Ishanu Chattopadhyay
P.I. willing to mentor undergraduate research volunteers interested, work study students or students requiring pay in Data Science, Machine Learning, Viral Evolution.
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Jasmine Nirody
We study the physics of how biological systems interact with their environments, as well as the role of these interactions in shaping organismal morphology and behavior.
We use a range of theoretical and empirical (laboratory + field) techniques to answer questions that sit at the intersection of behavior, biophysics, and evolution.
We work on problems across organismal systems and levels of biological organization. While the underlying mechanisms (and the techniques we use to study them) may vary as we shift our focus from molecular motors to bacteria to animals, the larger questions we are fascinated by remain the same!
- How do biological systems sense and respond to mechanical stresses in complex environments?
- In what environments do adaptive mechanics improve performance?
- How do flexible locomotive strategies affect the evolution of biomechanical structures?
Our research provides ample opportunities for undergraduate engagement. Please email Jasmine at jnirody@uchicago.edu to discuss options!
Jason MacLean
Opportunity to study single trial representations of sensory input and motor output in local neocortical circuits.
Our group studies single trial representations of sensory input and motor output in local neocortical circuits. Individual neurons are active differently even when the task conditions are identical. In part this is because a large majority of the activity that an experimenter records is not readily assigned to a specific sensory input or motor output. Rather than simple input output responses we postulate that many variables are simultaneously represented. Consequently, understanding the real time activity of the interconnected neurons in the brain will mean that we have achieved understanding of the code, and the computations, of neocortex. To do so we take an explicitly circuit centric, network science based, analytical perspective to recordings of hundreds of neocortical neurons. We complement this work and achieve further understanding by simulating and training spiking neuron networks.