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<!DOCTYPE html>
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<h2>Open Calls for Papers/Participation</h2>
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<li>ECCV <a href="https://dd-challenge-main.vercel.app/">"Sometimes Less is More: the 1st Dataset Distillation Challenge"</a>, Milan, Italy, Sep 2024</li>
<li>MICCAI Challenge on <a href="https://bionlplab.github.io/2024_MICCAI_CXRLT/">Long-tailed, Multi-label, and Zero-shot Classification on Chest X-rays (CXR-LT)</a>, Morocco, Oct 2024</li>
<li>NeurIPS <a href="https://llm-pc.github.io/">LLM Privacy Challenge</a>, Vancouver, Dec 2024</li>
<li>NeurIPS Workshop on <a href="https://genai4health.github.io/">GenAI for Health: Potential, Trust and Policy Compliance</a>, Vancouver, Dec 2024</li>
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<h2>VITA In the Press (selected)</h2>
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<ul>
<li> <b>Medical Xpress</b>: <a href="https://medicalxpress.com/news/2023-08-artificial-intelligence-automates-diagnosis-severe.html">"Artificial Intelligence automates the diagnosis of severe heart valve disease"</a>, Aug 2023 </li>
<li> <b>IEEE Intelligent Systems</b>: <a href="https://www.computer.org/csdl/magazine/ex/2023/02/10111517/1MIcRBcam2s">"AI’s 10 to Watch, 2022"</a>, Apr 2023 </li>
<li> <b>MIT News</b>: <a href="https://news.mit.edu/2023/new-technique-machine-learning-models-0322">"Learning to grow machine-learning models"</a>, Mar 2023 </li>
<li> <b>IEEE Computer Magazine</b>: <a href="https://www.computer.org/csdl/magazine/co/2022/04/09755195/1Cubx6Twc5G">"Virtual Roundtable Interview: Efficient Computer Vision for Embedded Systems"</a>, Apr 2022</li>
<li> <b>NSF News</b>: <a href="https://www.nsf.gov/cise/news/NeuralArchitecture.pdf">"Accelerating Neural Architecture Search with Theory-Grounded, Training-Free Metrics"</a>, Mar 2022</li>
<li> <b>Quanta Magazine</b>: <a href="https://www.quantamagazine.org/will-transformers-take-over-artificial-intelligence-20220310/">"Will Transformers Take Over Artificial Intelligence?"</a>, Mar 2022</li>
<li> <b>UT Engineering News</b>: <a href="https://www.engr.utexas.edu/news/archive/9204-5-questions-with-cockrells-newest-machine-learning-and-artificial-intelligence-expert-atlas-wang">"5 Questions with Cockrell’s Newest Machine Learning and Artificial Intelligence Expert, Atlas Wang"</a>, Mar 2021</li>
<li> <b>IDG Connect</b>: <a href="https://www.idgconnect.com/article/3602888/reducing-energy-use-in-neural-networks.html">"Reducing energy use in neural networks"</a>, Jan 2021</li>
<li> <b>MIT News</b>: <a href="https://news.mit.edu/2020/neural-model-language-1201">"Shrinking massive neural networks used to model language"</a>, Dec 2020 </li>
<li> <b>US Army Research Lab</b> selected <a href="https://arxiv.org/abs/2002.02308">our work </a> as No. 3 in US ARL’s <a href="https://www.army.mil/article/242136">“10 Coolest Techniques”</a> of the year [<a href="https://www.youtube.com/watch?v=6sg-4CxNbBk&feature=youtu.be&ab_channel=U.S.ArmyCCDCArmyResearchLaboratory">Video Demo</a>], Oct 2020 </li>
<li> <b>Tech Xplore</b>: <a href="https://techxplore.com/news/2020-07-deep-neural-networks-adversarial-d.html">"Fooling deep neural networks for object detection with adversarial 3-D logos"</a>, Jul 2020 </li>
<li> <b>Synced AI Technology & Industry Review</b>: <a href="https://syncedreview.com/2019/08/22/automl-gan-autogan-ai-can-now-design-better-gan-models-than-humans/">"AutoML + GAN = AutoGAN! AI can now design better GAN models than humans"</a>, Aug 2019 </li>
<li> <b>Adobe Research Blog</b>: <a href="https://research.adobe.com/smart-home-adversarial-machine-learning-could-protect-your-privacy">"Smart home? Adversarial machine learning could protect your privacy"</a>, Nov 2018 </li>
</ul>
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<h2>Datasets</h2>
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<div class="trend-entry d-flex">
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<ul>
<li>MIA'24, Long-tailed, multi-label, and zero-shot classification on chest X-rays (<b>CXR-LT</b>) dataset <a href="https://bionlplab.github.io/2024_MICCAI_CXRLT/">[Webpage]</a></li>
<li>IEEE TIP'23, Multi-Purpose Real Haze Benchmark (<b>A2I2-Haze</b>) dataset <a href=" https://a2i2-archangel.vision">[Webpage]</a></li>
<li>IEEE TPAMI'20 + ECCV'18, Privacy attributes in HMDB51 (<b>PA-HMDB51</b>) dataset <a href="https://htwang14.github.io/PA-HMDB51-website/index.html">[Webpage]</a></li>
<li>IJCV'20 + CVPR'19, Multi-Purpose Image Deraining (<b>MPID</b>) dataset <a href="https://github.com/lsy17096535/Single-Image-Deraining">[Webpage]</a></li>
<li>IEEE TIP'19, REalistic Single Image DEhazing (<b>RESIDE</b>) dataset <a href="https://sites.google.com/view/reside-dehaze-datasets">[Webpage]</a></li>
<li>ACM MM'15, Adobe Visual Font Recognition (<b>VFR</b>) dataset <a href="https://drive.google.com/drive/folders/1VJ8rlmxWjS2Xv0eFECfpRuNWuRrqh6h6?usp=sharing">[Webpage]</a></li>
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<h2>Courses</h2>
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At UT Austin
<ul>
<li> [Spring 2024] <a href="./spring_24.html">UT ECE 379K: Introduction to Computer Vision</a></li>
<li> [Fall 2023] <a href="./fall_23.html">UT ECE 381V/CS 395T: Advanced Topics in Computer Vision</a></li>
<li> [Spring 2023] <a href="./spring_23.html">UT ECE 381V/CS 395T: Advanced Topics in Computer Vision</a></li>
<li> [Fall 2022] <a href="./fall_22.html">UT ECE 379K: Introduction to Computer Vision</a></li>
<li> [Spring 2022] <a href="./spring_22.html">UT ECE 379K: Introduction to Computer Vision</a></li>
<li> [Fall 2021] <a href="./fall_21.html">UT ECE 381V/CS 395T: Advanced Topics in Computer Vision</a></li>
<li> [Spring 2021] <a href="./spring_21.html">UT ECE 381V: Advanced Topics in Computer Vision</a></li>
</ul>
At TAMU
<ul>
<li>[Spring 2020] <a href="http://people.tamu.edu/~atlaswang/SpringCSCE421.html">TAMU CSCE 421: Machine Learning (undergraduate)</a></li>
<li>[Fall 2019] <a href="http://people.tamu.edu/~atlaswang/Fall19CSCE633.html">TAMU CSCE 633: Machine Learning</a></li>
<li>[Summer 2019] <a href="https://sites.usp.br/datascience/spsas-learning-from-data/">Advanced Summer School of Learning from Data</a> (Invited short course at University of Sao Paulo, Brazil) </li>
<li>[Spring 2019] <a href="http://people.tamu.edu/~atlaswang/19CSCE633.html">TAMU CSCE 633: Machine Learning</a></li>
<li>[Fall 2018] <a href="http://people.tamu.edu/~atlaswang/18CSCE625.html">TAMU CSCE 625: Artificial Intelligence</a></li>
<li>[Summer 2018] <a href="https://www.youtube.com/channel/UCtak5IDFnWfSyVesnJnG3Mg/featured">Recent Advances of Deep Learning in Computer Vision</a> (Invited short course at University of Sao Paulo, Brazil)</li>
<li>[Spring 2018] <a href="http://people.tamu.edu/~atlaswang/18CSCE633.html">TAMU CSCE 633: Machine Learning</a></li>
<li>[Fall 2017] <a href="http://people.tamu.edu/~atlaswang/17CSCE689.html">TAMU CSCE 689: Machine Learning Methods in Computer Vision</a></li>
</ul>
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<h2>Codes</h2>
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<ul>
<li><a href="https://github.com/VITA-Group">https://github.com/VITA-Group</a></li>
</ul>
</div>
</div>
<div class="section-title" style="margin-bottom: 30px">
<h2>Other Softwares</h2>
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<div class="trend-entry d-flex">
<div class="trend-contents">
<ul>
<li>GaLore (ICML'24) has been integrated into HuggingFace, PyTorch, LLaMA-Factory, FedML, Axolotl, and bitsandbytes</li>
<li>H<sub>2</sub>O (NeurIPS'23) has been integrated into DeepSpeed by Microsoft, and Llama-Recipes by Meta</li>
<li>Our three popular image enhancement algorithms: AOD-Net, EnlightenGAN, and DeblurGAN-V2, are included into the open-source GNU Image Manipulation Program toolbox <a href="https://github.com/kritiksoman/GIMP-ML?fbclid=IwAR2ZcF0oKKItGQQFuxfvFxAfDOCW8FoEDISzkoFOmT130Vo7bQCcONJqbgg">(GIMP-ML)</a>, as <a href="https://www.youtube.com/watch?v=VWl6tyylO50&list=PLo9r5wFmpD5dRfeIthwuL52eNdXthRE7V&index=6&ab_channel=KritikSoman">deep-dehazing</a>, <a href="https://www.youtube.com/watch?v=SHrEWMWZ0dE&list=PLo9r5wFmpD5dRfeIthwuL52eNdXthRE7V&index=3&ab_channel=KritikSoman">enlighten</a>, and <a href="https://www.youtube.com/watch?v=adgHtu4chyU&list=PLo9r5wFmpD5dLWTyo6NOiD6BJjhfEOM5t&index=3&ab_channel=KritikSoman">deblur</a> plugins</li>
<li>DeblurGAN-V2 is also implemented by <a href="https://docs.openvino.ai/latest/omz_models_model_deblurgan_v2.html">Intel OpenVINO toolkit</a></li>
<li>DeepFont, an Adobe Photoshop built-in feature, as one of its leading contributors. <a href="https://helpx.adobe.com/photoshop/how-to/match-font-image.html">[Official Photoshop Manual]</a></li>
<li>Distributed Machine Learning (DML) ToolBox, as part of <a href="http://msrccs.github.io/Prajna/">Microsoft Prajna</a></li>
<li>Dehazing algorithms integrated in the Computer Vision Emergency Response (CVER) toolkit [by Pritish Uplavikar and Ryan Wells] <a href="http://cver.hrail.crasar.org/">[Webpage]</a></li>
</ul>
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