Luis Salamanca

Luis Salamanca

Lead Data Scientist
Academia
(Alumni)

Luis is originally from Spain, where he completed his bachelor's studies in Electrical engineering, and the Ms.C. on signal theory and communications, both at the University of Seville. During his Ph.D. he started focusing on machine learning methods, more specifically message passing techniques for channel coding, and Bayesian methods for channel equalization. He carried it out between the University of Seville and the University Carlos III in Madrid, also spending some time at the EPFL, Switzerland, and Bell Labs, USA, where he worked on advanced techniques for optical channel coding. When he completed his Ph.D. in 2013, he moved to the Luxembourg Center on Systems Biomedicine, where he switched his interest to neuroscience, neuroimaging, life sciences, etc., and the application of machine learning techniques to these fields. During his 4 and a half years there as a Postdoc, he worked on many different problems as a data scientist, encompassing topics such as microscopy image analysis, neuroimaging, single-cell gene expression analysis, etc. He joined the SDSC in April 2018.  As Lead Data Scientist, Luis coordinates projects in various domains. Several projects focus on the application of natural language processing and knowledge graphs to the study of different phenomena in social and political sciences. In the domains of architecture and engineering, Luis is responsible for projects centered on the application of novel generative methods to parametric modeling. Finally, Luis also coordinates different projects in robotics, ranging from collaborative robotic construction to deformable object manipulation.

Projects

LEAP

In Progress
LEArning to Print – towards data-driven real-time predictions for additive manufacturing

FastPoints2Mesh

In Progress
Data-Driven Inference of Mesh-based Representations for Deformable Objects from Unstructured Point Clouds

EvolvingDemocraSci

In Progress
Advancing parliamentary data analysis

DAAAD_Bridges

Completed
Domain-aware-AI Augmented Design of Bridge Structures
Energy, Climate & Environment

SEMIRAMIS

Completed
AI-augmented Architectural Design
Energy, Climate & Environment

NLP

Narratives in Law and Politics: A Computational Linguistics Approach
Digital Administration

DemocraSci

Completed
A research platform for Data-Driven Democracy Studies in Switzerland
Digital Administration

Citizen-Controlled

Completed
Citizen-controlled Data Science for Multiple Sclerosis Research
Biomedical Data Science

TE4med

Completed
Transposcriptome-based identifier for precision medicine
Biomedical Data Science

Publications

Mentioned in

November 1, 2022

SEMIRAMIS | A new approach to AI-Augmented architectural design

SEMIRAMIS | A new approach to AI-Augmented architectural design

As the world’s cities continue to grow, land is becoming increasingly scarce. However, open space is vital in urban areas. Semiramis is a new approach to AI-augmented architectural design, allowing designers a quick and easy selection of feasible performance values and a qualitative evaluation of the generated geometries.
December 21, 2018

A trip through Swiss politics and history

A trip through Swiss politics and history

Our aim is to create a database of who said what and when in both chambers of the Swiss parliament over the past 127 years. The Swiss Federal Archives recently carried out the digitalization of the proceedings of both the National Council and the Council of States. Thanks to these efforts, we can now openly access over 40,000 documents pertaining to all votes, speeches, laws, amendments to laws, etc., from 1891 to the present day.

Case Studies

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