Joseph G. Makin
Neuroscience · Purdue University West Lafayette
Publications
92
Citations
1,456
Est. group size
~2
Recurring co-author estimate
Active years
58
Publishing since 1969
Joseph G. Makin works on decoding brain activity into speech or text, using recordings from the brain's surface (ECoG) and cortex to help restore communication for people who cannot speak, such as those with paralysis. His work combines machine learning methods, including neural network models and self-supervised pretraining, with neuroscience data from both humans and macaque monkeys to study how populations of neurons encode movement and speech.
Publication output was low and steady for most of the last decade (about 1-3 per year), aside from a large 2018 spike likely due to a batch data release, with a modest recent uptick in 2023-2025.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Exponential-Family Harmoniums with Neural Sufficient Statistics
Proceedings of the AAAI Conference on Artificial Intelligence · 2025
- Pretraining with Masked Autoencoding Improves Speech Decoding from ECoG
2025
- Improving Speech Decoding from ECoG with Self-Supervised Pretraining
arXiv (Cornell University) · 2024
- Inferring population dynamics in macaque cortex
Journal of Neural Engineering · 2023
- Inferring Population Dynamics in Macaque Cortex
arXiv (Cornell University) · 2023
- Learning Recurrent Models with Temporally Local Rules
arXiv (Cornell University) · 2023
- An Introduction to Modern Statistical Learning
arXiv (Cornell University) · 2022
- Neuroprosthesis for Decoding Speech in a Paralyzed Person with Anarthria
New England Journal of Medicine · 2021
- Speech Decoding as Machine Translation
Springer briefs in electrical and computer engineering · 2021
- Machine translation of cortical activity to text with an encoder–decoder framework
Nature Neuroscience · 2020
- Nonhuman Primate Reaching with Multichannel Sensorimotor Cortex Electrophysiology
Zenodo (CERN European Organization for Nuclear Research) · 2020
- Real-time decoding of question-and-answer speech dialogue using human cortical activity
Nature Communications · 2019
- Machine translation of cortical activity to text with an encoder-decoder framework
bioRxiv (Cold Spring Harbor Laboratory) · 2019
- Nonhuman Primate Reaching With Multichannel Sensorimotor Cortex Electrophysiology: Broadband For Indy_20161207_02
Zenodo (CERN European Organization for Nuclear Research) · 2018
- Nonhuman Primate Reaching With Multichannel Sensorimotor Cortex Electrophysiology: Broadband For Indy_20160915_01
Zenodo (CERN European Organization for Nuclear Research) · 2018
- Zenodo (CERN European Organization for Nuclear Research)×57
- arXiv (Cornell University)×6
- Figshare×6
- Journal of Neural Engineering×2
- bioRxiv (Cold Spring Harbor Laboratory)×2
- Huzi Cheng
Neuroscience · Indiana University
- Jue Mo
Neuroscience · Purdue University West Lafayette
- Seungbin Park
Neuroscience · Purdue University West Lafayette
- Maria C. Dadarlat
Neuroscience · Purdue University West Lafayette
- Jamie D Costabile
Neuroscience · The Ohio State University
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
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