Shubham Goel - Databricks

Shubham Goel

Data Scientist, Autodesk

Shubham Goel is a Data Scientist and scrum master on the BIM 360 Data Science team. He works closely with construction customers to develop AI models that helps them reduce the complexity of the tasks they face. Shubham has a background in Machine learning and Data visualization. He has an MS from UC Berkeley and is a certified product owner. In the past Shubham has contributed to the launch of India’s first Nano-satellite, that still orbits earth.

UPCOMING SESSIONS

PAST SESSIONS

Applying Machine Learning to ConstructionSummit 2017

Autodesk is a leader in architecture, engineering and construction software. Autodesk’s BIM360 suite of cloud products for construction enables almost anytime, anywhere access to project-related data throughout the building construction lifecycle. It empowers those in the field to better anticipate and act, and those in the back office to optimize and manage all aspects of construction performance. In this talk we will share how we leverage machine learning to empower proactive construction risk management. These multi-modal applications coupled with external data collection points (e.g. sensors, drones) generate diverse data hosted by different underlying solutions. Generating insights and applying machine learning out of heterogeneous data with regards to data velocity, volume, variety, and veracity within multiple technology stacks is a big challenge. Spark enables managing our growing data heterogeneity in a scalable manner while being able to accommodate both streaming and batch mode data loads. Spark further enables our data science team to work more efficiently, reduces model-to-production conversion cycle, and facilitates the interplay between data management, machine learning, and insight generation to empower intelligent construction.

Learn more:
  • Machine Learning - Getting Started with Apache Spark on Databricks
  • Operationalizing Machine Learning at Scale
  • Using Databricks to Democratize Big Data and Machine Learning at McGraw-Hill Education