Matthew Leonard, PhD

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Associate Professor

Matt Leonard is a cognitive neuroscientist interested in how the brain understands sequences of speech sounds as words. After completing his PhD at UCSD and a postdoc at UCSF, Matt joined the faculty in the UCSF department of Neurological Surgery, where he continues work with the Chang Lab as he studies the neural basis of word representations using ECoG and stimulation techniques. He was also a co-PI on the DARPA-funded Targeted Neuroplasticity Training (TNT) program, which seeks to use non-invasive peripheral nerve stimulation to enhance and accelerate learning of complex cognitive tasks like language acquisition.

David Moses, PhD

Assistant Professor

David Moses completed his doctoral research in the Chang lab, where he studied speech perception, automatic speech recognition, brain state representations, and real-time neural signal processing. As a postdoc and now faculty member, he is continuing his research on automatic speech recognition and real-time neural signal processing.

Peng Cong, PhD (Case Western Reserve)

Professor, Director of Brain Interface Technology

Peng Cong is an industry-seasoned world-class medical device engineering leader. He was the designer for two of the world’s first implantable bidirectional brain interfaces, the Activa PC+S and Summit RC+S devices, at Medtronic and he led and completed overall implantable system development for Galvani, a $750M joint venture between Google and GSK representing one of the world’s first bioelectronics systems. Peng joined the UCSF Department of Neurosurgery as Professor and Director of Brain Interface Technology, where he works closely with clinical teams to explore cutting-edge brain interface technology for the treatment of neuropsychiatric disorders and the development of speech prostheses.

Anusha Allawala, PhD (Brown University)

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Anusha’s research is centered on optimizing neuromodulation for psychiatric disorders and improving our understanding of affective and cognitive processing in mood disorders. She received her PhD in Biomedical Engineering at Brown University. During graduate school she helped lead efforts on high-density intracranial monitoring and multi-modal behavioral measurement in patients with depression during deep brain stimulation at Baylor College of Medicine in collaboration with Dr. Sameer Sheth. As a postdoc she will work on efforts towards closed-loop neuromodulation for mood disorders.

Jon Gauthier, PhD (Massachusetts Institute of Technology)

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Jon's research is focused on computational modeling of spoken language understanding. He completed his Ph.D. in cognitive science at the Massachusetts Institute of Technology under the mentorship of Professor Roger Levy, where he used psycholinguistic models of word recognition to predict the neural response to speech. His current research combines methods from artificial intelligence and cognitive science to study how the brain represents aspects of language structure and meaning.

Shailee Jain, PhD (University of Texas at Austin)

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Shailee’s research is focused on understanding the neural code of speech and language processing in the brain through artificial neural networks. Her doctoral dissertation focused on understanding semantic & temporal processing in the human cortex, drawing from neuroscience, NLP and machine learning. As a postdoctoral scholar in the Chang lab, Shailee will be focusing on using both ECoG and single neuron recordings to understand how words are contextualized in speech and temporal processing across neural ensembles.

Ankit Khambhati, PhD (University of Pennsylvania)

Ankit Khambhati is a postdoctoral scholar in the Chang Lab. He is interested in understanding rules by which brain networks reorganize in support of continuously changing behavioral and brain states. He completed his Ph.D. in Bioengineering under Dr. Brian Litt at the University of Pennsylvania. His graduate work focused on building computational tools to map brain networks involved in the initiation and propagation of debilitating seizures, using electrophysiology data from human epilepsy patients. He next completed a postdoc with Dr. Danielle Bassett, where he built machine learning methods to understand the mechanics of brain network reorganization. In the Chang Lab, he aims to use these tools and understand how theoretical principles from network theory can inspire next-generation interventional approaches to rehabilitate affected networks in brain disorders.

Deborah Levy, PhD (Vanderbilt)

Deborah Levy completed her Ph.D. in Hearing and Speech Sciences with Dr. Stephen Wilson at Vanderbilt University in July 2021. Her research makes use of various neuroimaging techniques to uncover neural representations of linguistic constructs, both in healthy speakers and individuals with aphasia. In her dissertation work, Deborah used multivariate lesion-symptom mapping techniques to predict longitudinal language outcomes at multiple time points following stroke. As a postdoctoral scholar at the Chang lab, she will use similar machine-learning based methods to investigate the nature of language recovery following resective neurosurgery, incorporating electrophysiological measures to characterize language on both a structural and functional basis.

Jessie Liu, PhD (UC Berkeley-UCSF)

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Jessie completed her Ph.D. in bioengineering in the Chang Lab in 2023. Her dissertation research covered both the development of algorithms for speech neuroprosthetic technology and investigating speech-motor sequence control in the brain. As a postdoc, Jessie continues to work towards developing robust speech neuroprosthesis algorithms as well as further understanding the neural basis of speech production, using machine learning and statistical techniques.

Yitzhak Norman, PhD (Weizmann Institute)

Yitzhak (Itzik) Norman is a postdoctoral scholar in the Chang Lab. His research focuses on the neuronal mechanisms underlying the ability to encode, retrieve and reenact a previous conversation in our minds. During his PhD at the Weizmann Institute of Science, Itzik studied the role of hippocampal ripples in human declarative memory. As a postdoc, he investigates the cortical-hippocampal interplay during speech perception and production, and utilizes a combination of advanced brain imaging techniques (high-field 7T fMRI) with direct intracranial recordings (ECoG).

Terri Scott, PhD (Boston University)

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Terri is a postdoctoral scholar in the Chang lab. She completed her PhD in neuroscience at Boston University under the mentorship of Dr. Tyler Perrachione, where she studied the neural bases of phonological working memory using fMRI. Her current research interests include understanding the neural dynamics of verbal working memory and how those computations are deployed during language processing.

Many Xu, PhD (Johns Hopkins)

Many (Duo Xu) is a postdoctoral scholar in the Chang Lab. He sees speech production as a process of complex, flexible and highly context-dependent motor sequence generation, and he approaches the underlying mechanisms from single-neuron activities and circuit level computations. Many completed his Ph.D. in neuroscience at Johns Hopkins University under the supervision of Dr. Daniel H. O'Connor, where he uncovered neuronal populations that encode and control sensorimotor sequence execution and organization using a novel sequence task in animals. Outside of work, when he has time, Many creates science related contents on YouTube and Bilibili.

Xiaofang Yang, PhD (Princeton University)

Xiaofang is a postdoctoral scholar in the Chang Lab. She obtained her PhD from Princeton University, where she worked with Dr. Sabine Kastner to study the attentional modulation of visual and auditory perception. Her current research interest is functional connectivity and population coding in speech processing.

Yizhen Zhang, PhD (University of Michigan)

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Yizhen Zhang is a postdoctoral scholar in the Chang lab. She completed her Ph.D. in Electrical and Computer Engineering at the University of Michigan in June 2021. In her Ph.D. research supervised by Prof. Zhongming Liu, she studied neural encoding and decoding of naturalistic stimuli and brain-inspired artificial intelligence. Her current research interest is making AI models more like human learners by grounding language learning in perception (e.g., visual experience), action, and emotion.

Lingyun Zhao, PhD (Johns Hopkins)

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Lingyun is a postdoctoral scholar in the Chang Lab. He obtained his PhD in Johns Hopkins University where he worked with Dr. Xiaoqin Wang to study the vocal production and communication of nonhuman primates. His current research interest is the coordination in motor production and the sensorimotor mechanism in speech.

Samantha Brosler (Bioengineering)

Samantha graduated from the University of Pennsylvania in 2022 with a BSE in bioengineering and a concentration in neuroengineering. Now as a PhD student in the Chang lab, Samantha is interested in computational methods for speech and motor decoding and aims to focus on translational projects involving brain-computer interfaces. Outside of lab, she enjoys running, hiking, and playing ultimate frisbee.

Ilina Bhaya-Grossman (Bioengineering)

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Ilina received her undergraduate degree from the University of California, Berkeley in Computer Science and Cognitive Science in 2018. During her time at Berkeley, she worked with Dr. Arjen Stolk and Professor Robert Knight on a dual-EEG communication study attempting to shed light on the neurophysiological features of non-verbal human communication; this work was ultimately the focus of her honors thesis. Ilina is broadly interested in the neural correlates and theory underlying communication and hopes to continue her exploration of this area of study in the Chang lab with work on bilingual speech perception.

Kaylo Littlejohn (Electrical Engineering and Computer Sciences)

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Kaylo received his BS degree in Electrical Engineering from Columbia University in 2020. During his time at Columbia, Kaylo developed VR 3D real time closed loop brain machine interface paradigms under Dr. Paul Sajda. Now as a graduate student in the Chang Lab, Kaylo works on the BCI Restoration of Arm and Voice (BRAVO) clinical trial and is broadly interested in real time speech synthesis and machine learning applied to developing assistive communication devices.

Alex Silva (Bioengineering)

Alex received his BSE in bioengineering in 2020 from the University of Pennsylvania where he worked with Drs. Kathryn Davis and Brian Litt on mapping seizure spread patterns with intracranial EEG and diffusion tensor imaging. As a student in the Chang Lab and UCSF MD/PhD program, Alex aims to focus on translational projects in brain computer interface, intraoperative recording, and epilepsy. Outside of lab, he enjoys soccer, hiking, and exploring the Bay Area.

Kristin Sellers, PhD (UNC Chapel Hill)

Kristin Sellers is an Associate Professional Researcher in the Chang Lab. She completed her Ph.D. in Neurobiology at UNC-Chapel Hill and a post-doc in the Chang Lab from 2016 to 2020 working on the DARPA-funded SUBNETS project. Her work focuses on using neural activity to inform DBS implant location and closed-loop stimulation in clinical-trials patients and novel neurotechnologies, including new probe and device designs for use in humans. She also contributes to a community effort to adopt standardized data formats to enable easy data sharing and archiving.

Anthony Fong

Anthony Fong is interested in the human brain function, consciousness, and technological applications. At UCSF Anthony develops computer programs that can that receive real-time electrocorticography (ECoG) data, detects when there is change in the ECoG that corresponds to malignant state, and delivers therapeutic stimulation when this state is detected. During this process he collaborates with researchers, neurologists, and psychiatrists who develop the algorithms used to detect the malignant state.

Irina Hallinan

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Irina received her BS in Computer Science at Rice University and Master of Engineering in Electrical Engineering and Computer Sciences at University of California, Berkeley. During her master’s studies, under the guidance of Dr. Brian Barsky, she developed an assistive communication application for American Sign Language speakers. Prior to joining the Chang lab, Irina designed and developed interactive data-driven applications for scientists at NASA. As a Research and Development Engineer on the BCI Restoration of Arm and Voice (BRAVO) clinical trial, Irina aims to focus on developing intuitive brain-computer interfaces to assist both patients and researchers.

Viv Her

Catherine Wang

Catherine received her BA degree in Linguistics/Cognitive Science from the University of Southern California and her MS in Speech-Language Pathology from San Jose State University. She completed her clinical fellowship training at the Long Beach VA. In the Chang Lab, Catherine collects behavioral data on language recovery following resective neurosurgery. In addition to assessing research participants’ speech and language skills after surgery, she assists in conducting intraoperative research tasks. Catherine is passionate about applying research findings to improve clinical assessment and treatment of aphasia.

Vanessa Anderson

Vanessa is a Clinical Research Coordinator for the BRAVO project and Neurona clinical trial. She received her B.A. in Molecular and Cell Biology from the University of California, Berkeley in 2023. Under the guidance of Drs. Nina Dronkers and Maria Ivanova at UC Berkeley’s Aphasia Recovery Lab, Vanessa completed an honors thesis evaluating the effects of a novel exercise intervention designed to enhance recovery for stroke survivors and people with aphasia. She is passionate about improving outcomes and quality of life for people with speech and language disorders. In addition to her research pursuits, Vanessa is dedicated to making healthcare and health information more accessible.

Cady Kurtz-Miott

Cady Kurtz-Miott is a clinical research coordinator for the BRAVO clinical trial and the EXPY study with Brigham & Women’s Hospital. She received her B.A. in Biology from Lewis & Clark College in 2022. Previously, Cady worked as a research assistant under Dr. Michael Brainard at the UCSF Center for Integrative Neuroscience using electrical stimulation and other neurophysiology techniques to study sensory motor learning. She is passionate about improving medical technology and access to healthcare.

Quinn Greicius

Quinn is a Clinical Research Coordinator responsible for conducting intraoperative Neuropixels recordings and developing the related hardware, software, and analysis platforms. He graduated from Stanford University in 2021 with a B.S. in Mathematics.

Aria Lin

Aria Lin is a Clinical Research Coordinator for the emotion work in Chang Lab examining the neural mechanisms of human emotion. Aria received her B.S. in Bioengineering from the University of California, Berkeley in 2021. She previously worked in industry on the automation of a CRISPR-based, genetic engineering workflow. Aria is interested in understanding how emotion is represented in the brain and the implications that has for the diagnosis and treatment of psychiatric diseases.

Margaret Seaton

Margaret Seaton is a Clinical Research Coordinator working primarily with the BRAVO team, while also assisting with several other projects. Margaret received her B.A. in Human Biology from Stanford University in 2019 with a concentration in Public Health. During her time at Stanford, Margaret was as an undergraduate TA in the human biology department. She also worked as a research assistant at UCSD examining the effect of an exercise intervention on cognition in older adults. Since graduation, Margaret has completed a post-baccalaureate program in pre-health studies and returned to Stanford to work as a Medical Scribe. Margaret is interested in furthering the effort to understand and manage neurodegenerative diseases.