■ 01.2024 - now ■ Data Consultant/Researcher at Capgemini Invent
○ Lead research on Generative AI methodologies and systems
Designed a novel benchmarking framework for AI models, integrating performance, computational complexity, and environmental impact; delivered as an open-source Python evaluation toolkit (ACM publication)
Conducted comparative studies of large vs. small-scale LLMs in agentic AI systems of a cloud-based software company, quantifying trade-offs between energy efficiency, latency, and output quality; derived optimization strategies (arXiv preprint)
Technologies: Deep Learning, Benchmarks, Model Performance, Architecture, Complexity, Computation Complexity, Implementation Complexity, Interpretability, Environmental Impact, LLMs, Multi-agent Systems
○ Multi-Agent & AI Systems Development
Built a conformity assessment platform aligned with EU AI regulatory requirements for a defense client, automatically assigning risk/compliance labels to regulatory texts with confidence scores; reduced analysis time from 1 week to ~1 hour
Developed a mobile virtual assistant for operational and financial insights, featuring interactive visualizations and fully traceable outputs; enabled executive decision-making in minutes instead of 1 day
Designed a clinical research assistant supporting protocol strategy in drug development by leveraging PubMed literature; reduced literature review cycles from weeks to 1 day
Delivered enterprise-grade Document AI solutions (RAG-based) for audit workflows in the aerospace sector, including question answering, summarization, contract validation, and document comparison
Technologies: Chatbot, RAG, LLMs, MCP, Docling, Unstructured, Streamlit, GCP (Document AI), Azure (AI Search, OpenAI, AI Services, AI Foundry), AWS (Bedrock, ECS Fargate, SQS)
○ Fields: Airline Industry, Medical Industry, Defense Industry, Financial Industry, R&D
■ 04.2021 - 12.2023 ■ Data Scientist/Researcher at Quantmetry
○ R&D in Generative AI:
Developed Qolmat, an open-source library for imputing tabular and time-series data using generative models.
Implemented data augmentation techniques to improve service evaluation in the MAPIE project and contributed to quality evaluation of generated data.
Engineered generative models for synthetic designs with constraints and performed quality evaluations of generated data.
○ Technical Keywords: Data Augmentation, Generative Models, Generative Adversarial Network, Variational Auto-Encoder, Diffusion Models, Transformers, Trusted AI, Generative AI, NLP, Tabular Data, Time Series
○ Fields: Automotive Industry, R&D
■ 10.2017 - 02.2021 ■ PhD ■ Generative Probabilistic Alignment Models for Words and Subwords ○ NLP (Utility)
○ Researched alignment models for low-resource languages, focusing on subword tokenization and variational inference techniques.
○ Doctoral Project: 3 years in Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur (LIMSI)
○ Technical Keywords: Low-resource Languages, Variational Auto-Encoder, Subword Tokenization, Expectation-Maximization, Hidden Markov Models, Convolutional Neural Networks, Long Short-Term Memory Networks, SentencePiece, Giza++, Fastalign, Tensorflow, Pytorch, Python, Slurm
■ 03.2017 - 09.2017 ■ Neural Machine Translation ○ NLP (Utility)
○ Developed GAN-based Neural Machine Translation systems and explored reinforcement learning applications for improved translation quality.
○ Internship: 6 months in Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur (LIMSI)
○ Technical Keywords: Generative Adversarial Network, Reinforcement Learning, Convolutional Neural Network, Recurrent Neural Network, Python
○ Github: GAN-NMT
■ 09.2016 - 11.2016 ■ Axa Data Challenge ○ Data Challenge of DaSciM
○ Developed predictive models to address concept drift in time-series data.
○ Scholarly Project: 3 months in École Polytechnique (X)
○ Technical Keywords: Concept Drift, Tree Regressors, Random Forest Regressors, Gradient boosting regressors, Autoregressive models, Python, Scikit-Learn, Anaconda
■ 01.2016 - 03.2016 ■ Brain MRI Segmentation ○ Software Development (Medical)
○ Developed software for segmenting brain MRIs using 3D slicer and ITK.
○ Internship: 3 months in Kyoto Institute of Technology (KIT)
○ Technical Keywords: C++, 3D Slicer, ITK
○ Youtube: Demo
■ 06.2015 - 08.2015 ■ Developer ■ Project KList ○ iOS Development (Entertainment)
○ Internship: 3 months in NinePoints Co. Ltd
○ Technical Keywords: Swift, ObjectiveC, Xcode, Realm, Alamofire
○ Appstore: Klist
■ 02.2015 – 06.2015 ■ Project 3D Movie ○ 3D Development (Entertainment)
○ Graduation Project: 4 months in Arena Multimedia Institute (AMI)
○ Technical Keywords: Maya 3D
○ Youtube: The Ant and The Grasshopper
■ Machine Learning
○ Large Language Models, Retrieval-Augmented Generation
○ Variational Auto-Encoder, Generative Adversarial Networks, Diffusion Models
○ Convolutional Neural Networks, Recurrent Neural Networks, Transformers
○ Support Vector Machines, Back-propagation, Naive Bayes Classifier, Linear Regression, K-Nearest Neighbor, Decision Trees
○ Expectation-Maximization, DBSCAN, K-Means, Hierarchical Clustering
○ Boosting Algorithms, XGBoost, LightGBM
○ Pytorch, Theano, TensorFlow, Scikit-Learn, LibSVM, Weka, MLFlow, FastAPI, Slurm, AWS, Google Cloud, Azure, Jupyter Lab, DeepNote
○ Transformers, Spacy, SentencePiece, Spark, Giza++, Fastalign, Simalign, Eflomal
■ Software development ○ Python, Scala, R, Matlab ○ Java (J2EE), C/C++, C# ○ OpenCV, Qt ○ Lisp, Prolog, Jess ○ Netbean, Eclipse, Visual Studio, Anaconda, Spyder
■ Mobile development ○ Objective C, Swift, React ○ iOS, Android ○ XCode, Android Studio
■ Web development ○ HTML5, CSS3, JavaScript ○ PHP ○ jQuery ○ Dreamweaver ○ Adobe Flash
■ Multimedia development ○ Illustrator, CorelDraw ○ InDesign ○ Photoshop, Lightroom ○ Premiere Pro, After Effects ○ 3ds Max, Maya 3D
■ DB Management ○ SQL ○ MySQL, Microsoft SQL Server ○ Microsoft Access
■ Architectural Design ○ UML
■ Project management ○ Project planning and roadmapping, Agile methodologies, Documentation development ○ Trello, Microsoft Office Suite