Developed and implemented a novel data analysis framework for classifying complex systems and patterns. Engineered a machine learning-based forest fire detection system. Conducted and published research on the physics of complex systems. Organized international schools, seminars, and public lectures featuring acclaimed scientists from around the world.

Conducted and published research combining physics, data science, and complex systems. Mentored graduate students and taught advanced courses in statistical physics, quantum computing, mechanics, electricity & magnetism, and neuroscience.

Collaborated in a six-person multinational team to create a predictive analytics solution for the UK Gambling Commission, Britain's main gambling regulatory body. Built automated data processing system and forecasting models for lottery market analysis, predicting lottery proceeds across different time scales (monthly, quarterly, yearly). Developed also an interactive visualization tool for policy decision support.

Implemented data collection and analysis procedures for precise calibration measurements. Maintained detailed documentation of laboratory procedures and results using standardized data management practices.

Taught undergraduate laboratory courses in Mechanics and Electricity & Magnetism. Guided students through hands-on physics experiments and data analysis.

Analyzed experimental time-series data to identify chaotic behavior in semiconductor systems, as part of an international research project developing advanced humidity sensors. The project focused on creating improved sensing electronics through innovative parametrization methods.

Conducted research on quantum transport in two-dimensional electron systems. Simulated quantum point contact experiments to understand electron behavior under various conditions. Examined equilibrium states in quantum systems as part of senior thesis work.

Performed statistical and risk analyses of the Chernobyl nuclear disaster's long-term effects in Richard Wilson's lab. Conducted literature review and data analysis to assess ongoing impact 24 years after the event. Research focused on understanding implications for future nuclear incidents.

Conducted peer reviews for scientific articles submitted to the interdisciplinary journal, Chaos, Solitons & Fractals, focusing on topics related to nonlinear science.

Supervised a dynamic team of highly motivated and talented high school students from various schools across Turkey. Guided the team in developing and proposing a project for the Beamline for Schools competition at CERN.

Integral member of the core crew, actively participating in organizing and facilitating various events. Contributed to quantum computation workshops and hackathons conducted by QTurkey. Led study groups and provided mentorship to individuals enthusiastic about quantum computing within the community.

Organized the 5th and the 7th International Symposium on Chaos, Complexity, and Leadership.

Led the Robotics Club, overseeing club activities, projects, and events.

Graduation with high honors.

Thesis title: "From Metaphysics to Physics Emerging Human Social Life: A Study on Spinoza's Ethics"

Graduation with honors.

Thesis title: "Nonlinear Dynamics and Possible Chaoticity in Condensed Matter Systems"

Graduation with top ranking.

Thesis title: "Transport Properties of Quantum Point Contacts in The Presence of Edge States: Non-equilibrium vs. Equilibrated"

An intensive data science fellowship program that bridges academia and industry through hands-on practical projects. Collaborated with the UK Gambling Commission to develop a comprehensive predictive analytics pipeline, complete with a visualization application. This tool empowered policymakers by providing data-driven insights for regulatory decision-making in the gambling sector.

A specialized program exploring fundamental principles of complex systems theory and their real-world applications. Developed an agent-based model simulating Proof-of-Work blockchain dynamics, featuring an interactive interface to analyze centralization and decentralization patterns. The project demonstrated how key blockchain parameters influence network behavior and governance structures.

Outstanding Success in Assistantship for the MasterClass course organized jointly by Kadir Has University and FermiLab.

I analyzed the experimental nonlinear time-series data recorded from the measurements on various semiconductor thin films searching for a possible chaotic behavior.

A nematic phase, previously seen in the d=3 classical Heisenberg spin-glass system, occurs in the n-component cubic-spin spin-glass system, between the low-temperature spin-glass phase and the high temperature disordered phase, for number of components n >= 3, in spatial dimension d=3, thus constituting a liquid-crystal phase in a dirty (quenched-disordered) magnet. This result is obtained from renormalization-group calculations that are exact on the hierarchical lattice and, equivalently, approximate on the cubic spatial lattice. The nematic phase completely intervenes between the spin-glass phase and the disordered phase. The Lyapunov exponents of the spin-glass chaos are calculated from n=1 up to n=12 and show odd-even oscillations with respect to n.

A spin-glass system with a smooth or fractal outer surface is studied by renormalization-group theory, in bulk spatial dimension . Independently varying the surface and bulk random-interaction strengths, phase diagrams are calculated. The smooth surface does not have spin-glass ordering in the absence of bulk spin-glass ordering and always has spin-glass ordering when the bulk is spin-glass ordered. With fractal (d>2) surfaces, a sponge is obtained and has surface spin-glass ordering also in the absence of bulk spin-glass ordering. The phase diagram has the only-surface-spin-glass ordered phase, the bulk and surface spin-glass ordered phase, and the disordered phase, and a special multicritical point where these three phases meet. All spin-glass phases have distinct chaotic renormalization-group trajectories, with distinct Lyapunov and runaway exponents which we have calculated.

A spin system is studied with simultaneous permutation-symmetric Potts and spin-rotation-symmetric clock interactions in spatial dimensions d=2 and 3. The global phase diagram is calculated from the renormalization-group solution with the recently improved (spontaneous first-order detecting) Migdal-Kadanoff approximation or, equivalently, with hierarchical lattices with the inclusion of effective vacancies. Five different ordered phases are found: Conventionally ordered ferromagnetic, quadrupolar, antiferromagnetic phases and algebraically ordered antiferromagnetic, antiquadrupolar phases. These five different ordered phases and the disordered phase are mutually bounded by first- and second-order phase transitions, themselves delimited by multicritical points: Inverted bicritical, zero-temperature bicritical, tricritical, second-order bifurcation, and zero-temperature highly degenerate multicritical points. One rich phase diagram topology exhibits all of these phenomena.

A complexity classification scheme is developed from the fractal spectra of spin-glass chaos and demonstrated with multigeographic multicultural music and brain electroencephalogram signals. Systematic patterns are found to emerge. Chaos under scale change is the essence of spin-glass ordering and can be obtained, continuously tailor-made, from the exact renormalization-group solution of Ising models on frustrated hierarchical lattices. The music pieces are from genres of Turkish music, namely Arabesque, Rap, Pop, Classical, and genres of Western music, namely Blues, Jazz, Pop, Classical. A surprising group defection occurs.

All higher-spin (s≥1/2) Ising spin glasses are studied by renormalization-group theory in spatial dimension d=3, exactly on a d=3 hierarchical model and, simultaneously, by the Migdal-Kadanoff approximation on the cubic lattice. The s-sequence of global phase diagrams, the chaos Lyapunov exponent, and the spin-glass runaway exponent are calculated. It is found that, in d=3, a finite-temperature spin-glass phase occurs for all spin values, including the continuum limit of s→∞. The phase diagrams, with increasing spin s, saturate to a limit value. The spin-glass phase, for all s, exhibits chaotic behavior under rescalings, with the calculated Lyapunov exponent of λ=1.93 and runaway exponent of yR=0.24, showing simultaneous strong-chaos and strong-coupling behavior. The ferromagnetic-spin-glass and spin-glass-antiferromagnetic phase transitions occurring, along their whole length, respectively at pt=0.37 and 0.63 are unaffected by s, confirming the percolative nature of this phase transition.

The existence and limits of metastable droplets have been calculated using finite-system renormalization-group theory, for q-state Potts models in spatial dimension d=3. The dependence of the droplet critical sizes on magnetic field, temperature, and number of Potts states q has been calculated. The same method has also been used for the calculation of hysteresis loops across first-order phase transitions in these systems. The hysteresis loop sizes and shapes have been deduced as a function of magnetic field, temperature, and number of Potts states q. The uneven appearance of asymmetry in the hysteresis loop branches has been noted. The method can be extended to criticality and phase transitions in metastable phases, such as in surface-adsorbed systems and water.

All local bond-state densities are calculated for q-state Potts and clock models in three spatial dimensions, d=3. The calculations are done by an exact renormalization group on a hierarchical lattice, including the density recursion relations, and simultaneously are the Migdal-Kadanoff approximation for the cubic lattice. Reentrant behavior is found in the interface densities under symmetry breaking, in the sense that upon lowering the temperature, the value of the density first increases and then decreases to its zero value at zero temperature. For this behavior, a physical mechanism is proposed. A contrast between the phase transition of the two models is found and explained by alignment and entropy, as the number of states q goes to infinity. For the clock models, the renormalization-group flows of up to 20 energies are used.

In today’s connected, interdependent, fast, and globalized social world, conventional concepts and approaches for understanding social events have been getting weaker. There is a need of more dynamic points of view which will help us to grasp the underlying mechanisms of social dynamics and what is really happening beyond the phenomena that we observe as social events. Complexity science offers a fresh understanding of real systems, since they are usually complex. In the present study, an important concept of complexity science, self-organized criticality, is used gingerly to reinterpret the Arab Uprising, while a former study interpreted the Arab Uprising with the help of the concept “butterfly effect” of chaos theory. From chaos theory viewpoint, the starter event of the Arab Uprising which is the protest of a young Tunisian can be interpreted as the initial condition of the whole protest series and social movements. Although this approach supplies new ways of interpretations on the social movements, it misses the background state of the society. Self-organized criticality concept takes into account the whole society as a system and interprets the event not as an initial condition, but rather as a tipping point where the system which has reached a critical state begins to reorganize itself into a new state—a phase transition takes place. Has the Arab Uprising or as formerly so-called the Arab Spring finished? Was it a “spring” that the following days will bring the summer, or was it a “fall” that will bring the winter? Although the answer depends on one’s point of view, it will be understood only when the phase transition process is completed. Hence, the important thing, for everyone, is to understand the state of the society and the intentions of the organization of the society. That’s why this study seeks to explain dynamics of the Arab Uprising phenomenon with critical self-organization property of complexity theory as an alternative approach.