Gabriel joined the TIS lab in 2021 as a post-doctoral researcher to develop robust methods for machine learning. He completed his doctoral studies in econometrics at the University of St. Gallen where his dissertation focused on methods for predictive and causal machine learning. He holds a MSc in economics from the Vienna University of Economics and Business and a Bc in management from the Comenius University in Bratislava. Prior to joining EPFL he worked at the Swiss Institute for Empirical Economic Research on topics in machine learning and causal inference.
– PhD, to be awarded on 2/2022 – University of St. Gallen
– MSc, Vienna University of Economics and Business
– Bc, Comenius University in Bratislava
Maximilian joined the TIS lab in 2018 to investigate the impact of artificial intelligence (AI) on business strategy. Prior to EPFL, he graduated at the top of his class from University College London (UCL) with a Bachelor in Management Science. He subsequently studied theoretical computer science with a focus on deep neural networks for natural language processing at the University of Oxford, graduating with a Master’s degree in 2018. At EPFL, Maximilian empirically analyses how AI transforms different aspects of business, including strategy, competition and innovation.
– MSc, University of Oxford – Computer Science
– BSc, University College London – Management Science
Dr. Giovanni Liotta, Ph.D.
– Alumni –
Giovanni’s research examines entrepreneurship, venture capital financing and cleantech market dynamics. He holds a Bachelor and a Master Degrees in Management and Production Engineering from Politecnico di Milano (Italy). At EPFL he wrote his dissertation on venture capital investments in and green-tech funding. He has also worked as a business analyst for a supply chain consulting firm. After graduating from EPFL with his Ph.D., he continued on as a Post-doctoral researcher in the TIS lab working on Data Science projects and the prediction of IPO market valuation and under-pricing.
– PhD, EPFL – Strategic Management
– MA, Politecnico di Milano – Production Engineering
– BA, Politecnico di Milano – Management
Dr. Jeffrey Kuhn, Ph.D., J.D.
– Alumni –
Jeff Kuhn was a visiting doctoral student with the TIS Lab and a past and current collaborator on a range of projects. Jeff’s research and teaching interests include technological innovation, intellectual property, corporate strategy and entrepreneurship. Much of his research focuses on the causal impact of the patent system on firm decisions and outcomes. Prior to graduate school, he worked as a U.S. patent attorney for several years and is an active member of both the California State Bar and the United States Patent Bar. He applies his background as an attorney to ground his research in the functioning of institutions.
– PhD, University of California at Berkeley – Haas School of Business
– JD, University of California at Berkeley – Berkeley Law
– BS, Purdue University – Mathematics & Computer Science
– BA, Purdue University – Psychology
Dr. Omid Shahmirzadi, Ph.D.
– Alumni –
Omid completed his MA and PhD in computer science with a focus on distributed systems. After graduation, he turned his focus to data science, big data analysis, and statistical methods. He completed a post-doc at the Swiss Institute of Bioinformatics (SIB) where he worked on the statistical modeling of genetic data, and then joined the TIS lab at EPFL as a post-doctoral researcher working on machine learning and predictive analytics, with applications in business, econometrics and finance.
– PhD, EPFL – Computer Science
– MS, KTH – Computer Science
– Alumni –
Jonathan joined the TIS lab from the EPFL Data Science Masters Program to develop on a specialized word-embedding for the legal space. Building on the FastText algorithm from Facebook, FastLaw is a law-specific word embedding model trained on a large corpus of law-related text data provided by the Caselaw Access Project (CAP) from Harvard University. FastLaw was computed using Spark, a distributed cluster-computing framework, and the FastText algorithm.
Project Download: https://github.com/jbesomi/fastlaw
– MA, EPFL – Data Science (expected in 2021)
– BA, EPFL – Communication Systems
– Alumni –
As part of his Master’s thesis at EPFL, Christian designed and developed a big data pipeline in Spark to predict technology trends in the corpus of US patents. He defined a framework for extracting a density time series from the patenting space and implemented machine learning techniques to forecast changes in the space.
– MA, EPFL – Computer Science
– BS, EPFL – Computer Science
Notable Student Projects
Implementation of supervised methods and statistical models for Demand Forecasting of a transportation and supply chain leader.
Predictive analytics for airline flight delays.
Yasmine El Hafdi
Skills obsolescence and human capital investment
in the development of data-driven decision making.
Investment, commitment, and adoption of AI
in the pharmaceutical industry and clinical trials.
Opportunities for Data Science and the prediction of the response times
for the management of fire services.
Théophile de Cazenove
The management and valuation of Machine Learning projects.
Using the Internet of Things to enhance
customer relationship management (CRM).
The documentation of software in an agile environment.
Louis de Guyenro
Key success factors in private equity-backed buy and builds:
A case study of four deals.
Incorporating carbon emissions as a machine learning optimization
criterion in supply chain order planning.
Goal-oriented active learning
for the optimization of invoice relabelling and procurement.
Applied Data Analytics: A case study on demand forecasting
and replenishment for a large Swiss retailer.
The classification of Atrial Fibrillation in ECG signals
with machine learning techniques.
Strategic mechanisms to commercialize technology in a context of technological disruption.
Predictive analytics for airline flight delays:
Improving customer satisfaction during disruptions.
A text-analysis system to parse and disambiguate
financial disclosure forms.
The impact of remote and founding conditions
on the performance of virtual teams.
Why is it difficult to launch Big Data projects in Switzerland?
The positioning of African e-commerce conglomerates
to compete against mature, giant internet companies such as Amazon.
Design considerations for data visualization in online dashboards.