Carlos Fernandez-Granda
Associate Professor of Mathematics and Data Science
Develops machine learning and signal processing methods for medical imaging and scientific data, including deep denoising and super-resolution.
Carlos Fernandez-Granda's lab at NYU works on signal processing & information theory, data management & big data and speech enhancement & signal processing. 18 papers since 2023, 5 at top venues, mostly CVPR and ICML. 7 PhD students and 2 master's students. 30 alumni. Applications close .
At a glance
- papers, 2023–2026
- 5/ year
- at T1 venues
- 28%
- PhD students
- 7
- MS students
- 2
- alumni listed
- 30
Papers by yearfrom the lab homepage, 2023–2026
- 2 papers2026 · T1 1 · collecting
- 5 papers2025 · T1 1
- 4 papers2024 · T1 1
- 7 papers2023 · T1 2
T1 venuesOtherVenues: CVPR, ICML, NeurIPS, Science, TMLR
Research focuspaper titles that use each topic's words
- Data management & big data3 papers
- Signal processing & information theory1 paper
- Speech enhancement & signal processing1 paper
- super-resolution0 papers
- scientific data0 papers
Paper list
From the lab homepage.
20262 papers
- TMLR (T1)A Monte Carlo Framework for Calibrated Uncertainty Estimation in Sequence Prediction
- PLOS Digital HealthVision-language models for human motion understanding: Lessons from stroke rehabilitation
20255 papers
- IEEE Signal Processing MagazineLearn, Denoise and Discover: A Guide to Deep Denoising with an Application to Electron Microscopy
- MicronRevealing information from weak signal in electron energy-loss spectroscopy with a deep denoiser
- Geophysical Research LettersSamudra: An AI global ocean emulator for climate
- Science (T1)Visualizing nanoparticle surface dynamics and instabilities enabled by deep denoising
- Cambridge University PressWebsite with free pdf, videos, code, slides and solutions to exercises (opens in a new tab)
20244 papers
- Journal of Advances in Modeling Earth SystemsA Stable Implementation of a Data-Driven Scale-Aware Mesoscale Parameterization
- Magnetic Resonance in MedicineRapid quantitative magnetization transfer imaging: Utilizing the hybrid state and the generalized Bloch model
- ICML WorkshopTransfer Learning for Emulating Ocean Climate Variability across CO2 Forcing
- NeurIPS (T1)Uncertainty-aware Fine-tuning of Segmentation Foundation Models
20237 papers
- Journal of Advances in Modeling Earth SystemsBenchmarking of machine learning ocean subgrid parameterizations in an idealized model
- BioengineeringData-Driven Quantitation of Movement Abnormality after Stroke
- Nature BiotechnologyDictionary learning for integrative, multimodal, and scalable single-cell analysis Y. Hao, T. Stuart, M. Kowalski, S. Choudhary, P. Hoffman, A. Hartman, A. Srivastava, G. Molla, S. Madad, C. Fernandez-Granda, R. Satija
- ICML (T1)Evaluating Unsupervised Denoising Requires Unsupervised Metrics
- Journal of Advances in Modeling Earth SystemsGenerative data-driven approaches for stochastic subgrid parameterizations in an idealized ocean model
- Journal of Advances in Modeling Earth SystemsImplementation and Evaluation of a Machine Learned Mesoscale Eddy Parameterization into a Numerical Ocean Circulation Model
- CVPR (T1)Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive Learning
Where alumni went30 listed
Apply to NYUFall 2027
Computer Science PhD (Courant / Tandon)
- Round
- Single round (December)
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
Similar labsnearest by research summary
- CNSJTU
Liqing Zhang
- Computational neuroscience & cognition
- CNZhejiang
Kun Kuang
- Probabilistic & causal inference
- CNZhejiang
Lu Chen
- Graph mining & networks
- CNTsinghua
Miao Li
- Medical imaging & healthcare AI
- USMichigan
Danai Koutra
- Graph mining & networks
- USUIUC
Ning Luo
- Trustworthy & safe ML
Your notes
Save this lab to keep notes.
Data
Checked against the lab homepage.
- Collected
- Verified
- Papers
- The lab homepage
- Members
- Lab homepage
- Alumni
- Lab homepage
Tiers are venue classifications, not lab rankings.
NYUcloses