June Sallou

June Sallou

Assistant Professor in Sustainable Software Engineering

Wageningen University & Resarch

I am currently an Assistant Professor in Sustainable Software Engineering @Wageningen University & Research, in the Information Technology research group. I am curious about Green AI & Software, and Scientific Computing, and I am exploring how to apply Approximate Computing for sustainable (scientific) SE. Looking at the Sustainability in Software Engineering, I aim to help build more sustainable (scientific) software systems, and more specifically Green AI.

Interests
  • Green AI
  • Sustainability in SE
  • Approximate Computing
  • Scientific Modelling
Education
  • PhD in Software Engineering, 2022

    University of Rennes 1, France

  • MSc in Software Engineering, 2018

    University of Rennes 1, France

  • MSc in Bioinformatics, 2017

    University of Rennes 1, France

  • MEng in Agronomy and Environmental Science, 2016

    Bordeaux Sciences Agro, France

Research

I am currently an Assitant Professor in Sustainable Software Engineering in the Information Technology Group @Wageningen University & Research. My main interests lie in Sustainability in AI-enabled Software, and Scientific Computing. I aim at helping developers build more energy-efficient AI software systems. I am also curious about making research data and systems accessible to policymakers and the general public for informed decision making regarding sustainability (in ICT).

Previsouly, I did a Postdoc in Software Engineering @Delft University of Technology, in the SERG research team, under the mentorship of Luís Cruz. I am looking at Sustainability in Software Engineering, and more specifically at how to apply Approximate Computing to build more sustainable/greener (AI-based)(software) systems.

I started my academic journey doing PhD in Software Engineering at the University of Rennes 1. My doctorate was part of a collaboration between the IRISA and OSUR laboratories and reflected the desire to bring software engineering closer to the scientific field of hydrogeology. Thus, I participated in the research activities of the DiverSE and DIMENV@risce teams.

My work dealt with modelling for decision making and flood risk assessment (w.r.t climate change). I applied approximate computing techniques to scientific models in order to make the exploration of simulation and prediction results accessible to decision makers. In my journey to achieve that goal, I received valuable advice from my supervisors Johann Bourcier, Jean-Raynald de Dreuzy and Benoit Combemale.

Overall, my research work mainly focuses on Software Engineering and Sustainability. I am interested in how to apply Approximate Computing to reach more Sustainability in and thanks to Software Engineering.

Publications

(2024). Green AI in Action: Strategic Model Selection for Ensembles in Production. AIware'24.

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(2024). Breaking the Silence: the Threats of Using LLMs in Software Engineering. ICSE'24.

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(2023). Batching for Green AI - An Exploratory Study on Inference. SEAA'23.

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(2023). The Two Faces of AI in Green Mobile Computing: A Literature Review. SEAA'23.

PDF Cite DOI

Teaching

Wageningen University [2024-Present]

  • Programming in Python (INF22306): 2024

TU Delft, The Netherlands [2022-2024]

University of Rennes 1, ISTIC, France [2018-2022]

  • Analysis and Object-Oriented Design: 2019, 2020, 2021
  • Distributed Information Systems: 2019, 2020, 2021
  • Scientific Modelling: 2020
  • Software Architecture & Web Development: 2019

Services

Organisation

Conferences

ICST

  • 2025: Topic Diversity Co-Chair

ICT4S

  • 2024: Co-Chair of the Doctoral Symposium

  • 2023: Co-Chair of the Demonstrations & Posters Track

  • 2022: Session Chair (Hybrid & IRL sessions)

Seminars/Workshops

Program Committee Member

Conferences

  • SANER: SANER'24 [Short Papers and Posters Track] , SANER'25 [Short Papers and Posters Track]

  • MSR: MSR'24 [Data and Tool Showcase Track] , MSR'25 [Data and Tool Showcase Track]

  • QUATIC: QUATIC'24 [Sustainability as a Quality Concern Track]

  • ICT4S: ICT4S'23 [Main Track]

  • MODELS: MODELS'20 [Artifact Evaluation Committee] , MODELS'23 [Artifact Evaluation Committee]

  • RE: RE'22 [Co-reviewer, Research Track]

Workshops

Reviewer

Journals

Others

Awards & Distinctions

2023

Award
  • Best Paper Award [CAIN'23]
    • “Uncovering Energy-Efficient Practices in Deep Learning Training: Preliminary Steps Towards Green AI”






ReviewerSoSyM

2022

  • Best Poster - First prize of the jury [Alice & Eve 2022]
    • “Approximate Computing: A way towards Sustainability”

Contact