Daniel M. Tartakovsky

8.2k total citations · 1 hit paper
275 papers, 6.2k citations indexed

About

Daniel M. Tartakovsky is a scholar working on Environmental Engineering, Civil and Structural Engineering and Statistics, Probability and Uncertainty. According to data from OpenAlex, Daniel M. Tartakovsky has authored 275 papers receiving a total of 6.2k indexed citations (citations by other indexed papers that have themselves been cited), including 140 papers in Environmental Engineering, 62 papers in Civil and Structural Engineering and 49 papers in Statistics, Probability and Uncertainty. Recurrent topics in Daniel M. Tartakovsky's work include Groundwater flow and contamination studies (122 papers), Soil and Unsaturated Flow (49 papers) and Probabilistic and Robust Engineering Design (48 papers). Daniel M. Tartakovsky is often cited by papers focused on Groundwater flow and contamination studies (122 papers), Soil and Unsaturated Flow (49 papers) and Probabilistic and Robust Engineering Design (48 papers). Daniel M. Tartakovsky collaborates with scholars based in United States, Italy and Spain. Daniel M. Tartakovsky's co-authors include Shlomo P. Neuman, Marco Dentz, Alberto Guadagnini, C. L. Winter, Alexandre M. Tartakovsky, Ilenia Battiato, Dongbin Xiu, Delphine Roubinet, Tim Scheibe and Krishna Sriram and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and The Journal of Chemical Physics.

In The Last Decade

Daniel M. Tartakovsky

263 papers receiving 6.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

From Fluid Flow to Coupled Processes in Fractured Rock: Recent Advances and New Frontiers

2022 164 citations Hari Viswanathan, Jonathan Ajo‐Franklin et al. Reviews of Geophysics profile →

Peers

Countries citing papers authored by Daniel M. Tartakovsky

Since Specialization

Citations

This map shows the geographic impact of Daniel M. Tartakovsky's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel M. Tartakovsky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel M. Tartakovsky more than expected).

Fields of papers citing papers by Daniel M. Tartakovsky

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel M. Tartakovsky. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel M. Tartakovsky. The network helps show where Daniel M. Tartakovsky may publish in the future.

Co-authorship network of co-authors of Daniel M. Tartakovsky

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel M. Tartakovsky. A scholar is included among the top collaborators of Daniel M. Tartakovsky based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel M. Tartakovsky. Daniel M. Tartakovsky is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	High-precision geosteering via reinforcement learning and particle filters 2025 ·Computational Geosciences ·(unknown), (unknown), (unknown), Reidar B. Bratvold, Daniel M. Tartakovsky	1
2	Transfer learning of neural surrogates on multifidelity groundwater simulations 2025 ·Advances in Water Resources ·(unknown), Valentina Ciriello, Daniel M. Tartakovsky	1
3	Generalizable models of magnetic hysteresis via physics-aware recurrent neural networks 2025 ·Computer Physics Communications ·(unknown), (unknown), (unknown), (unknown), Koen Tiels, Daniel M. Tartakovsky, E.A. Lomonova	1
4	Data-aware forecast of harmful algal blooms with model error 2025 ·Water Research ·(unknown), Aleksey Y. Sheshukov, Peng Wang, Daniel M. Tartakovsky	1
5	Non-equilibrium thermal models of lithium batteries 2024 ·Journal of Power Sources ·Xiaoyu Yang, (unknown), (unknown), Daniel M. Tartakovsky	2
6	Data-driven models of nonautonomous systems 2024 ·Journal of Computational Physics ·(unknown), Daniel M. Tartakovsky	1
7	Efficient quadratures for high-dimensional Bayesian data assimilation 2024 ·Journal of Computational Physics ·(unknown), Peng Wang, Daniel M. Tartakovsky	1
8	Neural Differential Equation-Based Two-Stage Approach for Generalization of Beam Dynamics 2024 ·IEEE Transactions on Industrial Informatics ·(unknown), Hongrui Wang, (unknown), K. El Sayed, Alfredo Núñez, Daniel M. Tartakovsky, Rolf Dollevoet	2
9	ROLE OF PHYSICS IN PHYSICS-INFORMED MACHINE LEARNING 2024 ·OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) ·(unknown), (unknown), Daniel M. Tartakovsky	5
10	Fracture Characterization Via AI‐Assisted Analysis of Temperature Logs 2024 ·OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) ·(unknown), Roland N. Horne, Daniel M. Tartakovsky	0
11	Parsimonious models of in-host viral dynamics and immune response 2023 ·Applied Mathematics Letters ·(unknown), Francesco Giannino, Daniel M. Tartakovsky	11
12	Surrogate models of heat transfer in fractured rock and their use in parameter estimation 2023 ·Computers & Geosciences ·Guofeng Song, Delphine Roubinet, Xiaoguang Wang, Gensheng Li, Xianzhi Song, Daniel M. Tartakovsky	0
13	Discovery of sparse hysteresis models for piezoelectric materials 2023 ·Applied Physics Letters ·(unknown), (unknown), (unknown), Koen Tiels, E.A. Lomonova, Daniel M. Tartakovsky	9
14	Feature-informed data assimilation 2023 ·Journal of Computational Physics ·(unknown), Wei Kang, Daniel M. Tartakovsky	4
15	From Fluid Flow to Coupled Processes in Fractured Rock: Recent Advances and New Frontiers breakdown → 2022 ·Reviews of Geophysics ·Hari Viswanathan, Jonathan Ajo‐Franklin, Jens Birkhölzer, J. William Carey, Yves Guglielmi, Jeffrey D. Hyman, Satish Karra, L. J. Pyrak‐Nolte, Harihar Rajaram, G. Srinivasan, Daniel M. Tartakovsky	164
16	Thermal Experiments for Fractured Rock Characterization: Theoretical Analysis and Inverse Modeling 2021 ·Water Resources Research ·(unknown), Delphine Roubinet, Daniel M. Tartakovsky	20
17	Resource-Constrained Model Selection for Uncertainty Propagation and Data Assimilation 2020 ·SIAM/ASA Journal on Uncertainty Quantification ·Lun Yang, Peng Wang, Daniel M. Tartakovsky	2
18	Temperature estimation from current and voltage measurements in lithium-ion battery systems 2020 ·Journal of Energy Storage ·Peng Wang, (unknown), (unknown), Daniel M. Tartakovsky, Simona Onori	26
19	Mixing-Induced Precipitation Phenomena: Range of Applicability of Macroscopic Equations 2008 ·AGUFM ·Ilenia Battiato, Alexandre M. Tartakovsky, Daniel M. Tartakovsky, (unknown)	0
20	Mean and Variance of DNAPL Finger Development in a Saturated, Randomly Heterogeneous Porous Medium. 2001 ·AGU Fall Meeting Abstracts ·Daniel M. Tartakovsky, Shlomo P. Neuman	3

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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