Mohammad Akbari - Amirkabir University of Technology

Supervised MSc Theses

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Thesis title

By

Date

1

Job Recommender System Using Natural Language Processing Techniques & Collaborative Filtering

Sina Zamani & Mohammad Akbari

February 2024

2

Transfer Learning in Automatic Persian Speech Recognition for Voice Assistants

Mohammad Tahmasebi & Mohammad Akbari

February 2024

3

Persian social media data analysis to identify the events and their attributes

Mohammadali Sefidi Esfahani & Mohammad Akbari

September 2023

4

A Machine learning approach for Bipolar and border line disorder classification

Mohammad Javad Nazari & Mohammad Akbari

July 2023

5

An Empathetic Persian Chatbot

Fatemeh Inanloo Soltan Ahmadloo & Mohammad Akbari

July 2023

6

Modeling Protein Metabolite Interaction Using Metabolic Networks

Fayaz Soleymani Babadi & Mohammad Akbari

March 2023

7

A SELF-Supervised Music Recommender System to Reduce Nervous Driving

Arvin Esmaili & Mohammad Akbari

March 2023

8

Cross-learning transfer lerning for Question Answering

Kiana Ghezelbash & Mohammad Akbari

March 2023

9

Identification of biomarkers for predicting gestational age

Arezou Pakseresht & Mohammad Akbari

October 2022

10

Predicting the success of startups based on online data using machine learning

Mahsa Haj Lotfalia & Mohammad Akbari

October 2022

11

User Preference Learning via Conversation in Recommender Systems

Amir Hossein Karimi & Mohammad Akbari

October 2022

12

Multi-task learning for furniture and style detection

Hanieh Ghabelialla & Mohammad Akbari

July 2022

13

Multi-hop Question Answering based on deep learning

Shahrzad Zolghadr & Mohammad Akbari

March 2022

14

Liveness Detection in Face Recognition

Sharzad Esmat & Mohammad Akbari

March 2022

15

Audio – Visual Speech Recognition by Deep Neural Networks

Hekmat Beigverdi & Mohammad Akbari

March 2022

16

Recommender System via Graph Convolutional Networks

Ghazal Molazadeh & Mohammad Akbari

March 2022

17

action recognition using zero-shot learning

Zeynab Saeedi Dehshali & Mohammad Akbari

March 2022

18

Designing A Credit Scoring Ensemble Learning Model

Mahsan Abdoli & Mohammad Akbari

March 2021

Journal Papers

Portal Records

1

Sadeq Kord, Touraj Taghikhany, Mohammad Akbari, "A Novel Spatiotemporal 3D CNN Framework with Multi-task Learning for Efficient Structural Damage Detection", STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL, November 2023 Vol. online, Num. 1, Page 1-18, November 2023,

2

Mehdi Paykan Heyrati, Zahra Ghorbanali, Mohammad Akbari, Ghasem Pishgahi, Fatemeh Zare Mirakabad, "BioAct-Het: A Heterogeneous Siamese Neural Network for Bioactivity Prediction Using Novel Bioactivity Representation", ACS Omega, November 2023 Vol. 47, Num. 8, Page 44757-44772, November 2023,

3

Zahra Ghorbanali, Fatemeh Zare Mirakabad, Najmeh Salehi, Mohammad Akbari, Research Open Access Published: 03 October 2023 Drugrep-Hesiagraph: When Heterogenous, "DrugRep-HeSiaGraph: when heterogenous siamese neural network meets knowledge graphs for drug repurposing", BMC BIOINFORMATICS, October 2023 Vol. 374, Num. 24, Page 1-31, October 2023,

4

Farzaneh Rezaei, Mohammad Akbari, Yousef Rafiei, Abdolhossein Hemmati?Sarapardeh, "Compositional modeling of gas-condensate viscosity using ensemble approach", Scientific Reports, June 2023 Vol. 13, Num. 1, Page 1-21, June 2023,

5

Sepideh Bazzaz Abkenar, Mostafa Haghi Kashani, Mohammad Akbari, Ebrahim Mahdipour, "Learning textual features for Twitter spam detection: A systematic literature review", EXPERT SYSTEMS WITH APPLICATIONS, May 2023 Vol. 228, Num. 0, Page 0-0, May 2023,

6

Zahra Ghorbanali, Fatemeh Zare Mirakabad, Mohammad Akbari, Najmeh Salehi, Ali Masoudi-Nejad, "DrugRep-KG: Toward Learning a Unified Latent Space for Drug Repurposing Using Knowledge Graphs", JOURNAL OF CHEMICAL INFORMATION AND MODELING, April 2023 Vol. 10, Num. 21, Page 1-20, April 2023,

7

Mahsan Abdoli, Mohammad Akbari, Jamal Shahrabi, "Bagging Supervised Autoencoder Classifier for Credit Scoring", EXPERT SYSTEMS WITH APPLICATIONS, March 2023 Vol. 213, Num. 0, Page 2-13, March 2023,

8

Maryam Etemadi, Sepidehbazzaz Abkenar, Ahmad Ahmadzadeh, Mostafa Haghi Kashani, Parvaneh Asghari, Mohammad Akbari, Ebrahim Mahdipour, "A systematic review of healthcare recommender systems: Open issues, challenges, and techniques", EXPERT SYSTEMS WITH APPLICATIONS, September 2022 Vol. 213, Num. 0, Page 1-27, September 2022,

9

Yaghoob Karimi, Mostafa Haghi Kashani, Mohammad Akbari, Ebrahim Mahdipour, "Leveraging big data in smart cities: A systematic review", CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, June 2021 Vol. 33, Num. 21, Page 0-0, June 2021,

Other Records

1

Reza Rawassizadeh, Chelsea Dobbins, Mohammad Akbari, Michael Pazzani, "Indexing multivariate mobile data through spatio-temporal event detection and clustering", Sensors, 2019 Vol. 19, Num. 3, Page , 2019,

2

Mostafa Rezazad, Matthias Brust, Mohammad Akbari, Pascal Bouvry, Ngai-Man Cheung, "Detecting Target-Area Link-Flooding DDoS Attacks using Traffic Analysis and Supervised Learning", Advances in Information and Communication Networks, 2017 Vol. , Num. , Page , 2017,

3

, "Wellness Representation of Users in Social Media: Towards Joint Modelling of Heterogeneity and Temporality", Transaction on Knowledge and Data Engineering, 2017 Vol. 29, Num. 10, Page , 2017,

4

Mohammad Akbari, Xia Hu, Liqiang Nie, Tat-Seng Chua, "Towards Organizing Health Knowledge on Community-based Health Services", EURASIP Journal on Bioinformatics and Systems Biology, 2016 Vol. 17, Num. , Page , 2016,

5

Mohammad Akbari, Liqiang Nie, and Tat-Seng Chua, "aMM: Towards adaptive ranking of multi-modal documents", International Journal of Multimedia Information Retrieval, 2015 Vol. , Num. , Page , 2015,

6

Nie, Liqiang, Yi-Liang Zhao, Mohammad Akbari, Jialie Shen, and Tat-Seng Chua, "Bridging the vocabulary gap between health seekers and healthcare knowledge.", Transaction on Knowledge and Data Engineering, 2015 Vol. 27, Num. 2, Page , 2015,

Conference Papers

Other Records

1

Mohammad Akbari, Alberto Cetoli, Stefano Bragaglia, Andrew D. O’Harney, Marc Sloan, and Jun Wang, "Modeling User Return Time Using Inhomogeneous Poisson Process", The European Conference on Information Retrieval (ECIR), 2019

2

Alberto Cetoli, Stefano Bragaglia, Andrew D. O’ Harney, Marc Sloan, Mohammad Akbari, "A Neural Approach to Entity Linking on Wikidata", The European Conference on Information Retrieval (ECIR), 2019

3

Mohammad Akbari, and Rumi Chunara, "Using Contextual Information to Improve Blood Glucose Prediction", In Machine Learning for Healthcare Conference, 2019

4

Zou, Shihao, Zhonghua Li, Mohammad Akbari, Jun Wang, and Peng Zhang, "MarlRank: Multi-agent Reinforced Learning to Rank", The Conference on Information and Knowledge Management (CIKM), 2019

5

Ray Han, Mohammad Akbari, "Vertical Domain Text Classification: Towards Understanding IT Tickets using Deep Neural Networks", AAAI Conference on Artificial Intelligence, 2018

6

Mohammad Akbari, Rumi Chunara, "From the User to the Medium: Deep Profiling Across Web Communities to Augment Disease Epidemiology", The International AAAI Conference on Web and Social Media (ICWSM), 2018

7

Han, Jianglei, Ka Hian Goh, Aixin Sun, and Mohammad Akbari, "Towards Effective Extraction and Linking of Software Mentions from User-Generated Support Tickets", The Conference on Information and Knowledge Management (CIKM), 2018

8

Kunal Relia, Mohammad Akbari, Dustin Duncan, Rumi Chunara, "Socio-spatial Self-organizing Maps: Using Social Media to Assess Relevant Geographies for Exposure to Social Processes", ACM Conference on Computer-Supported Cooperative Work and Social Computing, 2018

9

Mohammad Akbari, Tat-Seng Chua, "Leveraging Behavioral Factorization and Prior Knowledge for Community Discovery and Profiling", The Tenth ACM International Conference on Web Search and Data Mining, 2017

10

Mohammad Akbari, Xia Hu, Liqiang Nie, Tat-Seng Chua, "On the Organization and Retrieval of Health QA Records for Community-based Health Services", International Joint Conference on Artificial Intelligence, 2016

11

Song, Xuemeng, Liqiang Nie, Luming Zhang, Mohammad Akbari, and Tat-Seng Chua, "Multiple social network learning and its application in volunteerism tendency prediction", The 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2015

12

Farseev, Aleksandr, Liqiang Nie, Mohammad Akbari, and Tat-Seng Chua, "Harvesting multiple sources for user profile learning: a big data study", The ACM on International Conference on Multimedia Retrieval, 2015

13

Nie, Liqiang, Mohammad Akbari, Tao Li, and Tat-Seng Chua, "A joint local-global approach for medical terminology assignment", The 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2014

14

Nie, Liqiang, Tao Li, Mohammad Akbari, Jialie Shen, and Tat-Seng Chua, "Wenzher: Comprehensive vertical search for healthcare domain", The 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2014

Journals Editorial Board

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Magazine Title

Date of Cooperation & Explanations

1

Associate Editor, Journal of Frontiers in Artificial Intelligence

2

IEEE Transaction on Knowledge and Data Engineering (TKDE).

3

ACM Transaction on Knowledge and Data Discovery (TKDD).

4

Pattern Recognition Letters Journal

5

Journal of Information Sciences.

6

Journal of Data Mining and Knowledge Discovery

7

Journal of Biomedical Informatics (JBI).

Taught Courses

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Course title

Description

Headlines

Date

1

Data Structures & Algorithms

Covers the design, analysis, and implementation of data structures and algorithms to solveengineering problems using an object?oriented programming language. Topics include elementary datastructures, (including arrays, stacks, queues, and lists), adv

Fall 2022

2

Computer Prog.

To familiarize the trainee with basic concepts of computer programming and developer tools. To present the syntax and semantics of the “C” language as well as data types offered by the Language. To allow the trainee to write their own programs us

Fall 2022

3

Machine Learning

This course provides a fundamental introduction to the mathematics, algorithms and practice of machine learning, focusing on representation, loss functions, and optimization.

Fall 2022