טדי לזבניק - הפקולטה למדעי המחשב והמידע

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A time-series clustering analysis of postinduction blood pressure trajectories, Glebov, M., Katsin, M., Berkenstadt, H., Orkin, D., Portnoy, Y., Schuchami, A. & Lazebnik, T., Dec 2026, In: Scientific Reports. 16, 1, 3745.
Detecting the metabolic transition to personalize nutritional timing: model development and preliminary validation in a large ICU cohort, Gargi, Y., Levran, N., Vine, J., Cohen, A., Weiner, D., Stein, D., Levi, O., Cohen, D., Klein, J., Taube, H. S., Glebov, M., Lazebnik, T., Saban, M., Efrat, S., Drori, E., Haviv, Y. & Segal, E., Dec 2026, In: Critical Care. 30, 1, 132.
Noradrenaline-trajectory phenotypes in septic shock: derivation and external validation in two independent cohorts, Yonatan, G., Cohen, A., Stein, D., Levi, O., Cohen, D., Klein, J., Taube, H. S., Vine, J., Glebov, M., Lazebnik, T., Saban, M., Haviv, Y. & Segal, E., Dec 2026, In: Intensive Care Medicine Experimental. 14, 1, 77.
Knowledge integration for physics-informed symbolic regression using pre-trained large language models, Taskin, B., Xie, W. & Lazebnik, T., Dec 2026, In: Scientific Reports. 16, 1, 1614.
Moving from table to graph in physics-informed spatio-temporal symbolic regression, Lazebnik, T. & Liberzon, A., Dec 2026, In: Scientific Reports. 16, 1, 16016.
Pre-transition nutrition dose and mortality using a CRP-Free operational metabolic transition framework: A MIMIC-IV transportability analysis, Gargi, Y., Levran, N., Stein, D., Levi, O., Cohen, D., Vine, J., Lazebnik, T., Segal, E. & Cohen, A., Oct 2026, In: Clinical Nutrition ESPEN. 75, 103431.
Cooperative Game-Theoretic Framework for Sustainable UN Financing: An Application to Global Public Goods Provision, Shami, L. & Lazebnik, T., Jul 2026, In: Economies. 14, 7, 263.
Chronic Stress, Immune Suppression, and Cancer Occurrence: Unveiling the Connection Using Survey Data and Predictive Models, Lazebnik, T. & Aharonson, V., Jun 2026, In: Medical sciences. 14, 2, 245.
Inducing state anxiety in LLM agents reproduces human-like biases in consumer decision-making, Ben-Zion, Z., Elyoseph, Z., Spiller, T. & Lazebnik, T., Jun 2026, In: npj Artificial Intelligence. 2, 1
Tighten the lasso: a convex hull volume-based anomaly detection method, Itai, U., Bar Ilan, A. & Lazebnik, T., Jun 2026, In: International Journal of Data Science and Analytics. 21, 1, 32.
Introducing “Inside” out of distribution, Lazebnik, T., Jun 2026, In: International Journal of Data Science and Analytics. 21, 1, 43.
Comparing partial differential equations and agent-based simulations in spatio-temporal modeling of cancer growth and shape, Lazebnik, T. & Friedman, A., 15 May 2026, In: Journal of Computational and Applied Mathematics. 477, 117183.
PDE and agent based simulation approaches to Ischemic Dermal Wound Closure, Lazebnik, T. & Friedman, A., May 2026, In: PLOS ONE. 21, 5 May, e0340624.
Harnessing AI-based computer vision to evaluate biological and behavioral variables in dog-dog play interactions, Cherry, D., Lazebnik, T., Henry, C. J. & Florkiewicz, B. N., 1 May 2026, In: Journal of Veterinary Behavior. 85, p. 7-15 9 p.
Whose LLM Is It Anyway? Linguistic Comparison and LLM Attribution for GPT-3.5, GPT-4 and Bard, Rosenfeld, A. & Lazebnik, T., May 2026, In: Mathematics. 14, 10, 1683.
Correction: Break a Lag: Triple Exponential Moving Average for Enhanced Optimization (Machine Learning, (2026), 115, 3, (58), 10.1007/s10994-025-06992-x), Peleg, R., Smadar, Y., Lazebnik, T. & Hoogi, A., May 2026, In: Machine Learning. 115, 5, 125.
Interpretable knowledge distillation via symbolic regression for feedforward neural networks, Shmuel, A., Koren, N., Glickman, O. & Lazebnik, T., Apr 2026, In: Neural Computing and Applications. 38, 7, 243.
An empirically-parameterized spatio-temporal extended-SIR model for combined dilution and vaccination mitigation for rabies outbreaks in wild jackals, Lazebnik, T., Samuel, Y., Tichon, J., Lapid, R., King, R., Nissimyan, T. & Spiegel, O., Apr 2026, In: Ecological Modelling. 514, 111487.
Break a Lag: Triple Exponential Moving Average for Enhanced Optimization, Peleg, R., Smadar, Y., Lazebnik, T. & Hoogi, A., Mar 2026, In: Machine Learning. 115, 3, 58.
Do Institutions Make Street-Level Bureaucrats Prosocial? Agent-Based Evidence Shows That New Public Management Does Not, Cohen, N. & Lazebnik, T., 1 Mar 2026, In: European Policy Analysis. 12, 2, e70024.
Close encounters of the cat kind: The influence of context and sex on facial signaling proximity in domesticated cats (Felis silvestris catus), Florkiewicz, B. N., Kanevsky, E., Zamansky, A. & Lazebnik, T., 1 Mar 2026, In: Journal of Veterinary Behavior. 84, p. 9-18 10 p.
Transforming norm-based to graph-based spatial representation for spatio-temporal epidemiological models, Lazebnik, T., 15 Feb 2026, In: Engineering Applications of Artificial Intelligence. 166, 113619.
Tell Me Who Your Neighbors Are and I Will Tell You Your Informal Economy Size: The Case of Sweden, Lazebnik, T., Shami, L. & Peretz-Andersson, E., 2026, (Accepted/In press) In: Computational Economics.
A quality-preserving model for test reduction in electronics production, Peretz-Andersson, E., Haneefa, N. & Lazebnik, T., 2026, (Accepted/In press) In: Frontiers in Mechanical Engineering. 1861443.
The impact of collective performance-related pay on street-level bureaucrats’ performance and clients’ outcomes, Cohen, N., Lazebnik, T. & Khalatnik, Y., 2026, (Accepted/In press) In: Public Performance and Management Review.
Follow the Forest Trail: Distillation by Gradient Boosting Models to Enhance Symbolic Regression Performance, Shmuel, A., Lazebnik, T. & Glickman, O., 2026, In: IEEE Access. 14, p. 19701-19712 12 p.
A Decision Tree Model for Profiling Citizens’ Support for Self-Help Strategies, Edri-Peer, O., Cohen, N. & Lazebnik, T., 2026, (Accepted/In press) In: Deviant Behavior.
Comparing manual vs. automated machine learning and deep learning models for predicting one-year mortality in elderly hip fracture patients, Shuchami, A., Glebov, M., Katsin, M., Portnoy, Y., Berkenstadt, H., Orkin, D. & Lazebnik, T., 2026, In: Frontiers in Medicine. 13, 1804645.
Combinatorics and complexity of chimpanzee (Pan troglodytes) facial signals, Florkiewicz, B. N. & Lazebnik, T., Dec 2025, In: Animal Cognition. 28, 1, 34.
Mind Your Manners: The Dynamics of Politeness in Human-AI vs. Human-Human Interactions, Lazebnik, T., Zalmanson, L. & Mokryn, O., 16 Oct 2025, In: Proceedings of the ACM on Human-Computer Interaction. 9, 7, CSCW450.
Developing a machine learning-based prediction model for postinduction hypotension, Katsin, M., Glebov, M., Berkenstadt, H., Orkin, D., Portnoy, Y., Shuchami, A., Yaniv-Rosenfeld, A. & Lazebnik, T., Oct 2025, In: Journal of Clinical Monitoring and Computing. 39, 5, p. 889-899 11 p.
Spatio-Temporal SIR Model of Pandemic Spread During Warfare with Optimal Dual-use Health Care System Administration using Deep Reinforcement Learning, Shuchami, A. & Lazebnik, T., 21 Jul 2025, In: Disaster Medicine and Public Health Preparedness. 19, e197.
Novel Objective Tool to Assess Tremor Reveals Unilateral Focused Ultrasound Improves Tremor Bilaterally, Aharonson, V., Lazebnik, T., Sinai, A., Nassar, M., Senderova, I., Constantinescu, M., Tov, L. L. & Schlesinger, I., Apr 2025, In: Neurology and Therapy. 14, 2, p. 565-574 10 p.
Global lightning-ignited wildfires prediction and climate change projections based on explainable machine learning models, Shmuel, A., Lazebnik, T., Glickman, O., Heifetz, E. & Price, C., Mar 2025, In: Scientific Reports. 15, 1, 7898.
Faces of time: a historical overview of rapid innovations in coding animal facial signals, Lazebnik, T. & Florkiewicz, B., 2025, In: Frontiers in Veterinary Science. 12, 1716633.
Spatio-temporal model of combining chemotherapy with senolytic treatment in lung cancer, Lazebnik, T. & Friedman, A., Jan 2025, In: Mathematical Biosciences. 379, 109342.
Individual variation affects outbreak magnitude and predictability in multi-pathogen model of pigeons visiting dairy farms, Lazebnik, T. & Spiegel, O., Jan 2025, In: Ecological Modelling. 499, 110925.
Machine and deep learning performance in out-of-distribution regressions, Shmuel, A., Glickman, O. & Lazebnik, T., 1 Dec 2024, In: Machine Learning: Science and Technology. 5, 4, 045078.
Temporal graphs anomaly emergence detection: benchmarking for social media interactions, Lazebnik, T. & Iny, O., Dec 2024, In: Applied Intelligence. 54, 23, p. 12347-12356 10 p.
Knowledge-integrated autoencoder model, Lazebnik, T. & Simon-keren, L., 15 Oct 2024, In: Expert Systems with Applications. 252, 124108.
Machine learning computational model to predict lung cancer using electronic medical records, Levi, M., Lazebnik, T., Kushnir, S., Yosef, N. & Shlomi, D., Oct 2024, In: Cancer Epidemiology. 92, 102631.
Improved prediction of settling behavior of solid particles through machine learning analysis of experimental retention time data, Keren, L. S., Lazebnik, T. & Liberzon, A., Feb 2024, In: International Journal of Multiphase Flow. 172, 104716.
Predicting lung cancer's metastats' locations using bioclinical model, Lazebnik, T. & Bunimovich-Mendrazitsky, S., 2024, In: Frontiers in Medicine. 11, 1388702.
A computational framework for physics-informed symbolic regression with straightforward integration of domain knowledge, Keren, L. S., Liberzon, A. & Lazebnik, T., Dec 2023, In: Scientific Reports. 13, 1, 1249.
Cancer-inspired genomics mapper model for the generation of synthetic DNA sequences with desired genomics signatures, Lazebnik, T. & Simon-Keren, L., Sep 2023, In: Computers in Biology and Medicine. 164, 107221.
Scheduling BCG and IL-2 Injections for Bladder Cancer Immunotherapy Treatment, Yaniv-Rosenfeld, A., Savchenko, E., Rosenfeld, A. & Lazebnik, T., Mar 2023, In: Mathematics. 11, 5, 1192.
Comparison of pandemic intervention policies in several building types using heterogeneous population model, Lazebnik, T. & Alexi, A., Apr 2022, In: Communications in Nonlinear Science and Numerical Simulation. 107, 106176.
Computer aided functional style identification and correction in modern russian texts, Savchenko, E. & Lazebnik, T., Mar 2022, In: Journal of Data, Information and Management. 4, 1, p. 25-32 8 p.
SubStrat: A Subset-Based Optimization Strategy for Faster AutoML, Lazebnik, T., Somech, A. & Weinberg, A. I., 2022, In: Proceedings of the VLDB Endowment. 16, 4, p. 772-780 9 p.
Novel method to analytically obtain the asymptotic stable equilibria states of extended sir-type epidemiological models, Lazebnik, T., Bunimovich-Mendrazitsky, S. & Shaikhet, L., Jul 2021, In: Symmetry. 13, 7, 1120.

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