CV

Also available in a printable format here

Education

• Ph.D Boston University, Computational Neuroscience, May 2023
• M.S. University of Colorado Boulder, Cognitive Neuroscience, 2018
  • Thesis: “A Model of Relational Reasoning Through Selective Attention”. PDF
• B.S. Boston University, Biomedical Engineering, 2012

Work experience

• Postdoctoral Appointee, Neuromorphic Computing, Sandia National Labs, 2023 - Present
• Graduate Research Fellow, Boston University, 2018 - 2023
  • Biological Predictive Coding: Created a novel, biologically inspired, machine learning architecture and learning rule for temporal prediction. Functions above state-of-the-art for both short-term and long-term sequence generation, with applications for lifelong learning, and generalization
  • Egocentric-Allocentric Transformations: Designed an explainable ML model which receives self-centered sensor and motor information, fusing sensor information through recurrent hidden layers. Hidden layers create explicit reference-frame transformations, in addition to low-dimensional latent representations.
  • Symbolic Predictive Learning: Created a novel architecture which utilizes predictive coding and dynamic attentional routing to solve a symbolic reasoning task
• Neural Modeler, e-Cortex Inc \& University of Colorado, 2016 - 2018
  • Symbolic Reasoning: Extended existing computational models of working memory to create a model capable of simple symbolic processing, utilizing attentional mechanisms.
  • Electrophysiology: Designed and ran a corresponding EEG experiment to test model predictions. Created novel causal frequency-time analyses to determine timecourse of functional connectivity
• Research Software Engineer, Boston University Center for Memory and Brain, 2012 - 2016
  • Software Design: Primary contributor for centralized MATLAB-based OOP software for standardized data storage and exploratory analyses of neural and behavioral data across multiple labs.
  • Data Pipelines: Created standardized data pipelines for preprocessing various unstructured data and combining into a centralized SQL database, automated by cloud-computing tasks.
  • Research: Primary statistical analysis expert for over ten peer-reviewed publications in systems and computational neuroscience, including time-series analysis, frequentist statistics, generalized linear models, and data visualization.
• Neuroimaging Research Assistant, Boston Medical Center, 2009 - 2012
  • Alzheimer’s Disease: Primary individual for data pipelines and novel analysis of structural MRI and behavioral data, leading to predictive models of clinical Alzheimer’s Disease progression.

Skills

• Programming
  • Python, MATLAB, R, C++, SQL
• Data Analysis
  • Machine Learning, Time Series Analysis, Bayesian Statistics
• Neural Modeling
  • Dynamical Systems, Deep Learning, Electrophysiology

Publications

G.W. Chapman, M.E. Hasselmo. "Predictive Learning By A Burstdependent Learning Rule", Neurobiology of Learning and Memory, 2023. PDF
A.S. Alexander, J.C. Tung, G.W. Chapman, A.M. Conner, L.E. Shelley, M.E. Hasselmo, D.A. Nitz. "Adaptive Integration Of Selfmotion And Goals In Posterior Parietal Cortex", Cell Reports, 2022. PDF
L.C. Carstensen, A.S. Alexander, G.W. Chapman, A.J. Lee, M.E. Hasselmo. "Neural Responses In Retrosplenial Cortex Associated With Environmental Alterations", iScience, 2021. PDF
M.E. Hasselmo, A.S. Alexander, A. Hoyland, J.C. Robinson, M.J. Bezaire, G.W. Chapman, A. Saudargiene, L.C. Carstensen, H. Dannenberg. "The Unexplored Territory Of Neural Models Potential Guides For Exploring The Function Of Metabotropic Neuromodulation", Neuroscience, 2020. PDF
A.S. Alexander, J.C. Robinson, H. Dannenberg, N.R. Kinsky, S.J. Levy, W. Mau, G.W. Chapman, D.W. Sullivan, M.E. Hasselmo. "Neurophysiological Coding Of Space And Time In The Hippocampus Entorhinal Cortex And Retrosplenial Cortex", Brain and Neuroscience Advances, 2020. PDF
J.R. Hinman, G.W. Chapman, M.E. Hasselmo. "Neuronal Representation Of Environmental Boundaries In Egocentric Coordinates", Nature Communications, 2019. PDF
A.S. Alexander, L.C. Carstensen, J.R. Hinman, F. Raudies, G.W. Chapman, M.E. Hasselmo. "Egocentric Boundary Vector Tuning Of The Retrosplenial Cortex", Science Advances, 2019. PDF
C.K. Monaghan, G.W. Chapman, M.E. Hasselmo. "Systemic Administration Of Two Different Anxiolytic Drugs Decreases Local Field Potential Theta Frequency In The Medial Entorhinal Cortex Without Affecting Grid Cell Firing Fields", Neuroscience, 2017. PDF
J.R. Hinman, M.P. Brandon, J.R. Climer, G.W. Chapman, M.E. Hasselmo. "Multiple Running Speed Signals In Medial Entorhinal Cortex", Neuron, 2016. PDF
M. Ferrante, C.F. Shay, Y. Tsuno, G.W. Chapman, M.E. Hasselmo. "Postinhibitory Rebound Spikes In Rat Medial Entorhinal Layer Ii/Iii Principal Cells Invivo Invitro And Computational Modeling Characterization", Cerebral Cortex, 2016. PDF
F. Raudies, M.P. Brandon, G.W. Chapman, M.E. Hasselmo. "Head Direction Is Coded More Strongly Than Movement Direction In A Population Of Entorhinal Neurons", Brain Research, 2015. PDF
A.L. Jefferson, K.A. Gifford, S. Damon, G.W. Chapman, D. Liu, J. Sparling, V. Dobromyslin, D. Salat. "Gray White Matter Tissue Contrast Differentiates Mild Cognitive Impairment Converters From Nonconverters", Brain Imaging and Behavior, 2015. PDF
Y. Tsuno, G.W. Chapman, M.E. Hasselmo. "Rebound Spiking Properties Of Mouse Medial Entorhinal Cortex Neurons In Vivo", The European journal of neuroscience, 2015. PDF
C.F. Shay, M. Ferrante, G.W. Chapman, M.E. Hasselmo. "Rebound Spiking In Layer Ii Medial Entorhinal Cortex Stellate Cells Possible Mechanism Of Grid Cell Function", Neurobiology of Learning and Memory, 2015. PDF
K. Gifford, D. Liu, S.M. Damon, G.W. Chapman, R.R. Romano, L.R. Samuels, Z. Lu, A.L. Jefferson. "Subjective Memory Complaint Only Relates To Verbal Episodic Memory Performance In Mild Cognitive Impairment", Journal of Alzheimers Disease, 2015. PDF