Richard Hakim

Richard Hakim, a diligent and accomplished neuroscience PhD candidate at Harvard University, is at the forefront of groundbreaking research in the field of brain computation. With an impressive academic background and a history of contributions to various aspects of neuroscience, Rich's work is both comprehensive and innovative.

Rich's journey in neuroscience began at Harvard, where he embarked on a path to unravel the intricacies of the brain. His research portfolio includes investigating visual processing, cortical microcircuit function, dendritic integration, and brain-machine interfacing. Notably, he has also played a pivotal role in developing tools and methodologies that have proven invaluable to the scientific community.

Originally hailing from Los Angeles, Rich had a distinguished career as a video editor in journalism and film before his transition into the world of science. His undergraduate studies took place at UC Berkeley, where he joined Hillel Adesnik's lab. Here, he delved into the fascinating realm of how oscillations in the visual cortex are instrumental in segmenting objects within images. His research also unveiled the significant role played by an unexpected type of inhibitory neuron in generating these oscillations.

Subsequently, Rich's academic pursuits led him to Harvard's Graduate Program in Neuroscience, where he continued his journey of exploration. Under the mentorship of Bernardo Sabatini, he spearheaded pioneering work using novel fluorescent voltage sensors to probe dendritic integration in the distal tufts of cortical pyramidal neurons, pushing the boundaries of our understanding of neural functioning.

In more recent endeavors, Rich's contributions have extended to the development of cutting-edge machine learning pipelines. These pipelines are instrumental in tracking neurons in fluorescent images and extracting meaningful behavioral measurements from video recordings of faces. These tools are used in conjunction with a novel brain-computer-interfacing microscope, capable of simultaneously monitoring the activity of thousands of neurons. Rich's research aims to elucidate how brains explore different activity patterns and learn to exploit patterns that lead to rewards.