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Contact Information
| Name | Gerasimos (Makis) Lampouras |
| Professional Title | Chief Scientific Officer, C Proof |
| gerasimos.lampouras@gmail.com |
Professional Summary
Gerasimos (Makis) Lampouras is the Chief Scientific Officer at C Proof, London. Prior to this, he was a Principal Research Scientist and served as the Team Leader of the NLP (Natural Language Processing) group in Huawei Noah’s Ark Lab, London.
Areas of interest generally fall somewhere between Natural Language Processing and Machine Learning, with his latest efforts focusing on the information seeking and synthesis capabilities of LLM-based Agents and on neuro-symbolic approaches for math and code reasoning. Briefly, his previous work has focused on LLM-based code synthesis and understanding, Natural Language Generation, Dialogue Systems, and overall Machine Learning applications for Natural Language Processing.
Formerly, he was a Research Associate at the University of Cambridge, University of Sheffield and University College London. He graduated and received his MSc and PhD from the Athens University of Economics and Business.
General Information
Experience
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2026 - Present London, UK
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2024 - 2026 London, UK
Team Leader of the London NLP Team
Huawei Technologies Research & Development (UK) Ltd
- Leading a group of ~10 Senior Research Scientists and Engineers researching how to address current NLP and Large Language Models challenges, e.g. how to improve LLM’s reasoning capabilities, LLM self-learning, LLM efficiency, LLMs for Programming Languages and Math, as well as related tasks.
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2023 - 2026 London, UK
Principal Research Scientist in NLP
Huawei Technologies Research & Development (UK) Ltd
- Research management and development of Code Language Models.
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2019 - 2023 London, UK
Senior Research Scientist in NLP
Huawei Technologies Research & Development (UK) Ltd
- Research and development focused on multilignual Natural Language Generation, evaluation, and Dialogue Systems.
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2018 - 2019 Cambridge, UK
Research Associate
University of Cambridge
- EPSRC eNeMILP project: Research on non-monotonic incremental prediction of structured outputs.
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2015 - 2018 Sheffield, UK
Research Associate
University of Sheffield
- EPSRC DILiGENt project: Research on domain-independent Natural Language Generation through imitating generation policies from unaligned corpora.
- EPSRC eNeMILP project: Research on non-monotonic incremental prediction of structured outputs.
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2015 London, UK
Research Associate
University College London
- EPSRC DILiGENt project: Research on domain-independent Natural Language Generation through imitating generation policies from unaligned corpora.
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2014 Athens, Greece
Research Assistant
Athens University of Economics and Business
- BioASQ: A Challenge on Large-Scale Biomedical Semantic Indexing and Question Answering.
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2011 - 2012 Athens, Greece
Research Assistant
Athens University of Economics and Business
- Researching a Linear Programming approach to multi-document text Summarization and Natural Language Generation from ontologies.
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2007 - 2009 Athens, Greece
Research Assistant
Athens University of Economics and Business
- INDIGO: Interaction with Personality and Dialogue Enabled Robots.
Education
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2009 - 2015 Athens, Greece
Ph.D. in Artificial Intelligence
Athens University of Economics and Business
- Dissertation: Natural Language Interaction with Semantic Web Ontologies.
- A robust framework supporting multilingual Natural Language Interaction with Semantic Web Ontologies.
- Global optimization of content selection and lexicalization for output compression.
- Automatic extraction and inference of Natural Language resources for Natural Language Generation.
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2006 - 2008 Athens, Greece
M.Sc. in Computer Science
Athens University of Economics and Business
- Dissertation: Methods to automatically detect definitions in document collections.
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2002 - 2006 Athens, Greece
Bachelor’s degree in Informatics
Athens University of Economics and Business
- Dissertation: Revision and larger-scale experimental evaluation of a method to handle definition questions in Question Answering systems.
Granted patents
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2024 Apparatus and method for the training of a code synthesis model
WIPO patent WO-2024213252-A1 · Huawei Technologies Co., Ltd. (assignee)
- Inventors: Philip John Gorinski, Matthieu Zimmer, Gerasimos Lampouras, Derrick Goh Xin Deik, Ignacio Iacobacci.
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2023 Hierarchical language generation with recurrent aggregation
WIPO patent WO-2023030637-A1 · Huawei Technologies Co., Ltd. (assignee)
- Inventors: Giulio Zhou, Gerasimos Lampouras.
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2021 Device and method for generating language
WIPO patent WO-2021204370-A1 · Huawei Technologies Co., Ltd. (assignee)
- Inventors: Giulio Zhou, Gerasimos Lampouras.
Workshop and Shared Task organization
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2024 Co-organizer
SCI-CHAT: Workshop on Simulation of Conversational Intelligence in Chat
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2022 Co-organizer
6th Workshop on Structured Prediction for NLP
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2020 Co-organizer
4th Workshop on Structured Prediction for NLP
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2019 Co-organizer
3rd Workshop on Structured Prediction for NLP
Chairing and service
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2023 - Present Area Chair
ACL Rolling Review (ARR)
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2024 Area Chair, “Summarization”
EACL 2024
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2024 Area Chair, “Evaluation and Validation Methodologies”
LREC-COLING 2024
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2023 Area Chair, “Generation & Summarization”
EACL 2023
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2021 Area Chair, “Resources and Evaluation”
EMNLP 2021
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2020 Sponsorship Chair
INLG 2020
Honors and Awards
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2025 Huawei Team Gold Medal Award
Huawei
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2025 Huawei Rising Star Award
Huawei
- Awarded in 2020, 2023 and 2025.
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2022 Huawei Innovation Pioneer Award
Huawei
- For work on PanGu-Coder: Program synthesis with function-level language modeling.
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2010 - 2013 Research Funding Program: Heracleitus II
European Union (ESF) and Greek national funds
- Ph.D. research fund co-financed by the European Union (European Social Fund – ESF) and Greek national funds through the Operational Program “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF).
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2006 - 2007 M.Sc. scholarships
Athens University of Economics and Business
- Awarded in the first and second semester of the M.Sc. program (3rd and 1st best position, respectively).