Bio: Neha Gupta is Head of Data Science| Machine Learning at Common Room. Before joining Common Room, Neha spent her time at companies such as Linkedin, Uber and Adobe working on challenging problems ranging from personalization, recommendations, forecasting and go-to-market ML.  Neha graduated with her Ph.D degree in Computer Science from University of Maryland, College Park. She has several publications in top tier conferences and has chaired two prior workshops on Offline and Online evaluation of ML Systems  in KDD (2019) and WWW (2015). 

Bio: Building on a foundation of master’s degrees in business & Organizational Research, Florian has acquired an extensive background in the tech industry, spanning over a decade, with a primary focus on utilizing data in all its dimensions to drive optimal business performance. During his tenure as a Data Analyst at Google, Florian was in charge of customer lead prioritization and sales call center performance enhancement for long-tail customers. At Expedia Group, Florian undertook various projects. Initially, he played a vital role in Supply Analytics, delivering insights for brands like Private Label Solution and Hotwire. Subsequently, Florian applied his expertise in Machine Learning Science to EG’s pricing optimization. In his present role, Florian leads the Machine Learning Science Teams, responsible for developing advanced algorithms that optimize the collaboration between Expedia Platform and Supply Partners, including hotels and vacation rentals. His team focuses on enhancing every stage of the partner journey, from lead acquisition and onboarding to overall optimization and partner experience, as well as the optimal communication channels to reach them. Recognizing the significance of a seamless two-sided platform like Expedia, Florian ensures that Supply Partners receive exceptional support throughout their Partner Journey, enabling travelers to access superior inventory effortlessly

Bio: Alvin has over 20 years experience using Statistics, Operations Research and Computer Science to solve predictive and prescriptive analytics problems in the CPG, advertising, transportation, hospitality, pharmaceutical, food service, gaming, telecom and technology industries.

Domain expertise in the application of Data Science to Marketing Mix Modeling and Optimization, Marketing Attribution Modeling, Recommender Systems, Personalized Marketing, Brand Awareness and Brand Equity Modeling, Customer Lifetime Value Modeling, Assortment Analysis and Optimization, Floor Space Optimization, Pricing and Promotion Analysis and Optimization, Personalized Pricing, and Revenue Management.

Bio: Paolo Massimi is an accomplished expert in customer journey optimization, user acquisition strategies, churn prevention, and product optimization. With a solid background in product analytics, data-driven insights, and advanced modeling techniques, he brings a wealth of experience to these domains. His profound expertise in machine learning and AI empowers him to deploy and evaluate ML models in production environments, consistently driving successful outcomes.

In his previous leadership roles, including Director of Guest and Host Data Science at Airbnb and Head of Rider Data Science at Uber, Paolo led highly skilled teams in data modeling, experimentation, and product analytics. Collaborating closely with C-level executives, he provided invaluable data support for insights, reports, and analysis, ultimately revolutionizing the customer journey, expanding user acquisition efforts, mitigating churn, and optimizing product performance.

At Airbnb, Paolo spearheaded several key initiatives that had a transformative impact on the platform. As the director of the Guest and Host Data Science team, he played a pivotal role in optimizing the guest search experience by collaborating extensively with the product and relevance team. Through his data-driven insights and modeling expertise, Paolo contributed to enhancing the search funnel, refining Airbnb supply categories, and optimizing Maps and Points of Interest (POI) integration. 

Additionally, Paolo led the data science work to redesign the onboarding flow for hosts, improving the host tool experience and implementing effective churn prevention strategies. His leadership and analytical approach ensured a seamless onboarding process, increasing host engagement and retention rates. Furthermore, Paolo played a critical role in launching the incentive platform for hosts at Airbnb. By leveraging his expertise in data analytics and machine learning, he designed and implemented an effective incentive program.

Paolo holds a Ph.D. in Mathematical Engineering from the esteemed Polytechnic of Milano and boasts an extensive publication record in his field. His exceptional contributions have earned him prestigious honors, while his passion for education led him to actively engage in teaching activities at renowned institutions like Stanford University and the Polytechnic of Milano.

Beyond his professional pursuits, Paolo finds joy in outdoor activities such as biking and skiing. He also nurtures his creative side through playing tennis and showcasing his musical talents on the piano and jazz guitar.