The Big Data and Deep Learning workshop tries to unveil the innovations and contributions in the field of Big Data and Artificial Intelligence. The workshop would discusses the out-of-the-box approaches and possible use cases in related to the application of machine learning and big data. The workshop would give an information-sharing platform for researchers and practitioners to share their experiences on designing and developing big data applications that would aid data driven decision making and reasoning. Last but not the least; it would highlight the open issues related to the application of machine learning problems.
The NorthCap University concentrates on research and entrepreneurship. Apart from its focus on teaching, we are collaborating with University of Dayton, USA, Michigan technological University, USA and ITB Ireland to fulfill the requirements. In addition, we have a team of experienced faculty and staff from reputed universities and IT industries.
|Participants from India||2000|
|Students from India||1500|
|Registered Authors from ICCIDS2018||Complimentary|
|Students from The NorthCap University, Gurugram||500|
Registration Charges: Registration for registered Authors from ICCIDS2018 is FREE.
L V (Venkat) Subramaniam is STSM & Senior Manager - Knowledge Engineering and Data Platforms, India Research Laboratory, New Delhi, India. He received the B.E. degree in Electronics and Communication Engineering from Mysore University, the M.S. degree in Electrical Engineering from Washington University, St. Louis, USA, and the Ph. D. degree in Electronics from the Indian Institute of Technology, New Delhi, India. The Knowledge Engineering and Data Platforms theme of his work has been the search for informative patterns in signals that include text, speech, image and others enhanced for different communication channels. He joined IBM Research India in 1998, where he currently leads a team of world class researchers developing the next generation Data and Knowledge Engineering technologies. He is a member of the IBM Academy of Technology and an IBM Master Inventor.He has firsthand experience in implementing knowledge solutions for telecom, finance, retail, pharma, government and entertainment sectors. He also has deep involvement in academics. He is on the Senate of IIIT Delhi since 2013.He has been on PhD thesis committees in IIT Delhi, India, Univ of Maryland, Baltimore County, USA and IIIT Delhi, India. He has awarded by IBM Outstanding Technical Achievement Award 2015(Market Impact of Social and Customer Analytics), IBM Outstanding Technical Achievement Award 2015(Data Fusion and Analytics), IBM Outstanding Technical Achievement Award 2011 Cleansing as a Transient Service (Data Quality Assessment and Management), IBM Outstanding Technical Achievement Award 2012(Noisy Text Analytics). He has invited to deliver talk on Data Cleansing as a Service, Univ of Waterloo, Waterloo, Canada, Oct 27, 2010; Data Quality Platform: Enhancing Enterprise Data Quality Using Web Data, Information on Demand, Las Vegas, NV, USA, Oct 25, 2010; Real World Text Analytics, Univ of Texas, Austin, USA, Oct 21, 2010; NLP for Noisy Text, Univ of Texas, Dallas, USA, Oct 19, 2010. He served as member of Editorial Board, International Journal on Document Analysis and Recognition (IJDAR). Click here for detailed profile.
Sachindra Joshi is a Senior Technical Staff Member and a research manager in IBM Research, India. He is currently leading the research efforts in building multi-modal conversational systems. He is focused on adapting and applying various machine learning and natural language processing techniques to build computing systems that can interact with humans in a natural manner. Prior to joining IBM research, Sachindra completed Masters degree in Computer Science and Engineering from Indian Institute of Technology Bombay, where he was the recipient of the gold medal award for standing first in the department. His current research interest lies in the area of dialog systems, text processing, natural language processing and machine learning. Click here for detailed profile.