I am interested in many fields of AI, especially ones pertaining to language and semantics.
The following is a list of publications and presentations/demos I've done throughout my PhD in these domains of interest.
Name | Ismail Harrando - إسماعيل هرندو | ||||||||
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Nationality | Moroccan | ||||||||
harrando.ismail (at) gmail.com | |||||||||
Links |
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R&D Internship in Computer Vision |
Studying Transfer Learning for Action Recognition |
Atos Bull |
February - September 2018 |
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R&D Internship in Timeseries Prediction and Log Analysis |
Neural Predictive Maintenance for |
Atos Bull |
April - September 2017 |
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Lab Internship |
Arabic Handwriting Recognition |
LabTIC - National School of Applied Science |
December 2016 - January 2017 |
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Comparing numerical methods for Optimization |
July 2015 (1 month) |
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PhD in Artificial Intelligence | |
Combining Semantics and Linguistic Information Extraction for Multimedia Understanding | |
Sorbonne University / EURECOM | |
2018 - Present | |
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Master of Science in Informatics (MoSiG) |
Artificial Intelligence and the Web Specialization |
Grenoble INP Ensimag / UGA IM²AG |
2017-2018 |
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Master of Engineering (Ingénieur d'état) in Computer Science |
Information Systems option |
National School of Applied Science of Tangier |
2012-2017 |
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NLP . CV . DS | PyTorch, HuggingFace, Scikit-learn, TensorFlow, Keras, Numpy, Pandas, NLTK, Matplotlib, OpenCV |
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KG & SW | RDF/OWL, SPARQL, Graph embeddings, PyTorch-Geometric |
Programming | Python, C++, C, Java, C#, Haskell, Prolog, Common Lisp |
Web | HTML5, CSS3, PHP (Laravel), JS (jQuery, Angular), Node.js, Bootstrap, Socket.io |
Database | Oracle (Optimization, Administration, Distribution), MySQL, MongoDB, Neo4j |
Miscellaneous | UML, XML, Git, Linux (Bash), Networking, AWS, Latex |
Languages | English (TOEFL - C2), French (TCF - C2) Arabic (Native), German (elementary) |
I am interested in many fields of AI, especially ones pertaining to language and semantics.
The following is a list of publications and presentations/demos I've done throughout my PhD in these domains of interest.
December 2021, 12th MediaEval Benchmarking Initiative for Multimedia Evaluation Workshop (MediaEval'2021), Online.
To tackle the problem of detecting COVID-19-related conspiracy theories in tweets, we used different approaches such as a combination of TFIDF and machine learning, transformer-based neural networks or Natural Language Inference.
[ code ]
Text Representation Deep Language Models Ensembling Text Classification
September 2021, 3rd Conference on Language, Data and Knowledge (LDK'2021), Zaragoza, Spain.
Wanna build a text classifier without any training data that can also explain its predictions? ZeSTE may be what you're looking for!
Zero-Shot Common Sense ConceptNet Text Classification
June 2021, 2nd International Workshop on Data-driven Personalisation of Television (DataTV @ IMX'2021), Online.
In this work, we present an approach to content segmentation that leverages topical coherence, language modeling and word embeddings to detect change of topics.
[ paper ]
Text Segmentation Topic Modeling Language Modeling Text Representation
June 2021, 18th Extended Semantic Web Conference (ESWC'2021 - Poster Track), Online.
Injecting real-world information (typically contained in Knowledge Graphs) and hand-crafted features into a pipeline for training end-to-end Natural Language Processing models is an open challenge. In this paper, we propose to approach the task of Named Entity Recognition, which is traditionally viewed as a Sequence Tagging problem, as a Graph Classification problem.
Graph Neural Network Knowledge Graph Named Entity Recognition Knowledge Injection
September 2021, 3rd Conference on Language, Data and Knowledge (LDK'2021)
How to make the results of topic modeling algorithms more understandable to humans? Try to add some common sense into the process :)
Topic Modeling Interpretability Human evaluation Common Sense
September 2021, 13th Conference on Recent Advances in NLP (RANLP'2021), Online
Topic Modeling Evaluation is an open problem in the Topic Modeling community. While the reliance on automatic evaluation remains more or less necessary to quickly assess the performance of a given topic model algorithm, there is no study that attempts to evaluate several algorithms in the literature given the same preprocessing, datasets, and metrics. That's what we did!
[ paper ]
NLP Evaluation Topic Modeling Coherence Survey
November 2020, 2nd Workshop for NLP Open Source Software (NLP-OSS @ EMNLP'2020)}, Online.
This API is built to dynamically perform training, inference, and evaluation for different topic modeling techniques. The API grant common interfaces and command for accessing the different models, make easier to compare them.
Open Source Python Library API Topic Modeling Evaluation
December 2021, 12th MediaEval Benchmarking Initiative for Multimedia Evaluation Workshop (MediaEval'2021), Online
Multimodal Deep Learning Convolutional Neural Network Content Representation
December 2021, International Workshop on Video Retrieval Evaluation (TRECVID'2021), Online
[ code ]
Zero-shot Learning Event-based classification Content Summarization
December 2020, 11th MediaEval Benchmarking Initiative for Multimedia Evaluation Workshop (MediaEval'2020), Online
Multimodal Deep LearningVisio-Linguistic Transformer Content Representation
November 2020, the International Workshop on Video Retrieval Evaluation (TRECVID'2020), Online
Text Matching Content Summarization
October 2019, 10th MediaEval Benchmarking Initiative for Multimedia Evaluation Workshop (MediaEval'2019), Sophia Antipolis, France.
Multimodal Deep Learning Convolutional Neural Network Content Representation
June 2019, The EBU Metadata Developer Network Workshop (EBU-MDN), Geneva, Switzerland
In the context of the European research project MeMAD (Methods for Managing Audiovisual Data), we face the challenge of modeling semantically audiovisual legacy metadata and results of automatic analysis from multiple partners and in an interoperable manner. In this talk, we will present an implementation of the EBU-CCDM/EBU Core data model for representing production and broadcasting information of TV and Radio programs provided by two industrial partners covering several channels. The resulting MeMAD knowledge graph provides metadata for more than 60K hours of audiovisual content, spanning multiple channels, audiovisual genres, themes and languages.
Multimedia Semantic Modeling Knowledge Graph Ontology
September 2021, the 3rd Edition of Knowledge-aware and Conversational Recommender Systems (KaRS @ RecSys'2021), Amsterdam, Netherlands
In this work, we study the potential of using off-the-shelf automatic annotation tools from the Information Extraction literature to improve recommendation performance without any extra cost of training, data collection or annotation.
Content-based Recommender Systems Multimedia Semantic Modeling Knowledge Graph Graph Embeddings Information Extraction
I love consuming media, and I love talking about it. I also love making lists. These are a few of my favorite things
The lists here are neither exhaustive (I had to limit my picks for one per artist/franchise) nor representative of the "best" in their respective media. An item in any of these lists reflects either and aesthetic, emotional or conceptual appreciation for the media (and sometimes just good ol' nostalgia). Peruse at your leasure! (and if you have any recommendation based on what you see, pleas let me know :))
This was the hardest list to narrow down, as I watch quite a lot of movies.
I still would like to watch more non-English films.
I used to watch anime and read manga religiously, less so nowaday (it doesn't help that 80% of new productions look and feel the same), but the occasional gems do pop up sometimes, and here's my collection :)
As much as I believe that video games have the potential to be the best entertainment medium, I don't play as much as I used to :/
PS: Half the games here are added for nostalgia value. I don't know if new games are just not as charming as their predecessors, or we just get jaded and dull as we grow older :[
I don't have the attention span to watch a series in general, so I usually stick to short series or the ones that are so good you have to binge them.
"Reading more books" seems to be the only new year resolution that I stick to. Here are a few of the ones I enjoyed in the last few years mostly. If for any reason you'd like to see what I'm reading, add me on Goodreads :)
I listen to music a lot, but I've only started listening to full albums recently, that's why most picks here are from this century :)
I've also limited myself to one album per artist, but I enjoy the discography of every artist included here (and similar artists).
I am also very open to recommendations!