Abhik Banerjee has been a great data science leader, leading teams comprising of data scientists and engineers. He completed his masters from the University of Cincinnati, where his research focused on various data mining techniques related to itemset mining and biclustering techniques applied to biomedical informatics datasets. He has been working in the areas of machine learning and data mining in the industry for the past 7-8 years, solving various problems related to supervised learning (classification and regression techniques, such as SVM, Bayes net, GBM, GLM, neural networks, deep nets, and so on), unsupervised learning (clustering, blustering, LDA, and so on), and various NLP techniques. He had been working on how these various techniques can be applied to e-mail, biomedical informatics, and retail domains in order to understand the customer better and improve their experience.
Abhik has a strong acumen of problem solving skills, spanning various technological solutions and architectures, such as Hadoop, MapReduce, Spark, Java, Python, machine learning, data mining, NLP, and so on.
Wei Di is a data scientist. She is passionate about creating smart and scalable analytics and data mining solutions that can impact millions of individuals and empower successful business.
Her interests cover wide areas, including artificial intelligence, machine learning, and computer vision. She was previously associated with eBay Human Language Technology team and eBay Research Labs, with a focus on image understanding for large-scale applications and joint learning from both visual and text information. Prior to this, she was with Ancestry.com, working on large-scale data mining and machine learning models in the areas of record linkage, search relevance, and ranking. She received her PhD from Purdue University in 2011, focusing on data mining and image classification.
Manjunath Narayana received his PhD in computer science from the University of Massachusetts, Amherst, in 2014. He obtained his MS degree in computer engineering from the University of Kansas in 2007 and his BE degree in electronics and communications engineering from B. M. S. College of Engineering, Bangalore, India, in 2004. He is currently a robotics scientist at iRobot Corporation, USA, developing algorithms for consumer robots. Prior to iRobot, he was a research engineer at metaio, Inc., working on computer vision research for augmented reality applications and 3D reconstruction. He has worked in the Computer Vision Systems Toolbox group in The MathWorks, Inc., developing object detection algorithms. His research interests include machine learning, robotics, computer vision, deep learning, and augmented reality. His research has been published at top conferences such as CVPR, ICCV, and BMVC.
Ravi Sharma is a lead data scientist and has expertise in both artificial intelligence and natural language processing. He is currently leading the data science research team at Msg.ai Inc., his commercial applications of data science include developing artificial chat bots for CPG brands, health care industry and entertainment industry. He has designed data collection systems and other strategies that optimize statistical efficiency and data quality. He has implemented a corporate big data-based data warehouse systems and distributed algorithms for high traffic. His areas of interest comprises the big data management platform, feature engineering, model building and tuning, exploratory data analysis, pattern analysis, outlier detection, collaborative filtering algorithms to provide recommendations and text analysis using NLP.