About me

 Applied Scientist

Jesus Lago​

I am an applied scientist at Amazon working on forecasting and ranking algorithms to predict the success of deals on the Amazon marketplace and rank them accordingly.

In addition to my job in forecasting research,  I carry out research and I co-supervise a PhD student in the area of AI and the energy transition, another research topic that I am interested in.

I hold a PhD degree from TU Delft in that same topic, i.e. AI applied to the energy transition, and my PhD research on this domain has received several awards.

I am the developer of optidef, a Latex library for defining optimization problems, and of the epftoolbox python library, the first open-access library for driving research in electricity price forecasting.

Experience

Applied Scientist

Applied Scientist at Amazon working on forecasting and ranking algorithms.

Research Scientist

Research scientist in AI techniques to facilitate the energy transition and the integration of renewable sources.

Research and teaching assistant

Research assistant in the area of optimization and optimal control. Teaching assistant in two M.Sc. courses.

Education

Ph.D. - AI for energy systems & markets

PhD in data science in the context of energy systems and energy markets with the end goal of advancing the energy transition through AI.

M.Sc. - Microsystems engineering

Masters degree in Microsystems engineering with a major in optimization and optimal control.

B.Sc.- Electronics, Control and Robotics

Five-year bachelor degree in Electronics, Automatic Control and Robotics

Awards

  • IEEE-CIS technical challenge on energy prediction from smart meter data
    Third-place award in the competition of the IEEE-CIS (Computational Intelligence Society) on prediction energy consumption from smart meters.

    Competition | Award

    November 2020

  • Cum Laude in PhD Graduation
    Cum Laude recognition for my PhD research.

    Certificate

    September 2020

  • Applied Energy Highly Cited Paper Award 2020
    Award for one of the most cited papers in Applied Energy in 2020.

    Announcement | Award

    August 2020

  • RTE forecasting competition on French grid load
    Third-place award in an international forecasting competition organized by RTE (the French TSO) where participants had to predict in real-time the day-ahead hourly electricity consumption in France for a period of 14 days.

    Award

    April 2018