Hello I'm

Muratcan Cicek

Ph.D. Candidate at UCSC, Google Ph.D. Fellow

About Me

I am Muratcan Cicek, a Ph.D. student in Computer Engineering at UCSC. I am studying Human-Computer Interaction and Computer Vision specifically to deliver Assistive Technologies. On the other hand, I am a person with motor impairments who utilizes Assistive Technologies every day. This fact makes me play both sides, basically, I develop what I use:

  • Phyton
  • Numpy
  • Scikit-learn
  • TensorFlow
  • Flutter
  • Android SDK
  • Firebase
  • SQL
  • Matlab
  • OpenCV
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What I Do

Machine Learning

I am studying Machine Learning since 2015 and have had several full-time experiences dealing with real-life problems.

Human-Computer Interaction

My most recent job experiences focused on HCI Research, and I have two solid publications in this field.

Assistive Technology

I bring my ML and HCI background together to propose Assistive Technology for those in need by combining my technical knowledge my own user experience as a person with motor impairments.

Education

PhD in Computer Engineering University of California
2017-2022

2017-Expected 2022

PhD in Computer Engineering, newly admitted with Chancellor’s Fellowship, Advisor: Roberto Manduchi, Relevant course work: Image Analyzing and Computer Vision, Analysis of Algorithms Teaching Assistantship on Fall 2018 for the Universal Access course Individual

Study 1: Gaze-Contingent Screen Magnification on Mobile Devices by using LSTM on TensorFlow Individual
Study 2: Fitts’ Law Evaluation of a robust head-based pointing that employs 3D Head-Tracking algorithms

B.S. in Computer Science Ozyegin University
2013-2017

2013-2017

B.S. in Computer Science, GPA: 3.68, High Honor Student 2013-2017
Relevant course work: Computer Vision, Automata Theory & Formal Languages, Advanced Object-Oriented Programming, iOS Application Development, Game Design and Development, Database Management Systems
Senior Project: Improving the product search algorithm of GittiGidiyor (eBay) by using machine learning

Work Experience

Research Intern Google, Mountain View – California
2020

June 2020 - October 2020
In the Euphonia Team by Google AI to further study Automatic Speech Recognition for people with dysarthria
  • The team proposes and develops personalized and generalized ASR models for dysarthric speech
  • Euphonia was the very first proof of concept application that accomplished true success and eventually launched to help more than 600 people with dysarthria.
  • My project mainly focused data selection strategies to improve ASR performance of personalized models
  • We evaluated entropy-based selection methods to reduce the necessary recording by the speaker
  • For the project, I utilized and get experienced with many of Google’s internal development tools.

Software Engineering Intern Google, Mountain View – California
2019

June 2019-September 2019
Summer Intern in Fuchsia UX Team at Google
  • Developed an edge-cutting Head-based Pointing on Flutter for both Android and iOS
  • Flutter allowed us to build a cross-platform App that provides touch-free interaction
  • Applied three different user studies to evaluate the proposed interaction against Fitts’ Law
  • Our research paper has been accepted to ASSETS2020 as “Designing and Evaluating Head-based Pointing on Smartphones for People with Motor Impairments”

Research Intern PhD eBay, San Jose – California
2018

June 2018-September 2018
Summer Intern in Computer Vision Team at eBay
  • Implemented an open-source on Head-based Pointing method for iOS
  • -This revolutionary interaction method does not require any physical touch to navigate Apps
  • -Available on github.com/eBay/HeadGazeLib
  • Research paper completed as “Mobile Head Tracking for eCommerce and Beyond”
  • -Preprint available on https://arxiv.org/abs/1812.07143
  • -Accepted by IS&T International Symposium on Electronic Imaging 2020
  • -The project was selected the top intern project of the year in the company
  • The technology has been recognized as one of Fast Company’s World Changing Ideas for 2019

Researcher Turkcell, Istanbul – Turkey
2016-2017

October 2016-December 2017
  • Worked as a researcher at Turkcell, Turkey’s largest GSM operator, to build a new music recommendation system for Fizy, which is a competitor to Spotify in Turkey
  • Analyzed the fingerprints of the songs from Fizy’s music library in terms of similarity and built the recommendation system based on the fingerprint similarity; used machine learning methods to integrate mood-based and lyrics-based recommendation methods to the recommendation system

Learning Engineer GittiGidiyor (an eBay subsidiary), Istanbul – Turkey
2016-2017

September 2016-September 2017
  • Implemented a parser to analyze massive clickstream data which streamed from Apache Kafka and stored on the Hadoop Distributed File System; used Spark via Python for the advanced analysis on the user behavior
  • Researched on the edge-cutting ranking algorithms; adapted a pair-wise ranking algorithm according to the current architecture; implemented this algorithm, ran offline to measure the outputs; used feature selection techniques to improve the accuracy

Programmer Fiba Holding, Istanbul – Turkey
2014-2017

February 2014- September 2017
  • Developed and maintained the Student Information System of Ozyegin University (sis.ozyegin.edu.tr) as a member of the IT office of Fiba Holding; the Student Information System of Ozyegin University is a web application that provides connection between all stakeholders of the university and is actively in use

Projects

Mobile Head Tracking for eCommerce and Beyond

Shopping is difficult for people with motor impairments. This includes online shopping. Proprietary software can emulate mouse and keyboard via head tracking.

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Project Euphonia’s new step: 1,000 hours of speech recordings

It is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout

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Designing and Evaluating Head-based Pointing on Smartphones

It is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout

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