Dr. Reza Khani

Assistant Professor
Office:  OCNL 304
Campus Zip: 888 
Phone: (530) 898-5831  
E-mail:  mkhani@csuchico.edu

Website:https://mkhani.yourweb.csuchico.edu

Ph.D. Western Michigan University

Microprocessor Design, CPU and GPU Microarchitecture, Estimation Theory (Kalman Filtering), GPGPU (NVIDIA CUDA), Parallel Computation, Machine Learning

• Education
  • Western Michigan University, 2021

          Ph.D. in Electrical and Computer Engineering

          Advisor: Dr. Ikhlas Abdel-Qader

  • California State University, Fullerton, 2015

          M.Sc. in Electrical Engineering

          Advisor: Dr. Mohinder S. Grewal

  • Islamic Azad University, Central Tehran Branch, 2003

          B.Sc. in Electrical Engineering

          Advisor: Dr. Arash Dana

• Experience
  • Assistant Professor of Electrical and Computer Engineering, 6/2022 - Present

  California State University, Chico

  • NVIDIA Deep Learning Institute Ambassador, 4/2019 - Present

  NVIDIA Corporation

  • Assistant Professor of Computer Engineering, 8/2018 - 5/2022

  Indiana Institute of Technology

  • Graduate Research/Teaching Assistant, 1/2016 - 7/2018

  Western Michigan University

  • Graduate Research/Teaching Assistant, 9/2013 - 12/2015

  California State University, Fullerton

• Research and Grants

  Research

           My research interests span a broad range of fields that include computer architecture, CPU and GPU microarchitecture; machine learning, risk analysis, estimation theory specially Kalman filter and their applications in various areas ranging from medical sciences to business and finance. More recently, I have been particularly interested in general-purpose GPU computing or GPGPU which is the use of a GPU to do general purpose scientific and engineering computing. Within this area I am investigating parallel applications specifically heat transfer and computational fluid dynamics (CFD) problems, Kalman filter algorithm, data structures and algorithms, scalability, parallel architectures, and programming machine learning algorithms for the GPU and particularly the implementations of machine learning in GPU microarchitecture. My research agenda focuses on the question of how to apply the Machine Learning techniques in the GPU and CPU microarchitecture to achieve higher performance. I also closely work and collaborate with NVIDIA, and I am part of the NVIDIA Deep Learning Institute (DLI).

  Grants

  • New Faculty Research fund, $26,000, California State University, Chico, 2022-2024

  • NVIDIA travel grant to participate in the NVIDIA GPU Technology Conference 2019, San Jose McEnery Convention Center on March 17-21, $2500, 2019

  • NVIDIA academic hardware and software/platform grant, $3000, 2019-2021

  • Intel travel fund to participate in the 2011 IDF conference (the Intel Developer Forum) in

  San Francisco, CA, $4000, 2011

• Recent Publications
   

  Peer-reviewed Journal Publications: 

  • Mohammadreza Khani and Ikhlas Abdel-Qader, “Machine learning based asynchronous computational framework for generalized Kalman filter,” Concurrency and Computation: Practice and Experience Journal, John Wiley & Sons Ltd., June 2021 (Under review).

  • Tai-Hsien Wu, Mohammadreza Khani, Lina Sawalha, James Springstead, John Kapenga, Dewei Qi, “A CUDA Based Implementation of a Fluid-Solid Interaction Solver: The Immersed Boundary Lattice-Boltzmann Lattice Spring Method,” Communications in Computational Physics (CiCP) Cambridge University Press, p1-32, 2017.

  • Chandrasekhar Putcha, Brian W. Sloboda, and Mohammadreza Khani, “Development Application of Composite Indices (CI): An Emerging Method to the Disciplines of Engineering, Economics and Finance,” European Scientific Journal (ESJ), Vol. 12, No. 28, ISSN: 1857 – 7881, October 2016.

  • Chandrasekhar Putcha S., Brian W. Sloboda, and Mohammadreza Khani, “A New Approach for a Forecasting Model in the Estimation of Social Security Benefits,” Journal of Applied Business and Economics, Vol. 18(2), 2016.

  • Chandrasekhar Putcha, S., Mina Khani, Mohammadreza Khani, and Paul Miller, “A Detailed Risk Analysis of Factors Contributing to Occurrence of Subdural Hematoma,” European Scientific Journal (ESJ), Vol.10, No.18, ISSN: 1857 – 7881, June 2014.

  Peer-reviewed conference publications:

  • Adam Tabba, Chandrasekhar Putcha, Brian Sloboda, Vineet Penumarthy, and Mohammadreza Khani, “Mathematical Analysis of Unemployment Benefits,” Global Conference on Business and Finance Proceedings, Vol. 11, No. 1, Pages 118-125, ISSN 2168-0612, Honolulu, Hawaii, January 4-7, 2016.

  • Chandrasekhar Putcha, Brian Sloboda, and Mohammadreza Khani, “A New Approach for a Forecasting Model in the Estimation of Social Security Benefits.” The 35th International Symposium on Forecasting, ISF 2015 Proceedings, Page 70, ISSN 1997-4124, Riverside, CA, June 21-24, 2015.

  • Chandrasekhar Putcha, Brian Sloboda, Vishwanath Putcha, Mohammadreza Khani, and Adam Tabba, “Financial Aspects of Determining Optimal Occupancy Factor for Hotels Based on Probabilistic Analysis.” Global Conference on Business and Finance Proceedings, Vol. 10, No. 1, Pages 39-46, ISSN 1941-9589, Las Vegas, Nevada, January 4-7, 2015.

    

  Poster Presentations and Workshops:

  • Conducted the following workshops in the NVIDIA GPU Technology Conference (GTC 2019), San Jose McEnery Convention Center on March 17-21, 2019:
    • Accelerating Applications with CUDA C/C++
    • High Performance Computing using Containers
    • Programming GPU-Accelerated POWER Systems with OpenACC

  • Tai-Hsien Wu, Mohammadreza Khani, Lina Sawalha, James Springstead, Dewei Qi, “To Implement a Lattice Boltzmann Lattice-Spring Method by Using CUDA.” 25th International Conference on Discrete Simulation of Fluid Dynamics (DSFD 2016), Guangdong, China, July 4-8, 2016.

  • Chandrasekhar Putcha, S., Mina Khani, Mohammadreza Khani, and Paul Miller, and Adam Tabba, “Validation of Risk Model Using Patient Clinical Data” was presented at the 2014 AMSUS Annual Education Meeting, Washington, DC Walter E. Washington Convention Center, 2-5 December 2014.

  • Chandrasekhar Putcha, S., Mina Khani, Mohammadreza Khani, and Paul Miller, “A Comprehensive Risk Factor to Predict Occurrence of Stroke,” was presented at AMSUS Conference held in Seattle, Washington, November 2013.
• Awards and Affiliations

  Awards and Honors

  • Featured on the Indiana Tech magazine summer 2019 issue for my contributions to the 2019 NVIDIA GPU Technology Conference in San Jose, 2019

  • Western Michigan University Graduate College Full Tuition Scholarship and Stipend, 1/2016

  • Cal State Fullerton travel grant to participate in the 2013 AMSUS (the Association of Military Surgeons of the United States) conference in Seattle, WA, 10/2013

  • Non-Resident Tuition Fee Waiver (NRTFW) Award by the College of Engineering and Computer Science of Cal State Fullerton, 8/2013

  • Professor & Mrs. Ting Pan Memorial Scholarship, 4/2013

  • Participated in the Iran Mathematical Olympiad, 1995-96

  Professional Activities

  • NVIDIA Deep Learning Institute Ambassador, 2019-Present
  • NVIDIA GPU Technology Conference Presenter and Workshop Instructor, 2019

  Professional Memberships:

  • ACM SIGARCH
  • Institute of Electrical and Electronics Engineers (IEEE)
  • IEEE Computer Society
  • Iranian Association of Electrical and Electronics Engineers

  Leadership Experience:

  • IEEE Club Advisor, California State University, Chico (2022-Present)