Furkan Danisman

Furkan Danisman

PhD student in Statistics. Teaching models to ask “what if?”

Research

Everything I've written, in four piles: Statistics, Economics, Healthcare and LLMs. Click one to filter. The plain-English version of each is on the About page, and citation counts live on Google Scholar, which updates more often than I do.

One dot per paper. first author   co-author. Hover for the title, click to jump to it.

Published

  1. Chiu, J., & Danisman, F. (2026). DeFi Lending: Returns, Leverage, and Liquidation Risks. Bank of Canada Staff Analytical Paper.
    TL;DR: What happens when you lend money to a stranger on the internet and the only chaperone is a smart contract. Read 300,000+ times — apparently more people care about this than about density estimation. Fair.
  2. Erul, E., Pacheco-Barcia, V., Alkan, A., Akkus, E., Danisman, F., Nixon, I., Eniu, A., & Urun, Y. (2026). Imposter Syndrome, Burnout, and Maladaptive Perfectionism Among Oncology Professionals: A Global Cross-Sectional Study. JCO Oncology Practice.
  3. Erul, E., Avcı, A.N., Akkus, E., Ayas, Ö.F., Danisman, F.B., & Utkan, G. (2025). Assessment of Fear of Cancer Recurrence in Patients with Colorectal Cancer and Its Association with Pet Ownership: A Cross-Sectional Study. Current Oncology, 32(11), 592.
  4. Kulturoglu, M.O., Aydin, F., Sagdic, M.F., Aslan, F., Oflaz, Z., Danisman, F.B., Kalaylioglu, Z., & Dogan, L. (2025). The Impact of Changes in Breast Density Over Time on Breast Cancer Risk. Scientific Reports, 15, 23900. [Paper]
  5. Erul, E., Aktekin, Y., Danisman, F.B., et al. (2025). Perceptions, Attitudes, and Concerns on Artificial Intelligence Applications in Patients with Cancer. Cancer Control, 32, 1–9.
  6. Acharya, S., Zhang, T.J., Kim, A., Haghighat, A., Xianlin, S., Shrestha, R.B., Mordig, M., Danisman, F., Chiu, J., Qi, Y.C., Schölkopf, B., Sachan, M., & Jin, Z. (2026). CauSciBench: Can LLMs Automate Causal Inference in Real-World Scientific Research? ICML 2026.
    TL;DR: A benchmark that asks whether LLMs can do the causal inference in real scientific papers, not just talk confidently about it.
  7. Danisman, F., Kilic, S.I., Amini, N., Orcun Ada, O., Aktas, S.G., & Sarul, G. (2023). METU Students' College Life Satisfaction. International Journal of Social Science Research and Review, 6(7), 12–37. [Paper]

Under Review

  1. Danisman, F.*, Zhang, L., Jin, Z., & Kong, D. (2026). Joint Supervision of Potential Outcomes for Causal Foundation Models. ICLR 2027.
    TL;DR: Causal foundation models usually learn each potential outcome on its own. We supervise both together — they are, after all, two halves of the same counterfactual.
  2. Chiu, J., & Danisman, F. (2026). DeFi Lending: Returns, Leverage, and Liquidation Risks. Journal of Financial Market Infrastructures.
  3. Danisman, F.*, Oflaz, Z., Kalaylioglu, Z., Kulturoglu, M.O., & Dogan, L. (2026). Decoupling Risk and Masking in Mammographic Density under Irregular Follow-Up Using a Latent Markov Progression–Detection Framework. Biometrical Journal. [Paper] [In the news]
    TL;DR: Dense breast tissue can both raise cancer risk and hide cancer on a mammogram. This model separates the two.
  4. Danisman, F.*, Jankowski, H., & de Souza, C.P.E. (2026). Bandwidth-Free Nonparametric Density Estimation for Grouped Data. Computational Statistics and Data Analysis. [Paper]
    TL;DR: Recovering a smooth density from data that only comes in bins (“50 people earn $100k–$120k”) — with no bandwidth to tune, because life already has enough hyperparameters.
  5. Danisman, F.*, Desai, A., Jiang, J., Rivadeneyra, F., & Azad, T. (2026). Strategic Interaction Among AI Agents: Evidence from Payment Systems. Management Science.
    TL;DR: We handed LLMs the treasury desks of a simulated large-value payment system and watched them strategize.

Talks, Posters & Other Peer-Reviewed Contributions

  1. Danisman, F.*, Oflaz, Z., & Kalaylioglu, Z. (2026). Decoupling Risk and Masking in Mammographic Density under Irregular Follow-Up Using a Latent Markov Progression–Detection Framework. Presentation, SSC 2026 Annual Meeting (national). Biostatistics Section Award for the best student research presentation.
  2. Danisman, F.*, Jankowski, H., de Souza, C., da Cruz, A., & Rakusin, R. (2025). Predicting New Onset Atrial Fibrillation: Black-Box and Interpretable Models. Poster, SSC 2025 Annual Meeting (national).
  3. Danisman, F.*, Nguyen, N., Raghuvanshi, A., & Bisnath, S. (2024). Augmentation of a Global Navigation Satellite System (GNSS). Poster, STEM Fellowship Conference (national).
  4. Danisman, F.*, Jankowski, H., & de Souza, C.P.E. (2025). Dens-OLog: Density Estimation with Optimized Log-Concavity. Presentation, SSC 2025 Annual Meeting (national).

Working Papers

  1. Arif, S., Danisman, F.*, Kong, D., Jin, Z., & Mihalcea, R. (2026). The Culture Within: Towards Mechanistic Understanding of Cultural Reasoning in LLMs. In preparation.
    TL;DR: Opening up LLMs to find where “culture” actually lives inside them.
  2. Danisman, F.*, Inan, E., Kong, D., & Jin, Z. (2026). Causal Stories: Representation of the Common Underlying Causal Events. In preparation.
    TL;DR: Different stories, same causal skeleton — learning to see it.