Maryam Vatankhah

Maryam Vatankhah


Assistant Professor
Computer Information Systems

EMAIL: mvatankhah@bmcc.cuny.edu

Office: F-1030M

Office Hours:

Phone: +1 (212) 220-1488

Professor Vatankhah is an experienced data scientist with deep knowledge of Computer Science, Math, and Electrical Engineering, over 4 years of experience and research in data analysis, machine learning, and artificial intelligence resulted in published peer-reviewed papers and conferences.

Expertise

Degrees

MBA, Zicklin School of Business (2020 – 2022)
Ph.D. in Engineering, Stevens Institute of Technology (2015 – 2018)
Master’s Degree, Computer Science (2013 – 2015)
Master’s Degree, Biomedical/Medical Engineering, Islamic Azad University (2007 – 2010)
Bachelor’s Degree, Electrical, Electronics and Communications Engineering, Islamic Azad University (1999 – 2004)

Courses Taught

Research and Projects

  • Machine learning-based digital curation platform for research assets
  • Transforming research in artificial intelligence for nourishment
  • Training future mobile programming professionals with industry-specific skills
  • Initiating data analytics tracks in CIS department
  • Tracking CUNY citizens’ concerns during Covid-19 pandemic to determine its
    educational impact
  • People’s concern level during Covid-19 and its relationship with the stock market
    variations using sentiment analysis of Twitter data
  • Tracking employee’s stress level at the workplace
  • Studying pain biomarkers using brain networks

Publications

    • Intermittent control model for ascending stair biped robot using a stable limit cycle model (Elsevier August 27, 2019)
    • Bio-inspired Model of Humanoid Robot for Ascending Movement (IEEE July 23, 2019)
    • Pain Level Diagnosis using Discrete Wavelet Transform (International Journal of Engineering and Technology May 1, 2015)
    • A New Method for Optimization of Digital Circuits Using Genetic Algorithm with Chaos Function (International Journal of Advanced Computing April 1, 2014)
    • Perceptual pain classification using ANFIS adapted RBF kernel support vector machine for therapeutic usage (Applied Soft Computing December 8, 2012)

Honors, Awards and Affiliations

  • PSC_CUNY Research Award (May 2021)
  • Studying pain biomarkers using brain networks, Anita Borg Scholarship , Grace Hopper Conference (Sep 2020)
  • Stevens Institute of Technology Innovation and Entrepreneurship Fellowship Award (Mar 2018)
  • Stevens Institute of Technology Innovation and Entrepreneurship Fellowship Award (Mar 2017)

 

Additional Information