Download Curriculum Vitae - Laboratoire d`Informatique de Grenoble

Hesam Amoualian
Data Scientist
8 Place Louis Jouvet
Grenoble, France 38100
H (+33)7 535 87788
B [email protected]
Education
2014 – 2017 Ph.D. - Computer Science, Machine Learning, Université Grenoble Alpes, Grenoble, France.
Scaling Latent Topic/Class Models to Big Data Collections and Streams
2010 – 2013 Master - Digital Electronics, Speech Processing &Recognition, Amirkabir University, Tehran, Iran.
Robustness of Speech Processing in Noisy Environment by Spectral Processing
2006 – 2010 Bachelor - Electrical Engineering, Telecommunication, Amirkabir University, Tehran, Iran.
Designing the Controller of Rotor of S-Band Antenna
2006 – 2010 Bachelor - Electrical Engineering, Electronics, Amirkabir University, Tehran, Iran.
Remote Control Infrared 12 Channels for Commanding the Rescue Robot
Professional Experience
2014 – 2017 Doctoral Researcher, Laboratoire d’Informatique de Grenoble, UGA, France.
Machine learning - Deep Learning - Text Mining - Natural Language Processing
2016 – 2016 Research Intern, Laboratory of statNLP, SUTD, Singapore.
NLP - Deep Learning, Semantic Processing, Question Answering
2011 – 2013 Research Engineer, Laboratory of Speech, Amirkabir University, Tehran, Iran.
Speech Processing - Automatic Speech Recognition - Voice Compressing - Microprocessor Programming
2010 – 2011 Research Engineer, Iran Telecommunication Research Center, Tehran, Iran.
New Generation Network - - Wireless Communication - FPGA Programming (part-time)
2009 – 2010 Research Engineer, Microwave Laboratory, Amirkabir University, Tehran, Iran.
Circuit Design - Digital Signal Processing - Control Design (part-time)
Teaching Experience
Fall – 2013 Teacher Assistant, Circuits with Pulse Techniques.
Spring – 2012 Teaching, Probability and Statistics.
Spring – 2011 Instructor, Electronic Circuits Lab, 2 Sections.
Research Interests
NLP Topic Modelling, Semantic and Syntactic Processing, Language Modelling
Machine Deep Learning and Neural Networks, Bayesian Statistical Theory and Inferences, Probabilistic
Learning Numerical Methods, Clustering and Classification, Distributed Optimization
Signal Digital Signal Processing, Speech Processing, Pattern Recognition, Information Theory
Technical Skills
Computer
ML
OS
Other
Python, Java, C, Perl, Matlab, R
Hadoop, Torch, Probabilistic Programming (Clojure & Anglican)
Windows, Linux(Ubuntu), Macintosh
SQLserver, Fpga Coding, Tex (Latex, Bibtex), Microsoft Office
Languages
Persian(Native), English(Fluent),French(Intermediate), Spanish(Intermediate)
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Thesis
PhD’s thesis:, Scaling Latent Topic/Class Models to Big Data Collections and Streams.
Abstract: Searching, filtering and organizing social media, as well as being able to rapidly identify important
new events, are major challenges faced by researchers. Several approaches like Latent Dirichlet Allocation and
their hierarchical extensions are particularly interesting as they yield state-of-the-art results and allow one to
categorize/annotate documents with existing taxonomies and to detect outliers and new events (event detection).
These models are mainly static and do not take into account the dynamics of the data, and the inference and
learning mechanisms usually rely on Markov Chain Monte-Carlo (MCMC) methods. The goal of this project was
precisely to address these two problems, by constructing new latent topic models able to handle dynamic data,
and by designing new learning and inference methods able to provide good estimates of the parameters of the
new models under real-time and one-pass constraints. The models and methods developed and implemented
during the PhD tested on real data collections and streams.
Master’s thesis:, Robustness of Speech Processing in Noisy Environment by Spectral Processing.
Abstract: In this project, the environmental impact of the noise on Speech Recognition system has been
investigated and different ways are presented to robust the system against these different effects. The issue of
robustness was raised with recognition at same time and scheme of the noise estimation and spectral subtraction
ares used for enhancing the results in speech robustness. In this scheme, enhancement project is divided into two
phases, the first is related to the noise estimation that new method (MSCPE) has been applied for it and the
second is relied on the estimation of the clean signal that leverages modified spectral subtraction.
Publication
2017 Streaming Parametric and Non-parametric Topic Models Leveraging Copulas.
H. Amoualian, M. Clausel, E. Gaussier, M.R. Amini, Submitted in journal of Machine Learning (JMLR)
2017 Topical Coherence in LDA-based Models through Induced Segmentation.
H. Amoualian, L. Wei, E. Gaussier, M.R. Amini, G. Balikas, M. Clausel, in Proceeding of the 55th annual
meeting of the Association for Computational Linguistics (ACL 2017)
2016 Streaming-LDA: a Copula-based Approach to Modeling Topic Dependencies in Document
Streams.
H. Amoualian, M. Clausel, E. Gaussier, M.R. Amini, in Proceeding of the 22nd Conference on Knowledge
Discovery and Data Mining (KDD 2016)
2016 Modelling topic dependencies in semantically coherent text spans with copulas.
G. Balikas, H. Amoualian, E. Gaussier, M. Clausel, M.R. Amini, in Proceeding of the 26th International
Conference on Computational Linguistics (COLING 2016)
2016 On-line LDA (doc-level) with Topical Correlation over Time.
H. Amoualian, E. Gaussier, M. Clausel, M.R. Amini, Presented in ATLAS 2016: an Interdisciplinary Workshop
on Mathematical and Algorithmimcal Approaches
2014 Robustness of Speech Processing with both of MSPCE Algorithm and Spectral Subtraction.
H. Amoualian, S.M. Ahadi, Master Thesis
2011 Basic of Mathematics and Physics Elementary.
Co-author in write, Parse Publication, 2009, ISBN: 177-2-654-23429-1
Conferences & Seminars
2016
2016
2015
2015
2014
2013
2011
SIGKDD, Conference on Knowledge Discovery and Data Mining, San Francisco, United States.
COLING, Conference on Computational Linguistics, Osaka, Japan.
DSAA, IEEE Conference on Data Science and Advanced Analytics, Paris, France.
MLSS, Machine Learning Summer School, Tubingen, Germany.
Spring School, Informatics Mathematics and Application, Grenoble, France.
SLAM used Unknown Association Data, 13th Iran Electrical Engineering Conference, Zanjan, Iran.
Protection of Information in Wireless Sensors Network, Electrical Engineering Week, Tehran, Iran.
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Honors & Awards
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Accepted for 4 months Internship funded by SUTD university/MIT branch in Singapore - 2016
Accepted by Machine Learning Summer School in Tubingen(MLSS) with Scholar - 2015
Scholarship Awarded Candidate by CNRS
Full Fund PhD by Ministry of Science of France
Exceptional Talent Award in Electrical Engineering (MSc)
Exceptional Talent Award in Electronics Engineering (BSc)
Exceptional Talent Award in Telecommunication Engineering (BSc)
Ranked 3th among all students of Electrical Engineering (Electronics)
Ranked 5th among all students of Electrical Engineering (Telecommunication)
Finalist of Electrical Engineering Olympiads in Electrical Department of Amirkabir University
Ranked 217th among more than 400000 participants in Iranian Nation-Wide University Entrance Exam
Semi-finalist of National Mathematics and Information Olympiads in Iran
Student of National Organization for Development of Exceptional Talents
Professional Certifications
Arm, Microsoft SQL, Microprocessor Programming(Fpga-Dsp), Embedded System
Programming(Android)
Interests
Sports (Tennis, Chess), Gadget Play (Drones), Photography (Portrait)
References
Eric Gaussier, Professor, Laboratoire d’Informatique de Grenoble (LIG), UGA.
(+33)04-57421500
[email protected]
Massih-Reza Amini, Professor, Laboratoire d’Informatique de Grenoble (LIG), UGA.
(+33)04-57421445
[email protected]
Marianne Clausel, Associate Professor, Laboratoire Jean Kuntzmann (LJK), UGA.
(+33)04-76635693
[email protected]
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