-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathinterests.html
74 lines (71 loc) · 4.02 KB
/
interests.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
<!DOCTYPE html>
<html>
<script>
(function(i,s,o,g,r,a,m){i['GoogleAnalyticsObject']=r;i[r]=i[r]||function(){
(i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o),
m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)
})(window,document,'script','https://www.google-analytics.com/analytics.js','ga');
ga('create', 'UA-79723811-1', 'auto');
ga('send', 'pageview');
</script>
<head>
<title>Nikolaos (Nikos) Nikolaou</title>
<!-- link to main stylesheet -->
<link rel="stylesheet" type="text/css" href="/css/main.css">
</head>
<body>
<nav>
<ul>
<li><a href="/">Home</a></li>
<li><a href="/cv">CV</a></li>
<li><a href="/publications">Publications</a></li>
<li><a href="/presentations">Presentations</a></li>
<li><a href="/interests">Interests</a></li>
<li><a href="/students">Students</a></li>
<!--<li><a href="/blog">Blog</a></li>-->
</ul>
</nav>
<div class="container">
<div class="blurb">
<h1>Nikolaos (Nikos) Nikolaou</h1>
<h2>Research Interests</h2>
<p>On the machine learning theory side, my interests revolve around the following:
<ul style="list-style-type:disc;">
<li><b>Causal Inference</b> -- going beyond statistical associations to identifying cause-effect relationships and quantifying effects of interventions</li>
<li><b>Learning Theory & Generalization</b> -- characterizing predictive models whose predictions are good beyond the sample they were trained on; guiding learning algorithms towards producing such models</li>
<li><b>Ensemble Learning</b> -- combining several weaker predictive models to construct stronger ones</li>
<li><b>Information Theory</b> -- quantifying & leveraging the information content of random variables regarding one another</li>
<li><b>Feature Selection</b> -- identifying (ideally minimal subsets of) input variables useful for predicting target variables</li>
<li><b>Model Selection</b> -- comparing predictive models</li>
<li><b>Uncertainty Quantification</b> -- quantifying the uncertainty of predictive models in their predictions</li>
<li><b>Multi-modal Data Fusion</b> -- methods for leveraging information from data coming from multiple sources</li>
<li><b>Model Interpretability</b> -- obtaining explanations for predictive models' predictions and/or inner workings</li>
<li><b>Resource-efficient Learning</b> -- methods for making machine learning algorithms -especially deep neural networks- more data-efficient and/or computationally-efficient</li>
</ul>
</p>
<p>The application areas I worked or I am currently working in, include:
<ul style="list-style-type:disc;">
<li>Emotion recognition from music</li>
<li>Photovoltaic power generation (Predicting effects of partial shading, modelling solar irradiance variability) </li>
<li>Adaptive computer memory controller design</li>
<li>Earth observation</li>
<li>Astronomy & Planetary Science (exoplanet detection, exoplanet characterization, galaxy classification, inferring galactic redshift)</li>
<li>Nuclear Fusion (predicting tritium breeding, accelerating fusion reactor plasma simulations)</li>
<li>Pharmaceutics & Healthcare (medical imaging, bioinformatics focusing on survival modelling for oncology)</li>
</ul>
</p>
</div><!-- /.blurb -->
</div><!-- /.container -->
<footer>
<ul>
<li><a href="mailto:[email protected]">Email</a></li>
<li><a href="https://github.com/nnikolaou">Github</a></li>
<li><a href="https://www.linkedin.com/in/nikos-nikolaou-60931986/">LinkedIn</a></li>
<li><a href="https://www.researchgate.net/profile/Nikos_Nikolaou5">Researchgate</a></li>
<li><a href="https://scholar.google.com/citations?user=R6b6Rp8AAAAJ&hl=en">Google Scholar</a></li>
<li><a href="https://www.ucl.ac.uk/astrophysics/people/dr-nikolaou-nikolaos-research-associate">Contact</a></li>
<li><a href="http://www.cs.man.ac.uk/%7Enikolaon/index.html">Manchester Page</a></li>
</ul>
</footer>
</body>
</html>