Experience

• Northeastern University, Boston, MA, USA, 2028 (expected)
  • Research Assistant
    • Research Labs: DNAL, INSI, SPIRAL
    • Developed communication-aware distributed inference, Markovian experimental design, and 5G NR spectrum-sensing frameworks to address the bandwidth, energy, non-stationarity, and interference challenges of machine learning at the network edge, spanning optimization theory through deployment.
• OrthoKinetic Track, Boston, MA, USA, 2026
  • Data Science Intern
    • Developed machine learning pipelines for sEMG-based neuromuscular monitoring to enable objective assessment of performance, injury risk, and recovery across sports, rehabilitation, clinical, and defense applications.
• Neurocess Limited, London, England, 2023
  • Data Science / Machine Learning Engineer (Remote)
    • Built few-shot Siamese CNN–Transformer architectures for multivariate sEMG time-series analysis to solve athlete performance monitoring under limited data, achieving similarity-based classification and anomaly detection across unseen motion patterns in PyTorch and Keras.
• KOCLAB, National Magnetic Resonance Research Center (UMRAM), Ankara, Turkey, 2022
  • Undergraduate Researcher
    • Implemented deep learning models based on RNNs and Transformers to address missing data and temporal dependencies in biomedical time-series, producing imputation and forecasting pipelines validated in PyTorch experiments.
• Bilkent University, Ankara, Turkey, 2021
  • Teaching Assistant
    • Tutored students and graded assignments for Calculus I, Calculus II for 60 students per semester.
• TUBITAK SAGE, Ankara, Turkey, 2021
  • Intern
    • Designed nano-drone hardware and software simulations in Altium Designer to improve agility and reduce detectability in defense applications, supporting early-stage validation of stealth-oriented aerial platforms.
• UMRAM, Ankara, Turkey, 2020
  • Intern
    • Implemented and tested MATLAB-based interfaces for fundamental electronic devices (gaussmeter, analog filter, and DC power supply) to support scalable experimentation for future research, resulting in a publication in Medical Physics.