About
How to pronounce my name: (sha-FUCK billie-G) or IPA -> ([ʃɑ.ˈfɑk] [biɭiʤi])
I am an AWS certified Software Engineer with robust experience in large-scale distributed systems, cloud services, search engines, and data science in general. My expertise lies in solving real-world, high-scale problems related to low-latency micro-services, especially information retrieval, personalization, and discovery.
I’m currently working at Insider as a Machine Learning/Software Engineer, where I build and scale a SaaS product search engine. I’ve led, developed, and contributed to key search features including AutoCompletion, Semantic/Hybrid Search, Category Merchandising, as well as countless improvements to their micro-services architecture, infrastructure, and large-scale data processing workflows.
Before joining Insider, I was a Research Engineer at Huawei’s AppGallery Search Team, responsible for retrieval, ranking, and query understanding problems. Some of the search features I’ve led and developed (such as semantic search, spelling correction, etc.) are used by 100s of millions of users with planet-scale low-latency.
I did my BSc @YTU CS. My BSc thesis was on multimodal transformers and natural language grounding, with applications on low-resource cross-modal retrieval, visual question answering, and few-shot image classification.
I like long-distance running, playing piano, and cycling.
Publications and Preprints
- Can Özbey, Talha Çolakoğlu, M. Şafak Bilici, Ekin Can Erkuş, “A Unified Formulation for the Frequency Distribution of Word Frequencies using the Inverse Zipf’s Law”, in Special Interest Group on Information Retrieval (SIGIR), 2023. (paper)
- M. Şafak Bilici, Mehmet Fatih Amasyali, “Transformers as Neural Augmentors: Class Conditional Sentence Generation via Variational Bayes”, arXiv preprint arXiv:2205.09391, 2022. (paper, repository)
- E. Sadi Uysal, M. Şafak Bilici, B. Selin Zaza, M. Yiğit Özgenç, Onur Boyar, “Exploring The Limits Of Data Augmentation For Retinal Vessel Segmentation”, arXiv preprint arXiv:2105.09365, 2021. (paper, repository)
- M. Şafak Bilici, Mehmet Fatih Amasyali, “Variational Sentence Augmentation For Masked Language Modeling”, in Innovations in Intelligent Systems and Applications Conference (ASYU), 2021. (paper, repository)
Software
- bayesmedaug: bayesmedaug optimizes your data augmentation hyperparameters for medical image segmentation tasks by using Bayesian Optimization and Gaussian Process.
- x-tagger: x-tagger is a Natural Language Processing toolkit for sequence labeling in its simplest form.
Contact
- m.safak.bilici@gmail.com
TL;DR
I may be slow to respond