Shammur Chowdhury
Scientist at Qatar Computing Research Institute
Doha, Qatar
Summary
👤
Senior🎓
Top SchoolShammur Chowdhury is a scientist and applied researcher with eight years of experience in speech processing, conversational AI, and representation learning, currently based at the Qatar Computing Research Institute. He brings a strong academic foundation—a PhD in ICT from the University of Trento—and a track record of postdoctoral and research roles that bridge R&D and applied projects in industry and academia. His research focuses on the micro-dynamics of turn-taking, overlaps and silences in spontaneous, in-vivo conversations, aiming to quantify how turn-switching and conversational silence shape interaction success. As a consultant and collaborator, he blends signal processing expertise with modern machine learning techniques to build conversational systems and speech representations. Beyond publications, he has hands-on experience creating speech technologies (including Bangla TTS work) and mentoring students, reflecting both technical depth and teaching experience. He is driven by understanding conversational competitiveness and subtle social signals—insights that often emerge from nuanced silence as much as from speech.
8 years of coding experience
7 years of employment as a software developer
Bachelor of Science (B.S.), Computer Science, Electronics and Communication Engineering, Bachelor of Science (B.S.), Computer Science, Electronics and Communication Engineering at BRAC UniversityDoctor of Philosophy - PhD, Information and Communication Technology, Doctor of Philosophy - PhD, Information and Communication Technology at Università degli Studi di TrentoA'Level, Science, A'Level, Science at MasterMind
English, Bangla
Github Skills (33)
multilingual7
benchmarking7
arabic6
corpus6
broadcast5
speech5
benchmark5
large-language-models4
clustering3
alt3
llm3
lda3
mlp3
machine-learning2
recorderjs2
Programming languages (3)
Github contributions (5)
qcri/Arabic_speech_code_switching
Aug 2020 - Apr 2022
The first Dialectal Arabic Code Switching - DACS corpus from broadcast speech. Annotated at the token-level, considering both the linguistic and the acoustic cues. This dataset is a potential benchmark for DCS in spontaneous speech.
Contributions:7 commits, 2 PRs, 9 pushes in 1 year 8 months
code-switchingcorpusdatasetlinguistictoken
shammur/alt_public
Oct 2020 - Nov 2024
ALT research group publications
Contributions:1 PR, 5 pushes, 1 branch in 4 years 1 month
deep-learningaltmachine-learningpublicationsresearch-group
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