Dr. Raja Jayaraman
Dr. raja jayaraman Associate Professor Industrial And Systems Engineering

Contact Information
raja.jayaraman@ku.ac.ae +97123124177


Raja Jayaraman received his Bachelor's and Master's degrees in Mathematics from India in 1996 and 1999, a Master's degree in Industrial Engineering from New Mexico State University in 2005, and a Ph.D. degree in Industrial Engineering from Texas Tech University in 2008. He was a post-doctoral research fellow (August 2008- August 2011) at the Center for Innovation in Healthcare Logistics, University of Arkansas. His post-doctoral research was on technology adoption and innovative practices for improving the healthcare supply chain, logistics, and service delivery. He has led several successful research projects and pilot implementation on adopting supply chain data standards in the US healthcare system. 

In August 2011, he joined as Assistant Professor in the Department of Industrial and Systems Engineering, Khalifa University, Abu Dhabi, United Arab Emirates, and was promoted to Associate Professor in November 2017. Raja teaches graduate and undergraduate courses in supply chain and logistics, optimization, stochastic models, systems engineering, and quality management. 

  • Ph.D. Industrial Engineering, Texas Tech University, USA
  • MSc. Industrial Engineering, New Mexico State University, USA
  • MSc. Mathematics, Anna University, Chennai, India
  • BSc. Mathematics, University of Madras, India

  • Advanced Stochastic Processes (ISYE432)
  • Introduction to Industrial & Systems Engineering (ECCE432)
  • Operations Research 1 (ISYE251)
  • Quality Control & Reliability (ISYE311)
  • Supply ChainLogistics and Transportation Networks (ISYE430)
  • Systems Engineering (ESMA633)
  • Systems Optimization (ENGR605)

Affiliated Research Institutes/Centers
  • Research Center for Digital Supply Chain and Operations Management

Research Interests
  • Digital Manufacturing and Supply Chain; Industry 4.0 tools and applications
  • Industry 4.0 tools and applications
  • Quality 4.0, Operational Excellence
  • Multicriteria Optimization
  • Healthcare Systems Engineering

Research Projects

Predictive Analytics for Supply Chains 

Supply chain and logistics management primarily deals with managing efficient flow of information and products from several sources to their respective destinations. Globalization and rapid development across several industries has made supply chains more complex, and susceptible to higher risks that requires sophisticated tools and analytical solutions to manage and predict demand owing to longer lead times. Making decisions merely based on past data and trends can no longer provide competitive advantage to companies. In turn, supply chain analytic tools exploit the dynamics and interconnectedness in forecasting, pricing, procurement, storage, distribution and other areas. Globalized supply chains have offered new business opportunities and markets with a renewed focus on quality and cost.  Supply Chain Analytics aims at researching new methods and tools to integrate and improve-performance of complex and extended enterprise supply chains using predictive analytics and self-optimizing logistics. As supply chains get bigger and more complex, the amount of data generated by the network grows correspondingly. Data is also being collected from several channels such as linked instrumentation and sensors. To fully understand and act on the "state" of the supply network, it is becoming increasingly important to use a data-driven approach to process and analyze this data in support of supply chain planning and management requirements. This project employs predictive analytics techniques to analyze variables such as inventory levels, customer demand, capacity of transportation channels and even equipment maintenance requirements.

Digital Operations Management 

Due to globalization, the modern supply chains often span several countries and continents. Traceability of the products in such supply chains becomes hard or almost impossible due to different registration systems involved in the process. At the same time, visibility, traceability and transparency for the end customers are the major efficiency and sustainability pillars for any Supply Chain System. All of these three pillars require enhanced digitalization for enabling paperless, borderless and highly trusted access to all relevant information for all parties using the supply chains. Blockchain is a newly emerging technology that is capable to provide necessary security, visibility, traceability and transparency of the digital transactions in any supply chain (and other businesses). Blockchains are decentralized, distributed ledgers of transactions that run on multiple computers around the world—making a storage system that is robust against attacks and hacking. Blockchains can be public or private network . Also, Ethereum blockchain allows for programmability to include algorithms, rules, conditions, and flow logic to be executed by all participating blockchain nodes. The execution outcomes of all of these nodes are shared and eventually agreed by all blockchain nodes—and therefore, achieving high trust and credibility throughout the blockchain ledgers which is globally accessed by participating stakeholders. Smart contract code will be developed and written to provide undisputed, credible, and authenticated control functionalities related to cargo and shipment identity, access, generated data (e.g., normal readings, push and pull notifications, alerts, etc.), ownership, origination and history, state, movements, etc.  Ethereum Blockchain can be used to record, track, govern access, and even perform automating billing using Ether cryptocurrency of a container or a cargo as it is being shipped, moved, handled, inspected, and approved among multiple stakeholders.

IoT-Driven Blockchain Solution for Superior Management of Healthcare Supply Chain and Medical Data

Cold supply chain management in healthcare is the generic term for management of sensitive medical items throughout the manufacturing, shipment, transport, distribution and storage processes until its ultimate use on patients.  During the supply chain phases, medical items and products such as pharmaceuticals, vaccines, blood samples, human tissue, and organs should be stored, shipped, and transported with stringent conditions that have to be met all the time. These conditions include temperature, humidity, light, oxygen, vibration, etc. Static measurements at points of transfer are commonly recorded throughout healthcare supply chains, but capabilities in current systems do not permit continuous monitoring, recording and tracking the temperature as products are transported locally within a country and or globally across international borders. In addition, it is pivotal to verify the quality and integrity to ensure that the shipment has not been tampered with and all vital conditions are within a specified range. Due to the presence of multiple uncontrolled variables in the manufacturing-distribution process, developing an appropriate monitoring system is essential. IoT and blockchain can provide the perfect solution for this critical problem.  

Research Staff and Graduate Students:

Ilhaam A Omar Research Associate
Haya Hasan Research Associate
Madine Mohammed Research Associate
Ammar Battah Research Associate
Ahmad Musamih PhD Student
Abdulrahim Haroun Ali PhD Student
Salah Emad Al-Nazer MSc. ESMA Student
Shand Sane MSc. ESMA Student
Aysha Salem Alnuaimi MSc. ESMA Student
Additional Info

Raja’s current research interests focus on a multidisciplinary approach to engineering problems applying systems engineering, process optimization, operational excellence, and digital transformation tools to characterize, model, and study complex systems in supply chains, digital manufacturing, healthcare delivery, distribution, logistics, and maintenance. Raja has  published over 80 journal articles, 24 refereed conference proceedings, including one best paper award, 9 book chapters, and magazine articles.Raja is a senior member of the Institute of Industrial & Systems Engineering (IISE) and a member of the Institute for Operations Research and Management Science (Informs). He serves on the editorial board of the International Journal of Quality, Reliability and Management(IJQRM) and the International Journal of Lean Six-Sigma (IJLSS).