Dr Mehmet Suzen MInstP

• cascading Periodic Spectral Ergodicity (cPSE):
  A complexity measure for connectionist machine learning
  Manuscript arXiv:1911.07831
  Python notebook on nbview
  Available in Bristol Package v0.2.6 as a single function.
  
  
• Generalised learning in time-series: reconstructive cross-validation (rCV)
  Manuscript arXiv:1910.09394
  Python notebook on nbview : Prototype implementation with Ornstein-Uhlenbeck processes
  
  
• Compressive transition path sampling: How to simulate rare event for longer time scales?
  Manuscript: arXiv:1804.09781
  
  
• Spectral ergodicity could explain deep learning.
  Manuscript: arXiv:1704.08303
  Software:
  • Python Package Bristol Parallel Random Matrix Tools
  Talks :
  • Spectral ergodicity for explainable deep learning:A simulation approach
  • Spectral Ergodicity in Deep Learning Architectures
  
  
• Effective ergodicity in single-spin-flip dynamics
  Phys. Rev. E 90, 032141 (2014) DOI: 10.1103/PhysRevE.90.032141
  Mehmet Suezen
  

Thesis

• Induced Charge Computation, PhD Dissertation, FIAS, Goethe University, Frankfurt/Main
  Academic descendant of Carl Fredrich Gauss: math genealogy
• Chaotic behaviour of geodesics, MSc Thesis in Theoretical Physics, Cyprus

Selected Blog Posts

• Bringing back the Occam's razor to modern connectionist machine learning. (December 2019)
• On modern data scientist: A blind empiricist is not a data scientist (September 2019)
• Research as a core driver in AI and Data Science (January 2019)
• Understanding overfitting: an inaccurate meme in supervised learning (August 2017)
• Practical Kullback-Leibler (KL) Divergence: Discrete Case (January 2017)
• Economy and dynamic modelling: Haavelmo's approach (July 2016)
• S-shaped data: Smoothing with quasibinomial distribution (January 2016)
• Testing emergent gravity: Gravitational Lensing to atom interferometer (January 2017)
• Understanding the empirical law of large numbers and the gambler's fallacy (August 2016)

Supervisions and mentoring service to community

• Mentor Data Scientists and engineers: Machine learning and data mining projects.
  Warwick/London/Cologne: 2015-16, 2018-2019.
• Mentor postdoc colleagues on compressed sensing algorithms.
  Barcelona (ICFO), 2009-2010.
• Onboard and provide initial guidance for Marcello Sega, Sofia Kantorovich on
  induced charge computation algorithms and
  ensemble equivalence in single molecule stretching.
  Frankfurt am Main (FIAS) 2006-2009.
• Supervise Computer Science undergraduate projects.
  Network anomaly detection.
  Cyprus, 2005.

(c) 2016, 2017, 2018, 2019 by Mehmet Suezen
suzen at acm dot org
All rights reserved
Do not copy or distribute without prior permission.