORNs) is first processed by an incoherent feed forward …

Contrastive Similarity Matching for Supervised Learning

We propose a novel biologically plausible solution to the credit assignment problem motivated by observations in the ventral visual …

Internal state configures olfactory behavior and early sensory processing in Drosophila larvae

The first olfactory processing center in the larval Drosophila brain uses information about feeding state to shape behavior. Animals …

Optimal compressed sensing strategies for an array of nonlinear olfactory receptor neurons with and without spontaneous activity

There are numerous different odorant molecules in nature but only a relatively small number of olfactory receptor neurons (ORNs) in …

A systematic study of the determinants of protein abundance memory in cell lineage

Proteins are essential players of life activities. Intracellular protein levels directly affect cellular functions and cell fate. Upon …

Early-warning signals of critical transition: Effect of extrinsic noise

Complex dynamical systems often have tipping points and exhibit catastrophic regime shift. Despite the notorious difficulty of …

Network Motifs Capable of Decoding Transcription Factor Dynamics

Transcription factors (TFs) can encode the information of upstream signal in terms of its temporal activation dynamics. However, it …

Odor-evoked inhibition of olfactory sensory neurons drives olfactory perception in Drosophila

Inhibitory response occurs throughout the nervous system, including the peripheral olfactory system. While odor-evoked excitation in …

Large-Scale Porous Hematite Nanorod Arrays: Direct Growth on Titanium Foil and Reversible Lithium Storage

Porous single-crystalline hematite (α-Fe2O3) nanorod array has been synthesized on large-area Ti foil via a facile hydrothermal method …



Postdoctoral researcher

Harvard University

Aug 2019 – Present Cambridge, MA

Research projects:

  • Developed biologically plausible learning algorithms.
  • Unraveled causes and dynamics of drifting neural representations.
  • Characterized ensemble-level odor coding properties in C. elegans, olfactory information processing in fly larvae

Visiting student

University of California, Berkeley

Jun 2016 – Sep 2016 Berkeley, CA
Visiting scholar at the Hernan Garcia Lab at the Department of Molecular and Cell Biology. Designed and performed experimental study on the temperature-dependent speed of embryogenesis in Drosophila Melanogaster

Visiting student

University of California, Santa Barbara

Aug 2015 – Sep 2016 Santa Barbara, CA
As as summer school student, I Investigated embryogesis process of insect embryos using quantitative fluorescence microscopy.

Ph.D Student

Peking University

Sep 2012 – Jul 2019 Beijing, China

I was advised by Dr. Chao Tang at the Center for Quantitative Biology, Peking University. My research was focused on quantitative and systems biology, biophysics and computational neuroscience. Research projects:

  • Established a theoretical framework for nonlinear compressed sensing problems and applied it to the peripheral olfactory systems.
  • Investigated the effect of extrinsic noise in early warning signals in nonlinear complex systems.

Undergraduate research assistant

Central China Normal University

Jun 2009 – Nov 2010 Wuhan, China
Successfully prepared the hematite nanorods array, and studied its electrochemical properties as an anode material and reversible lithium storage

Recent Posts


Distinction in Teaching

Been recognized for excellence in teaching during the Fall semester of 2020 in the course Neural Computation.

Recent & Upcoming Talks













  • 29 Oxford Street, Cambridge, MA 02138