Metehan Cekic, PhD
Applied Scientist, Amazon
metehancekic [at] gmail [dot] com
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Hi!
I am currently working as an Applied Scientist at Ring AI at Amazon, where I focus on Acoustic Event Detection (AED). Previously, I worked on the development of conversational AI and Automatic Speech Recognition (ASR) models at AWS AI.
Before joining AWS, I completed my Ph.D. in the Electrical and Computer Engineering department at UC Santa Barbara, where I had the privilege of being advised by Prof. Upamanyu Madhow. My research experience has given me a profound interest in Deep Learning and its applications, which I continue to pursue in my current role.
I completed my undergraduate studies with dual B.S. degrees in electrical & electronics engineering and physics from Bogazici University, Istanbul, Turkey, in 2017. I am also passionate about sharing my knowledge and regularly publish blog posts on various topics related to my field. If you are interested, you can find a list of my publications and code on my website.
Recent News
[Jul 2024] I’m happy to share that I’ve joined Ring AI at Amazon as an Applied Scientist.
[Jun 2024] Our paper titled "PEAVS: Perceptual Evaluation of Audio-Visual Synchrony Grounded in Viewers' Opinion Scores" is accepted to the The 18th European Conference on Computer Vision ECCV 2024.
[Feb 2024] I wanted to share a personal update with you all. Recently, I underwent knee surgery. The procedure was a success, and I'm now in the recovery phase.
[May 2023] Thrilled to announce a joyous personal update: I have recently embraced the delightful fatherhood journey. I am full of gratitude for the outpouring of well-wishes and support from our dear ones.
[Oct 2022] We've presented our paper titled "Neuro-Inspired Deep Neural Networks with Sparse, Strong Activations" at the IEEE International Conference in Image Processing (ICIP), 2022, Bordeaux. We are thankful to the community for their valuable comments and suggestions.
[Sep 2022] I’m happy to share that I’m starting a new position as Applied Scientist at Amazon Web Services (AWS)
[Aug 2022] I successfully defended my Ph.D! [Presentation]
[Jun 2022] Our paper titled "Towards robust, interpretable neural networks via Hebbian/anti-Hebbian learning: A software framework for training with feature-based costs" is accepted to the Elsevier Software Impacts.
[Jun 2022] Our paper titled "Neuro-Inspired Deep Neural Networks with Sparse, Strong Activations" is accepted to the IEEE International Conference in Image Processing (ICIP).
[Jun 2022] Our paper titled "Early Layers Are More Important For Adversarial Robustness" is accepted as a workshop paper for the Thirty-ninth International Conference on Machine Learning (ICML), New Frontiers in Adversarial Machine Learning.
[Jun 2022] Our paper titled "Layerwise Hebbian/anti-Hebbian (HaH) Learning In Deep Networks: A Neuro-inspired Approach To Robustness" is accepted as a workshop paper for the Thirty-ninth International Conference on Machine Learning (ICML), New Frontiers in Adversarial Machine Learning.
[Jan 2022] Our paper titled "Self-supervised Speaker Recognition Training Using Human-Machine Dialogues" is accepted to the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP).
[Nov 2021] We've presented our paper titled "Wireless Fingerprinting via Deep Learning: The Impact of Confounding Factors" at the 55th Asilomar Conference on Signals, Systems, and Computers, 2021, Asilomar. We are thankful to the community for their valuable comments and suggestions.
[May 2021] I am excited to announce that I will be joining the Alexa speech team at Amazon as an Applied Scientist Intern over Summer 2021.
[Dec 2020] I've recently talked to a Turkish Podcast about machine learning and artificial intelligence.
How do machines learn? What does the human brain have to do with artificial intelligence? If you are curious about these questions and more information, this episode is for you!
[Oct 2020] Successfully passed my PhD candidacy exam! [Presentation]
[Dec 2019] We've presented our paper titled "Robust Wireless Fingerprinting via Complex-Valued Neural Networks" at Globecom, 2019, Hawaii. We are thankful to the community for their valuable comments and suggestions.
[May 2018] I've been awarded the Outstanding Electrical and Computer Engineering Teaching Assistant (TA) award. I feel very fortunate to be a TA of smart and talented UCSB students.
Gallery
In my leisure time, I enjoy walking and exploring the surrounding areas. I find great pleasure in experiencing new environments and am always eager to expand my horizons. Additionally, I value social interaction and enjoy engaging with diverse groups of people. I find that interacting with new individuals provides me with invaluable insights and perspectives that I can apply to both my personal and professional life.
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