News | Aylin Naebzadehhttps://aylinnaebzadeh.github.io/news/NewsWowchemy (https://wowchemy.com)en-usThu, 08 Aug 2024 00:00:00 +0000https://aylinnaebzadeh.github.io/media/icon_hu60b00facb642d5c4a6e81d28c27a98a7_27079_512x512_fill_lanczos_center_3.pngNewshttps://aylinnaebzadeh.github.io/news/<link>https://aylinnaebzadeh.github.io/news/newslist/</link><pubDate>Thu, 08 Aug 2024 00:00:00 +0000</pubDate><guid>https://aylinnaebzadeh.github.io/news/newslist/</guid><description><h3 id="news">News</h3> <div style="text-align: justify;"> <ul> <li>[8/2026] Our paper, <strong>&ldquo;Broadband Wide Field of View Imaging with Computational Mirrors&rdquo;</strong> has been accepted as an <strong>oral</strong> presentation at the European Conference on Computer Vision (<a href="https://lnkd.in/gYcTBbyi" target="_blank" rel="noopener">ECCV'26</a>).</li> <li>[5/2026] Our paper, <strong>&ldquo;CARD: Correlation Aware Restoration with Diffusion&rdquo;</strong> has been accepted at the IEEE/CVF Conference on Computer Vision and Pattern Recognition (<a href="https://openaccess.thecvf.com/content/CVPR2026/papers/Naebzadeh_CARD_Correlation_Aware_Restoration_with_Diffusion_CVPR_2026_paper.pdf" target="_blank" rel="noopener">CVPR'26</a>).</li> <li>[3/2026] I joined <span style="color: #d76bc3;">Apple </span> in Cupertino, CA as a <strong>Data and Machine Learning Intern</strong> for Spring and Summer 2026.</li> <li>[3/2026] I successfully passed my <strong>PhD Qualifying Exam</strong> and officially advanced to candidacy!</li> <li>[11/2025] Our paper, <strong>&ldquo;MMP: Towards Robust Multi-Modal Learning with Masked Modality Projection&rdquo;</strong> has been accepted at the 2025 IEEE International Conference on Big Data (<a href="https://ieeexplore.ieee.org/abstract/document/11401652" target="_blank" rel="noopener">BigData'25</a>).</li> <li>[11/2025] Our paper, <strong>&ldquo;TDiff: Thermal Plug-and-Play Prior with Patch-Based Diffusion&rdquo;</strong> has been accepted at the 1st ACM International Workshop on Thermal Sensing and Computing (<a href="https://dl.acm.org/doi/pdf/10.1145/3737905.3769286" target="_blank" rel="noopener">HotSense'25</a>).</li> </ul> </div></description></item><item><title>Newshttps://aylinnaebzadeh.github.io/news/news/Thu, 08 Aug 2024 00:00:00 +0000https://aylinnaebzadeh.github.io/news/news/ <h3 id="news">News</h3> <div style="text-align: justify;"> <ul> <li> <p>[8/2026] Our paper, <strong>&ldquo;Broadband Wide Field of View Imaging with Computational Mirrors&rdquo;</strong> has been accepted as an <strong>oral</strong> presentation at the European Conference on Computer Vision (<a href="https://lnkd.in/gYcTBbyi" target="_blank" rel="noopener">ECCV'26</a>).</p> </li> <li> <p>[5/2026] Our paper, <strong>&ldquo;CARD: Correlation Aware Restoration with Diffusion&rdquo;</strong> has been accepted at the IEEE/CVF Conference on Computer Vision and Pattern Recognition (<a href="https://openaccess.thecvf.com/content/CVPR2026/papers/Naebzadeh_CARD_Correlation_Aware_Restoration_with_Diffusion_CVPR_2026_paper.pdf" target="_blank" rel="noopener">CVPR'26</a>).</p> </li> <li> <p>[3/2026] I joined <span style="color: #d76bc3;">Apple </span> in Cupertino, CA as a <strong>Data and Machine Learning Intern</strong> for Spring and Summer 2026.</p> </li> <li> <p>[3/2026] I successfully passed my <strong>PhD Qualifying Exam</strong> and officially advanced to candidacy!</p> </li> <li> <p>[11/2025] Our paper, <strong>&ldquo;MMP: Towards Robust Multi-Modal Learning with Masked Modality Projection&rdquo;</strong> has been accepted at the 2025 IEEE International Conference on Big Data (<a href="https://ieeexplore.ieee.org/abstract/document/11401652" target="_blank" rel="noopener">BigData'25</a>).</p> </li> <li> <p>[11/2025] Our paper, <strong>&ldquo;TDiff: Thermal Plug-and-Play Prior with Patch-Based Diffusion&rdquo;</strong> has been accepted at the 1st ACM International Workshop on Thermal Sensing and Computing (<a href="https://dl.acm.org/doi/pdf/10.1145/3737905.3769286" target="_blank" rel="noopener">HotSense'25</a>).</p> </li> </ul> </div>