added ucu seminar

_news/ucuseminar.md

@@ -0,0 +1,8 @@
+---
+layout: post
+date:   2024-11-19 08:30:00
+inline: true
+---
+
+[Ukrainian Catholic University](https://ucu.edu.ua/en/) (UCU) launched a series of online and in-person meet-ups on the topic of Responsible AI, in collaboration with the **Center for Responsible AI** at NYU. The first event featured [Denys Herasymuk](https://airesponsibly.net/people/denys/), one of the first research fellows in the [#RAIforUkraine](https://airesponsibly.net/RAIforUkraine/) program, who shared his personal experience as well as the results of his research. The event attracted a strong turnout! [Read more details here](/news_events/2024/ucu-seminars).
+

_posts/2024-11-19-ucu-seminars.md

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+---
+layout: post
+title:  Meetup Series @UCU on Responsible AI
+date:   2024-11-19 12:00:00
+description: Ukrainian Catholic University (UCU) launched a series of online and in-person meet-ups on the topic of **Responsible AI**, in collaboration with the **Center for Responsible AI** at NYU. The first event featured Denys Herasymuk, one of the first research fellows in the \#RAIforUkraine program, who shared his personal experience as well as the results of his research. The event attracted a strong turnout! Read more details here.
+tags: 
+categories: seminar 
+event: true
+preview: /assets/img/events/RAIforUkraine_Thumb_Meetup1.jpg
+---
+
+<div class="row mt-3">
+    <div class="col-sm mt-10 mt-md-0">
+        {% include figure.html path="/assets/img/events/RAIforUkraine_Meetup1.jpg" class="img-fluid rounded z-depth-1" %}
+    </div>
+</div>
+<br>
+
+[Ukrainian Catholic University](https://ucu.edu.ua/en/) (UCU) launched, in collaboration with the **Center for Responsible AI** at NYU, a long-awaited series of meet-ups on the topic of Responsible AI.
+
+The goal was to invite individuals who contribute to the advancement of responsible AI development and its practical applications. The first meeting was led by [Denys Herasymuk](https://airesponsibly.net/people/denys/), one of the first research fellows in the [#RAIforUkraine](https://airesponsibly.net/RAIforUkraine/) program. He shared his personal experiences along with the findings from his research, which he conducted in collaboration with his mentors.
+
+
+### Responsible Approaches to Missing Value Imputation and Model Selection in Machine Learning
+
+
+**Abstract:** 
+The talk will cover my experience in the “RAI for Ukraine” program and highlight our research on responsible AI, focusing on advancements aimed at ensuring the stability and fairness of machine learning models. I will begin by sharing key insights and accomplishments from my time in the program, followed by a brief introduction to model stability and uncertainty quantification. Next, I will highlight the challenges of incorporating these dimensions of model performance into the model selection process. Building on this foundation, I will introduce our comprehensive software library for model auditing and responsible model selection, called Virny, along with an interactive tool called VirnyView. Finally, I will present our Shades-of-Null benchmark for responsible missing value imputation. This large-scale empirical study, involving 23,940 experimental pipelines, provides a comprehensive and rigorous evaluation of various families of imputation methods on a wide range of evaluation metrics, in plausible and socially meaningful missingness scenarios.
+
+The talk will be based on these two papers:
+- Denys Herasymuk, Falaah Arif Khan, and Julia Stoyanovich: [Responsible Model Selection with Virny and VirnyView](https://dl.acm.org/doi/10.1145/3626246.3654738) (SIGMOD’24);
+- Falaah Arif Khan, Denys Herasymuk, Nazar Protsiv, Julia Stoyanovich: [Still More Shades of Null: A Benchmark for Responsible Missing Value Imputation](https://arxiv.org/abs/2409.07510) (under submission to VLDB’25).
+
+A big thank you to **Tetiana Zakharchenko** for co-hosting and organizing the event!
+
+The next meet-up is set for **November 28 at 6:00 PM in Kyiv**, and it will feature **Mariana Romanyshyn**, Area Tech Lead at **Grammarly**. Stay tuned for further details!
+
+
+<br>
+<br>

_site/people/julia/index.html

@@ -120,6 +120,8 @@
                   <div class="dropdown-divider"></div>
                   <a class="dropdown-item" href="/education/#playbook">Algorithmic transparency</a>
                   <div class="dropdown-divider"></div>
+                  <a class="dropdown-item" href="/education/#algorithmia">Algorithmia</a>
+                  <div class="dropdown-divider"></div>
                   <a class="dropdown-item" href="/education/#weareai">We are AI</a>
                   <div class="dropdown-divider"></div>
                   <a class="dropdown-item" href="/education/#comics">Comics</a>
@@ -1017,12 +1019,12 @@ <h1 class="post-title">Julia Stoyanovich</h1>
         <div id="DBLP:journals/corr/abs-2401-16744" class="col-sm-8">
 
           <!-- Title -->
-          <div class="title">ShaRP: Explaining Rankings with Shapley Values</div>
+          <div class="title">ShaRP: A Novel Feature Importance Framework for Ranking</div>
           <!-- Author -->
           <div class="author">
 
 
-          Venetia Pliatsika, João Fonseca, Tilun Wang, and Julia Stoyanovich</div>
+          Venetia Pliatsika, João Fonseca, Kateryna Akhynko, Ivan Shevchenko, and Julia Stoyanovich</div>
 
           <!-- Journal/Book title and date -->
 
@@ -1039,8 +1041,8 @@ <h1 class="post-title">Julia Stoyanovich</h1>
           <!-- Hidden bibtex block -->
           <div class="bibtex hidden">
             <figure class="highlight"><pre><code class="language-bibtex" data-lang="bibtex"><span class="nc">@article</span><span class="p">{</span><span class="nl">DBLP:journals/corr/abs-2401-16744</span><span class="p">,</span>
-  <span class="na">author</span> <span class="p">=</span> <span class="s">{Pliatsika, Venetia and Fonseca, Jo{\~{a}}o and Wang, Tilun and Stoyanovich, Julia}</span><span class="p">,</span>
-  <span class="na">title</span> <span class="p">=</span> <span class="s">{ShaRP: Explaining Rankings with Shapley Values}</span><span class="p">,</span>
+  <span class="na">author</span> <span class="p">=</span> <span class="s">{Pliatsika, Venetia and Fonseca, Jo{\~{a}}o and Akhynko, Kateryna and Shevchenko, Ivan and Stoyanovich, Julia}</span><span class="p">,</span>
+  <span class="na">title</span> <span class="p">=</span> <span class="s">{ShaRP: A Novel Feature Importance Framework for Ranking}</span><span class="p">,</span>
   <span class="na">journal</span> <span class="p">=</span> <span class="s">{CoRR}</span><span class="p">,</span>
   <span class="na">volume</span> <span class="p">=</span> <span class="s">{abs/2401.16744}</span><span class="p">,</span>
   <span class="na">year</span> <span class="p">=</span> <span class="s">{2024}</span><span class="p">,</span>
@@ -1050,7 +1052,7 @@ <h1 class="post-title">Julia Stoyanovich</h1>
   <span class="na">timestamp</span> <span class="p">=</span> <span class="s">{Tue, 06 Feb 2024 14:15:49 +0100}</span><span class="p">,</span>
   <span class="na">biburl</span> <span class="p">=</span> <span class="s">{https://dblp.org/rec/journals/corr/abs-2401-16744.bib}</span><span class="p">,</span>
   <span class="na">bibsource</span> <span class="p">=</span> <span class="s">{dblp computer science bibliography, https://dblp.org}</span><span class="p">,</span>
-  <span class="na">keywords</span> <span class="p">=</span> <span class="s">{working,ranking,explainability,transparency}</span>
+  <span class="na">keywords</span> <span class="p">=</span> <span class="s">{working,ranking,explainability,transparency,RAIforUkraine}</span>
 <span class="p">}</span></code></pre></figure>
           </div>
         </div>