Distinguished ACM Speaker:
Based in NY, USA
Dr. Biplav Srivastava is a Senior Researcher & Master Inventor, IBM Research and an ACM Distinguished Scientist and Distinguished Speaker. His research deals with enabling people to make rational decisions despite real world complexities of poor data, changing goals and limited resources. His expertise is in Artificial Intelligence, Services and Sustainability, and has over 20 years of experience, primarily in research, working with collaborators, customers, governments and universities around the world, resulting in many science firsts and commercial innovations, 100+ papers and 35+ US patents issued.
His current focus is on how AI techniques can be used along with open data and APIs for real world usage applications in Smart City (Sustainability) and enterprise integration. As part of this, he represented IBM at W3C’s working group on Government Linked Data. Previously, he had explored
influential services discovery and composition techniques in this space.
Biplav received Ph.D. in 2000 and M.S. in 1996 from Arizona State University, USA and B.Tech. in 1993 from IIT-BHU, India, all in Computer Science. He actively participates in professional services globally including running the ‘AI in India’ virtual Google group, organizing conference tracks, workshops and tutorials, and as a Program Committee member for more than 50 events.
More details can be found at: https://sites.google.com/site/biplavsrivastava/.
To request a single lecture/event, click on the desired lecture and complete the Request this Lecture Form.
- AI Planning as an Enabler for Modern System Integration :
Planning is a central technique in AI for automatically guiding an agent to its goals. From its initial days of application in robotics, it is seeing wider applications in system integration, like web services composition, that t...
- Big, Open, Data and Semantics for a Real-World Application Near You:
State-of-the-art Artificial Intelligence (AI) and data management techniques have been demonstrated to process large volumes of noisy data to extract meaningful patterns and drive decisions in diverse applications ranging from space exp...
- AI Techniques for Intelligent Traffic Management:
Traffic management is a pressing problem for cities around the world. Moreover, it is a highly visible perspective of a city's life affecting all aspects of its citizens' economic and personal activities. Consequently, there is substan...
- Joys and Challenges of On Demand Research in Industry:
Industrial labs provide an alternative career option to research minded graduates in addition to academia. The opportunities to bring one's innovations to practical products are immense but there are also unique challenges, e.g., making th...
- Putting Water Quality Data to Productive Use by Integrating Historical and Real-time Sensing Data :
Water is unique in its role as a life preserver. It is important to all members of a society. However, if one is looking for quality data to make data-driven decisions, one is lost. This is surprising given that there is a rich history of samp...
- Semantic Web for Data Integration:
This talk is a tutorial to make advanced undergraduate students and early researchers aware of semantic web techniques and learn to use them in everyday applications. This event will have a mix of class lectures and practice sessions to learn ...
- Understanding Approaches for Composition, Execution and Adaptation of Web Services:
The demand for quickly delivering new applications is increasingly becoming a business imperative today. Application development is often done in an ad hoc manner, without standard frameworks or libraries, thus resulting in poor reuse o...
To request a tour with this speaker, please complete this online form.
If you are not requesting a tour, click on the desired lecture and complete the Request this Lecture form.
All requests will be sent to ACM headquarters for review.