Aylin Naebzadeh

Example Talk

Sat, 01 Jun 2030 13:00:00 +0000

Click on the Slides button above to view the built-in slides feature.

Slides can be added in a few ways:

Create slides using Wowchemy’s Slides feature and link using slides parameter in the front matter of the talk file
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Embed your slides (e.g. Google Slides) or presentation video on this page using shortcodes.

Further event details, including page elements such as image galleries, can be added to the body of this page.

Invited Job Talks

Sat, 01 Jun 2030 13:00:00 +0000

Click on the Slides button above to view the built-in slides feature.

Slides can be added in a few ways:

Create slides using Wowchemy’s Slides feature and link using slides parameter in the front matter of the talk file
Upload an existing slide deck to static/ and link using url_slides parameter in the front matter of the talk file
Embed your slides (e.g. Google Slides) or presentation video on this page using shortcodes.

Further event details, including page elements such as image galleries, can be added to the body of this page.

APARSIN: A Multi-Variety Sentiment and Translation Benchmark for Iranic Languages

Sun, 01 Mar 2026 00:00:00 +0000

Advances of Informal to Formal Persian Text Conversion: A Survey

Thu, 01 Jan 2026 00:00:00 +0000

Wed, 12 Nov 2025 00:00:00 +0000

3D Reconstruction and Neural Rendering

Many real-world tasks require understanding scenes in 3D from sparse or unconstrained inputs. I work on reconstructing 3D scenes using COLMAP for camera pose estimation, followed by neural rendering methods such as NeRF and Gaussian Splatting for high-fidelity reconstruction and view synthesis. My work includes integrating object detection and spatial reasoning into these pipelines, enabling more accurate and semantically aware 3D representations.

Wed, 12 Nov 2025 00:00:00 +0000

Diffusion-Based Image Restoration

Real-world imaging systems introduce complex degradations that standard diffusion models are not designed to handle. My work focuses on developing diffusion-based restoration methods that remain reliable under realistic sensor conditions, including spatially correlated noise, low resolution, and thermal imaging artifacts. I explore principled transformations such as whitening to convert correlated sensor noise into forms compatible with diffusion sampling, enabling accurate restoration without retraining. I also design patch-based diffusion frameworks that learn local thermal priors from small image regions and use overlapping patch denoising with smooth blending to reconstruct full-resolution outputs. Across denoising, super-resolution, and deblurring, these approaches improve robustness and generalization for both RGB and thermal images and aim to make diffusion-based restoration practical for real-world deployment.

Wed, 12 Nov 2025 00:00:00 +0000

Robust Multimodal Learning

Multimodal systems often struggle when one or more input sources are missing, corrupted, or imbalanced. My work develops learning strategies that preserve performance under these real-world conditions by enabling models to reason effectively with incomplete information. This includes designing projection-based methods that learn to estimate missing modality representations directly from the available ones and training unified models that handle all missing-modality configurations without the need for modality-specific retraining or complex adaptation procedures. I also explore efficient fine-tuning techniques, such as LoRA-based unimodal adaptation, to reduce computational overhead while maintaining strong performance across diverse modalities and tasks. These efforts benefit from my background in NLP, which strengthens my understanding of cross-modal interactions and how language models can support robust reasoning when some modalities are absent.

Wed, 12 Nov 2025 00:00:00 +0000

Research

My research spans computer vision, NLP, multimodal learning, and 3D reconstruction, with a focus on building reliable ML systems that operate robustly under real-world conditions. I develop diffusion-based methods for image restoration that handle real sensor noise, low-quality inputs, and cross-domain degradations. I also work on improving the robustness of multimodal models when information is missing, corrupted, or imbalanced across modalities. Beyond 2D vision, I explore 3D reconstruction and neural rendering, including camera pose estimation, NeRF, and Gaussian Splatting. More broadly, my work connects generative modeling, visual understanding, and trustworthy AI, strengthened by my background in natural language processing.

Diffusion Models for Inverse Problems

Robust Multimodal Learning

3D Reconstruction

GinGer at SemEval-2025 Task 11: Leveraging Fine-Tuned Transformer Models and LoRA for Sentiment Analysis in Low-Resource Languages

Tue, 01 Jul 2025 00:00:00 +0000

Selected Academic Projects

Wed, 01 Jan 2025 00:00:00 +0000

Predicting COVID-19 From Chest X-Ray Images

Built a deep learning pipeline to predict COVID-19 from chest X-ray images using transfer learning on pre-trained SqueezeNet.
Applied data augmentation and preprocessing to improve generalization on limited medical data.

Tile Crack Detection with U-Net

Developed an image segmentation model to detect surface cracks on tiles using U-Net.
Combined classical image processing with deep learning to localize fine-grained defects.

Genetic and Ant Colony Algorithms

Implemented a Genetic Algorithm to solve cubic equations and explore convergence behavior.
Implemented an Ant Colony Optimization algorithm for task scheduling problems.

Football Match Fuzzy Predictor

Designed a fuzzy logic controller to predict football match outcomes using interpretable rules.
Used the Simpful library to define linguistic variables and construct fuzzy rule bases.

Image Recalling Hopfield Network

Implemented a Hopfield network for recalling patterns on Fashion-MNIST–style image data.
Extended the Hopfield formulation to handle a TSP-like optimization setting.

SOM and RBF Clustering

Implemented Self-Organizing Maps (SOM) and Radial Basis Function (RBF) networks for classification tasks.
Used TensorFlow and Keras to train and compare different clustering and representation schemes.

MLP From Scratch

Implemented a multilayer perceptron from scratch for classification problems.
Used Keras to experiment with momentum and weight decay for optimization and regularization.

Artificial Intelligence Course Projects

Built a deep-learning–based model to recognize different clothing types from images.
Completed UC Berkeley–style Pac-Man AI projects, covering search, reinforcement learning, CSP, and MDP formulations.

Smart Sensor-Embedded Games for Autism and Alzheimer’s

Co-designed smart games to support Alzheimer’s patients and autistic children, focusing on engagement and cognitive support.
Developed sensor-embedded puzzles and interactive game rooms to assist caregivers with monitoring and assessment.

Thu, 08 Aug 2024 00:00:00 +0000

Academic Awards

Awarded an M.Sc. Admission Offer for Outstanding Students by the University of Science and Technology, Computer Engineering Department (2024).
Received an Undergraduate Tuition Fee Waiver for Exceptional Students at University of Science and Technology (2020).
Ranked 206th out of over 400,000 students in National University Entrance Exam, placing in the Top 0.07% (2020).

Thu, 08 Aug 2024 00:00:00 +0000

News

[8/2026] Our paper, “Broadband Wide Field of View Imaging with Computational Mirrors” has been accepted as an oral presentation at the European Conference on Computer Vision (ECCV'26).
[5/2026] Our paper, “CARD: Correlation Aware Restoration with Diffusion” has been accepted at the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR'26).
[3/2026] I joined Apple  in Cupertino, CA as a Data and Machine Learning Intern for Spring and Summer 2026.
[3/2026] I successfully passed my PhD Qualifying Exam and officially advanced to candidacy!
[11/2025] Our paper, “MMP: Towards Robust Multi-Modal Learning with Masked Modality Projection” has been accepted at the 2025 IEEE International Conference on Big Data (BigData'25).
[11/2025] Our paper, “TDiff: Thermal Plug-and-Play Prior with Patch-Based Diffusion” has been accepted at the 1st ACM International Workshop on Thermal Sensing and Computing (HotSense'25).

Thu, 08 Aug 2024 00:00:00 +0000

Peer Review

Review activity for ACM transactions on architecture and code optimization.
Review activity for IEEE computer architecture letters.
Review activity for Parallel computing.

Artifact Evaluation Committee

International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS'25).
International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS'24).
International Symposium on Computer Architecture (ISCA'24).

Professional Services

Audio/Video Chair of the ASPLOS’24 Conference.

Talks

Gave a talk on “Hardware/Software Approaches for Accelerating Graph Processing Workloads” in the School of Computing at Binghamton University, Spring 2025.
Gave a talk on “Redundancy Removal for Accelerating Graph Processing Workloads” in the Department of Computer Science at Tulane University, Spring 2025.
Present Common Graph and Core Graph projects at Society of Women Engineers, University of California, Riverside, Winter 2024.
Present Common Graph project at Highlights of Parallel Computing Conference, Florida, USA, Spring 2023.

Thu, 08 Aug 2024 00:00:00 +0000

Teaching Experience

[Spring 2024] Mentor(Product Owner) - System Analysis and Design course.
[Fall 2023 | Spring 2024 | Fall 2024] Mentor(Scrum Master) - System Analysis and Design course.
[Fall 2022] Teaching Assistant - Data Structures course.
[Spring 2021] Teaching Assistant - Advanced Programming course.
[Fall 2021] Teaching Assistant - Discrete Mathematics course.
[Fall 2021] Teaching Assistant - Fundamentals of Computer Programming course.

News

Thu, 08 Aug 2024 00:00:00 +0000

News

[8/2026] Our paper, “Broadband Wide Field of View Imaging with Computational Mirrors” has been accepted as an oral presentation at the European Conference on Computer Vision (ECCV'26).
[5/2026] Our paper, “CARD: Correlation Aware Restoration with Diffusion” has been accepted at the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR'26).
[3/2026] I joined Apple  in Cupertino, CA as a Data and Machine Learning Intern for Spring and Summer 2026.
[3/2026] I successfully passed my PhD Qualifying Exam and officially advanced to candidacy!
[11/2025] Our paper, “MMP: Towards Robust Multi-Modal Learning with Masked Modality Projection” has been accepted at the 2025 IEEE International Conference on Big Data (BigData'25).
[11/2025] Our paper, “TDiff: Thermal Plug-and-Play Prior with Patch-Based Diffusion” has been accepted at the 1st ACM International Workshop on Thermal Sensing and Computing (HotSense'25).

MultiCGCN: multi-label text classification using GCNs and heterogeneous graphs

Mon, 01 Jan 2024 00:00:00 +0000

NICA at EXIST CLEF Tasks 2024

Mon, 01 Jan 2024 00:00:00 +0000

NICA at Quantum Computing CLEF Tasks 2024

Mon, 01 Jan 2024 00:00:00 +0000

Slides

Tue, 05 Feb 2019 00:00:00 +0000

Create slides in Markdown with Wowchemy

Wowchemy | Documentation

Features

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3-in-1: Create, Present, and Publish your slides
Supports speaker notes
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Inline code: variable

Code block:

porridge = "blueberry"
if porridge == "blueberry":
 print("Eating...")

Math

In-line math: $x + y = z$

Block math:

$$ f\left( x \right) = ;\frac{{2\left( {x + 4} \right)\left( {x - 4} \right)}}{{\left( {x + 4} \right)\left( {x + 1} \right)}} $$

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{{% fragment %}} One {{% /fragment %}}
{{% fragment %}} **Two** {{% /fragment %}}
{{% fragment %}} Three {{% /fragment %}}

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One Two Three

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Themes

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white: White background, black text, blue links
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sky: Blue background, thin dark text, blue links

night: Black background, thick white text, orange links
serif: Cappuccino background, gray text, brown links
simple: White background, black text, blue links
solarized: Cream-colored background, dark green text, blue links

Custom Slide

Customize the slide style and background

{{< slide background-image="/media/boards.jpg" >}}
{{< slide background-color="#0000FF" >}}
{{< slide class="my-style" >}}

Custom CSS Example

Let’s make headers navy colored.

Create assets/css/reveal_custom.css with:

.reveal section h1,
.reveal section h2,
.reveal section h3 {
 color: navy;
}

Questions?

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Documentation

Mon, 01 Jan 0001 00:00:00 +0000

Invited talks

[11/2023] Exploring Safety in Large Language Models YouTube 40:30 mins | News
- 80th Annual Convention of Jiaotong University Alumni Association in SoCal (交通大学南加州校友会80周年庆), Los Angeles, CA, US
[11/04/2023] AI and Large Language Models
- UCR Family Day/Homecoming seminar, Riverside CA, US
[08/2023] Fast Text Generation with Text-Editing Models
- KDD Tutorial, Long Beach, CA, US
[08/2023] Safeguarding the Potential in Large Language Models
- KDD SoCal Day, Long Beach, CA, US
[08/2023] Large Language Models & AI Unleashed
- UCR REU, Riverside, CA, US
[07/2023] Introduction to Large Language Models
- Redlands & UCR Higher School AI Academy, Riverside, CA, US
[05/18/2023] What Future Do We Want with Artificial Intelligence?
- TEDx UCR | YouTube, Riverside, CA, US
[2021] Robust and Trustworthy NLP Through The Lens of Text Summarization
- University of California, Riverside, March 2021, Riverside, CA, US
- National University of Singapore, March 2021, Singapore
- Google AI, March 2021, US
- University of Waterloo, February 2021, Waterloo, Canada
- University of Utah, February 2021, Salt Lake City, UT, US
- Simon Fraser University, February 2021, Burnaby, Canada
- HEC Montreal & Mila, February 2021, Montreal, Canada
- Queen’s University, January 2021, Kingston, Canada

Panelists

[10/2023] Impact of Generative AI
- UCR BCOE Council of Advisors meeting, Tweet
[09/2023] Academic Perspectives on ChatGPT
- National Institute of Statistical Sciences (NISS) Webinar
[09/2023] Panel: Artificial Intelligence (AI) in Higher Education
- UCR Marketing & Communications Conference 2023
[06/2023] Biasly - AI to detect and correct misogynistic language
- AI4Good Lab, Montreal, Canada (remote)

Media Interviews

[10/2023] Faculty members discuss AI’s possible impacts at UCR - UCR News

Awards

Mon, 01 Jan 0001 00:00:00 +0000

Academic Awards

Awarded an M.Sc. Admission Offer for Outstanding Students by the University of Science and Technology, Computer Engineering Department (2024).
Received an Undergraduate Tuition Fee Waiver for Exceptional Students at University of Science and Technology (2020).
Ranked 206th out of over 400,000 students in National University Entrance Exam, placing in the Top 0.07% (2020).

Resources

Mon, 01 Jan 0001 00:00:00 +0000

Services

Mon, 01 Jan 0001 00:00:00 +0000

Peer Review

Review activity for ACM transactions on architecture and code optimization.
Review activity for IEEE computer architecture letters.
Review activity for Parallel computing.

Artifact Evaluation Committee

International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS'25).
International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS'24).
International Symposium on Computer Architecture (ISCA'24).

Professional Services

Audio/Video Chair of the ASPLOS’24 Conference.

Talks

Gave a talk on “Hardware/Software Approaches for Accelerating Graph Processing Workloads” in the School of Computing at Binghamton University, Spring 2025.
Gave a talk on “Redundancy Removal for Accelerating Graph Processing Workloads” in the Department of Computer Science at Tulane University, Spring 2025.
Present Common Graph and Core Graph projects at Society of Women Engineers, University

of California, Riverside, Winter 2024.

Present Common Graph project at Highlights of Parallel Computing Conference, Florida, USA,

Spring 2023.

Talks

Mon, 01 Jan 0001 00:00:00 +0000

Invited talks

[11/2023] Exploring Safety in Large Language Models YouTube 40:30 mins | News
- 80th Annual Convention of Jiaotong University Alumni Association in SoCal (交通大学南加州校友会80周年庆), Los Angeles, CA, US
[11/04/2023] AI and Large Language Models
- UCR Family Day/Homecoming seminar, Riverside CA, US
[08/2023] Fast Text Generation with Text-Editing Models
- KDD Tutorial, Long Beach, CA, US
[08/2023] Safeguarding the Potential in Large Language Models
- KDD SoCal Day, Long Beach, CA, US
[08/2023] Large Language Models & AI Unleashed
- UCR REU, Riverside, CA, US
[07/2023] Introduction to Large Language Models
- Redlands & UCR Higher School AI Academy, Riverside, CA, US
[05/18/2023] What Future Do We Want with Artificial Intelligence?
- TEDx UCR | YouTube, Riverside, CA, US
[2021] Robust and Trustworthy NLP Through The Lens of Text Summarization
- University of California, Riverside, March 2021, Riverside, CA, US
- National University of Singapore, March 2021, Singapore
- Google AI, March 2021, US
- University of Waterloo, February 2021, Waterloo, Canada
- University of Utah, February 2021, Salt Lake City, UT, US
- Simon Fraser University, February 2021, Burnaby, Canada
- HEC Montreal & Mila, February 2021, Montreal, Canada
- Queen’s University, January 2021, Kingston, Canada

Panelists

[10/2023] Impact of Generative AI
- UCR BCOE Council of Advisors meeting, Tweet
[09/2023] Academic Perspectives on ChatGPT
- National Institute of Statistical Sciences (NISS) Webinar
[09/2023] Panel: Artificial Intelligence (AI) in Higher Education
- UCR Marketing & Communications Conference 2023
[06/2023] Biasly - AI to detect and correct misogynistic language
- AI4Good Lab, Montreal, Canada (remote)

Media Interviews

[10/2023] Faculty members discuss AI’s possible impacts at UCR - UCR News

Teachings

Mon, 01 Jan 0001 00:00:00 +0000

Teaching Experience

[Spring 2024] Mentor(Product Owner) - System Analysis and Design course.
[Fall 2023 | Spring 2024 | Fall 2024] Mentor(Scrum Master) - System Analysis and Design course.
[Fall 2022] Teaching Assistant - Data Structures course.
[Spring 2021] Teaching Assistant - Advanced Programming course.
[Fall 2021] Teaching Assistant - Discrete Mathematics course.
[Fall 2021] Teaching Assistant - Fundamentals of Computer Programming course.