Béatrice Moissinac Email & Phone Number

Reporting directly to the CISO regarding AI Trust & Safety at Zendesk.I am currently implementing an AI Risk Management framework.

Applied AI research in Threat Detection and Identity Security to research and develop security controls (Bot detection, adaptive Multi-factor authentication, user fingerprint and user profiling, SQL Injection detection, anomaly detection) features and products. I lead cross-team efforts between threat researchers, data scientists, and software engineers to.

New York City Metropolitan Area

Applied research and product development in AI for Identity Security (ML-based security controls), Platform (Anomaly Detection), user and developer experience (Data Mining) for Okta | Customer Identity Cloud Product Unit (Formerly AuthØ). I also actively work toward AI literacy, AI Governance & Ethics, and thought leadership for AI applied to.

Greater New York City Area

As an applied ML researcher, I lead R&D projects to leverage alternative data for factor modeling. My role includes managing and mentoring 4 junior data scientists, designing and implement novelML solutions on parallelized cloud computing platform, and stakeholder management. Recent implementations on Spark include label propagation, community detection.

Région De Corvallis, Oregon, États-Unis

Learning Analytics in the wild! Educational Data Mining for program review, accessibility, and equity evaluation. Using systematic and continuous data stream from wireless networks, computer labs, and printers, I show what and how student use technology and learning spaces on campus, as well as predict its impact on student success.Key Words: Educational.

Greater New York City Area

(Internship) I researched, developed, and implemented an adaptive testing system using a multidimensional Item Response Theory (MIRT) model. I developed a new approach that reconciles both compensatory and noncompensatory approaches in MIRT such that the teacher does not have to change their question set when using an MIRT approach. Research paper was.

Yorktown Heights

Summer research internship at IBM Research in the Cognitive System Performance group. My project is titled "CHARLIE: Curriculum Heuristic for Active Learning Intent Explanation". In the context of the design of conversational agent, we implement an adaptive tutor to facilitate the work of the designer and improve the overall performance of the.

Région De Eugene, Oregon, États-Unis

Churn rate prediction: Using Customer Relation Management software data, as well as service usage, I built a data pipeline with Scala and Spark. The pipeline outputs churn probabilities. The data analysis included sentiment analysis using Stanford Core NLP, MDP, and regression modeling.

Région De Corvallis, Oregon, États-Unis

In partnership with Technology Across the Curriculum (a unit from Academics Technology) and the Public Health department, I developed a virtual learning environment for high school students to practice sport nutrition. This includes the creation of data collection processes, pipelines, and data validation. I also supervised up to 6 undergraduate student.

Gap, France

I investigated statistical model to capture relevant parameters in hotel attendance. The goal was to predict booking rate and to develop a model of pricing management. I produced a tool for the consulting company that automates the process.

Doctor Of Philosophy (Phd), Artificial Intelligence

Activities and Societies: CGE, ChickTechMy PhD dissertation includes exploring AI application for education. My research includes adaptive.

Master Of Science (Ms), Artificial Intelligence

Activities and Societies: European Student Association, CGE, ChickTechI investigated how to use multi-agent systems and reinforcement.

Master'S Degree, Econometrics And Data Mining, Valedictorian

M1 EQUADES: First year of French Master, focusing on Quantitative Economics and Decision Making, as exchange student at Oregon State.

Bachelor'S Degree, Econometrics And Quantitative Economics