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- Applied Scientist, Amazon, Pittsburgh, PA (Summer 2023)
- Designed structured prompts to contextualize ASR models using LLMs
- Used Icefall package for ASR model, used GPT-2 and LLaMa for LLM prompting
- Applied Scientist, Amazon, Seattle, WA (Summer 2021)
- Worked with time series data for demand forecasting and developed model interpretation tools
- Used Shapley Values, Influential Instances, Partial Dependence Plots to develop a python code base that could be used across ML models
- Deep Learning Scientist, SimBioSys, Urbana-Champaign, IL (Summer 2020)
- Developed a new semantic segmentation algorithm based on deep learning for detecting breast cancer in 3D MRI
- Prepared a semantic segmentation data-set for lung cancer
- Research Intern, Max Planck Institute at Stuttgart (Summer 2017)
- Worked on multi-disciplinary team in designing a localization method for the endoscopic capsule robot by using deep learning algorithms
- Gathered real-world sensor data and prepared a data-set to be used in deep learning training
- Research Intern, ASELSAN Advanced Sensing Research Program Department – Ankara, Turkey (Summer 2017)
- Performed time and frequency domain passive acoustic mapping, sparsity-based microbubble detection using constrained optimization methods for ultrasound imaging
- Undergraduate Research Intern, METU, Ankara (Summer 2016)
- Applied classical image processing techniques in agricultural context
- Detected chemically-degraded sugar beet piles by building&using a low-cost thermal imager