lucalanzendoerfer.ch

Website review lucalanzendoerfer.ch

 Generated on February 21 2026 04:10 AM

Old data? UPDATE !

The score is 51/100

SEO Content

Title

Luca Lanzendörfer

Length : 17

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Description

Length : 0

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Keywords

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Og Meta Properties

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Property Content
title Homepage
type article
url https://lucalanzendoerfer.com/
site_name Luca Lanzendörfer
description Luca Lanzendörfer lanzendoerfer at ethz.ch PhD student at ETH Zurich I'm currently working as a PhD student at ETH Zurich, advised by Prof. Roger Wattenhofer. My work focuses mainly on applications of

Headings

H1 H2 H3 H4 H5 H6
1 3 6 8 0 0
  • [H1] Luca Lanzendörfer
  • [H2] lanzendoerfer at ethz.ch
  • [H2] I’m currently working as a PhD student at ETH Zurich, advised by Prof. Roger Wattenhofer. My work focuses mainly on applications of Deep Learning. Previously, I worked as a Machine Learning Engineer on Natural Language Processing, Computer Vision and Recommender System solutions in Zurich and on self-driving cars in Silicon Valley. I received my graduate degree at ETH Zurich in Computer Science focused on Visual Computing and Machine Learning.
  • [H2] Previous Projects
  • [H3] PhD student at ETH Zurich
  • [H3]
  • [H3] YOLO-ing the Visual Question Answering Baseline
  • [H3] Giving Matrix Factorization A Boost
  • [H3] Twende!
  • [H3] Water jets with divergence-free SPH
  • [H4] Project for the Deep Learning course of 2017 at ETH Zurich.
  • [H4] Abstract- We propose a model for Visual Question Answering (VQA) based on iBOWIMG. Our model uses image features with attention extracted from InceptionV3 as well as object features extracted from the VQA dataset using YOLO object detection. Our model is able to achieve a competitive score on the VQA v1 test-dev scoreboard. Furthermore, we analyse shortcomings of the dataset and explore the current state of VQA.
  • [H4] Project for the Computational Intelligence Lab of 2017 at ETH Zurich.
  • [H4] Abstract- Collaborative Filtering methods have become widely used in consumer oriented e-commerce through different matrix factorization methods. We demonstrate how Collaborative Filtering methods based on matrix factorization can be further improved by boosting many specialized SVD and Neural Network approaches to obtain a competitive score on the CIL dataset.
  • [H4] Project for the Game Programming Lab of 2017 at ETH Zurich.
  • [H4] Abstract- A 2D top-down split screen multiplayer racing game. The game features pixel art graphics and contains various features that make multiplayer fun and engaging. Additionally, to further increase replayability we designed a formal grammar to procedurally generate race tracks. Programmed using MonoGame Engine in C# to run on Windows PC and Microsoft Xbox.
  • [H4] Project for the Physically-based Simulation course of 2016 at ETH Zurich.
  • [H4] Abstract- Simulation of a photorealistic fountain water show using a variation of Smoothed Particle Hydrodynamics called PCISPH. We created a custom implementation of Marching Cubes for the surface reconstruction. Visualization was done using the physically-based Mitsuba renderer. We simulated 1 mio. particles for around 100’000 timesteps on the ETH Euler compute cluster. Each reconstructed surface contains 4 mio. vertices and 10 mio. faces and we ray-traced around 250 mio. rays per frame.

Images

We found 5 images on this web page.

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Text/HTML Ratio

Ratio : 6%

This page's ratio of text to HTML code is below 15 percent, this means that your website probably needs more text content.

Flash

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Iframe

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URL Rewrite

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Underscores in the URLs

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In-page links

We found a total of 8 links including 2 link(s) to files

Anchor Type Juice
Skip to content Internal Passing Juice
ETH Zurich External Passing Juice
Zurich External Passing Juice
Silicon Valley External Passing Juice
YOLO-ing the Visual Question Answering Baseline External Passing Juice
Giving Matrix Factorization A Boost External Passing Juice
Twende! External Passing Juice
Water jets with divergence-free SPH External Passing Juice

SEO Keywords

Keywords Cloud

using vqa mio learning visual features matrix eth zurich project

Keywords Consistency

Keyword Content Title Keywords Description Headings
zurich 8
eth 8
learning 4
using 4
mio 4

Usability

Url

Domain : lucalanzendoerfer.ch

Length : 20

Favicon

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Printability

We could not find a Print-Friendly CSS.

Language

Good. Your declared language is en.

Dublin Core

This page does not take advantage of Dublin Core.

Document

Doctype

HTML 5

Encoding

Perfect. Your declared charset is UTF-8.

W3C Validity

Errors : 0

Warnings : 0

Email Privacy

Great no email address has been found in plain text!

Deprecated HTML

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Speed Tips

Excellent, your website doesn't use nested tables.
Too bad, your website is using inline styles.
Too bad, your website has too many CSS files (more than 4).
Too bad, your website has too many JS files (more than 6).
Perfect, your website takes advantage of gzip.

Mobile

Mobile Optimization

Apple Icon
Meta Viewport Tag
Flash content

Optimization

XML Sitemap

Great, your website has an XML sitemap.

https://lucalanzendoerfer.com/wp-sitemap.xml

Robots.txt

http://lucalanzendoerfer.ch/robots.txt

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Analytics

Missing

We didn't detect an analytics tool installed on this website.

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PageSpeed Insights


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