
Meet Our Innovators
Thomas Chen, PhD
Business Challenge Endowment Professor, Electrical and Computer Engineering; Faculty Member, School of Biomedical Engineering (SBME)
Areas of Collaborative Interest
- Licensing our technologies
- Design of VLSI (Very Large Scale Integration) Systems for Biomedical Applications
- Low-Power Analog and Mixed Signal Circuit Design
- Bioelectronics
- Biosensors
- CAD Methodology for VLSI Systems
Innovation Portfolio
The Bioanalytical Lab for Integrated Sensor Systems (BLISS) is a research group at Colorado State University that focuses on developing analytical devices integrating microelectronics, microfluidics, chemistry, and biology to address pressing challenges in medicine and global health. BLISS works jointly with a number of other research laboratories in the Department of Electrical & Computer Engineering, School of Biomedical Engineering, Department of Biomedical Sciences, and Department of Chemistry, to engage in multidisciplinary research activities to bring new diagnostic and medical instrumentation technologies to the field. The interdisciplinary research activities include design and manufacturing of integrated circuits and integrated fluidic devices, device surface preparation, and test and characterization of devices in a variety of application settings. Specifically, research interests of the lab lie in the areas of large scale integrated systems for high density and high performance sensing and computation systems, analog and digital circuit design and low power implementations for biomedical applications, biosensors, and microfluidic devices.
Dextronics
Whiteridge Biosciences
- US20180224394A1, WO2018148312A1: Handheld electrochemical sensing platform
- US8010334B2: Method and apparatus for evaluating integrated circuit design performance using basic block vectors, cycles per instruction (CPI) information and microarchitecture dependent information*
- US7844928B2: Method and apparatus for evaluating integrated circuit design performance using enhanced basic block vectors that include data dependent information*
- US7770140B2: Method and apparatus for evaluating integrated circuit design model performance using basic block vectors and fly-by vectors including microarchitecture dependent information*
- US7139986B2: Systems and methods for determining costs associated with a selected objective*
- US7000204B2: Power estimation based on power characterizations*
- US6951001B2, FR2844373A1: Method for analysis of interconnect coupling in VLSI circuits*
- US6858897B2, JP2004336035A: Individually adjustable back-bias technique*
- US6711720B2,FR2839568A1: Method of optimizing high performance CMOS integrated circuit designs for power consumption and speed through genetic optimization*
- US6785870B2, DE10307268A1: Method of optimizing high performance CMOS integrated circuit designs for power consumption and speed using global and greedy optimizations in combination*
- US6728941B2, GB2386721B: Method of modeling the crossover current component in submicron CMOS integrated circuits designs*
- US6687888B2, JP2003308350A: Method of optimizing high performance CMOS integrated circuit designs for power consumption and speed*
*Assignee other than Colorado State University Research Foundation