Main Content

Livestream: Experts Discuss "AI and Data x Supply Chain"

9:00 am – 11:00 am EDT livestream

Event Details

Date: Tuesday April 13, 2021 | 09:00 AM - 11:00 AM
Speaker(s): Chantal Bisson-Krol, Director, Machine Learning, Kinaxis Inc.

Simai He, Chief Scientist, Cardinal Operations; Distinguished Professor, Department of Management Science, Shanghai University of Finance and Economics

Dr. Mani Janakiram, Sr. Director, Global Supply Chain, Intel Corporation

Sinem Kinay, PhD Candidate, Operations Management, Rotman School of Management

Moderator: Brian Keng, Data Scientist in Residence, TD Management Data and Analytics Lab; Adjunct Professor, Data Science, Rotman School of Management, University of Toronto; Chief Data Scientist, Kinaxis Inc.

Opening Remarks: Susan Christoffersen, Co-Academic Director, TD Management Data and Analytics Lab; William A. Downe BMO Chair in Finance; Professor, Finance, Rotman School of Management
Topic: AI and Data x Supply Chain
Venue:

Please register to receive the link to the livestream.

Location: Online
Cost: Free. All are welcome. Pre-registration is required.
Register Now

Synopsis:  Experts and practitioners in supply chain management discuss how they are leveraging AI and data to improve supply chains. The topics of each presentation will help contextualize the volatile environment with supply chain disruptions observed in 2020.

 
9:00 AM: OPENING REMARKS

Susan Christoffersen, Co-Academic Director of the TD Management Data and Analytics Lab, William A. Downe BMO Chair in Finance and Professor of Finance at the Rotman School of Management

9:04 AM: WELCOME 

Brian Keng, Data Scientist in Residence, TD Management Data and Analytics Lab; Adjunct Professor, Data Science, Rotman School of Management, University of Toronto; Chief Data Scientist, Kinaxis Inc.

9:05 AM: MANAGE A SUPPLY CHAIN NETWORK IN MITIGATION OF A PANDEMIC: A CASE STUDY FROM EAST ASIA

Simai He, Chief Scientist, Cardinal Operations; Distinguished Professor, Department of Management Science, Shanghai University of Finance and Economics

 

9:35 AM:  UTILIZING AUTOML IN DEMAND FORECASTING TO INCORPORATE DISPARATE DATA SOURCES

Chantal Bisson-Krol, Director, Machine Learning, Kinaxis Inc.

 

10:05 AM: STORE SEQUENCING FOR ONLINE ORDER FULFILLMENT IN AN OMNI-CHANNEL RETAILER
Sinem Kinay
, PhD Candidate, Operations Management, Rotman School of Management

10:35 AM: AUTONOMOUS DIGITAL SUPPLY CHAIN 
Dr. Mani Janakiram, Sr. Director, Global Supply Chain, Intel Corporation

11:05 AM: CLOSING REMARKS
Brian Keng
, Data Scientist in Residence, TD Management Data and Analytics Lab; Adjunct Professor, Data Science, Rotman School of Management, University of Toronto; Chief Data Scientist, Kinaxis Inc.


Please note:
 Registrants are welcome to join us for the full event or for the specific topics that interest them. The full event schedule is available showcasing the start times for each session, the topic for discussion and the presenter.

BIOGRAPHIES
Chantal Bisson-Krol is the Director of Machine Learning at Kinaxis who leads the development of multiple intelligent solutions to solve enterprise supply chain problems. One of her primary focuses has been the research and development of automated machine learning solutions for Kinaxis' flagship SaaS product RapidResponse. 

Chantal is passionate about weaving machine learning technology into business solutions with a focus on ease-of-use and interpretability.  She also holds several patents, granted and pending, related to the application of AI to supply chain management. Before joining Kinaxis, Chantal led the development of the BlackBerry Identity Management platform underpinning consumer and enterprise applications at BlackBerry Limited. 

Prior to BlackBerry, she held various positions at Bell-Northern Research, Nortel and Ericsson leading the development of real-time software platforms implementing telecom and data communications protocols at different layers of the OSI stack.  At Nortel she pioneered the use of COTS software and the introduction of Continuous Integration of COTS-based OAM&P platforms. 
Chantal holds a Bachelor of Computer Science degree from Concordia University.  She also serves on the Board of Directors of Kanata Montessori School.

Abstract: 
This presentation will describe the use of Automated Machine Learning in Kinaxis Rapid Response Demand Planning solutions. It will give an overview of the methods used to take advantage of the growing list of available data signals without prior semantic knowledge of the data. We conclude with a few case studies of successful use of these techniques to improve demand forecast accuracy.



Simai He
is the Chief Scientist of Cardinal Operations, and a distinguished professor in the Department of Management Science, Shanghai University of Finance and Economics. His research focuses on optimization theory, operations research and supply chain management, and published in Operations Research, Mathematics of Operations Research, Mathematical Programming, etc. 
He is also on the final list (together with JD.com) of the 2021 INFORMS Franz Edelman Competition.  Cardinal Operations is a leading OR-oriented startup company in China which provides end-to-end solutions for retail, logistics and manufacturing industries. They provide expertise using the independently-developed mathematical optimization solver COPT (Cardinal Optimizer) in solving large-scale optimization problems. Together with its big data team and operations management experts, Cardinal Operations provides unique integrated supply chain and operations management solutions for firms.

Abstract: Nowadays the whole world is fighting together against the pandemic. This disruptive environment creates a huge burden for the supply chain networks as well as the daily operations management of firms. By leveraging advanced forecasting technologies, state-to-art operations management techniques and the self-developed leading mathematical programming solver COPT, Cardinal Operations will present a case study where they developed an integrated solution package which can automatically identify huge spikes in demand quickly, provide robust and adaptive procurement plans, and generate global optimum replenishment/delivery plans within minutes.



Dr. Mani Janakiram, is a Senior Director with Intel and in his 21 years at Intel, he has managed and delivered several strategic projects in factory operations, capacity planning, process control, data, analytics, strategy, supplier management, IOT, factory science, and supply chain. 
His 25+ years of experience also includes Automotive and Aerospace industries. Mani holds two patents and has published 75+ papers on supply chain, statistical modeling, capacity modeling, data mining, Lean Six Sigma, factory operations, and process control. 
He is an adjunct professor at Arizona State University (Supply Chain/Business) and serves on various committees, including AZ Tech Council, ASU Network Value Chain, MIT CTL, Informs, APICS/ASCM, and CSMCP. Mani holds a PhD in Industrial & Systems Engineering from Arizona State University and an MBA from Thunderbird School of Global Management. 
He is a recognized Six Sigma Master Black Belt, holds an APICS CSCP certification, and is an ACSM Fellow and is one of the Top 50 Analytics Executives (Drexel University, CIO).

Abstract: Intel’s supply chain is considered to be among the top supply chains of the world based on our ability to be responsive and reliable to our customers, stakeholders and to the eco systems. Technological advancements such as AI, IOT, Advanced Analytics have played a critical role in making our supply chain a key enabler for Intel’s success. In this presentation, we will go over our supply chain capability, application of AI and Analytics to propel our supply chain towards an intelligent and autonomous digital supply chain and will share a couple of use cases along with lessons learned.



Sinem Kinay is a PhD candidate in the Operations Management and Statistics Area, at Rotman School of Management. Prior to joining Rotman, she received her bachelor’s and master’s degrees from Industrial Engineering Department of Bilkent University. 
Sinem’s research interests are mainly business analytics and optimization. Her current research focuses are on e-commerce fulfillment decisions and developing heuristics that use large-scale data sets by one of the largest retailers in Canada.

Abstract: We investigate a data-driven approach to the online order fulfillment processes of a Canadian omni-channel retailer. Online orders are primarily satisfied by a distribution center and in case of insufficient inventory, brick-and-mortar stores can ship the order. However, stores can accept or reject a fulfillment request based on local information unknown to the retailer. The retailer must then establish a sequence of stores to request fulfillment to minimize expected transportation and delay costs. We investigate policies for single and multi-item order problems and evaluate different heuristics that leverage a large-scale data set provided by the retailer.

 

 

Hosted by:

Sponsored by: 

 

Questions:  events@rotman.utoronto.ca, Megan Murphy


Never miss an event
Sign up for upcoming events notifications »


Cancellation Policy

Cancellations received in writing to events@rotman.utoronto.ca 24 hours prior to the event will receive a refund less a $10 administration fee per person. If we do not receive written notice of your cancellation, you will be charged the full amount for this session. Substitutions are always welcome.

Rotman's Event Privacy Policy

We adhere to both FIPPA and CASL. Read our Event Privacy Statement for details.

CLICK HERE