Anaïs Berkes

Hey there! I am a PhD candidate in the Energy & Environment Group, led by Professor Srinivasan Keshav, at the Department of Computer Science & Technology, University of Cambridge. My research, funded by the Gates Cambridge Trust, focuses on leveraging Machine Learning for the decarbonisation of buildings.

Previously, I have explored the design and operation of sustainable energy systems for residential homes, incorporating technologies such as solar PV, stationary batteries, and bidirectional EVs. My work led to the development of SOPEVS, an innovative algorithm that personalises the joint sizing and operation of solar PV and storage for single-family homes. Additionally, I created SPAGHETTI, a synthetic data generation tool for modelling EV usage traces.

Currently, my research is centred on combining reinforcement learning with decision transformers to optimise the operation of HVAC systems, energy storage and EV charging in commercial buildings. I hold a degree in Computer Science from ETH Zürich.

Scholarships & Awards

Gates Cambridge Trust
The most prestigious postgraduate scholarship at the University of Cambridge, funded by the Bill and Melinda Gates Foundation. (October 2023 - September 2027)
Heidelberg Laureate
The Heidelberg Laureate Forum brings together the recipients of the most prestigious awards in mathematics and computer science with 200 selected exceptional young researchers from all over the world. (2024)
Lauréate du Concours Général
The Concours Général is an academic competition held every year between students in French High schools all over the world. Students who show great ability in one field are selected by their headmaster to represent the school internationally. Winners of the competition become life-long members of the Association. (2018)

Education

University of Cambridge, Jesus College
PhD in Computer Science (October 2023 - Present)
Developing a holistic AI-driven framework for the decarbonisation of buildings.
ETH Zürich
BSc Computer Science (2019 - 2023) Focus: Machine Learning, Computer Systems.

Working Experience

Wingman Campus Fund
Zürich, Switzerland
Partner (September 2021 - October 2022) Part of the founding partners of the Campusfund, investing in student founders from ETH, EPFL and HSG.
Archlet
Zürich, Switzerland
Quality Assurance Engineer (June 2021 - September 2022) Working in the Product Team on the automation of end-to-end tests for the Archlet platform. Oversight of the software release processes.
ETH Zürich
Zürich, Switzerland
Teaching Assistant for the Computer Science Network of Women (CSNOW) (2021) Teaching an introductory programming course to female High school students.
ETH Zürich
Zürich, Switzerland
Teaching Assistant for Digital Design and Computer Architecture (Feb 2021 - July 2021) Teaching labs for the course Digital Design and Computer Architecture run by the SAFARI Research Group and led by Professor Onur Mutlu. I taught around 100 students on a weekly basis, correcting lab reports and supervising labs. I have also prepared and taught the exam preparation course for the entire student cohort.
Ghelia - Sony Computer Science Laboratories
Tokyo, Japan
Machine Learning Software Development Intern (March 2019 - June 2019) R&D Section of the Professional System Solutions Division. I created a prototype for an adjusted WaveGAN implementation for synthesizing raw audio using generative adversarial networks. This prototype was later integrated into a larger AI-based solution used by Ghelia´s customers.

Publications

SOPEVS: Sizing and Operation of PV-EV-Integrated Modern Homes A. Berkes, S. Keshav
ACM E-Energy'24 (2024)
SPAGHETTI: a synthetic data generator for post-Covid electric vehicle usage A. Berkes, S. Keshav
Energy Informatics, 7(1), 1-21. (2024)

The SOPEVS Webapp is available here.

Talks

SOPEVS: Sizing and Operation of PV-EV-Integrated Modern Homes Energy and Environment Group, University of Cambridge
24th of May 2024
Reimagining Residential Microgrids: Policy Implications of Bidirectional Electric Vehicles, Solar Energy and Work-from-Home Trends Energy and Environment Group, University of Cambridge
16th of February 2024
The Optimal Design of PV-EV Integrated Domestic Microgrids - A Post-Pandemic Perspective Energy and Environment Group, University of Cambridge
24th of January 2024
Designing PV-EV integrated Residential Microgrids in the post-COVID World Energy and Environment Group, University of Cambridge
16th of June 2023

Poster

Decarbonising Residential Homes in the UK: Synergy Benefits of PV, EVs and Work-From-Home The Architecture of Green Energy Systems: The Underlying Problem and Its Challenges Poster Session, IMSI Institute, University of Chicago
17th of June 2024 -
Download Poster

Extracurricular Experience

Momentum
Founding Member (September 2021 - Present) Connecting young entrepreneurs with tech and business backgrounds to create a network of like-minded individuals across European universities.
CSNOW – Network of Women in Computer Science at ETH Zürich
Committeee Member and Teaching Assistant (February 2021 - October 2022) CSNOW was founded in 1993 and is part of the Computer Science Department. Women are strongly underrepresented at the department with 15% (see statistics). Our goal is to draw attention to the problematic effects of this unequal gender distribution and to counteract them. To this end, we organise various events and support female students with offers such as the mentoring programme, career workshops, interview series and networking events.
VIS - Verein der Informatik Studierenden an der ETH Zürich
University Policy Committeee (March 2021 - October 2021) The official Association of Computer Science Students at ETH Zurich (VIS) was founded in 1984 and is a professional association of the Association of Students at ETH (VSETH). For the more than 1,900 Bachelor and Master students of Computer Science, Data Science and Computational Biology and Bioinformatics, the VIS is the first point of contact for events, excursions, support during their studies and representation vis-à-vis the Department of Computer Science at ETH Zurich.