Maysam Behmanesh

Postdoctoral Researcher at LIX, École Polytechnique, IP-Paris

I'm a Postdoctoral Researcher in the GeomeriX group at the LIX research laboratory of École Polytechnique IP-Paris working with Prof. Maks Ovsjanikov. I graduated with Ph.D. in Computer Engineering (Artificial Intelligence) from University of Isfahan (UI) in February 2022. I worked for five years in machine learning topics under the supervision of Dr. Peyman Adibi. My current research is related to machine learning especially geometric deep learning with emphasis on graphs and multimodal machine Learning. From 2019 to 2020, I continued my research in GIPSA-Lab with Grenoble Institute of Technology, Grenoble, France, as a visiting scholar under the supervision of Prof. Jocelyn Chanussot.

News

April, 2023
Publication

Our paper "TIDE: Time Derivative Diffusion for Deep Learning on Graphs", with Maximilian Krahn and Maks Ovsjanikov has been accepted at ICML 2023.

December, 2022
Preprint

Our new work entitled "TIDE: Time Derivative Diffusion for Deep Learning on Graphs", joint with Maximilian Krahn and Maks Ovsjanikov is now available as a preprint.

October, 2022
Publication

Our paper, Geometric Multimodal Deep Learning With Multiscaled Graph Wavelet Convolutional Network (joint with Peyman Adibi, Saeed Ehsani, and Jocelyn Chanussot) is published in IEEE Transactions on Neural Networks and Learning Systems. PDF

April, 2022
New position

I have started a new journey as a Postdoctoral Researcher in the GeoViC group at the LIX research laboratory of École Polytechnique.

February 2th, 2022
PhD Defense

I successfully defended my PhD dissertation with the "Excellent" degree.

Dec 12th, 2021
Talk

I gave a talk on Geometric multimodal deep learning for the annual research week seminar at the University of Isfahan (slides).

Nov 27th, 2021
Preprint

Our new work entitled "Geometric Multimodal Deep Learning with Multi-Scaled Graph Wavelet Convolutional Network", joint with Peyman Adibi, Jocelyn Chanussot, and Saeed Ehsani is now available as a preprint.

May 12th, 2021
Preprint

Our new work on Cross-Modal and Multimodal Data Analysis (joint with Peyman Adibi, Jocelyn Chanussot, and Saeed Ehsani) is available as a preprint.

March 23th, 2021
Talk

I gave a talk at CE department: Geometric multimodal learning adjusted on manifolds (slides).

January 6th,2021
Publication

Our paper, Geometric Multimodal Learning Based on Local Signal Expansion for Joint Diagonalization (joint with Peyman Adibi, Jocelyn Chanussot, Christian Jutten, and Saeed Ehsani) is published in IEEE Transactions on Signal Processing. PDF

August 15th, 2020
Publication

Our work on Imbalanced Data Classification (joint with Peyman Adibi and Hessein Karshenas) is available as a preprint.

October 8th, 2019
New Position

I started a new position as a visiting scholar in GIPSA-Lab with Grenoble Institute of Technology, Grenoble, France.

July 29th, 2019
scholarship

I have been awarded a scholarship by the Ministry of Science, Research and Technology (MSRT) of Iran to carry out part of my ongoing PhD. research study as a visiting scholar. This scholarship is awarded to a limited number of students.

April 10th, 2019
Research Opportunity

I was invited by Prof. Jocelyn Chanussot to join the OSUG group in GIPSA-Lab with Grenoble Institute of Technology, Grenoble, France.

March 14th, 2019
Talk

I gave an oral presentation at 24th National CSI Computer Conference, CSICC-2019, Sharif University of Technology, Tehran.

January 14th, 2019
Conference

Our conference paper, Geometric Learning of Multimodal Data for Semisupervised Domain Adaptation with Simultaneous Diagonalization of Laplacianes (joint with Peyman Adibi) has been accepted for oral presentation at 24th National CSI Computer Conference, CSICC-2019.

December 18th, 2018
Workshop

Holding a workshop on artificial intelligence: Geometric Learning: Multimodal, Multi Kernel, and Deep Perspective (joint with Peyman Adibi and Zahra Hanifelou).

November 29th, 2018
defense

I pass my thesis proposal defense on Using Geometric Structure of Data for Multimodal Manifold Learning.

June 25th, 2018
comprehensive Ph.D. exam

I successfully passed comprehensive Ph.D. exam with rank 1st among all Artificial Intelligence PhD. students (2016) .

August 25th, 2017
PhD-courses

During two semesters, I successfully passed 9 PhD-courses including, Advanced in Pattern Recognition, Advanced in Data Mining, Advanced in Image processing, Advanced in Machine Learning, Advanced in Neural Networks, and Advanced in Machine Vision.

September 22th, 2016
Ph.D. program

I started my Ph.D. program in Computer Engineering (Artificial Intelligence) at University of Isfahan (UI), one of the most prestigious and beautiful universities in Iran.

Publication

-Maysam Behmanesh, Maximilian Krahn, and Maks Ovsjanikov, "TIDE: Time Derivative Diffusion for Deep Learning on Graphs ," in ICML 2023, PDF, Code


-Maysam Behmanesh, Peyman Adibi, Mohammad Saeed Ehsani, and Jocelyn Chanussot, "Geometric Multimodal Deep Learning With Multiscaled Graph Wavelet Convolutional Network," in IEEE Transactions on Neural Networks and Learning Systems, 2022, doi: 10.1109/TNNLS.2022.3213589, PDF , Code


-Maysam Behmanesh, Peyman Adibi, Jocelyn Chanussot and Sayyed Mohammad Saeed Ehsani, "Cross-Modal and Multimodal Data Analysis Based on Functional Mapping of Spectral Descriptors and Manifold Regularization," CoRR, 2021, arXiv PDF


-Maysam Behmanesh, Peyman Adibi, Jocelyn Chanussot, Christian Jutten, and Sayyed Mohammad Saeed Ehsani, "Geometric multimodal learning based on local signal expansion for joint diagonalization," IEEE Transactions on Signal Processing, vol. 69, 2021, pp. 1271-1286 PDF, Code


-Maysam Behmanesh, Peyman Adibi, and Hossein Karshenas, "Weighted Least Squares Twin Support Vector Machine with Fuzzy Rough Set Theory for Imbalanced Data Classification," CoRR, 2021, arXiv PDF, Code


-Maysam Behmanesh and Peyman Adibi, "Geometric Learning of Multimodal Data for Semisupervised Domain Adaptation with Simultaneous Diagonalization of Laplacians," in Proceedings of 24th National CSI Computer Conference, CSICC-2019, Sharif University of Technology, Tehran, Iran, February 2019


-Maysam Behmanesh and Majid Mohammadi, "Adaptive Neuro-Fuzzy Inference System with Self-Feedback and Imperialist Competitive Learning Algorithm for Chaotic Time Series Prediction," Computational Intelligence in Electrical Engineering, vol. 7(4), 2017, pp. 13-30 PDF (in Persian)


-Maysam Behmanesh, Majid Mohammadi, and Vahid Sattari, "Chaotic Time Series Prediction using Improved ANFIS with Imperialist Competitive Learning Algorithm," International Journal of Soft Computing and Engineering (IJSCE), vol. 4(4), 2014, pp. 25-33 PDF


Maysam Behmanesh and Majid Mohammadi, "Improved Adaptive Neuro-Fuzzy Inference System with Imperialist Competitive Learning Algorithm (ICA-ANFIS)," 7th Iranian Conference on Electrical and Electronics Engineering (ICEEE 2015), Gonabad, Iran, 2015


-Maysam Behmanesh and Majid Mohammadi, "Air Temperature Prediction with Wavelet Transform and Improved Adaptive Neuro-Fuzzy Inference System," 14th Iranian Conference on Fuzzy Systems (ICFUZZYS14), Tabriz, Iran, 2014


Maysam Behmanesh and Majid Mohammadi, "Adaptive Neuro-Fuzzy Inference System Trained with Imperialist Competitive Learning Algorithm for Chaotic Time Series Prediction," 14th Iranian Conference on Fuzzy Systems (ICFUZZYS14), Tabriz, Iran, 2014


-Maysam Behmanesh and Mehdi Eftekhari, "Combining Improved Wang Mendel's Method and Memetic Algorithm for Prediction," 12th Iranian Conference on Intelligent Systems (ICS12), Bam, Iran, 2013

Experience

Research Experience

Visiting Scholar in GIPSA-Lab with Grenoble Institute of Technology, Grenoble, France. Superviser: Prof. Jocelyn Chanussot.

Research Assistant in Machine Learning and Pattern Recognition and Computational Intelligence Group (MAPCO). Supervisor: Dr. Peyman Adibi.

Member of Artificial Intelligence Lab. at SBUK. Supervisor: Dr. Majid Mohammadi.

Journals’ Peer-Reviewer

IEEE Transactions on Geoscience and Remote Sensing

Pattern Recognition

Information Science

International Journal of Fuzzy Systems (IJFS)

Researchs

Coding Skills

90 %

Python

TensorFlow
Pytorch
Keras

90 %

MATLAB

Neuro-Fuzzy
Neural Net.
Signal Proc.

90 %

Programming

C++
C#
ASP.NET

85 %

Database Manag.

SQL Server
Oracle
MySQL

85 %

Data Mining

Clementine
RapidMiner
Weka

90 %

Other

Windoes Server
Linux
LaTex

CONTACT Me

Please feel free to contact me.

Address

1 Rue Honoré d'Estienne d'Orves
Alan Turing Building, Office 2028
École Polytechnique
91120 Palaiseau Cedex, France