601 Big Data in Chemical and Pharmaceutical Processes


Description:
Contributions are invited on the topic of big data methods in chemical and pharmaceutical processes.

Sponsor:
Data and Information Systems


Chair:
Ravendra Singh
Assistant Research Professor
Rutgers, The State University of New Jersey
Department of Chemical and Biochemical Engineering
98 Brett Road
Piscataway, NJ
08854
Fax Number: +17324452581
Email: ravendra.singh@rutgers.edu

Co-Chair:
Q. Peter He
Associate Professor
Auburn University
Chemical Engineering
Auburn, AL
36088
Fax Number: 334-724-4188
Email: qhe@auburn.edu


Papers:
601a
Machine Learning for Automated Meal Detection in Glucose Control Systems for People with Diabetes
Sediqeh Samadi, Illinois Institute of Technology; Mudassir Rashid, Illinois Institute of Technology; Iman Hajizadeh, Illinois Institute of Technology; Jianyuan Feng, Illinois Institute of Technology; Mert Sevil, Illinois Institute of Technology; Caterina Lazaro, Illinois Institute of Technology; Nicole Hobbs, Illinois Institute of Technology; Rachel Brandt, Illinois Institute of Technology; Ali Cinar, Illinois Institute of Technology
601b
Source Analysis of Process Variability in Multi-Step Bio-Process Manufacturing
Yuan Jin, University of Southern California; S. Joe Qin, University of Southern California; Victor M. Saucedo, Genentech; Zheng Li, Genentech; Angela Meier, Genentech; Siddhartha Kunda, Genentech; Briana Lehr, Genentech; Salim Charaniya, Genentech
601c
Multi-Rate Hard and Soft Sensors Fusion for Monitoring Chemical Processes
Zhenyu Wang, The Dow Chemical Company; Leo H. Chiang, The Dow Chemical Company
601d
A New Big Data Benchmark Problem: Fluid Catalytic Cracker Under Model Predictive Control
Omar S. Santander, The University of Texas at Austin; Michael Baldea, The University of Texas at Austin
601e
Computation-Driven Mechanistic Understanding of the Cellular Cost and Regulation of Melanin Production
Rajib Saha, University of Nebraska-Lincoln; Wheaton Schroeder, University of Nebraska - Lincoln
601f
Using Data Variety for Modeling and Control of Batch Processes
Abhinav Garg, McMaster University; Prashant Mhaskar, McMaster University
601g
Optimal Input and Sensor Selection for System Health Assessment
Kyle A. Palmer, University of Connecticut; George M. Bollas, University of Connecticut
601h
Performance Characterization and Fault-Tolerant Control of Multi-Rate Sampled-Data Process Systems with Unknown Measurement Delays
James Allen, University of California, Davis; Nael H. El-Farra, University of California, Davis
Abstract Submissions Closed
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