Daniel H. Grollman

723 total citations
19 papers, 419 citations indexed

About

Daniel H. Grollman is a scholar working on Artificial Intelligence, Control and Systems Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Daniel H. Grollman has authored 19 papers receiving a total of 419 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 11 papers in Control and Systems Engineering and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Daniel H. Grollman's work include Reinforcement Learning in Robotics (8 papers), Robot Manipulation and Learning (6 papers) and Machine Learning and Algorithms (4 papers). Daniel H. Grollman is often cited by papers focused on Reinforcement Learning in Robotics (8 papers), Robot Manipulation and Learning (6 papers) and Machine Learning and Algorithms (4 papers). Daniel H. Grollman collaborates with scholars based in United States, Switzerland and Canada. Daniel H. Grollman's co-authors include Odest Chadwicke Jenkins, Aude Billard, Benjamin Pitzer, Graylin Jay, Halit Bener Suay, Sarah Osentoski, Frank Wood, Christopher Crick, Tom Williams and Qin Zhu and has published in prestigious journals such as Journal of Field Robotics, International Journal of Social Robotics and Interaction Studies Social Behaviour and Communication in Biological and Artificial Systems.

In The Last Decade

Daniel H. Grollman

18 papers receiving 391 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daniel H. Grollman United States	10	284	277	63	50	49	19	419
Halit Bener Suay United States	12	216 0.8×	280 1.0×	60 1.0×	53 1.1×	49 1.0×	21	434
Konstantinos Chatzilygeroudis Greece	10	166 0.6×	211 0.8×	61 1.0×	94 1.9×	46 0.9×	26	384
Vincent Berenz Japan	11	205 0.7×	116 0.4×	101 1.6×	78 1.6×	47 1.0×	24	420
Andrea Bajcsy United States	9	122 0.4×	115 0.4×	60 1.0×	27 0.5×	23 0.5×	19	298
Manuel Mühlig Germany	10	191 0.7×	123 0.4×	78 1.2×	57 1.1×	25 0.5×	19	274
Jacky Liang United States	7	258 0.9×	192 0.7×	174 2.8×	98 2.0×	92 1.9×	12	516
Tijn van der Zant Netherlands	11	103 0.4×	183 0.7×	197 3.1×	19 0.4×	44 0.9×	19	386
Dilip Kumar Limbu Singapore	8	145 0.5×	65 0.2×	39 0.6×	54 1.1×	64 1.3×	22	274
Daehyung Park United States	10	148 0.5×	169 0.6×	106 1.7×	44 0.9×	29 0.6×	26	329
Benjamin Burchfiel United States	9	244 0.9×	120 0.4×	150 2.4×	81 1.6×	56 1.1×	16	506

Countries citing papers authored by Daniel H. Grollman

Since Specialization

Citations

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

Fields of papers citing papers by Daniel H. Grollman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel H. Grollman

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

All Works

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19 of 19 papers shown

Baraka, Kim, Erdem Bıyık, Serena Booth, et al.. (2025). Human-Interactive Robot Learning: Definition, Challenges, and Recommendations. ACM Transactions on Human-Robot Interaction. 15(2). 1–31.

Williams, Tom, Qin Zhu, & Daniel H. Grollman. (2020). An Experimental Ethics Approach to Robot Ethics Education. Proceedings of the AAAI Conference on Artificial Intelligence. 34(9). 13428–13435. 6 indexed citations

Mead, Ross, et al.. (2018). HRI 2018 Workshop. 399–400. 3 indexed citations

Grollman, Daniel H.. (2017). Avoiding the Content Treadmill for Robot Personalities. International Journal of Social Robotics. 10(2). 225–234. 2 indexed citations

Grollman, Daniel H., et al.. (2014). Estimating People's Subjective Experiences of Robot Behavior. National Conference on Artificial Intelligence. 2 indexed citations

Grollman, Daniel H.. (2014). Robots: Pets or people?. Interaction Studies Social Behaviour and Communication in Biological and Artificial Systems. 15(2). 205–209. 1 indexed citations

Billard, Aude & Daniel H. Grollman. (2013). Robot learning by demonstration. Scholarpedia. 8(12). 3824–3824. 57 indexed citations

Osentoski, Sarah, Benjamin Pitzer, Christopher Crick, et al.. (2012). Remote Robotic Laboratories for Learning from Demonstration. International Journal of Social Robotics. 4(4). 449–461. 20 indexed citations

Demirdjian, David, et al.. (2012). Handheld operator control unit. 137–138. 3 indexed citations

10.

Grollman, Daniel H. & Aude Billard. (2012). Robot Learning from Failed Demonstrations. International Journal of Social Robotics. 4(4). 331–342. 28 indexed citations

11.

Grollman, Daniel H. & Aude Billard. (2011). Donut as I do: Learning from failed demonstrations. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 3804–3809. 46 indexed citations

12.

Grollman, Daniel H. & Aude Billard. (2011). Learning from failure. 145–146. 2 indexed citations

13.

Grollman, Daniel H. & Odest Chadwicke Jenkins. (2010). Incremental learning of subtasks from unsegmented demonstration. 63 indexed citations

14.

Jenkins, Odest Chadwicke & Daniel H. Grollman. (2010). Teaching old dogs new tricks: incremental multimap regression for interactive robot learning from demonstration. 6 indexed citations

15.

Jenkins, Odest Chadwicke, et al.. (2008). Wiimote interfaces for lifelong robot learning. National Conference on Artificial Intelligence. 61–66. 15 indexed citations

16.

Grollman, Daniel H. & Odest Chadwicke Jenkins. (2008). Sparse incremental learning for interactive robot control policy estimation. 3315–3320. 44 indexed citations

17.

Grollman, Daniel H. & Odest Chadwicke Jenkins. (2007). Dogged Learning for Robots. Proceedings - IEEE International Conference on Robotics and Automation/Proceedings. 2483–2488. 90 indexed citations

18.

Grollman, Daniel H. & Odest Chadwicke Jenkins. (2007). Learning robot soccer skills from demonstration. 276–281. 22 indexed citations

19.

Grollman, Daniel H., Odest Chadwicke Jenkins, & Frank Wood. (2006). Discovering natural kinds of robot sensory experiences in unstructured environments. Journal of Field Robotics. 23(11-12). 1077–1089. 9 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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