Sourav Dey

Chief TechnOLOGY Officer

Sourav Dey, PhD, is co-founder and the Chief Technology Officer at Manifold, where he leads the system design of intelligent software products and machine learning platform technology. He works closely with product managers and business stakeholders to ensure that AI engineering teams are building the right product, in addition to building the product right. Recent product successes include deep learning for system identification for a global pharma company’s research organization; and HIPAA-compliant, AI-powered treatment suggestions for a digital therapeutics company that’s in use with patients today.

Prior to Manifold, Sourav led teams building smart thermostats and security systems at Google-Nest, where he designed and implemented production ML pipelines using the Python data stack. He also held a joint engineering and business development role at Ingenu, a startup creating a novel wireless M2M and “Smart Grid” solution. While there, he was a major contributor to the 802.15.4k standards body. Earlier in his career, he worked at Qualcomm as a Senior Systems Engineer, implementing communication algorithms in commercial chipsets.

He has authored over a dozen papers and patents for his work on digital therapeutics, indoor localization, intrusion detection, user similarity, and wireless. He holds PhD, MS, and BS degrees from MIT in Electrical Engineering and Computer Science.



ODSC West MLOps: ML Engineering Best Practices from the Trenches Oct. 29–Nov. 1
San Francisco, CA
Strata NY Efficient ML Engineering: Tools and Best Practices Sept. 23–26
New York, NY
ODSC East Reproducible Data Science Using Orbyter Apr. 30–May 1
Boston, MA
Strata Data Conference Applications of Mixed Effects Random Forests Mar. 25–28
San Francisco, CA
Strata Data Conference Streamlining a Machine Learning Project Team Mar. 25–28
San Francisco, CA
PyData Los Angeles Attacking Clustered Data With a Mixed Effects Random Forests Model in Python Oct. 21–23
Los Angeles, CA
Global Big Data Conference Applications of Mixed Effects Random Forests Aug. 30
Santa Clara, CA
ODSC Accelerate AI Meetup Using ML & Data Science to Solve Real Business Problems Jul. 17
San Francisco, CA
IoT Global Innovation Forum Augmented Intelligence: AI & IoT for Triage from Precision Medicine to Predictive Maintenance Jul. 10–11
Portland, OR
IoT Slam Live Augmented Intelligence: AI & IoT for Triage from Precision Medicine to Predictive Maintenance Jun. 21–22
R.T.P., NC
DataWorks Summit 6 Steps for Implementing AI to Enable Efficiency in the Enterprise Jun. 17–21
San Jose, CA
DataEDGE Using Machine Learning and Data Science to Solve Real Business Problems Apr. 24
Berkeley, CA
MIT AI Conference Applying AI: Platforms to Solutions Apr. 20–22
San Francisco, CA
Internet of Things Summit The Energy Efficient IoT Backbone of the Future is Already Here Apr. 12–13
San Francisco, CA
AnacondaCon  Lean AI for Predictive Maintenance Apr. 8–11
Austin, TX
Global Data Science Conference Know Your Customers: How to Implement Customer-Centric AI Systems Apr. 2–4
Santa Clara, CA
ODSC Webinar Applications of Mixed Effects Random Forests Dec. 19
MIT AI Conference How AI will Optimize Marketplaces Mar. 25
Redwood City, CA