About
Vani Mandava is a Director of Data Science at Microsoft Research at Redmond with over a decade of experience in engineering teams designing and shipping software that in use by millions of users across the world. She is passionate about enabling academic researchers and institutions develop technologies that fuel data-intensive scientific research using advanced techniques in data management, data mining, especially leveraging Microsoft cloud and AI platform.
She has enabled the adoption of data mining best practices in various v1 products across Microsoft client, server and services in MS-Office, Sharepoint, Online Services (Bing Ads) organizations and in the Academic Search service. She co-authored a book ‘Developing Solutions with Infopath’ and holds patents in service engineering. She leads Microsoft Research Outreach efforts at Data Science Institutions in US universities. She co-chaired KDD Cup 2013 and partners with many academic and government agencies including NSF supported Big Data Innovation hub effort, a consortia coordinated by top US data scientists and expected to advance data-driven innovation nationally in the US.
Publications
Videos
Other
Patents
- 20110239057 Centralized service outage communication (Mohan Thimmappa, Vani Mandava)
- 20100082813 – Multiple parallel user experiences provided by a single set of internet hosting machines (Margaret H. Li, Maxim A. Ivanov, Vani Mandava, Vadim V. Varfolomeyev)
Conference/Workshop
- SC17 – Keynote talk: MTAGS17: 10th Workshop on Many-Task Computing on Clouds, Grids, and Supercomputers
- SC17 – Tutorial: Scientific Computing in the Cloud (w/ Dennis Gannon, Ian Foster)
- SC17 – BoF panelist: Building Efficient Clouds for HPC, Big Data, and Deep Learning Middleware and Applications
- ACM KDD 2017 – Tutorial: Cloud Based Data Mining tools for storage, distributed processing, and machine learning systems for scientific data (w/ Dennis Gannon)
- IEEE IC2E 2017 – Scaling Science in the Cloud workshop (w/ Dennis Gannon)
- ImageXD 2017 – Image processing using machine learning in the cloud
- MSR India Academic Summit 2017 – Track: Data Science for Social Good
- ICDM 2016 – Workshop Chair: Cloudmine – Data Mining Systems and Applications in the Cloud
- South BD Hub – High Impact Applications of Data Science in Precision Medicine, Health Analytics, and Health Disparities workshop
- ABI Grace Hopper 2016 – Poster Committee
- ACT-W 2015 (Advancing the Careers of Technical Women) Seattle, Accepted Speaker – Data Science in the Cloud
- ACM 2nd IKDD 2015 CoDS Industry Track, Data Science in the Cloud using Microsoft Azure
- ACM Sigspatial 2015 – Local Arrangements Chair
- ABI Grace Hopper 2014 – Data Science Track Lead, Posters judge
- ACM KDD 2013 – KDD Cup Co-chair
Articles
- Microsoft partners with National Science Foundation to empower data science breakthroughs
- Calling all AI Innovators – Cloud AI Challenge
- Creating intelligent water systems to unlock the potential of Smart Cities
- Transportation Data Science at Microsoft
- NSF Big Data Innovation Hubs collaboration — looking back after one year
- A new understanding of the world through grassroots Data Science education at UC Berkeley
- Microsoft continues to support data science research with $3M cloud credits to NSF BIGDATA program
- Microsoft boosts NSF’s Big Data Regional Innovation Hubs with $3M in cloud computing credits
- Mind meld, Microsoft Research style
- Data mining competition takes center stage in Chicago – KDD Cup 2013
