Daniel Seita

1.2k total citations
22 papers, 534 citations indexed

About

Daniel Seita is a scholar working on Control and Systems Engineering, Biomedical Engineering and Artificial Intelligence. According to data from OpenAlex, Daniel Seita has authored 22 papers receiving a total of 534 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Control and Systems Engineering, 13 papers in Biomedical Engineering and 5 papers in Artificial Intelligence. Recurrent topics in Daniel Seita's work include Robot Manipulation and Learning (14 papers), Soft Robotics and Applications (11 papers) and Surgical Simulation and Training (4 papers). Daniel Seita is often cited by papers focused on Robot Manipulation and Learning (14 papers), Soft Robotics and Applications (11 papers) and Surgical Simulation and Training (4 papers). Daniel Seita collaborates with scholars based in United States, Switzerland and Sweden. Daniel Seita's co-authors include Ken Goldberg, John Canny, Jeffrey Ichnowski, Brijen Thananjeyan, Minho Hwang, Ashwin Balakrishna, Ryan Hoque, Nawid Jamali, Soshi Iba and Pete Florence and has published in prestigious journals such as Theoretical Computer Science, Autonomous Robots and IEEE Transactions on Automation Science and Engineering.

In The Last Decade

Daniel Seita

21 papers receiving 511 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Daniel Seita United States 14 300 174 163 107 71 22 534
Ashwin Balakrishna United States 11 305 1.0× 150 0.9× 107 0.7× 137 1.3× 49 0.7× 30 554
Jeffrey Ichnowski United States 16 393 1.3× 180 1.0× 207 1.3× 83 0.8× 42 0.6× 51 621
Brijen Thananjeyan United States 15 367 1.2× 261 1.5× 169 1.0× 176 1.6× 44 0.6× 25 688
Ajay Kumar Tanwani United States 12 278 0.9× 116 0.7× 107 0.7× 130 1.2× 35 0.5× 26 517
Michael Laskey United States 15 519 1.7× 257 1.5× 223 1.4× 193 1.8× 37 0.5× 26 711
Jihong Zhu United Kingdom 10 333 1.1× 176 1.0× 157 1.0× 38 0.4× 53 0.7× 18 521
Karl Van Wyk United States 12 497 1.7× 216 1.2× 235 1.4× 85 0.8× 25 0.4× 22 680
Erwin Coumans United States 8 299 1.0× 281 1.6× 213 1.3× 255 2.4× 41 0.6× 13 697
Leon Žlajpah Slovenia 16 657 2.2× 370 2.1× 210 1.3× 69 0.6× 16 0.2× 65 910

Countries citing papers authored by Daniel Seita

Since Specialization
Citations

This map shows the geographic impact of Daniel Seita'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 Seita with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Seita more than expected).

Fields of papers citing papers by Daniel Seita

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Seita. 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 Seita. The network helps show where Daniel Seita may publish in the future.

Co-authorship network of co-authors of Daniel Seita

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Seita. A scholar is included among the top collaborators of Daniel Seita 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 Seita. Daniel Seita is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Seita, Daniel, et al.. (2025). Cross-Domain Multi-Modal Few-Shot Object Detection via Rich Text. 6570–6580.
2.
Seita, Daniel, et al.. (2023). Bagging by Learning to Singulate Layers Using Interactive Perception. 3176–3183. 2 indexed citations
3.
Seita, Daniel, et al.. (2023). AutoBag: Learning to Open Plastic Bags and Insert Objects. 3918–3925. 22 indexed citations
4.
Seita, Daniel, et al.. (2022). Learning to Singulate Layers of Cloth using Tactile Feedback. 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 7773–7780. 16 indexed citations
5.
Hwang, Minho, Jeffrey Ichnowski, Brijen Thananjeyan, et al.. (2022). Automating Surgical Peg Transfer: Calibration With Deep Learning Can Exceed Speed, Accuracy, and Consistency of Humans. IEEE Transactions on Automation Science and Engineering. 20(2). 909–922. 19 indexed citations
6.
Huang, Huang, Jonathan Wang, Jeffrey Ichnowski, et al.. (2022). Real2Sim2Real: Self-Supervised Learning of Physical Single-Step Dynamic Actions for Planar Robot Casting. 2022 International Conference on Robotics and Automation (ICRA). 8282–8289. 26 indexed citations
7.
Zhang, Harry, Jeffrey Ichnowski, Daniel Seita, et al.. (2021). Robots of the Lost Arc: Self-Supervised Learning to Dynamically Manipulate Fixed-Endpoint Cables. 4560–4567. 23 indexed citations
8.
Seita, Daniel, Pete Florence, Jonathan Tompson, et al.. (2021). Learning to Rearrange Deformable Cables, Fabrics, and Bags with Goal-Conditioned Transporter Networks. 4568–4575. 92 indexed citations
9.
Sundaresan, Priya, Brijen Thananjeyan, Ashwin Balakrishna, et al.. (2021). Learning Dense Visual Correspondences in Simulation to Smooth and Fold Real Fabrics. 11515–11522. 35 indexed citations
10.
Hwang, Minho, Brijen Thananjeyan, Jeffrey Ichnowski, et al.. (2021). Intermittent Visual Servoing: Efficiently Learning Policies Robust to Instrument Changes for High-precision Surgical Manipulation. 7166–7173. 23 indexed citations
11.
Hoque, Ryan, Ashwin Balakrishna, Michael Luo, et al.. (2021). LazyDAgger: Reducing Context Switching in Interactive Imitation Learning. 502–509. 19 indexed citations
12.
Hwang, Minho, Daniel Seita, Brijen Thananjeyan, et al.. (2020). Applying Depth-Sensing to Automated Surgical Manipulation with a da Vinci Robot. 22–29. 25 indexed citations
13.
Seita, Daniel, Ryan Hoque, Minho Hwang, et al.. (2020). Deep Imitation Learning of Sequential Fabric Smoothing From an Algorithmic Supervisor. 9651–9658. 72 indexed citations
14.
Hwang, Minho, Brijen Thananjeyan, Daniel Seita, et al.. (2020). Efficiently Calibrating Cable-Driven Surgical Robots With RGBD Sensing, Temporal Windowing, and Linear and Recurrent Neural Network Compensation. 3 indexed citations
15.
Pan, Xinlei, Daniel Seita, Yang Gao, & John Canny. (2019). Risk Averse Robust Adversarial Reinforcement Learning. 8522–8528. 39 indexed citations
16.
Seita, Daniel, Ryan Hoque, Minho Hwang, et al.. (2019). Deep Imitation Learning of Sequential Fabric Smoothing Policies. 9 indexed citations
17.
Seita, Daniel, Sanjay Krishnan, Roy Fox, et al.. (2018). Fast and Reliable Autonomous Surgical Debridement with Cable-Driven Robots Using a Two-Phase Calibration Procedure. 42 indexed citations
18.
Seita, Daniel, Nawid Jamali, Michael Laskey, et al.. (2018). Robot Bed-Making: Deep Transfer Learning Using Depth Sensing of Deformable Fabric.. 10 indexed citations
19.
Blanchet-Sadri, F., Daniel Seita, & David S. Wise. (2016). Computing abelian complexity of binary uniform morphic words. Theoretical Computer Science. 640. 41–51. 3 indexed citations
20.
Seita, Daniel, Florian T. Pokorny, Jeffrey Mahler, et al.. (2016). Large-scale supervised learning of the grasp robustness of surface patch pairs. 15. 216–223. 13 indexed citations

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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