Integrating Machine Learning with Mathematical Optimization: Resource Matching

Resource Matching Optimization

Large professional services companies employ thousands of experts to deliver a wide variety of services, making labor the industry’s highest expense. Current manual processes and tools used within labor resources management present many limitations leading to poor demand fulfillment, low labor resource utilization, high project delivery costs, and poor customer satisfaction.

Webinar Summary

Large professional services companies employ thousands of experts to deliver a wide variety of services, making labor the industry’s highest expense. Current manual processes and tools used within labor resources management present many limitations leading to poor demand fulfillment, low labor resource utilization, high project delivery costs, and poor customer satisfaction.

During this webinar recording, we:

– Walk through an optimization application demo that integrates machine learning and mathematical optimization technologies

– Address the fundamental problem of resource management, including how to match workforce resources with the right skills and capabilities, for the right job, at the right time, location, and cost.

This demo is the result of a collaboration between the Recruitology data sciences team and Tere Gonzalez, Senior Data Scientist at Hitachi Lab.

Presenters

Dr Cipriano Santos

This webinar is presented by Dr. Pano Santos and Tere Gonzalez. 

Dr. Santos retired from Hewlett-Packard Laboratories as Distinguished Technologist. He worked in the Palo Alto, CA office. During his 23 years at HP Labs, he developed and implemented several decision support tools for Product Life-cycle Management, Customer Relationship Management, Large Data Centers Computing Resources Allocation, Professional Services Workforce Planning, Airline Dispatcher Workload Distribution Optimization, and Operating Room Planning & Scheduling. He holds 18 patents and 17 refereed research publications. Santos has a Bachelor’s Degree in Applied Mathematics from the University of Mexico (UNAM), and a Master’s and PhD degrees in Operations Research from the University of Waterloo, Canada.

Tere GonzalezMaría Teresa (Tere) González Díaz is a research engineer in the Industrial AI lab at the Center of Social innovation – Hitachi Labs Americas. Tere works in projects that combine images, voice, and text to implement AI solutions in transportation and mobility domains. Prior to this, she worked in Hewlett Packard Laboratories in Palo Alto, CA. She developed decision support systems based on mathematical optimization models to improve services for human resources and healthcare. Tere has three granted patents and more than 10 in process. She holds a MSc Degree in Information Technologies from Monterrey Institute of Technology. Her experience and interests are in deep learning, machine learning, big data, and Augmented Reality (AR) that can help develop the next generation of services to improve people’s lives.

Presented Materials

You can download the presented slides and the RMO whitepaper as an additional resource to this webinar.