Wednesday, April 24, 2019

Onsite Interactive Training Session for Data Analysts/Data Scientists

Dr. Zhou is offering a brand new service: a half-day (3 hours) interactive training session to help a company's data analysts/data scientists improve their skills and productivity. The format of the interactive training session is as follows:

1. Dr. Zhou first gives a 1.5 hours presentation to describe successful cases of using data analytics to solve business problems, share best practices, and talk about challenges.
2. For the remaining 1.5 hours, the audience asks questions and is actively engaged in discussion with Dr. Zhou.  This the best part!  As one of the scientists said, "Dr. Zhou has helped me solve an issue that I had struggled with for years".

The training session is designed for all data analysts/data scientists. Dr. Zhou shares his battle-tested strategies and best practices that are useful for them regardless what specific analytics tools or programming languages they use.

On April 23, 2019, Dr. Zhou delivered the interactive training session to one of the top three property insurance company located in Boston. It was extremely well received. The picture attached shows that I am making the presentation (in addition to people in the room, there are more people joining the meeting through the phone.) 



The following are the testimonials from two persons who took the course.

"We have learnt a lot from Dr.Zhou'", Gang Xu, Director, Data Science at Lincoln Financial Group
"Dr. Zhou gave us a great overview of procedures of doing a solid predictive analysis and illustrated real life AI consulting business cases. Dr. Zhou is really experienced in the AI space and his presentation was very well received by data scientists from Lincoln Financial Group. I would highly recommend any data science group to have Dr. Zhou sharing his experiences. "-  Dr. Hao Zhou, Principal Analyst,  Data Science at Lincoln Financial Group

The following are testimonials about my previous talks and training activities.

"It was a fortune to have Jay come to our computer science department to share his experience in solving business problems with predictive analytics on February 28, 2017. What Jay had presented in his 3 talks, each lasting for 1 hour in different topics of data mining, was totally impressive and beyond our wildest expectation. Having built competition-winning predictive models for some of the biggest companies and produced hundreds of millions of dollars’ savings, Jay shared the secret of his success with students and faculty without reservation. His strong presentations were such an inspiration for our computer science students and faculty and his methodology was innovative and powerful , even for very seasoned data scientists among the audience. Jay, thank you so much for your hard work preparing and delivering these presentations! " - Dr. Wei Ding, Professor at University of Massachusetts Boston

"Jay is more than just a coder, he is a great trainer, and a good presenter of theoretical data mining concepts so that they can be understood by most. "-James Lukenbill, Director of IT Project Management, Optum

Bio of Dr.Jiang Zhou
Dr. Jiang Zhou has two decades of experience building predictive models across industries including telecommunication, banking, insurance, and smart city. These solutions have resulted in over $200 million savings for clients. Dr. Zhou has been involved in three real world competitions to build best predictive models, i.e., a customer credit risk model for a top three cell phone company, a bank card fraud detection model for a top 15 bank, and a direct sales model for a marketing company. Dr. Zhou's models have won all these competitions. He has founded/co-founded data analytics companies, including Business Data Miners, Smart Credit and AI Strike. Previously, he was a chief statistician at Lightbridge, a vice president at Citizens Bank and a consulting member of technical staff at Oracle. Dr. Zhou is the author of an award-wining blog on data analytics https://www.deep-data-mining.com/

The normal price for the training service is $6,500. If your company is interested in the service, please contact Dr. Zhou at jay.zhou@deep-data-mining.com 

Wednesday, April 17, 2019

CALL FOR PAPERS

Workshop on Data Mining in Industrial Internet of Things (DMIIOT)
to be held in conjunction with the IEEE International Conference on Data Mining 2019 in Beijing
Data generated by industrial internet of things (IIOT) have been growing at an exponential rate. Data mining plays an essential role in deriving actionable information from these raw data. By applying a variety of data mining technologies to historical and real time IIOT data, building supervised or unsupervised models, deploying them into the production environment to help business make better decisions, significant value can be created resulting in reduced waste, improved efficiency and broaden opportunity.  The marriage between data mining and IIOT has found applications in industries such as manufacturing, energy, healthcare, retail, smart city and transportation.
The workshop will provide a venue for researchers and practitioners from both data mining and IIOT communities to exchange ideas, share best practices, discuss challenges and future directions. By fostering communication and collaboration, we drive innovative applications of data mining to IIOT. This workshop will be held along with 2019 IEEE International Conference on Data Mining, Beijing (http://icdm2019.bigke.org).
 This workshop calls for papers that cover topics including, but not limited to, the following:
  • Data mining algorithms for IIOT
  • Data mining architectures in IIOT environment
  • Data mining applications in areas including manufacturing, energy, healthcare, smart city, transportation, etc.
  • Best practices, challenges and future developments
This workshop would like to call for research papers sharing the experiences from the real data and real-world practice. We do not require technical innovations (using existing data mining techniques is totally acceptable). All accepted workshop papers will be published in formal proceedings published by the IEEE Computer Society Press indexed by EI.

Paper Submissions:

Deadline: 7 August 2019, 11:59PM Pacific Time.

Rules:

ICDM workshop follows the same submission requirement as ICDM papers.
  • Long paper (up to 8 pages) and short paper (up to 4 pages). The page limit includes the bibliography and any possible appendices.
  • All papers must be formatted according to the IEEE Computer Society proceedings manuscript style, following IEEE ICDM 2019 submission guidelines available at: http://icdm2019.bigke.org/
  • Papers should be submitted in PDF format, electronically, through email to paper@aistrike.us.
  • All accepted papers will be included in the IEEE ICDM 2019 Workshops Proceedings volume published by IEEE Computer Society Press and will also be included in the IEEE Xplore Digital Library. Therefore, papers must not have been accepted for publication elsewhere or be under review for another workshop, conferences or journals.
IMPORTANT DATES


Paper Submission Deadline: 7 August 2019, 11:59 PM Pacific Time.
Paper Notification: 4 September 2019
Camera Ready Version: 8 September 2019
Workshop: 8 November 2019
Steering Committee
  • Dr. Jay Lee (Univ. of Cincinnati)
  • Dr. Qi Li (Peking University) 
  • Dr. Shaofu Lin (Beijing University of Technology)
  • Dr. Shyam Varan Nath (Oracle)
  • Dr. Richard Mark Soley (Industrial Internet Consortium)
  • Dr. Honggang Wang (University of Massachusetts- Dartmouth)
  • Dr. Jiansheng Zhang (Tsinghua University)


Program Committee
  • Dr. Zhaoheng Gong (Harvard University)
  • Dr. Jay Lee (Univ. of Cincinnati)
  • Dr. Shaofu Lin (Beijing University of Technology)
  • Mr. Song Luo (China Academy of Information and Communication Technology)
  • Dr. Shyam Varan Nath (Oracle)
  • Dr. Honggang Wang (University of Massachusetts- Dartmouth)
  • Dr. Jiansheng Zhang (Tsinghua University)

Workshop Chairs
  • Dr. Ping Chen (University of Massachusetts-Boston) 
  • Dr. Jiang (Jay) Zhou (AI Strike LLC)