Curriculum Vitae Download PDF

Jeremy R. Manning, Ph.D.

Director, Contextual Dynamics Laboratory

Department of Psychological and Brain Sciences

Dartmouth College

HB 6207, Moore Hall

Hanover, NH 03755

U.S.A.

Email: jeremy.r.manning@dartmouth.edu

Phone: 603.646.2777

URL: http://www.context-lab.com

Employment

Associate Professor, Dartmouth College, Hanover, NH (2024 – )

Department of Psychological and Brain Sciences

Additional affiliation: Cognitive Science

Tenured: 2024

Assistant Professor, Dartmouth College, Hanover, NH (2015 – 2024)

Department of Psychological and Brain Sciences

Additional affiliation: Cognitive Science

Reappointed: 2018

Postdoctoral Research Associate, Princeton University, Princeton, NJ (2011 – 2015)

Princeton Neuroscience Institute and Department of Computer Science

Advisors: Kenneth Norman, Ph.D. and David Blei, Ph.D.

Education

Ph.D. in Neuroscience, University of Pennsylvania, Philadelphia, PA (2011)

Advisor: Michael Kahana, Ph.D.

Dissertation: Acquisition, storage, and retrieval in digital and biological brains

B.S. in Neuroscience (High honors, Magna cum laude), Brandeis University, Waltham, MA (2006)

Advisor: Robert Sekuler, Ph.D.

Dissertation: Modeling human spatial navigation using a degraded ideal navigator

B.S. in Computer Science (Magna cum laude), Brandeis University, Waltham, MA (2006)

Grants, honors, and awards (selected)

  1. NSF Grant (2026): AI generated interpretive labels for exhibits to support engagement and learning in science museums
    Award amount: $900,000; Role: PI (with Joyce Ma, Co-PI)
  2. Scholarly Innovation and Advancement Award (2026): Targeted Dream Incubation for Mental Health
    Award amount: $50,000; Role: PI
  3. Linda B. and Kendrick R. Wilson III 1969 Fellowship (2024–2025)
  4. John M. Manley Huntington Award for Newly Tenured Faculty (2024)
    Awarded to recently tenured Dartmouth faculty members who have an outstanding record of teaching and research
  5. CompX Faculty Grant (2024): Developing the next generation of multi-scale large language models
    Award amount: $15,000; Role: PI
  6. NSF CAREER Award (2022): Mapping and enhancing the acquisition of conceptual knowledge using behavior, neural signals, and natural language processing models
    Award amount: $881,612; Role: PI
  7. Elected member, Memory Disorders Research Society (2021)
  8. NIMH Grant (2021): Serotonin modulation of the development of neural circuits underlying reward processing and impulsivity in adolescents
    Award amount: $568,974; Role: Co-I (PI: Katherine Nautiyal)
  9. NIH Grant Supplement (2019): Dissecting serotonergic and dopaminergic contributions to the neural circuits underlying impulsive behavior
    Award amount: $93,190; Role: Co-I (PI: Katherine Nautiyal)
  10. National Institute on Drug Abuse Center for Technology and Behavioral Health Pilot Grant (2019): Linking mental health and exercise via remote sensing
    Award amount: $20,000; Role: Co-PI (PI: David Bucci; Co-PI: Lorie Loeb)
  11. Dartmouth Junior Faculty Fellowship (2018)
  12. Walter and Constance Burke Research Initiation Award (2018)
    Award amount: $25,000; Role: PI
  13. DARPA Grant: Memory Enhancement with Modeling (MEM; 2018)
    Award amount: $55,558; Role: PI (sub-award of DARPA RAM N66001-14-2-4-032)
  14. i-CORPS Pilot Grant: Developing a mobile device for estimating dynamic attention states (2018).
    Award amount: $3,000; Role: Co-PI (PI: Peter Tse)
  15. Diamond Research Development Award (2017): Improving memory and context reinstatement at perceptual event boundaries
    Award amount: $199,997; Role: Co-PI (PI: Barbara Jobst)
  16. Dartmouth Leslie Center for the Humanities award for developing a course incorporating the theme of "revolution" (2017; for Storytelling with Data; PSYC 81.06).
    Award amount: $5,000; Role: Course Instructor
  17. Social Impact Practicum (2017; for Storytelling with Data; PSYC 81.06)
    Award amount: $2,000; Role: Course Instructor
  18. Young Minds and Brains (2017): The impact of exercise on attention, memory, and stress
    Award amount: $100,000; Role: PI (with David Bucci, Co-PI)
  19. NSF EPSCoR Grant (2016): The neural basis of attention
    Award amount: $6,000,000; Role: Co-I (PI: Peter Tse)
  20. NIMH Ruth L. Kirshstein National Research Service Award for an Individual Predoctoral Fellowship (2010): The neural representation of context and its role in free recall
    Award amount: $57,762; Role: PI
  21. NIH Computational Neuroscience Training Grant (2008)
    Role: Trainee
  22. NIH Systems and Integrative Biology Training Grant (2006)
    Role: Trainee

Publications

Undergraduate trainees are denoted by underlined text, graduate trainees are indicated by italicized text, and postdoctoral trainees are indicated by underlined and italicized text.

  1. Fitzpatrick PC, Tahir A, Xu J, Park SH, Manning JR (2026) Delayed recountings preserve but simplify the semantic geometry of earlier recountings. PsyArXiv: mhxtd.
  2. Siu C, Pirzada ST, Glick CC, Betzel R, Petri G, Manning JR, Williams L, Saggar M (2026) Global topology of brain-wide co-fluctuations links task states, personality, and behavioral symptom dimensions. Communications Biology: In press.
  3. Fitzpatrick PC, Heusser AC, Manning JR (2026) Text embedding models yield detailed conceptual knowledge maps derived from short multiple-choice quizzes. Nature Communications, 17: 2055.
  4. Stropkay HF, Chen J, Latifi MJ, Rockmore DN, Manning JR (2025) A stylometric application of large language models. arXiv: 2510.21958.
  5. Manning JR (2025) Why we're so preoccupied by the past. Scientific American: Online.
  6. Owen LLW, Manning JR (2024) High-level cognition is supported by information-rich but compressible brain activity patterns. Proceedings of the National Academy of Sciences, USA, 121(35): e2400082121.
  7. Xu X, Zhu Z, Zheng X, Manning JR (2024) Temporal asymmetries in inferring unobserved past and future events. Nature Communications, 15: 8502.
  8. Fitzpatrick PC, Manning JR (2024) Davos: a Python package "smuggler" for constructing lightweight reproducible notebooks. SoftwareX, 25: 101614.
  9. Manning JR (2024) Context reinstatement. In Kahana MJ and Wagner AD, Ed. The Oxford Handbook of Human Memory. New York, NY: Oxford University Press. Chapter 38.
  10. Jolly E, Sadhukha S, Iqbal M, Molani Z, Walsh T, Manning JR, Chang LJ (2023) People are represented and remembered through their relationships with others. PsyArXiv: bw9r2.
  11. Ziman K, Lee MR, Martinez AR, Adner ED, Manning JR (2023) Category-based and location-based volitional covert attention are mediated by different mechanisms and affect memory at different timescales. PsyArXiv: 2ps6e.
  12. Manning JR, Whitaker EC, Fitzpatrick PC, Lee MR, Frantz AM, Bollinger BJ, Romanova D, Field CE, Heusser AC (2023) Feature and order manipulations in a free recall task affect memory for current and future lists. PsyArXiv: erzfp.
  13. Manning JR (2023) How can I identify stimulus-driven neural activity patterns in multi-patient ECoG data? In Axmacher N, Ed. Intracranial EEG: A Guide for Cognitive Neuroscientists. Cham, Switzerland: Springer. Chapter 48.
  14. Manning JR, Notaro GM, Chen E, Fitzpatrick PC (2022) Fitness tracking reveals task-specific associations between memory, mental health, and physical activity. Scientific Reports, 12: 13822.
  15. Kumar M, Anderson MJ, Antony JW, Baldassano C, Brooks PP, Cai MB, Chen P-HC, Ellis CT, Henselman-Petrusek G, Huberdeau D, Hutchinson JB, Li YP, Lu Q, Manning JR, Mennen AC, Nastase SA, Richard H, Schapiro AC, Schuck NW, Shvartsman M, Sundaram N, Suo D, Turek JS, Turner D, Vo VA, Wallace G, Wang Y, Williams JA, Zhang H, Zhu X, Capotă M, Cohen JD, Hasson U, Li K, Ramadge PJ, Turk-Browne NB, Willke TL, Norman KA (2022) BrainIAK: The Brain Imaging Analysis Kit. Aperture, 1(4): 1–19.
  16. Owen LLW, Chang TH, Manning JR (2021) High-level cognition during story listening is reflected in high-order dynamic correlations in neural activity patterns. Nature Communications, 12: 5728.
  17. Scangos KW, Khambhati AN, Daly PM, Owen LLW, Manning JR, Ambrose JB, Austin E, Dawes HE, Krystal AD, Chang EF (2021) Distributed subnetworks of depression defined by direct intracranial neurophysiology. Frontiers in Human Neuroscience, 15: 746499.
  18. Chen HT, Manning JR, van der Meer MAA (2021) Between-subject prediction reveals a shared representational geometry in the rodent hippocampus. Current Biology, 31(19): 4293–4304.e5.
  19. Manning JR (2021) Episodic memory: mental time travel or a quantum 'memory wave' function? Psychological Review, 128(4): 711–725.
  20. Xie T, Cheong JH, Manning JR, Brandt AM, Aronson JP, Jobst BC, Bujarski KA, Chang LJ (2021) Minimal functional alignment of ventromedial prefrontal cortex intracranial EEG signals during naturalistic viewing. bioRxiv: 2021.05.10.443308.
  21. Chang LJ, Jolly E, Cheong JH, Rapuano KM, Greenstein N, Chen PHA, Manning JR (2021) Endogenous variation in ventromedial prefrontal cortex state dynamics during naturalistic viewing reflects affective experience. Science Advances, 7(17): eabf7129.
  22. Ziman K, Manning JR (2021) Unexpected false feelings of familiarity about faces are associated with increased pupil dilations. bioRxiv: 2021.02.22.432360.
  23. Heusser AC, Fitzpatrick PC, Manning JR (2021) Geometric models reveal behavioural and neural signatures of transforming experiences into memories. Nature Human Behaviour, 5(7): 905–919.
  24. Owen LLW, Muntianu TA, Heusser AC, Daly PM, Scangos KW, Manning JR (2020) A Gaussian process model of human electrocorticographic data. Cerebral Cortex, 30(10): 5333–5345.
  25. Chang L, Manning JR, Baldassano C, de la Vega A, Fleetwood G, Geerligs L, Haxby J, Lahnakoski J, Parkinson C, Shappell H, Shim WM, Wager T, Yarkoni T, Yeshurun Y, Finn E (2020) Naturalistic data analysis. Zenodo: 10.5281/zenodo.3937849.
  26. Heusser AC, Ziman K, Owen LLW, Manning JR (2018) HyperTools: A Python toolbox for gaining geometric insights into high-dimensional data. Journal of Machine Learning Research, 18(152): 1–6.
  27. Heusser AC, Manning JR (2018) Capturing the geometric structure of episodic memories for naturalistic experiences. Conference on Cognitive Computational Neuroscience: PS-2B.16.
  28. Ziman K, Heusser AC, Fitzpatrick PC, Field CE, Manning JR (2018) Is automatic speech-to-text transcription ready for use in psychological experiments? Behavior Research Methods, 50(6): 2597–2605.
  29. Manning JR, Zhu X, Willke TL, Ranganath R, Stachenfeld K, Hasson U, Blei DM, Norman KA (2018) A probabilistic approach to discovering dynamic full-brain functional connectivity patterns. NeuroImage, 180: 243–252.
  30. Heusser AC, Fitzpatrick PC, Field CE, Ziman K, Manning JR (2017) Quail: A Python toolbox for analyzing and plotting free recall data. The Journal of Open Source Software, 2(18): 424.
  31. Anderson MJ, Capota M, Turek JS, Zhu X, Willke TL, Wang Y, Chen P-H, Manning JR, Ramadge PJ, Norman KA (2016) Enabling factor analysis on thousand-subject neuroimaging datasets. IEEE International Conference on Big Data (Big Data): 1151–1160.
  32. Manning JR, Hulbert JC, Williams J, Piloto L, Sahakyan L, Norman KA (2016) A neural signature of contextually mediated intentional forgetting. Psychonomic Bulletin and Review, 23(5): 1534–1542.
  33. Benson NC, Manning JR, Brainard DH (2014) Unsupervised learning of cone spectral classes from natural images. PLoS Computational Biology, 10(6): e1003652.
  34. Manning JR, Ranganath R, Keung W, Turk-Browne NB, Cohen JD, Norman KA, Blei DM (2014) Hierarchical Topographic Factor Analysis. IEEE International Workshop on Pattern Recognition in Neuroimaging: 1–4.
  35. Manning JR, Ranganath R, Norman KA, Blei DM (2014) Topographic Factor Analysis: a Bayesian model for inferring brain networks from neural data. PLoS One, 9(5): e94914.
  36. Manning JR, Lew TF, Li N, Sekuler R, Kahana MJ (2014) MAGELLAN: a cognitive map-based model of human wayfinding. Journal of Experimental Psychology: General, 143(3): 1314–1330.
  37. Manning JR, Kahana MJ, Norman KA (2014) The role of context in episodic memory. In Gazzaniga MS and Mangun GR, Ed. The Cognitive Neurosciences, Fifth Edition. Cambridge, MA: MIT Press. Chapter 47.
  38. Manning JR, Gershman SJ, Norman KA, Blei DM (2012) Factor topographic latent source analysis: factor analysis for brain images. Proceedings of the NIPS Workshop on Machine Learning and Interpretation in Neuroimaging, 2: Online.
  39. Manning JR, Sperling MR, Sharan A, Rosenberg EA, Kahana MJ (2012) Spontaneously reactivated patterns in frontal and temporal lobe predict semantic clustering during memory search. The Journal of Neuroscience, 32(26): 8871–8878.
  40. Manning JR, Kahana MJ (2012) Interpreting semantic clustering effects in free recall. Memory, 20(5): 511–517.
  41. Manning JR, Polyn SM, Baltuch G, Litt B, Kahana MJ (2011) Oscillatory patterns in temporal lobe reveal context reinstatement during memory search. Proceedings of the National Academy of Sciences of the United States of America, 108(31): 12893–12897.
  42. Jacobs J, Manning JR, Kahana MJ (2010) Response to Miller: "Broadband" vs. "high gamma" electrocorticographic signals. The Journal of Neuroscience, 30: Online.
  43. Manning JR, Jacobs J, Fried I, Kahana MJ (2009) Broadband shifts in local field potential power spectra are correlated with single-neuron spiking in humans. The Journal of Neuroscience, 29(43): 13613–13620.
  44. Manning JR, Brainard DH (2009) Optimal design of photoreceptor mosaics: why we do not see color at night. Visual Neuroscience, 26(1): 5–19.

Invited talks (selected)

  1. Generative Episodic Memory: Constructing Scenarios of the Past (Keynote Speaker, 2025)
  2. Brandeis University (2025)
  3. University of Virginia (2024)
  4. University of Pennsylvania (2023)
  5. Cornell University (2023)
  6. Boston University (2023)
  7. Harvard University (2022)
  8. University of California, Irvine (2022)
  9. Ruhr Universität Bochum (2022)
  10. Microsoft Research (2022)
  11. Carnegie Mellon University (2021)
  12. National Institutes of Mental Health (2021)
  13. Boston College (2020)
  14. Facebook Reality Labs (2020)
  15. University of California, Berkeley (2020)
  16. University of Oregon (2020)
  17. Context and Episodic Memory Symposium (2019)
  18. Society for Affective Science (2019)
  19. Uber (2019)
  20. Northeastern University (2018)
  21. Society for Neuroscience (2018)
  22. University of Pennsylvania (2018)
  23. Bard College (2017)
  24. Harvard University (2017)
  25. University of Texas at Austin (2017)
  26. Society for Neuroscience (2016)
  27. Brown University (2015)
  28. Columbia University (2015)
  29. Dartmouth College (2015)
  30. Georgetown University (2015)
  31. Johns Hopkins University (2015)
  32. Context and Episodic Memory Symposium (2014)
  33. Manhattan Area Memory Meeting (2014)
  34. Pattern Recognition in Neuroimaging (2014)
  35. Context and Episodic Memory Symposium (2013)
  36. University of Massachusetts, Amherst (2013)
  37. Dartmouth College (2013)
  38. Charles River Analytics (2012)
  39. Natick Soldier Systems Center (2012)
  40. Princeton University (2011)
  41. Society for Mathematical Psychology (2011)
  42. University of Pennsylvania (2011)

Software

  1. Manning JR (2026) CDL Slides: our lab's software package for creating themed slides and posters. GitHub.
  2. Manning JR (2026) Claude History Surfer: easily navigate your Claude Code prompt history. GitHub.
  3. Manning JR (2026) Claude Skill Compounder: a Claude Code hook that continually asks Claude to spin off insights and discoveries into new skills. GitHub.
  4. Manning JR (2026) Thunderbird Snooze: Thunderbird plugin that adds a "snooze message" feature similar to Gmail. GitHub.
  5. Manning JR (2026) Dream Stream: Android and web-based application for delivering sleep-stage triggered cues to guide lucid dreaming. GitHub. Demo.
  6. Manning JR (2026) Knowledge Mapper: map out an approximation of everything you know by answering multiple-choice quiz questions. GitHub. Demo.
  7. Manning JR (2026) Scheduler: a self-hosted appointment scheduling system like YouCanBook.me or Calendly, but free, open-source, and fully under your control. GitHub. Docs.
  8. Manning JR (2026) LLM Geometry Visualizer: understand LLMs using geometric approaches and visualizations. GitHub. Demo.
  9. Manning JR (2026) Fourier Control Theory: an interactive demo showing that a robot arm whose joints spin at constant rates is a Fourier series, and vice versa. GitHub. Demo.
  10. Manning JR (2026) Sky Viewer: enter a date, location, direction, and time of day, and get back an animated visualization of the stars. GitHub. Demo.
  11. Manning JR (2026) Dino Trivia: a two-player dinosaur trivia game. GitHub. Demo.
  12. Manning JR (2026) Claude Context Bar: a Claude Code mod that draws the context window as a stacked bar under the prompt. GitHub.
  13. Manning JR (2026) Markdown Buddy: MacOS Finder Quick View plugin for displaying markdown and other text-based files with syntax highlighting and high-quality rendering. GitHub.
  14. Manning JR (2026) Android Scholar: Android Google Scholar application. GitHub.
  15. Manning JR (2025) Knowledge Map Renderer: construct Blender-based renders of knowledge maps. GitHub.
  16. Manning JR (2025) Clustrix: Clustrix is a Python package that enables seamless distributed computing on clusters. With a simple decorator, you can execute any Python function remotely on cluster resources while automatically handling dependency management, environment setup, and result collection. GitHub.
  17. Manning JR (2025) llmXive: an LLM-driven system for automating scientific discovery. GitHub. Demo.
  18. Manning JR (2025) LLM Demos: a collection of interactive language model demonstrations. GitHub. Demo.
  19. Manning JR, Manjunatha H, Kording K (2023) Chatify: add an LLM-based "teaching assistant" to Jupyter notebooks. GitHub.
  20. Fitzpatrick PC, Manning JR (2022) Davos: manage project dependencies for notebook-based projects. GitHub.
  21. Manning JR (2021) DataWrangler: format and clean data, with a special focus on applying natural language processing models to text data. GitHub.
  22. Manning JR (2021) Abstract2Paper: auto-generate an entire paper from a prompt or abstract. GitHub.
  23. Owen LLW, Chang TH, Manning JR (2019) Timecorr Toolbox: estimate dynamic high-order correlations in multivariate timeseries data. GitHub.
  24. Owen LLW, Heusser AC, Manning JR (2018) SuperEEG Toolbox: infer full-brain activity patterns from a small(ish) number of ECoG electrodes using Gaussian process regression. GitHub.
  25. Heusser AC, Fitzpatrick PC, Field CE, Ziman K, Manning JR (2017) Quail: analyze and visualize free recall data. GitHub.
  26. Heusser AC, Ziman K, Owen LLW, Manning JR (2017) HyperTools: visualize and manipulate high-dimensional data. (Way better than the MATLAB version!) GitHub.
  27. Capota M, Turek J, Chen P-HC, Zhu X, Manning JR, Sundaram N, Keller B, Wang Y, Shin YS (2017) BrainIAK Toolbox: collaboration with the Princeton Neuroscience Institute and Intel Labs to implement a bunch of useful brain analysis tools, including Hierarchical Topographic Factor Analysis. GitHub.
  28. Heusser AC, Ziman K, Fitzpatrick PC, Field CE, Manning JR (2017) autoFR: a verbal free recall experiment that incorporates automatic speech-to-text processing, ready-to-run on Amazon Mechanical Turk. GitHub.
  29. Manning JR (2016) CDL-bibliography: the bibliography management system used by the Contextual Dynamics Lab. GitHub.
  30. Manning JR (2016) Hyperplot Tools: plot and manipulate high-dimensional data. MATLAB Central File Exchange: 56623.
  31. Manning JR (2014) Hierarchical Topographic Factor Analysis: efficiently identify functional brain networks in fMRI data. Download.
  32. Manning JR (2013) MATLAB Ipsum: generate filler text using MATLAB. MATLAB Central File Exchange: 43428.
  33. Manning JR (2013) Easy resample: simple interface for interpolating or resampling a 1D signal. MATLAB Central File Exchange: 43320.
  34. Manning JR (2012) Chuck Close-ify: automatically create artwork in Chuck Close's iconic style based on existing photographs. MATLAB Central File Exchange: 38770.
  35. Manning JR (2012) Plot fMRI images: quick and easy method for generating 2D and 3D brain plots. GitHub. MATLAB Central File Exchange: 36139.
  36. Manning JR (2012) Generate synthetic fMRI data: Generate synthetic data for testing fMRI analyses and models. MATLAB Central File Exchange: 36125.
  37. Manning JR (2012) Sane pColor: create 2D images that don't look blurry in OS X's Preview PDF viewer. MATLAB Central File Exchange: 35601.
  38. Manning JR (2012) Attach: MATLAB implementation of the attach function in R. MATLAB Central File Exchange: 35436.
  39. Manning JR (2012) Get tight subplot handles: allows user to exert finer control over subplot spacing in MATLAB. MATLAB Central File Exchange: 35435.
  40. Manning JR (2012) Slices: efficiently slice a tensor along the nth dimension. MATLAB Central File Exchange: 35439.

Teaching and instruction

Open courses (selected)

  1. Laboratory in Psychological Science; doi.org/10.5281/zenodo.6596761
  2. Human Memory; doi.org/10.5271/zenodo.5182787
  3. Introduction to Programming for Psychological Scientists; doi.org/10.5281/zenodo.5136795
  4. Storytelling with Data; doi.org/10.5281/zenodo.5182774
  5. Methods in Neuroscience at Dartmouth Computational Summer School
  6. Computational Neuroscience; doi.org/10.5281/zenodo.10235877

Mentorship (selected)

Senior thesis students are denoted by asterisks (*)

Postdoctoral Advisees

  1. Hung-Tu Chen (2024 – 2025; current position: Meta)
  2. Gina Notaro (2017 – 2018; current position: HRL Laboratories)
  3. Andrew Heusser (2016 – 2018; current position: PyMC Labs)

Graduate Advisees

  1. Claudia Gonciulea (Doctoral student; 2025 – )
  2. Mark Taylor (Masters student, Quantitative Biomedical Sciences; 2021)
  3. Paxton Fitzpatrick (Doctoral student; 2021 – )
  4. Xinming Xu (Doctoral student; 2021 – )
  5. Caroline Lee (Doctoral student; 2019 – 2021)
  6. Deepanshi Shokeen (Masters student, Quantitative Biomedical Sciences; 2018 – 2020)
  7. Max Bluestone (Masters student, Quantitative Biomedical Sciences; 2018 – 2020)
  8. Kirsten Ziman (Doctoral student; 2017 – 2022; current position: Postdoctoral researcher at Princeton University)
  9. Hanli Li (Masters student, Computer Science; co-advised with Qiang Liu; 2016)
  10. Lucy Owen (Doctoral student; 2016 – 2021; current position: Assistant Professor at University of Montana)
  11. Tom Hao Chang (Masters student, Computer Science; co-advised with Qiang Liu; 2016 – 2017; current position: Robinhood)

Thesis Committees

  1. Anthony Dunn (Advisor: David Kraemer)
  2. Benjamin Graul (Advisor: Tor Wager)
  3. Yeongji Lee (Advisor: David Kraemer)
  4. Arati Sharma (Advisor: Kate Nautiyal; Graduated 2026)
  5. Clara Sava-Segal (Advisor: Emily Finn; Graduated 2026)
  6. Jane Han (Advisor: James Haxby; Graduated 2026)
  7. Lindsey Tepfer (Advisor: Mark Thornton; Graduated 2026)
  8. Yong Hoon Chung (Advisor: Viola Störmer; Graduated 2026)
  9. Manish Mohapatra (Advisor: Matthijs van der Meer; Graduated 2025)
  10. Megan Hillis (Advisor: David Kraemer; Graduated 2025)
  11. Omri Raccah (Advisor: David Poeppel; Graduated 2024)
  12. Courtney Jimenez (Advisor: Meghan Meyer; Graduated 2024)
  13. Hung-Tu Chen (Advisor: Matthijs van der Meer; Graduated 2024)
  14. Dhaval Bhatt (Advisor: Meghan Meyer; Graduated 2023)
  15. Tiankang Xie (Advisor: Luke Chang; Graduated 2023)
  16. Vassiki Chauhan (Advisors: Ida Gobbini and James Haxby; Graduated 2021)
  17. Emily Irvine (Advisor: Matthijs van der Meer; Graduated 2020)
  18. Eli Bowen (Advisor: Richard Granger; Graduated 2020)
  19. Eshin Jolly (Advisor: Luke Chang; Graduated 2020)
  20. Stephen Meisenhelter (Advisor: Barbara Jobst; Graduated 2020)
  21. Feilong Ma (Advisor: James Haxby; Graduated 2019)
  22. Kevin Hartstein (Advisor: Peter Tse; Graduated 2019)
  23. Beau Sievers (Advisor: Thalia Wheatley; Graduated 2018)
  24. Kristina Rapuano (Advisor: Luke Chang; Graduated 2018)
  25. Luke Eglington (Advisor: Sean Kang; Graduated 2018)
  26. Gina Notaro (Advisor: Solomon Diamond; Graduated 2017)

Specialist Committees

  1. Yuxin (Lily) Tong (Advisor: Matthijs van der Meer)
  2. Anthony Dunn (Advisor: David Kraemer)
  3. Yuqi Zhang (Advisors: Richard Granger and James Haxby)
  4. Covert Geary (Advisor: John Murray)
  5. Menghan Yang (Advisor: Luke Chang)
  6. Deepasri Prasad (Advisor: Caroline Robertson)
  7. Zizhuang Miao (Advisor: Tor Wager)
  8. Benjamin Graul (Advisor: Tor Wager)
  9. Yeongji Lee (Advisor: David Kraemer)
  10. Thomas Botch (Advisors: Emily Finn and Caroline Robertson)
  11. Alexis Kidder (Advisor: Brad Duchaine)
  12. Dhaval Bhatt (Advisor: Meghan Meyer)
  13. Courtney Jimenez (Advisor: Meghan Meyer)
  14. Clara Sava-Segal (Advisor: Emily Finn)
  15. Wasita Mahaphanit (Advisor: Luke Chang)
  16. Jane Han (Advisor: James Haxby)
  17. Megan Hillis (Advisor: Caroline Robertson)
  18. Anna Mynick (Advisor: Caroline Robertson)
  19. Marissa Clark (Advisor: Luke Chang)
  20. Robert Quon (Advisor: Barbara Jobst)
  21. Mira Nencheva (Advisor: Casey Lew-Williams)
  22. Marvin Maechler (Advisor: Peter Tse)
  23. Eli Bowen (Advisor: Richard Granger)
  24. Emma Templeton (Advisor: Thalia Wheatley)
  25. Feilong Ma (Advisor: James Haxby)
  26. Youki Tanaka (Advisor: Matthijs van der Meer)

Undergraduate Advisees

  1. Abe Lobsenz (2026 – )
  2. Andy Kim (2026)
  3. Carson Kochansky (2026 – )
  4. Dylan Unruh (2026 – )
  5. Katherina Cohen (2026 – )
  6. Maggie Cabot (2026 – )
  7. Mak Kelly (2026 – )
  8. Malique Auguste (2026 – )
  9. Martin Palencia-Gomez (2026 – )
  10. Miles McDonald (2026 – )
  11. Neui Wadwalai (2026 – )
  12. Pattapol "Phoom" Sirimangklanurak (2026 – )
  13. Sadie Jackson (2026 – )
  14. Sreshth Tiwari (2026 – )
  15. Xzana Duranovich (2026 – )
  16. Ahmad Wahab (2025 – 2026)
  17. Aidan Miller (2025 – 2026)
  18. Alexandra Wingo (2025 – )
  19. Alishba Tahir (2025 – )
  20. Andrew Richardson (2025 – 2026)
  21. Angelyn Liu (2025 – )
  22. Annabelle Morrow (2025 – 2026)
  23. Azaire Andre (2025 – )
  24. Ben Hanson (2025 – 2026)
  25. Colson Duncan (2025 – )
  26. Ellie Mattox (2025 – 2026)
  27. Emmy Thornton (2025)
  28. Evan McDermid (2025 – 2026)
  29. Isaac Cheon (2025 – )
  30. Jackson C. Sandrich (2025 – 2026)
  31. Jason Kang (2025 – )
  32. Jaysen Quan (2025)
  33. Joy Maina (2025)
  34. Keene Dampal (2025)
  35. Kevin Chang (2025 – 2026)
  36. Luca Gandrud (2025 – 2026)
  37. Owen Phillips (2025 – 2026)
  38. Rodrigo Vega Ayllon (2025)
  39. Sam Haskel* (2025 – 2026)
  40. Theo Larson (2025 – )
  41. Will Lehman (2025 – )
  42. Abigayle McCusker (2024)
  43. Andrew Cao (2024)
  44. Ansh Motiani (2024)
  45. Can Kam (2024)
  46. Chelsea Joe (2024 – 2026)
  47. Chloe Terestchenko (2024)
  48. Everett Tai (2024)
  49. Harrison Stropkay* (2024 – 2025)
  50. Jacob Bacus (2024 – 2026)
  51. Kaitlyn Peng* (2024)
  52. Manraaj Singh (2024)
  53. Matthew Givens (2024 – 2025)
  54. Miel Wewerka (2024)
  55. Rohan Goyal (2024)
  56. Torsha Chakraverty (2024)
  57. Aaryan Agrawal (2023 – 2024)
  58. Ameer Talha Yasser (2023)
  59. Andrew Shi (2023)
  60. Ash Chinta (2023)
  61. Charles Baker (2023)
  62. DJ Matusz (2023 – 2024)
  63. Elias Emery (2023)
  64. Emma Reeder (2023 – 2024)
  65. Francisca Fadairo (2023)
  66. Grace Wang (2023)
  67. Grady Redding (2023 – 2024)
  68. Jake McDermid (2023 – 2025)
  69. Jennifer Xu (2023 – 2026)
  70. Maura Hough (2023 – 2024)
  71. Megan Liu (2023 – 2024)
  72. Michael Chen (2023 – 2024)
  73. Mira Chiruvolu (2023 – 2024)
  74. Om Shah (2023 – 2026)
  75. Raselas Dessalegn (2023)
  76. Safwan Rashid (2023)
  77. Sarah Parigela (2023 – 2026)
  78. Sergio Campos Legonia (2023)
  79. Xueyao Zheng (2023)
  80. Yue Zhuo (2023)
  81. Yvonne Chen (2023)
  82. Alexander Marcoux (2022)
  83. Benjamin Lehrburger (2022)
  84. Dawson Haddox (2022)
  85. Goutham Veeramachaneni (2022)
  86. Jessna Brar (2022)
  87. Kevin Cao (2022)
  88. Molly McQuoid (2022)
  89. Samuel Crombie (2022)
  90. Wenhua Liang (2022)
  91. Zachary Somma (2022)
  92. Ziyan Zhu (2022 – 2023)
  93. Aidan Adams (2021)
  94. Anna Mikhailova (2021 – 2022)
  95. Ansh Patel (2021 – 2024)
  96. Brian Chiang (2021 – 2022)
  97. Damini Kohli (2021)
  98. Daniel Carstensen* (2021 – 2024)
  99. Daniel Ha (2021)
  100. Natalie Schreder (2021 – 2023)
  101. Swestha Jain (2021 – 2022)
  102. Thomas Corrado (2021 – 2022)
  103. William McCall (2021 – 2023)
  104. Austin Zhang (2020)
  105. Chelsea Uddenberg (2020 – 2021)
  106. Chetan Palvuluri (2020)
  107. Chris Jun (2020 – 2022)
  108. Chris Long (2020 – 2021)
  109. Chris Suh (2020 – 2021)
  110. Darren Gu (2020 – 2021)
  111. Esme Chen (2020 – 2021)
  112. Ethan Adner (2020 – 2022)
  113. Greg Han (2020 – 2021)
  114. Helen Liu (2020)
  115. Kelly Rutherford (2020)
  116. Kunal Jha* (2020 – 2024)
  117. Luca Lit (2020)
  118. Tehut Biru* (2020 – 2021)
  119. Tyler Chen (2020 – 2022)
  120. Vivian Tran (2020)
  121. Aaron Lee (2019 – 2020)
  122. Anne George (2019 – 2020)
  123. Sarah Park (2019 – 2020)
  124. Shane Hewitt (2019 – 2020)
  125. Soo Hwan Park (2019 – 2021)
  126. Tudor Muntianu (2019 – 2021)
  127. William Chen (2019 – 2020)
  128. Alejandro Martinez (2018 – 2020)
  129. Ann Carpenter (2018)
  130. Darya Romanova (2018)
  131. Iain Sheerin (2018)
  132. Kirsten Soh (2018)
  133. Mustafa Nasir-Moin (2018)
  134. Rachael Chacko (2018)
  135. Seung Ju Lee (2018)
  136. William Baxley (2018 – 2021)
  137. Armando Ortiz (2017)
  138. Bryan Bollinger (2017 – 2018)
  139. Christina Lu (2017)
  140. Emily Whitaker (2017 – 2018)
  141. Paxton Fitzpatrick* (2017 – 2019)
  142. Stephen Satterthwaite (2017 – 2018)
  143. Aamuktha Porika (2016 – 2017)
  144. Allison Frantz (2016 – 2017)
  145. Aman Agarwal (2016)
  146. Campbell Field (2016 – 2018)
  147. Clara Silvanic (2016)
  148. Gal Perlman (2016)
  149. Jake Rost (2016)
  150. Jessica Tin (2016)
  151. Joseph Finkelstein (2016)
  152. Madeline Lee (2016 – 2020)
  153. Marisol Tracy (2016 – 2017)
  154. Peter Tran (2016)
  155. Sheherzad Mohydin (2016)
  156. Wei Liang Samuel Ching (2016 – 2017)

Service

Professional organizations

  1. Dartmouth-Kalaniyot (2024 – ) Co-founder, Board member
  2. National Science Foundation (2023, 2024, 2025) Panel member
  3. NeuroMatch Academy (2021 – ) Developer and project mentor (computational neuroscience and deep learning tracks)
  4. Artificial Intelligence and Statistics (AISTATS; 2021 – 2024) Area chair (natural language processing and machine learning)
  5. Methods in Neuroscience at Dartmouth (MIND) Summer School (2017 – ) Co-founder

Dartmouth committee memberships

  1. Graduate Committee (2026–, 2020–2021, 2016–2019)
  2. Undergraduate Committee (2025–2026, 2021–2022, 2015–2016)
  3. Social (Department Well-Being) Committee (2023–2024, 2024–2025)
  4. Cognitive Neuroscience Faculty Search Committee (2018)
  5. Molecular and Systems Biology Faculty Search Committee (2017)
  6. Cognitive Neuroscience Faculty Search Committee (2016)

Ad-hoc reviewer

Advances in Cognitive Psychology, Agence Nationale de la Recherche, American Journal of Psychology, Cell Reports, Cerebral Cortex, Cognition, Cognition and Emotion, Cortex, Computational and Systems Neuroscience (Cosyne), eLife, International Conference on Machine Learning (ICML), International Joint Conference on Artificial Intelligence, International Journal of Social Research Methodology, Israel Science Foundation, Journal of Cognitive Psychology, Journal of Mathematical Psychology, National Science Foundation (USA), Nature, Nature Communications, Nature Computational Science, Nature Human Behaviour, Neural Computation, NeuroImage, Neural Information Processing Systems (NeurIPS), Neuropsychologia, PLoS Biology, PLoS Computational Biology, Proceedings of the National Academy of Sciences, Psychological Reports, Psychological Review, Psychonomic Bulletin and Review, Science, Scientific Data, Scientific Reports, Society for Artificial Intelligence and Statistics (AISTATS), Swiss National Science Foundation, The Journal of Neuroscience