EHSAN NAZERFARD
Assistant Professor
Department of Computer Engineering
Artificial Intelligent and Robotics
Department of Computer Engineering
Artificial Intelligent and Robotics
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Email:
nazerfard
aut.ac.ir
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h-index (Scopus):
7
Citations (Scopus):
231
Supervised MSc Theses
#
Thesis title
By
Date
1
Predicting Patients recovery Process based on medical records using deep learning
Amir Hossein Batouei & Ehsan Nazerfard
October 2021
2
image retrieval based on using statistical modeling
Maryam Taheri Golpayegani & Ehsan Nazerfard
October 2021
3
Deep Learning For Human Activity Recognition Using Mobile and Wearable Sensors
Mohammad Tavakkoli & Ehsan Nazerfard
September 2021
4
Improved environmental perception in Autonomous Vehicles using deep neural neworks
Milad Bohlouli & Ehsan Nazerfard
September 2021
5
Design and implemention of dialogue system between human and chatbot using deep learning
Alireza Farasat Memar & Ehsan Nazerfard
December 2020
6
addressing learning challenge in imbalanced datasets
Rasool Panahi & Ehsan Nazerfard
July 2020
7
A an unsupervised method for strategy detection in iterated prisoners dilemma
Saleh Jafarizadeh & Ehsan Nazerfard
July 2020
8
Routing Optimization in Knowledge-Defined Networking: A Deep Learning Approach
Samira Mokabberi & Ehsan Nazerfard
July 2020
9
providing a method for link prediction in complex networks
Masoud Malek & Ehsan Nazerfard
July 2020
10
Abnormal activity detection for the elderly people in smart homes
Zahra Atashgahy & Ehsan Nazerfard
September 2019
11
Cross-subject Transfer Learning in Human Activity Recognition using Generative Adversarial Networks
Elnaz Soleimani & Ehsan Nazerfard
February 2019
12
Activity Recognition on Streaming Sensor Data
Parviz Asghari & Ehsan Nazerfard
February 2018
13
Predicting Drug-drug Interactions In Physician Prescriptions
Mohammadreza Abdollahi & Ehsan Nazerfard
October 2016
Journal Papers
Portal Records
1
Elnaz Soleimani, Ehsan Nazerfard, "Cross-Subject Transfer Learning in Human Activity Recognition Systems using Generative Adversarial Networks", NEUROCOMPUTING, November 2020
Vol. 0,
Num. 0,
Page 1-11,
November 2020,
2
Milad Sadat Mohammadi, Morteza Nazari-Heris, Ehsan Nazerfard, Mehrdad Abedi, Somayeh Asadi, Houtan Jebelli, "Intelligent Approach for Residential Load Scheduling", IET GENERATION TRANSMISSION & DISTRIBUTION, September 2020
Vol. 14,
Num. 21,
Page 4738-4745,
September 2020,
3
M.S.M, M.N.H, Ehsan Nazerfard, Mehrdad Abedi, S.A, H.J, "Intelligent approach for residential load scheduling", IET GENERATION TRANSMISSION & DISTRIBUTION, September 2020
Vol. 14,
Num. 21,
Page 4738-4745,
September 2020,
4
Parviz Asghari, Elnaz Soleimani, Ehsan Nazerfard, "Online Human Activity Recognition Employing Hierarchical Hidden Markov Models", Journal of Ambient Intelligence and Humanized Computing, June 2019
Vol. 11,
Num. 1,
Page 1-12,
June 2019,
5
Ehsan Nazerfard, "Temporal Features and Relations Discovery of Activities from Sensor Data", Journal of Ambient Intelligence and Humanized Computing, May 2018
Vol. 10,
Num. 1,
Page 1-15,
May 2018,
Conference Papers
Portal Records
1
Ali Risheh, Seyed Amirmohammad Jalili Shani, Ehsan Nazerfard, "Smart Irrigation IoT Solution using Transfer Learning for Neural Networks ", 10th International Conference on Computer and Knowledge Engineering, October 2020
2
Rasool Panahi, Nima Sedghiyeh, Ehsan Nazerfard, "A novel data cleaning method for learning in imbalanced datasets based on k-nearest neighbors ", 10th International Conference on Computer and Knowledge Engineering, October 2020
3
Yoosof Mashayekhi, Ehsan Nazerfard, Alireza Ranjbar, Samira Shirzadeh, "The MinMax Fuzzy C-Means ", 5th International Conference on Knowledge-Based Engineering and Innovation, February 2019
4
Parviz Asghari, Ehsan Nazerfard, "Activity Recognition using Hierarchical Hidden Markov Models on Streaming Sensor Data ", The 9th International Symposium on Telecommunications, December 2018
5
Masoomeh Rahimi Ghazikalayeh, Asghar Zarei, Ehsan Nazerfard, Mohammad Hassan Moradi, "Ensemble Methods Combination for Motor Imagery Tasks in Brain Computer Interface ", International Iranian Conference on Biomedical Engineering-ICBME, November 2016
Taught Courses
#
Course title
Description
Headlines
Date
1
Machine Learning
The objective of Machine Learning is to study algorithms capable of learning from past experiences and data
Fall 2021
2
Applied Machine Learning
Today, machine learning is widely used in various fields of science and engineering. The purpose of this course is to acquaint students of different engineering fields with machine learning in a practical way. In this course, different algorithms tha
Fall 2021
3
Applied Linear Algebra
The course consists of the topics of linear algebra and its applications and optimization that are extensively used in different fields of computer engineering. The course contains topics of linear equations, matrices, eigenvalues and eigenvectors, v
Fall 2021
4
Data Structures and Algorithms
In this course, the students will learn important data structures as well as algorithms required to deal with these data structures
Fall 2021
5
Machine Learning
The objective of Machine Learning is to study algorithms capable of learning from past experiences and data
Spring 2021
6
Data Mining
Data mining is a practice of data processing and applying algorithms on the data available from domain to solve domain related problems. Data mining involves six common classes of tasks: • Anomaly detection (outlier/change/deviation detection) –
Spring 2021
7
Machine Learning
The objective of Machine Learning is to study algorithms capable of learning from past experiences and data
Fall 2020
8
Applied Linear Algebra
The course consists of the topics of linear algebra and its applications and optimization that are extensively used in different fields of computer engineering. The course contains topics of linear equations, matrices, eigenvalues and eigenvectors, v
Fall 2020