Alborz Geramifard

1.2k total citations
28 papers, 494 citations indexed

About

Alborz Geramifard is a scholar working on Artificial Intelligence, Computer Networks and Communications and Computer Vision and Pattern Recognition. According to data from OpenAlex, Alborz Geramifard has authored 28 papers receiving a total of 494 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Artificial Intelligence, 8 papers in Computer Networks and Communications and 8 papers in Computer Vision and Pattern Recognition. Recurrent topics in Alborz Geramifard's work include Reinforcement Learning in Robotics (15 papers), Speech and dialogue systems (6 papers) and Topic Modeling (6 papers). Alborz Geramifard is often cited by papers focused on Reinforcement Learning in Robotics (15 papers), Speech and dialogue systems (6 papers) and Topic Modeling (6 papers). Alborz Geramifard collaborates with scholars based in United States, Canada and Israel. Alborz Geramifard's co-authors include Jonathan P. How, Joshua Redding, Girish Chowdhary, Nazım Kemal Üre, Mykel J. Kochenderfer, Christopher Amato, Michael Bowling, Nicholas Roy, Csaba Szepesvári and Richard S. Sutton and has published in prestigious journals such as The International Journal of Robotics Research, Journal of Machine Learning Research and Journal of Intelligent & Robotic Systems.

In The Last Decade

Alborz Geramifard

27 papers receiving 466 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alborz Geramifard United States 13 306 132 112 74 71 28 494
Nicholas K. Jong United States 10 305 1.0× 128 1.0× 297 2.7× 101 1.4× 85 1.2× 12 673
Shayegan Omidshafiei United States 10 229 0.7× 82 0.6× 91 0.8× 45 0.6× 86 1.2× 31 403
Syed Umar India 9 209 0.7× 46 0.3× 92 0.8× 53 0.7× 85 1.2× 45 420
Hanna Pasula United States 9 422 1.4× 211 1.6× 79 0.7× 92 1.2× 49 0.7× 12 679
Yali Du United Kingdom 12 275 0.9× 88 0.7× 61 0.5× 29 0.4× 93 1.3× 35 516
Xuyan Tu China 11 206 0.7× 65 0.5× 85 0.8× 20 0.3× 60 0.8× 107 439
Mario Aldape-Pérez Mexico 14 233 0.8× 150 1.1× 32 0.3× 38 0.5× 156 2.2× 41 551
Daniele Giardino Italy 10 158 0.5× 55 0.4× 88 0.8× 35 0.5× 71 1.0× 22 442
Bikramjit Banerjee United States 11 370 1.2× 33 0.3× 96 0.9× 25 0.3× 68 1.0× 44 500

Countries citing papers authored by Alborz Geramifard

Since Specialization
Citations

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

Fields of papers citing papers by Alborz Geramifard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alborz Geramifard

This figure shows the co-authorship network connecting the top 25 collaborators of Alborz Geramifard. A scholar is included among the top collaborators of Alborz Geramifard 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 Alborz Geramifard. Alborz Geramifard 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.
Kottur, Satwik, et al.. (2022). Navigating Connected Memories with a Task-oriented Dialog System. 2495–2507.
2.
Wu, Qingyang, Zhenzhong Lan, Kun Qian, et al.. (2022). Memformer: A Memory-Augmented Transformer for Sequence Modeling. 308–318. 8 indexed citations
3.
Lê, Hung, Chinnadhurai Sankar, Seungwhan Moon, et al.. (2021). DVD: A Diagnostic Dataset for Multi-step Reasoning in Video Grounded Dialogue. 5651–5665. 6 indexed citations
4.
Kottur, Satwik, Chinnadhurai Sankar, Yu Zhou, & Alborz Geramifard. (2021). DialogStitch: Synthetic Deeper and Multi-Context Task-Oriented Dialogs. 21–26. 2 indexed citations
5.
Kottur, Satwik, Paul Crook, Seungwhan Moon, et al.. (2021). An Analysis of State-of-the-Art Models for Situated Interactive MultiModal Conversations (SIMMC). 144–153. 1 indexed citations
6.
Geramifard, Alborz, et al.. (2015). RLPy: a value-function-based reinforcement learning framework for education and research. Journal of Machine Learning Research. 16(1). 1573–1578. 17 indexed citations
7.
Geramifard, Alborz. (2013). A Tutorial on Linear Function Approximators for Dynamic Programming and Reinforcement Learning. now publishers, Inc. eBooks. 14 indexed citations
8.
Geramifard, Alborz, Joshua Redding, & Jonathan P. How. (2013). Intelligent Cooperative Control Architecture: A Framework for Performance Improvement Using Safe Learning. Journal of Intelligent & Robotic Systems. 72(1). 83–103. 27 indexed citations
9.
Geramifard, Alborz, et al.. (2013). A Tutorial on Linear Function Approximators for Dynamic Programming and Reinforcement Learning. 6(4). 375–451. 75 indexed citations
10.
Amato, Christopher, Girish Chowdhary, Alborz Geramifard, Nazım Kemal Üre, & Mykel J. Kochenderfer. (2013). Decentralized control of partially observable Markov decision processes. 2398–2405. 68 indexed citations
11.
Joseph, Joshua, Alborz Geramifard, John W. Roberts, Jonathan P. How, & Nicholas Roy. (2013). Reinforcement learning with misspecified model classes. 939–946. 10 indexed citations
12.
Geramifard, Alborz, Joshua Redding, James Joseph, Nicholas Roy, & Jonathan P. How. (2012). Model estimation within planning and learning. 793–799. 2 indexed citations
13.
Geramifard, Alborz, Finale Doshi, Joshua Redding, Nicholas Roy, & Jonathan P. How. (2011). Online Discovery of Feature Dependencies. International Conference on Machine Learning. 881–888. 25 indexed citations
14.
Geramifard, Alborz, Joshua Redding, Nicholas Roy, & Jonathan P. How. (2011). UAV cooperative control with stochastic risk models. 3393–3398. 18 indexed citations
15.
Redding, Joshua, Nazım Kemal Üre, Alborz Geramifard, et al.. (2011). Multi-Agent Planning for Persistent Missions with Automated Battery Management. AIAA Guidance, Navigation, and Control Conference. 6 indexed citations
16.
Redding, Joshua, Alborz Geramifard, Han‐Lim Choi, & Jonathan P. How. (2010). Actor-Critic Policy Learning in Cooperative Planning. AIAA Guidance, Navigation, and Control Conference. 5 indexed citations
17.
He, Ruijie, Abraham Bachrach, Michael Achtelik, et al.. (2009). On the Design and Use of a Micro Air Vehicle to Track and Avoid Adversaries. The International Journal of Robotics Research. 29(5). 529–546. 35 indexed citations
18.
Bowling, Michael, Alborz Geramifard, & David Wingate. (2008). Sigma point policy iteration. Adaptive Agents and Multi-Agents Systems. 379–386. 3 indexed citations
19.
Geramifard, Alborz, et al.. (2006). Biased Cost Pathfinding. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 2(1). 112–114. 23 indexed citations
20.
Geramifard, Alborz, et al.. (2005). A Hybrid Three Layer Architecture for Fire Agent Management in Rescue Simulation Environment. International Journal of Advanced Robotic Systems. 2(2). 5 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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