Bionet Academics


The Bionet Group offers and coordinates a number of courses and student projects in Computational Neurocience. For related courses see also the optional MS Concentration in Systems Biology and Neuroengineering and Concentration in Data-Driven Analysis and Computation, both offered by the Department of Electrical Engineering.

Graduate/Post-graduate Courses

Spring 2021:ECBM E6070 Computing with Brain Circuits of Model Organisms

Project Opportunities

A range of interdisciplinary projects are open to Columbia students majoring in Electrical/Computer Engineering, Computer Science, or Neurobiology/Neuroscience. Projects typically start at the beginning of the Fall, Spring, or Summer semester and are available on a rolling basis. Internships are also available. Students selected to work on independent projects are expected to register for a project course and receive academic credit. Interested students should send their résumés or CVs to Prof. Aurel A. Lazar.

Related student activity: Fruit Fly Brain Hackathon. More information on the research activities of the Bionet Group is available here.

MS Thesis in Electrical Engineering: Concentration in Systems Biology and Neuroengineering

Enrollment in ELEN E6003 Master's Thesis requires a minimum of 3 points of credit in ELEN E6001 or E6002 and the approval of a thesis advisor.

Additional course requirements for a Master's Thesis in the Bionet lab:

These courses are also listed in the optional Concentration in Systems Biology and Neuroengineering. For further details please contact Professor Aurel A. Lazar.

MS Research Specialization: Concentration in Systems Biology and Neuroengineering

The Department of Electrical Engineering offers qualified MS students the option to pursue the MS Research Specialization. This specialization is merit-based; each student needs to find a full-time faculty member in Electrical Engineering who is willing to supervise their research. Students need to first do at least 3 credits of 6001/6002 (as part of the 24 credits in their first two semesters) under the supervision of their research advisor and then need recommendation from their research advisor to apply and be admitted to concentration by the department.

Admitted students will typically take a 6-credit (zero tuition) research course ENGI E4990 in their third semester, in addition to the remaining 6 credits of their other third-semester courses, to achieve a total of 12 credits and full-time status in their third semester. They can then take another 6-credit (zero tuition) research course ENGI E4990 in their fourth semester. The course is a letter-grade course and can be taken in the fall or spring. The grades will be included on the transcript. ENGI E4990 credits do not count as credits for the MS degree. See https://bulletin.engineering.columbia.edu/interdisciplinary-engineering-courses for the bulletin description.

Interested students are encouraged to contact Professor Aurel A. Lazar.

Past Graduate/Post-graduate Courses

Spring 2019:EEBM E6095 Computing with Brain Circuits
Spring 2018:ECBM E6070 Fruit Fly Brain as NeuroInformation Processor
Spring 2016:ECBM E6040 Neural Networks and Deep Learning
Spring 2015:EEBM E9070 Computing with Brain Circuits
Spring 2014:EEBM E6092 Big Data in Neuroscience
Spring 2013:EEBM E6020 Methods of Computational Neuroscience
Spring 2012:EEBM E9070 Massively Parallel Neural Computation
Spring 2012:EEBM E6091 Neuromorphic Engineering
Spring 2010:EEBM E9070 Neural Encoding and Computation in Sensory Systems
Spring 2009:EEBM E9070 Brain Circuits and Information
Spring 2008:EEBM E6020 Methods of Computational Neuroscience
Fall 2007:ELEN E6082 Global Brain Modeling (external)
Spring 2007:ELEN E9060 Representation and Processing of Olfactory Information
Spring 2006:ELEN E9060 Dendritic Computation
Spring 2006:ELEN E6080 Methods of Signal Processing in Computational Neuroscience
Spring 2005:ELEN E6906 Information Representation in Sensory Systems
Fall 2004:ELEN E6711 Stochastic Models in Information Systems
Spring 2003:ELEN E6901 Time Encoding, Channels and Information