Experience

Columbia University Graduate School of Arts and Sciences

• United States
• Higher Education
• 1 - 100 Employee

• Postdoctoral Research Scientist

  • Sep 2022 - Present

• Graduate Research And Teaching Assistant

  • Jan 2017 - Sep 2022

  • PhD student at the Bionet lab, building computational tools and workflows to build realistic models from modern computational neuroscience datasets.• Worked on GPU-accelerated modeling and optimization of biologically accurate neural circuits.• Built machine learning libraries for revealing the structure of connectomics datasets through node embeddings and clustering.• Helped design course material and assignments for multiple graduate-level courses at the intersection of electrical engineering and neuroscience. Show less



Columbia University

• United States
• Higher Education
• 700 & Above Employee

• PHD Candidate

  • May 2020 - Sep 2022

  • Post-thesis proposal PhD student focusing on using machine learning algorithms and GPU-accelerated simulations to explore the function of detailed biological spiking neural networks constructed from cutting-edge electron microscopy data. • Post-thesis proposal PhD student focusing on using machine learning algorithms and GPU-accelerated simulations to explore the function of detailed biological spiking neural networks constructed from cutting-edge electron microscopy data.



Columbia University

• United States
• Higher Education
• 700 & Above Employee

• Graduate Research Assistant at Center for Computational Learning Systems

  • Sep 2016 - Dec 2016

  • Fully funded final semester of the MSc through a deep learning project with Con Edison. • Research project to apply cutting edge deep learning algorithms for object detection in thermal camera images to find manholes at risk. • Developed the front-end and the back-end convolutional neural network architecture for object detection by curating and labeling a dataset by hand and using transfer learning to achieve a high testing set performance. • Fully funded final semester of the MSc through a deep learning project with Con Edison. • Research project to apply cutting edge deep learning algorithms for object detection in thermal camera images to find manholes at risk. • Developed the front-end and the back-end convolutional neural network architecture for object detection by curating and labeling a dataset by hand and using transfer learning to achieve a high testing set performance.



The Earth Institute, Columbia University

• United States
• Research Services
• 1 - 100 Employee

• Graduate Researcher

  • May 2016 - Sep 2016

  • Developed high-performing deep learning models to control solar-powered microgrids in Africa by generating power limit schedules for the customers in the microgrid under varying conditions. • Developed high-performing deep learning models to control solar-powered microgrids in Africa by generating power limit schedules for the customers in the microgrid under varying conditions.



Center for Computational Learning Systems at Columbia University

• Graduate Researcher

  • Jan 2016 - May 2016

  • Designed and implemented machine learning algorithms to target structures requiring repairs in Con Edison infrastructure using features extracted from thermal images. • Designed and implemented machine learning algorithms to target structures requiring repairs in Con Edison infrastructure using features extracted from thermal images.



Istanbul Technical University

• Türkiye
• Higher Education
• 700 & Above Employee

• Undergraduate Scholar

  • Mar 2014 - Dec 2014

  Worked on the implementation of novel cross-modal metric learning methods for a TUBITAK (The Scientific and Technological Research Council of Turkey) research project. Worked on the implementation of novel cross-modal metric learning methods for a TUBITAK (The Scientific and Technological Research Council of Turkey) research project.



ArtGe Technologies

• Türkiye
• IT Services and IT Consulting

• Student Intern

  • Aug 2014 - Sep 2014

  • Investigated the potential of various supervised learning methods like convolutional neural networks for the automatic extraction of crop statistics from agricultural image datasets. • Built a convolutional network for regression with hinge loss operating on high resolution images of farmland and trained it on hand-annotated datasets to create an initial prototype. • Investigated the potential of various supervised learning methods like convolutional neural networks for the automatic extraction of crop statistics from agricultural image datasets. • Built a convolutional network for regression with hinge loss operating on high resolution images of farmland and trained it on hand-annotated datasets to create an initial prototype.



Istanbul Technical University Signal Processing Laboratory

• Istanbul, Turkey

• Student Intern

  • Jul 2013 - Aug 2013

  Implemented various state-of-the-art face detection and recognition algorithms. Considered the use of some unconventional integral transforms for feature extraction. Investigated the use of such feature extraction methods for the analysis of sequential time series data. Implemented various state-of-the-art face detection and recognition algorithms. Considered the use of some unconventional integral transforms for feature extraction. Investigated the use of such feature extraction methods for the analysis of sequential time series data.