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jdey4/README.md

Hi, I am Jayanta Dey 👋

I am a machine learning researcher with a PhD in Biomedical Engineering from Johns Hopkins University. I develop learning systems that can adapt to changing data, retain knowledge over time, and make reliable predictions under uncertainty, with applications spanning foundation models, continual learning, multimodal AI, and healthcare.

🔬 Research

  • 🧠 SHARP — Sleep-inspired foundation model for efficient long-range, non-stationary learning; CoLLAs 2026 Oral
  • ♾️ Continual Learning — Developed SiLLy and forward/backward transfer evaluation methods through DARPA L2M research with Microsoft Research
  • 🎯 Reliable AI — Developed geodesic-kernel uncertainty calibration methods evaluated across 45+ datasets
  • 🏥 Clinical AI — Developing LLM-based methods for clinical reasoning using multi-center trauma data
  • 📚 16 publications | 250+ citations | h-index 7

🛠️ Selected Open Source

  • ProgLearn — continual learning
  • hyppo — Multivariate hypothesis testing
  • SHARP — Sleep-inspired hierarchical accelerated replay
  • KDG — Kernel-density-based learning and calibration

📄 Selected Research

TPAMI • TMLR • CoLLAs • PLOS One

📄 Curriculum Vitae
🎓 Google Scholar
💼 LinkedIn

Pinned Loading

  1. neurodata/ProgLearnneurodata/ProgLearnPublic

    NeuroData's package for exploring and using progressive learning algorithms

    Jupyter Notebook 39 44

  2. neurodata/hypponeurodata/hyppoPublic

    Python package for multivariate hypothesis testing

    Python 252 96

  3. neurodata/kdgneurodata/kdgPublic

    Exploring and using kernel density algorithms

    Jupyter Notebook 5 6

  4. sharpsharpPublic

    Jupyter Notebook 1

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jdey4 (Jayanta Dey) · GitHub
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Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: Pull Sharkx2Achievement: Arctic Code Vault Contributor
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jdey4/README.md
Hi, I am Jayanta Dey 👋
I am a machine learning researcher with a PhD in Biomedical Engineering from Johns Hopkins University. I develop learning systems that can adapt to changing data, retain knowledge over time, and make reliable predictions under uncertainty, with applications spanning foundation models, continual learning, multimodal AI, and healthcare.
🔬 Research
  • 🧠 SHARP — Sleep-inspired foundation model for efficient long-range, non-stationary learning; CoLLAs 2026 Oral
  • ♾️ Continual Learning — Developed SiLLy and forward/backward transfer evaluation methods through DARPA L2M research with Microsoft Research
  • 🎯 Reliable AI — Developed geodesic-kernel uncertainty calibration methods evaluated across 45+ datasets
  • 🏥 Clinical AI — Developing LLM-based methods for clinical reasoning using multi-center trauma data
  • 📚 16 publications | 250+ citations | h-index 7
🛠️ Selected Open Source
  • ProgLearn — continual learning
  • hyppo — Multivariate hypothesis testing
  • SHARP — Sleep-inspired hierarchical accelerated replay
  • KDG — Kernel-density-based learning and calibration
📄 Selected Research
TPAMI • TMLR • CoLLAs • PLOS One
📄 Curriculum Vitae

🎓 Google Scholar

💼 LinkedIn

Pinned
Loading
  1. neurodata/ProgLearnneurodata/ProgLearnPublic
    
NeuroData's package for exploring and using progressive learning algorithms 
    Jupyter Notebook
39

44

  2. neurodata/hypponeurodata/hyppoPublic
    
Python package for multivariate hypothesis testing

    Python
252

96

  3. neurodata/kdgneurodata/kdgPublic
    
Exploring and using kernel density algorithms

    Jupyter Notebook
5

6

  4. sharpsharpPublic
    Jupyter Notebook
1


, 'i');
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jdey4 (Jayanta Dey) · GitHub
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 · 13
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Achievements
Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: Pull Sharkx2Achievement: Arctic Code Vault Contributor
Achievements
Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: Pull Sharkx2Achievement: Arctic Code Vault Contributor

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jdey4/README.md
Hi, I am Jayanta Dey 👋
I am a machine learning researcher with a PhD in Biomedical Engineering from Johns Hopkins University. I develop learning systems that can adapt to changing data, retain knowledge over time, and make reliable predictions under uncertainty, with applications spanning foundation models, continual learning, multimodal AI, and healthcare.
🔬 Research
  • 🧠 SHARP — Sleep-inspired foundation model for efficient long-range, non-stationary learning; CoLLAs 2026 Oral
  • ♾️ Continual Learning — Developed SiLLy and forward/backward transfer evaluation methods through DARPA L2M research with Microsoft Research
  • 🎯 Reliable AI — Developed geodesic-kernel uncertainty calibration methods evaluated across 45+ datasets
  • 🏥 Clinical AI — Developing LLM-based methods for clinical reasoning using multi-center trauma data
  • 📚 16 publications | 250+ citations | h-index 7
🛠️ Selected Open Source
  • ProgLearn — continual learning
  • hyppo — Multivariate hypothesis testing
  • SHARP — Sleep-inspired hierarchical accelerated replay
  • KDG — Kernel-density-based learning and calibration
📄 Selected Research
TPAMI • TMLR • CoLLAs • PLOS One
📄 Curriculum Vitae

🎓 Google Scholar

💼 LinkedIn

Pinned
Loading
  1. neurodata/ProgLearnneurodata/ProgLearnPublic
    
NeuroData's package for exploring and using progressive learning algorithms 
    Jupyter Notebook
39

44

  2. neurodata/hypponeurodata/hyppoPublic
    
Python package for multivariate hypothesis testing

    Python
252

96

  3. neurodata/kdgneurodata/kdgPublic
    
Exploring and using kernel density algorithms

    Jupyter Notebook
5

6

  4. sharpsharpPublic
    Jupyter Notebook
1


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jdey4 (Jayanta Dey) · GitHub
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🎯
Focusing
19
followers
 · 13
following

Achievements
Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: Pull Sharkx2Achievement: Arctic Code Vault Contributor
Achievements
Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: Pull Sharkx2Achievement: Arctic Code Vault Contributor

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jdey4/README.md
Hi, I am Jayanta Dey 👋
I am a machine learning researcher with a PhD in Biomedical Engineering from Johns Hopkins University. I develop learning systems that can adapt to changing data, retain knowledge over time, and make reliable predictions under uncertainty, with applications spanning foundation models, continual learning, multimodal AI, and healthcare.
🔬 Research
  • 🧠 SHARP — Sleep-inspired foundation model for efficient long-range, non-stationary learning; CoLLAs 2026 Oral
  • ♾️ Continual Learning — Developed SiLLy and forward/backward transfer evaluation methods through DARPA L2M research with Microsoft Research
  • 🎯 Reliable AI — Developed geodesic-kernel uncertainty calibration methods evaluated across 45+ datasets
  • 🏥 Clinical AI — Developing LLM-based methods for clinical reasoning using multi-center trauma data
  • 📚 16 publications | 250+ citations | h-index 7
🛠️ Selected Open Source
  • ProgLearn — continual learning
  • hyppo — Multivariate hypothesis testing
  • SHARP — Sleep-inspired hierarchical accelerated replay
  • KDG — Kernel-density-based learning and calibration
📄 Selected Research
TPAMI • TMLR • CoLLAs • PLOS One
📄 Curriculum Vitae

🎓 Google Scholar

💼 LinkedIn

Pinned
Loading
  1. neurodata/ProgLearnneurodata/ProgLearnPublic
    
NeuroData's package for exploring and using progressive learning algorithms 
    Jupyter Notebook
39

44

  2. neurodata/hypponeurodata/hyppoPublic
    
Python package for multivariate hypothesis testing

    Python
252

96

  3. neurodata/kdgneurodata/kdgPublic
    
Exploring and using kernel density algorithms

    Jupyter Notebook
5

6

  4. sharpsharpPublic
    Jupyter Notebook
1


, 'i');
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var __m = "youtube.com";
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jdey4 (Jayanta Dey) · GitHub
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🎯
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19
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 · 13
following

Achievements
Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: Pull Sharkx2Achievement: Arctic Code Vault Contributor
Achievements
Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: Pull Sharkx2Achievement: Arctic Code Vault Contributor

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jdey4/README.md
Hi, I am Jayanta Dey 👋
I am a machine learning researcher with a PhD in Biomedical Engineering from Johns Hopkins University. I develop learning systems that can adapt to changing data, retain knowledge over time, and make reliable predictions under uncertainty, with applications spanning foundation models, continual learning, multimodal AI, and healthcare.
🔬 Research
  • 🧠 SHARP — Sleep-inspired foundation model for efficient long-range, non-stationary learning; CoLLAs 2026 Oral
  • ♾️ Continual Learning — Developed SiLLy and forward/backward transfer evaluation methods through DARPA L2M research with Microsoft Research
  • 🎯 Reliable AI — Developed geodesic-kernel uncertainty calibration methods evaluated across 45+ datasets
  • 🏥 Clinical AI — Developing LLM-based methods for clinical reasoning using multi-center trauma data
  • 📚 16 publications | 250+ citations | h-index 7
🛠️ Selected Open Source
  • ProgLearn — continual learning
  • hyppo — Multivariate hypothesis testing
  • SHARP — Sleep-inspired hierarchical accelerated replay
  • KDG — Kernel-density-based learning and calibration
📄 Selected Research
TPAMI • TMLR • CoLLAs • PLOS One
📄 Curriculum Vitae

🎓 Google Scholar

💼 LinkedIn

Pinned
Loading
  1. neurodata/ProgLearnneurodata/ProgLearnPublic
    
NeuroData's package for exploring and using progressive learning algorithms 
    Jupyter Notebook
39

44

  2. neurodata/hypponeurodata/hyppoPublic
    
Python package for multivariate hypothesis testing

    Python
252

96

  3. neurodata/kdgneurodata/kdgPublic
    
Exploring and using kernel density algorithms

    Jupyter Notebook
5

6

  4. sharpsharpPublic
    Jupyter Notebook
1


, 'i');
if (__m === '*' || __re.test(location.href)) {
// Auto-enable theater mode on YouTube
(function() {
function tryTheater() {
var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]');
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var __m = "*";
var __re = new RegExp('^' + ".*" + '
jdey4 (Jayanta Dey) · GitHub
Skip to content
View jdey4's full-sized avatar
🎯
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🎯
Focusing
19
followers
 · 13
following

Achievements
Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: Pull Sharkx2Achievement: Arctic Code Vault Contributor
Achievements
Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: Pull Sharkx2Achievement: Arctic Code Vault Contributor

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jdey4/README.md
Hi, I am Jayanta Dey 👋
I am a machine learning researcher with a PhD in Biomedical Engineering from Johns Hopkins University. I develop learning systems that can adapt to changing data, retain knowledge over time, and make reliable predictions under uncertainty, with applications spanning foundation models, continual learning, multimodal AI, and healthcare.
🔬 Research
  • 🧠 SHARP — Sleep-inspired foundation model for efficient long-range, non-stationary learning; CoLLAs 2026 Oral
  • ♾️ Continual Learning — Developed SiLLy and forward/backward transfer evaluation methods through DARPA L2M research with Microsoft Research
  • 🎯 Reliable AI — Developed geodesic-kernel uncertainty calibration methods evaluated across 45+ datasets
  • 🏥 Clinical AI — Developing LLM-based methods for clinical reasoning using multi-center trauma data
  • 📚 16 publications | 250+ citations | h-index 7
🛠️ Selected Open Source
  • ProgLearn — continual learning
  • hyppo — Multivariate hypothesis testing
  • SHARP — Sleep-inspired hierarchical accelerated replay
  • KDG — Kernel-density-based learning and calibration
📄 Selected Research
TPAMI • TMLR • CoLLAs • PLOS One
📄 Curriculum Vitae

🎓 Google Scholar

💼 LinkedIn

Pinned
Loading
  1. neurodata/ProgLearnneurodata/ProgLearnPublic
    
NeuroData's package for exploring and using progressive learning algorithms 
    Jupyter Notebook
39

44

  2. neurodata/hypponeurodata/hyppoPublic
    
Python package for multivariate hypothesis testing

    Python
252

96

  3. neurodata/kdgneurodata/kdgPublic
    
Exploring and using kernel density algorithms

    Jupyter Notebook
5

6

  4. sharpsharpPublic
    Jupyter Notebook
1


, 'i');
if (__m === '*' || __re.test(location.href)) {
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try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
jdey4 (Jayanta Dey) · GitHub
Skip to content
View jdey4's full-sized avatar
🎯
Focusing
🎯
Focusing
19
followers
 · 13
following

Achievements
Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: Pull Sharkx2Achievement: Arctic Code Vault Contributor
Achievements
Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: Pull Sharkx2Achievement: Arctic Code Vault Contributor

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jdey4/README.md
Hi, I am Jayanta Dey 👋
I am a machine learning researcher with a PhD in Biomedical Engineering from Johns Hopkins University. I develop learning systems that can adapt to changing data, retain knowledge over time, and make reliable predictions under uncertainty, with applications spanning foundation models, continual learning, multimodal AI, and healthcare.
🔬 Research
  • 🧠 SHARP — Sleep-inspired foundation model for efficient long-range, non-stationary learning; CoLLAs 2026 Oral
  • ♾️ Continual Learning — Developed SiLLy and forward/backward transfer evaluation methods through DARPA L2M research with Microsoft Research
  • 🎯 Reliable AI — Developed geodesic-kernel uncertainty calibration methods evaluated across 45+ datasets
  • 🏥 Clinical AI — Developing LLM-based methods for clinical reasoning using multi-center trauma data
  • 📚 16 publications | 250+ citations | h-index 7
🛠️ Selected Open Source
  • ProgLearn — continual learning
  • hyppo — Multivariate hypothesis testing
  • SHARP — Sleep-inspired hierarchical accelerated replay
  • KDG — Kernel-density-based learning and calibration
📄 Selected Research
TPAMI • TMLR • CoLLAs • PLOS One
📄 Curriculum Vitae

🎓 Google Scholar

💼 LinkedIn

Pinned
Loading
  1. neurodata/ProgLearnneurodata/ProgLearnPublic
    
NeuroData's package for exploring and using progressive learning algorithms 
    Jupyter Notebook
39

44

  2. neurodata/hypponeurodata/hyppoPublic
    
Python package for multivariate hypothesis testing

    Python
252

96

  3. neurodata/kdgneurodata/kdgPublic
    
Exploring and using kernel density algorithms

    Jupyter Notebook
5

6

  4. sharpsharpPublic
    Jupyter Notebook
1


, 'i');
if (__m === '*' || __re.test(location.href)) {
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var enabled = true;
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if (!style) {
style = document.createElement('style');
style.id = 'universal-dark-mode-style';
document.head.appendChild(style);
}
// Dark mode CSS - inverts colors but preserves images/video
style.textContent = '
/* Invert everything except media */
html {
filter: invert(1) hue-rotate(180deg) !important;
background: #1a1a2e !important;
}
/* Restore images, videos, iframes, canvas */
img, video, iframe, canvas, svg, picture, [style*="background-image"] {
filter: invert(1) hue-rotate(180deg) !important;
}
/* Preserve specific elements that should not be inverted */
.no-dark-mode, .no-dark-mode *,
[data-theme="light"], [data-theme="light"],
.ace_editor, .ace_editor *,
.CodeMirror, .CodeMirror *,
.monaco-editor, .monaco-editor *,
.markdown-body pre, .markdown-body pre *,
.highlight, .highlight *,
pre code, pre code * {
filter: none !important;
}
/* Fix common UI elements */
.modal, .popup, .dropdown-menu, .tooltip, .popover {
filter: invert(1) hue-rotate(180deg) !important;
background: #2d2d44 !important;
border-color: #444 !important;
}
/* Scrollbars */
::-webkit-scrollbar { background: #1a1a2e !important; }
::-webkit-scrollbar-thumb { background: #444 !important; }
::-webkit-scrollbar-thumb:hover { background: #555 !important; }
/* Selection */
::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
';
}
function removeDarkMode() {
var style = document.getElementById('universal-dark-mode-style');
if (style) style.remove();
}
// Toggle with Alt+Shift+D
document.addEventListener('keydown', function(e) {
if (e.altKey && e.shiftKey && e.key === 'D') {
e.preventDefault();
enabled = !enabled;
if (enabled) {
applyDarkMode();
console.log('[Universal Dark Mode] Enabled');
} else {
removeDarkMode();
console.log('[Universal Dark Mode] Disabled');
}
}
});
// Apply on load
applyDarkMode();
// Re-apply on dynamic content
var observer = new MutationObserver(function(mutations) {
if (enabled && !document.getElementById('universal-dark-mode-style')) {
applyDarkMode();
}
});
observer.observe(document.head, { childList: true });
console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');
})();
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();
jdey4 (Jayanta Dey) · GitHub
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Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: Pull Sharkx2Achievement: Arctic Code Vault Contributor
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Achievement: Pair ExtraordinaireAchievement: YOLOAchievement: Pull Sharkx2Achievement: Arctic Code Vault Contributor

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jdey4/README.md
Hi, I am Jayanta Dey 👋
I am a machine learning researcher with a PhD in Biomedical Engineering from Johns Hopkins University. I develop learning systems that can adapt to changing data, retain knowledge over time, and make reliable predictions under uncertainty, with applications spanning foundation models, continual learning, multimodal AI, and healthcare.
🔬 Research
  • 🧠 SHARP — Sleep-inspired foundation model for efficient long-range, non-stationary learning; CoLLAs 2026 Oral
  • ♾️ Continual Learning — Developed SiLLy and forward/backward transfer evaluation methods through DARPA L2M research with Microsoft Research
  • 🎯 Reliable AI — Developed geodesic-kernel uncertainty calibration methods evaluated across 45+ datasets
  • 🏥 Clinical AI — Developing LLM-based methods for clinical reasoning using multi-center trauma data
  • 📚 16 publications | 250+ citations | h-index 7
🛠️ Selected Open Source
  • ProgLearn — continual learning
  • hyppo — Multivariate hypothesis testing
  • SHARP — Sleep-inspired hierarchical accelerated replay
  • KDG — Kernel-density-based learning and calibration
📄 Selected Research
TPAMI • TMLR • CoLLAs • PLOS One
📄 Curriculum Vitae

🎓 Google Scholar

💼 LinkedIn

Pinned
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  1. neurodata/ProgLearnneurodata/ProgLearnPublic
    
NeuroData's package for exploring and using progressive learning algorithms 
    Jupyter Notebook
39

44

  2. neurodata/hypponeurodata/hyppoPublic
    
Python package for multivariate hypothesis testing

    Python
252

96

  3. neurodata/kdgneurodata/kdgPublic
    
Exploring and using kernel density algorithms

    Jupyter Notebook
5

6

  4. sharpsharpPublic
    Jupyter Notebook
1