Faculty
Adjunct Professor
Scott Chin
Dr. Scott Chin’s research is focused on machine learning, deep learning, neural networks, FPGA architectures and EDA algorithms. Since finishing
his Ph.D. at UBC in 2011, where his research on computational scalability of computer aided design (CAD) algorithms won multiple awards, Scott has worked at multiple successfully exited high-tech startups.
Starting in 2011, Scott joined Veridae Systems as an early employee to develop complex routing and mapping algorithms for Veridae’s flagship Certus product. Veridae was quickly acquired by Tektronix. After Tektronix, Scott founded his own highly successful mobile app development company with over 10M downloads and strategic development grants from both Microsoft and Nokia. Later, Scott joined Invionics where he continued to develop complex software and algorithms for Invionics’ leading-edge Invio EDA Platform. Invio was acquired by EDA leader Verific Design Automation. Scott’s work on cutting-edge developments continued when he joined Qualcomm, as a result of acquisition, to implement unique and proprietary software/hardware technologies that were quickly adopted across Qualcomm's IC portfolio.
Currently, Scott is Principal Architect and VP Research of Vancouver-based start-up Singulos Research Inc. where he is focused on developing innovative Deep Learning based IP and solutions.
Courses
| ELEC 402 |
Introduction to VLSI Systems The chip design process using VLSI design styles in CMOS technology. Data path, control and register file design and layout. Clocking schemes, flip-flop and latch-based design. VHDL/Verilog design project using CAD tools. [3-0-2] |
| CPEN 311 |
Digital Systems Design Advanced combinational and sequential electronic system design. Hardware specification, modeling, and simulation using hardware description languages (HDLs) and CAD tools. Design with programmable logic including FPGA's. Applications include complex state machines, microcontrollers, arithmetic circuits, and interface units. Credit can be given for only one of CPEN 311 or EECE 379. [3-3-0] |
| CPEN 400D |
Deep Learning Course Description Although deep learning is based on many well known artificial intelligence (AI) concepts dating back decades or more, it has come to prominence again based on the number of recent successes. A combination of improved algorithms, increased access to data, and the availability of low-cost/high-performance computing resources have dramatically improved the performance of deep learning for certain application areas. |
Contact
Office:The University of British Columbia
4025 - 2332 Main Mall
Vancouver BC V6T 1Z4
Canada
http://www.singulosresearch.com
