jair wuilloud

Provided data, LLM, and problem-solving expertise as a contractor for multiple clients including DeltaGen.ai, OpenAI, Tradework, and HumanMadeMachines. My work involved developing conversational agents, solving physics problems for AI model training, and building prototypes for information extraction and automation.

As CTO of AI, I am developing Apollo AI, an AI-powered research engine designed to optimize discovery, IP protection, and funding processes. This involves implementing LLM/Action-based Agents, asynchronous flows, and hierarchical/swarm agents.

As Co-Founder & CTO, I lead the training, testing, benchmarking, and R&D efforts for tiny LLMs. My role involves developing and refining methods and tools to optimize performance in this specialized area.

Conducted data analysis and algorithm development, supervised PhD students, and produced scientific papers, presentations, and posters. My work involved advanced computational methods for theoretical physics.

Performed model and DB price validation and implementation for Credit/Securitization. Developed tools for testing and data structure.

Provided training in machine learning and developed core algorithms. For LocaFox, I developed a simulation demonstrating optimization software, and for Mapegy, I assessed the feasibility of matching correlations between stock market indices and company R&D investments.

Supported the engineering team with analyses, models, and ideas. Developed a Proof of Concept (PoC) through user/item interaction simulations for a recommender system targeting lawyers, and analyzed Reuters news to develop an early prototype for personalized news.

Developed prototypes and Proofs of Concept (PoCs) for Twitter Data Analysis related to company names, designing techniques and proposals for learning strategies. Wrote components for production systems.

Developed a chatbot for the helpline to support the engineering team. Created a "Food Ontology" for classification, clustering, and scraping, including training with historical data and test harness development.

Co-developed a real-time collaborative application for Black Cabs from scratch, including front-end, back-end with API integration, and system deployment with analytics and monitoring. Led data generation, collection, and Proofs of Concept (PoCs) using image processing and reinforcement learning on trajectories.

Conducted R&D and implemented prototypes for an AI-focused startup, including presentations, demos, and engineer training. Contributed to a provisional patent for a semantic engine.

Developed an innovative multidimensional conversational system of systems, including an iOS app and a fully integrated online editor/tester. Utilized High Dimensional Computing (SDMs), Symbolic Logic, and Brain-inspired models.

Conducted pilots and Proofs of Concept (PoCs) focusing on the interplay of behavioral simulations and campaign learning. Designed a US-compliant data architecture capable of compressing 500 million behavioral data points per day.

Developed neuro-inspired models for patient histories and participated in US-based competitions. Processed Medicare datasets in real-time to return basic correlations.

Automated the transliteration workflow by designing a graph editor for rule creation and automating code generation for transliteration rules. Trained transformer models and integrated production-ready models, significantly improving Hebrew diacritization to achieve state-of-the-art results.

Developed prototypes and Proofs of Concept (PoCs) for an e-commerce recommendation system. Designed an analytic system monitoring key performance indicators (KPIs) and developed deep learning libraries, including a behavior-driven simulation mimicking user behavior.

Developed recommendation and community-based car-sharing report services. Created highly efficient fuzzy matching algorithms for identifying similar trajectories in spacetime.

Led R&D to production efforts, including data pipelines, articles, code, and prototypes. Trained a generative weather model on 40TB of data, achieving high accuracy in forecasting.

As Co-Founder & Tech Lead, I built and led a team of six to develop Dr.Doc, a web-based solution for automating letter generation for medical doctors. I also created an AI Scientist system for automated, explainable research and diagnosis, while conducting research, market surveys, and securing funding.

Activities and societies: Data analysis and algorithms development, PhD Student supervision, papers/presentations/posters

Conducted postdoctoral research in Theoretical Particle Physics at the Albert Einstein Center for Fundamental Physics. Focused on data analysis, algorithm development, and supervised PhD students.

Completed a PhD thesis in Quantum Field Theory, focusing on exotic numerical models for QCD and supersymmetry. The research was conducted under the advisement of Gernot Münster.

Obtained a Master's degree in Mathematical Physics from the University of Geneva. This program provided a strong foundation in advanced mathematical concepts applied to physics.

Earned a Bachelor's degree in Physics from the University of Geneva. The curriculum covered fundamental principles of physics.

Completed Scientific Maturity at Highschool of Nyon. This program provided a strong foundation in scientific subjects.