Student projects ‒ LHST ‐ EPFL

This page lists the projects currently open at the Laboratory for the History of Science and Technology (LHST). If you are interested in working on one of the projects listed below, please write directly to the contact person, with Prof. Baudry cc’ed in your email.

The project descriptions are only brief outlines and we are in general flexible about the particulars.

This project, in collaboration with the Institute of Psychology (IP) from the University of Lausanne (UNIL) is the final part of the SNSF research project MICE conducted by Prof. Rémy Amouroux. The aim of MICE is to produce the first transnational historical study of the reception and indigenization of behavior therapy in the Francophone context between the early 1960s and the 1990s.

This student project addresses the circulation and reception of psychotherapy in French-speaking Europe through distant reading of two newsmagazines: Psychology Today and its French variation Psychologie. The goal is to trace the role played by the specialized press in disseminating behavior therapy to a large audience.

The corpus includes two magazines in French and English, available in bulk downloads with different OCR quality. These are: Psychology Today (1967-1971) and Psychologie (1970-1980). The goal of the project will be to observe whether there is a progressive rising of new psychotherapeutic tools and whether this phenomenon is concomitant/related to the rise of criticism towards psychoanalysis. The project will attempt to establish whether it is possible to observe coherent clusters of: critique of psychoanalysis; psychotherapy and new psychotherapeutic tools (ie. cognitive behavioral therapy).

This project will be done in collaboration with Prof. Jérôme Baudry (EPFL), Prof. Rémy Amouroux and Dr. Elsa Forner (UNIL).

Project type: semester project or master’s thesis.

Prerequisites: Prior experience in text mining; solid data analysis skills; knowledge in NLP and computational linguistics; interest in history and social sciences a plus; language skills in both English and French.

Contact: [email protected].

The project investigates how digital tools can be used to study the dynamics of innovation in science and technology, from the eighteenth century to today. Innovation—the production of the new—is often said to be radical and path-breaking; yet, what can history teach us about the actual rhythms of innovation? Looking at past centuries of technological development, do we see continuity or discontinuity? Can we identify waves of innovation (and imitation)? How new is the new and how did people strategically describe and draw technology to present it as new? How did inventors in the past address the dangers and potential negative consequences of their activity? Analyzing and/or building a corpus of patents of invention, you will choose and apply state-of-the-art NLP/machine learning methods and/or use your statistical and data science knowledge.

Below are some more detailed examples of themes for semester projects and master’s theses, but you can also propose your own questions. You will work with an interdisciplinary team of historians and computer scientists.

– Classifying patents and technology: Categorizing innovation is difficult. Categories are static, innovation is dynamic. Innovation can and does happen in-between established categories. Yet, it is very important to categorize patents, because the dynamic of innovation and the logic of taking out patents differ according to technology and to industry. However, such labels are usually missing from the datasets. The availability of the textual description of patents presents a great opportunity to address the challenge of classification.

– Technological risk & safety: Sometimes, bridges collapse, furnaces and steam engines explode, electrical sparks cause fires or kill people. Did historical patents discuss the invention being potentially dangerous? What did they say about this issue? How did that evolve over time? Do these concerns cluster in certain technologies / industries?

– Irresponsible innovation: While many of the negative consequences of technology are classic examples of unintended consequences (say, climate change), this is not always the case. For instance, when it was decided in the early 1920s to add tetraethyl lead to gasoline to increase octane, the toxic effects of lead were well known. Do historical patents show traces of other examples of innovation that could demonstrably have been concerning at the time? How common or uncommon are those patents?

– Extending the geographical scope of possible investigations: Most studies relying on the full text of historical patents rely on those issued by the United States of America, because of their easy availability in digitized form. To investigate similar questions for other countries, the available scanned material would need to be prepared and processed to be turned into clean digital full text, and results from off-the-shelf OCR software are of varying and sometimes questionable quality. This would be an interesting challenge for people interested in computer vision and OCR, and in bringing about a less one-sided view of innovation.