Profile note
My name is Mohammad KHalooei ('محمد خالوئی' in Persian). I am an artificial intelligence researcher and also fascinated by doing scientific research in Deep learning & Big data fields of academia. And being an enthusiastic entrepreneur at the same time is interestingly intriguing.
By now, I'm a Ph.D. candidate of Amirkabir University of Technology (Tehran Polytechnic) under supervision of Prof. Mohammad Mehdi Homayounpour and Dr. Maryam Amirmazlaghani. My research field of academia is Adversarial Machine learning and Robustness of Deep Neural Networks.
International Publications
In this paper, we propose a novel self-supervised representation learning by taking advantage of a neighborhood-relational encoding (NRE) among the training data. Conventional unsupervised learning methods only focused on training deep networks to understand the primitive characteristics of the visual data, mainly to be able to reconstruct the data from a latent space. Different from the previous work, NRE aims at preserving the local neighborhood structure on the data manifold. Therefore, it is less sensitive to outliers.
( arxiv)
- ( theCVF)
This research inspired by the success of generative adversarial networks for training deep models in unsupervised and semi-supervised settings, we (4 colleague) propose an end-to-end architecture for one-class classification. Our architecture is composed of two deep networks, each of which trained by competing with each other while collaborating to understand the underlying concept in the target class, and then classify the testing samples. One network works as the novelty detector, while the other supports it by enhancing the inlier samples and distorting the outliers. The intuition is that the separability of the enhanced inliers and distorted outliers is much better than deciding on the original samples. The proposed framework applies to different related applications of anomaly and outlier detection in images and videos.
( arxiv)
- ( theCVF)
- ( IEEE)
- ( GitHub)
Experiences
AAIC is stands for Amirkabir Artificial Intelligence Competitions which was held in Tehran, IRAN. This is the forth experience which was held in Tehran and organized with one of the most technology based university of IRAN - Amirkabir University of Technology (Tehran Polytechnic). The fourth mission of AAIC competition had four leagues such as : Face recognition, Object recognition from few training examples, Stock market prediction, Persian named entity recognition and Voice command recognition field. The CEO of the fifth mission of AAIC was Prof. Safabakhsh and Dr. Nickabadi.
Speech processing is the study of speech signals and the processing methods of signals. The signals are usually processed in a digital representation, so speech processing can be regarded as a special case of digital signal processing, applied to speech signals. In this course, we also mention deep learning approaches in speech processing and speech related applications. This course was taught by Prof. Homayounpour.
Statistical Machine Learning (SML in a brief) is a second graduate level course in advanced machine learning, assuming students have taken Machine Learning and Intermediate Statistics. In this course, we cover the Wasserman Statistical Machine Learning book. This course was taught by Dr. Nickabadi.
Optimization is the selection of a best element (with regard to some criterion) from some set of available alternatives. Convex optimization is a subfield of mathematical optimization that studies the problem of minimizing convex functions over convex sets. Machine learning algorithms use optimization all the time. We minimize loss, or error, or maximize some kind of score functions. Gradient descent is the "hello world" optimization algorithm covered on probably any machine learning course. This course was taught by Dr. Amirmazlaghani.
AAIC is stands for Amirkabir Artificial Intelligence Competitions which was held in Tehran, IRAN. This is the forth experience which was held in Tehran and organized with one of the most technology based university of IRAN - Amirkabir University of Technology (Tehran Polytechnic). The fourth mission of AAIC competition had four leagues such as : Face recognition, Object recognition from few training examples, Stock market prediction, Persian named entity recognition and Voice command recognition field. The CEO of the forth mission of AAIC was Prof. Safabakhsh and Dr. Nickabadi.
Pattern Recognition Letters is a peer-reviewed scientific journal that is published by North Holland, an imprint of Elsevier, on behalf of the International Association for Pattern Recognition. The journal produces 16 issues per year covering research on pattern recognition. A certificate of outstanding contribution reviewer in November 2018 was awarded to me.
Statistical Machine Learning (SML in a brief) is a second graduate level course in advanced machine learning, assuming students have taken Machine Learning and Intermediate Statistics. This course was taught by Dr. Nickabadi.
Most parts of my researches is devoted to the newest Deep learning topics, and multimedia user behavior analysis.
Core ML is the machine learning framework used across Apple products, including Siri, Camera, and QuickType. CoreML is integrated machine learning models into your app. Core ML is the foundation for domain-specific frameworks and functionality. Core ML supports Vision for image analysis, Natural Language for natural language processing, and GameplayKit for evaluating learned decision trees. Core ML itself builds on top of low-level primitives like Accelerate and BNNS, as well as Metal Performance Shaders. The machine learning stack Core ML is optimized for on-device performance, which minimizes memory footprint and power consumption. Running strictly on the device ensures the privacy of user data and guarantees that your app remains functional and responsive when a network connection is unavailable.
Machine and Vision Intelligence was part of the IAPR programs and it was organized by “Computer Vision, Pattern recognition and machine Learning Italian Association” (CVPL), affiliated to International Association for Pattern Recognition (IAPR) with support of Technical Committees TC-03 (Neural Networks and Computational Intelligence) and TC-12 (Multimedia and Visual Information Systems). VSIMAC was organized by Prof. Alfredo Petrosino, Prof. Francesco Camastra and Dr. Fabio Narducci.
Most of projects have some analysis part in different data type (i.e. location, sensor, numerical, image, video and sound).
Most parts of my research focus is on Deep learning online courses (MOOCs) . Also, we provide the first deep learning lectures in IRAN and most of our focusable notes are from online and hot topic resources.
Most part of my research focus is on Big data online courses (MOOCs) .
Sentiment analysing of WWW social commenting infrastructure.
- - Qualified for participating RoboCup2017 competition at Nagoya, japan
- - Participating in IRAN OPEN 2017 at Tehran and won 5'th prize
- - Qualified for participating in RoboCup2016 competition at Leipzig, German
- - Participating in IRAN OPEN 2016 at Tehran and won third prize
- - Participating in IRAN OPEN 2015 at Tehran
- - Participating in AUT Cup 2015 at Amirkabir university
Presentations
Machine/Deep learning
Some of my public presentation files: [I try to gather all presentation files and placed them here! (in near future :))]
| Date | Title, location & slides | |
|---|---|---|
|
2019 Dec 31 |
Robustness of Deep Neural Networks English slides
Sharif University of Technology Audiences : Bachelor, Master and PhD students, influencer, industery internship section Winter Seminar Series (WSS) :: https://wss.ce.sharif.edu/2019/workshop/194/ |
|
2019 Dec 5 |
Adversarial Machine learning English slides
Amirkabir University of Technology (Tehran Polytechnic) Audiences : Bachelor, Master and PhD students, influencer, industery internship section Amirkabir Artificial Intelligence Fall Summit 2019 :: http://aaic.aut.ac.ir/events/fall2019 |
|
2019 July 23 |
Robustness of Deep Neural Networks (Adversarial Attacks & Defenses) English slides
Amirkabir University of Technology (Tehran Polytechnic) Audiences : Bachelor, Master and PhD students, influencer, industery internship section Amirkabir Artificial Intelligence Summer Summit (AAIS) of SSC :: http://aaiss.ceit.aut.ac.ir |
|
2018 Dec 6 |
Life of the points ('زندگی نقطه ها') Persian slides
Sharif University of Technology Amirkabir University of Technology (Tehran Polytechnic) Audiences : Bachelor and Master students, influencer, industery internship section Life Of The Point Presentation
This presentation was held at Sharif University of Technology on December 6th, 2018. Also, similar event was held at Amirkabir University of Technology (Tehran Polytechnic).
|
 |
2018 Dec 23 |
Generative Adversarial Networks English slides
Sharif University of Technology Audiences : Bachelor, Master and PhD students, R&D researcher of industries |
 |
2018 Aug |
Dense Human Pose Estimation In The Wild (DensePose) English slides
Italy, IAPR School on Machine and Vision Intelligence Audiences : Master and PhD students, R&D researcher of industries of Italy |
 |
2018 Aug |
Adversarially Learned One-Class Classifier for Novelty Detection English slides
Italy, IAPR School on Machine and Vision Intelligence Audiences : Bachelor, Master and PhD students, R&D researcher of industries |
|
2018 |
Generative Adversarial Networks (application) Persian & English slides
Part Financial Information Processing Company Audiences : Public (+ submission) |
|
2018 |
Generative Adversarial Networks (definition) Persian & English slides
Part Financial Information Processing Company Audiences : Public (+ submission) |
|
2017 Dec |
Neural network visualizations Persian slides
Sharif University of Technology Audiences : Bachelor, Master and PhD students, R&D researcher of industries, IT mans |
|
2016 |
Data Analyzing with deep learning approach in bigdata stack (Deep Neural Network) Persian slides
Sharif University of Technology Audiences : Graduated and Under-graduated student, It mans |
|
2016 |
Data Analyzing with deep learning approach in bigdata stack (introduction) Persian slides
Sharif University of Technology Audiences : Graduated and Under-graduated student, It mans |
I will update this table in near future ...
Projects
Some research and industrial projects :