Maryam Vatankhah

Effective advisor communicates well with people of all levels and backgrounds. Excellent eye for detail enabling quick identification of areas for improvement and suggesting strategies to help students reach goals. Focused on introducing challenges utilizing interpersonal skills, excellent time management and problem-solving skills.

Hands on experience in artificial intelligence, supervised and unsupervised and semi-supervised learning algorithms. Lead novel research in finding relation between electroencephalogram (EEG) signal features and perceptual pain levels and clarifying the relation of classified signal to pain origin. The project resulted in publications. Used several machine learning algorithms for increasing the sensitivity of the system namely: ANFIS, SVM, Neural Network, CNN. Made several pattern recognition’s models to find the best features of the model namely: Fractal dimension, Discrete Wavelet Transform, PCA, LDA. Lead a project to identify sleep patterns in different sleep stages and classify them to be used in sleep clinics and insomnia treatment devices. Different machine learning algorithms and pattern recognition methods has been used to get the best output. Neural Network, Genetic algorithm and SVM Lead to publications. Conducted a project as the Ph.D. dissertation focused on learning a bio-inspired intelligent system based on neural motor control. With the perturbation, demand for robustness and flexibility of the system significantly increases. I have chosen two approaches to address the issue associated with system robustness in perturbations: 1) Developing a computational model learning from human intelligent system using state space. 2) Optimizing the model to select the most robust model during perturbations. Thesis won Innovation and Entrepreneurship fellowship award for 2 consecutive years and lead to some publications . Lead a collaborative project with Columbia university medical center to detect the onset of epileptic seizures. The result opened a new insight in epilepsy therapy and preventive methods in clinical trials. As another phase of the project the dependency between recordings in comatose subarachnoid hemorrhage (SAH) patients at ICU have been investigated. The results shown that some variables play important rule in datasets and the system highly depended to these features. Lead a collaborative project with Columbia university medical center to investigate the effect of missing values in clinical recordings. Causal relations have been studied and an imputation method has been used to decrease the effect of missing values. Naïve Bayes, SVM and KNN, Dynamic Bayesian Network, Simulated annealing. Used NLP algorithms for sentiment analysis of the Twitter data to find the concern level of people in the period of Covid-19. The concern level of all states of the U.S is compared and discussed considering some factors such as fatality rate and confirm cases. Used Twitter API to get data. Python textBlob, twieepy library and Tensor-flow were used. This research has been submitted as a grant proposal to CRIG and its status is still pending. Lead a project to identify the brain biomarkers under cognitive tasks such as attention and memory. Graph theory is using to identify underlying emergent brain patterns. This research submitted as a grant proposal and won PSC-CUNY research award.

• NSF ATE (Advanced Technology Education) program, titled “Navigating Underrepresented Minority Students to In-Demand Tech Careers in Secure Mobile Programming in NYC Region.” This proposal was funded with $625,608, 7/1/2022 – 6/30/2025.
• PSC CUNY grant TRADA-52-318 awarded on 4/15/2021 for Connectivity Analysis of EEG Activity during Pain research proposal.
• Stevens Institute of Technology Innovation and Entrepreneurship fellowship award, 2017
• Stevens Institute of Technology Innovation and Entrepreneurship fellowship award, 2018
• Anita Borg Scholarship Grace Hopper Conference, 29 Sep-2 Oct, 2020

• Vatankhah, Maryam, Hamid R. Kobravi, and Arthur Ritter. "Intermittent control model for ascending stair biped robot using a stable limit cycle model." Robotics and Autonomous Systems (2019): 103255.
• Asadpour, Vahid, Reza Fazel-Rezai, Maryam Vatankhah, and Mohammad-Reza Akbarzadeh-Totonchi. "Pain Identification in Electroencephalography Signal Using Fuzzy Inference System." Brain-Computer Interface (2022): 43.
• Maryam Vatankhah
• Hamid Reza Kobravi, Arthur Ritter. “Bio-Inspired Model of Humanoid Robot for Ascending Movement”2019, 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society, German
• Maryam Vatankhah,Vahid Asadpour “Perceptual pain classification using ANFIS adapted RBF kernel support vector machine for therapeutic usage” Applied soft computing, 2012.
• Maryam Vatankhah, Amir.M Toliyat.A “ pain Level Diagnosis using Discrete Wavelet Transform. International Journal of Engineering and Technology, Vol.8, No.5, May 2016.
• Amir M.Toliyat, Mahdi Yaghoobi, Mehdi Abolhassani, Maryam Vatankhah “A New Method for Optimization of Digital Circuits Using Genetic Algorithm with Chaos Function” International Journal of Advanced Computing” 0975-7686, 2014.
• Maryam Vatankhah,Vahid Asadpour.” Intelligent system for Diagnosing Sleep Stages using wavelet coefficients” 2010 IEEE World congress on Computational Intelligence, Spain.
• Maryam Vatankhah, Mehdi Yaghubi.” Adaptive Nero-Fuzzy Inference System for classification of EEG signals using Fractal Dimension”2009 UKSim 3rd European modeling Symposium On Computer Athens, Greece.
• MaryamVatankhah, Mohamd.R.Akbarzadeh.T.” GA/SVM for Diagnosis Sleep Stages using Non-linear and Spectral Features” 2009 , Online World Conference on Soft Computing in Industrial Applications.
• MaryamVatankhah, Mohamd.R.Akbarzadeh.T.” EEG Pain Level Diagnosis using Intelligent Systems” 2010

• CSC 101 principles in information technology and computation
• CSC103 introduction to data analytics
• CSC 111 introduction to programming I
• CSC 211 introduction to programming II
• CSC 231 discrete structure and applications to computer science
• CSC 350 software development
• CSC 21200 Data Structure-City College CUNY
• CSC 10200 Introduction to Computing- City College CUNY
• MA 120 Introduction to Calculus- Stevens Institute of Technology
• CS 544 Health Informatics- Stevens Institute of Technology
• CS 115 Introduction to Programming - Stevens Institute of Technology
• CISC 1100 Structure of Computer Science- Fordham University
• APAN PS5335 Machine Learning: Concept and Application- Columbia University

· NSF ATE (Advanced Technology Education) program, titled “Navigating Underrepresented Minority Students to In-Demand Tech Careers in Secure Mobile Programming in NYC Region.” This proposal was funded with $625,608, 7/1/2022 – 6/30/2025.

· PSC CUNY grant TRADA-52-318 awarded on 4/15/2021 for Connectivity Analysis of EEG Activity during Pain research proposal.

· Stevens Institute of Technology Innovation and Entrepreneurship fellowship award, 2017

· Stevens Institute of Technology Innovation and Entrepreneurship fellowship award, 2018

· Anita Borg Scholarship Grace Hopper Conference, 29 Sep-2 Oct, 2020