Vincent Granville Email & Phone Number

Kirkland, WA, US

San Francisco, US

GenAI platform based on xLLM, the game-changing technology that started the LLM 2.0 revolution. Boosting productivity, automating tasks, delivering ROI at scale to Enterprise customers. Without GPU, hallucinations, security issues, or latency. With zero weight, real-time fine tuning, exhaustive but concise results, customizable relevancy scores, and a.

Seattle, WA, US

Building better, faster, and less expensive GenAI products with explainable AI, such as NoGAN (data synthesizer). Key product: xLLM, a fast in-memory agentic multi-LLM system built from scratch, with zero weight, no training, no latency, no hallucination, fully contextual from the ground up, with real-time fine-tuning. For scientific or enterprise search.

Leuven, BE

Helping Fortune 100 company InBev implement my xLLM technology as an alternative to OpenAI and LangChain to boost relevancy (hallucination-free), reduce latency, and increase speed by several orders of magnitude, while increasing security via sub-LLMs accessible to authorized users only. Offering a better solution for search and cataloging, to help users.

Issaquah, WA, US

AI optimization research lab, developing state-of-the-art technology with a focus on high quality and fast algorithms, thus cost effective. Our GenAI Web APIs are accessible on GenAItechLab.com. Covering synthetic tabular data, artificial DNA sequences, time series & geospatial data generation, agent-based modeling, synthetic graphs, and customized LLMs.

Issaquah, WA, US

The company was acquired in 2020. I am still a contributing author.

Redmond, Washington, US

Developed a strategy to collect the right data and detect minuscule change points in time series associated with KPI's (when the changes occur, their amplitudes and directions). Goal: assessing the impact of events influencing core metrics. Example: changing the definition of a website user resulting in shift in user count, or changing some features on.

El Segundo, CA, US

• Optimizing advertising campaigns, Ad arbitrage. Projects and technology include:
• Created list of top commercial keywords accounting for 85% of all pay-per-click revenue
• Leveraged Google API's to automatically find millions of high yield keywords
• Automated taxonomy creation (NLP)
• Click fraud detection (click jacking and Botnet detection)
• Internet traffic quality scoring using hidden decision trees

San Jose, CA, US

Keyword pricing optimization. Improving keyword bid pricing algorithm to update bids on millions of keywords purchased on Google AdWords. Automated daily updates. Setting bids for large tail of keywords with no conversion history, based on aggregation methods (NLP). Detection of new keywords.

Mountain View, CA, US

Built scoring system to measure traffic quality associated to keywords and publishers, for keyword ad networks, search engines, or advertisers (the customers). Scores were used for fraud detection, removal of bad publishers and keyword pricing. Detected major Botnets. Developed proofs of concept, attracting Looksmart and eBay as customers.

US

VC-funded startup. Prototyped automated bidding and click/keyword scoring solutions for search engines, ad networks and advertisers. Worked with the engineering team to implement HDT (hidden decision tree) algorithms. Worked on score standardization and IP blacklist/whitelist architecture. Developed patent-pending statistical technologies and other.

Bellevue, Washington, US

Click scoring technology, query intelligence, web analytics, business intelligence related to mobile search. Designed click fraud detection algorithms to process billions of clicks. Created rule selection and rule discovery system for fraud detection, based on machine learning (unsupervised clustering), design of experiments, robust cross validation and.

San Francisco, California, US

Detected abnormalities in traffic monitoring systems resulting in a major fix in the Tealeaf reporting system. The bug resulted in visitors and web session statistics to be wrong for all big vendors relying on multiple servers, with visitor session data collected across multiple servers broken down by error in multiple sessions / multiple users.

Foster City, California, US

Developed proprietary feature selection system (200x faster than SAS Enterprise Miner) to detect first instances of fraud and horizontal (single ping) fraud in real time. Production of US zip code maps showing fraud simultaneously in the time, location, recency and volume dimensions. SAS, Perl, C, R, Splus.

San Francisco, CA, US

Web analytics. Attribution modeling using time series techniques. Inventory forecasting (NBCi). Price elasticity modeling. Web scraping. Advertising mix optimization for both NBC Internet (NBCi) and CNET. Customer profiling. User retention, churn, survival models. Data Warehousing. Web traffic forecast (with automated alarm system to notify product.

Washington, DC, US

Environmental statistics. MCMC. Hierarchichal Bayesian models. Clustering. Storm modeling (time series, spatial processes). Hanford nuclear reservation: risk analysis using space / time models to detect radioactive leakage into the nearby Columbia river (funded by the EPA.) Simulation of bivariate exponential distributions.

Postgraduate Degree, Computational Statistics

Doctor Of Philosophy - Phd, Computational Statistics, Mathematics