Melissa Mozifian

2.0k total citations · 1 hit paper
5 papers, 1.1k citations indexed

About

Melissa Mozifian is a scholar working on Control and Systems Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Melissa Mozifian has authored 5 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Control and Systems Engineering, 3 papers in Artificial Intelligence and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Melissa Mozifian's work include Anomaly Detection Techniques and Applications (2 papers), Simulation Techniques and Applications (1 paper) and Manufacturing Process and Optimization (1 paper). Melissa Mozifian is often cited by papers focused on Anomaly Detection Techniques and Applications (2 papers), Simulation Techniques and Applications (1 paper) and Manufacturing Process and Optimization (1 paper). Melissa Mozifian collaborates with scholars based in Canada, United States and Germany. Melissa Mozifian's co-authors include Steven L. Waslander, Ali Harakeh, Jungwook Lee, Jason S. Ku, Sebastian Höfer, Jan Peters, Florian Golemo, Chris Atkeson, Kostas E. Bekris and Dieter Fox and has published in prestigious journals such as IEEE Transactions on Automation Science and Engineering and arXiv (Cornell University).

In The Last Decade

Melissa Mozifian

5 papers receiving 1.1k citations

Hit Papers

align trajectories sort by overperformance

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.

Joint 3D Proposal Generation and Object Detection from View Aggregation

2018 1.0k citations Jason S. Ku, Melissa Mozifian et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Melissa Mozifian Canada	4	876	522	250	216	154	5	1.1k
Ali Harakeh Canada	8	1.2k 1.4×	650 1.2×	317 1.3×	264 1.2×	181 1.2×	10	1.5k
Jason S. Ku United States	10	1.3k 1.4×	747 1.4×	291 1.2×	264 1.2×	188 1.2×	26	1.7k
Jin Fang China	12	721 0.8×	367 0.7×	183 0.7×	156 0.7×	96 0.6×	22	1.0k
Tianwei Yin United States	4	1.1k 1.2×	509 1.0×	228 0.9×	169 0.8×	140 0.9×	7	1.3k
Zetong Yang Hong Kong	6	1.2k 1.3×	665 1.3×	215 0.9×	305 1.4×	268 1.7×	7	1.4k
Siyu Zhu China	14	1.2k 1.3×	395 0.8×	182 0.7×	138 0.6×	204 1.3×	35	1.4k
Yuxing Mao China	6	1.6k 1.8×	887 1.7×	366 1.5×	415 1.9×	297 1.9×	11	2.0k
Will Maddern United Kingdom	17	1.3k 1.5×	1.1k 2.2×	219 0.9×	227 1.1×	254 1.6×	19	1.7k
Michael Himmelsbach Germany	14	528 0.6×	495 0.9×	444 1.8×	374 1.7×	168 1.1×	21	1.1k
Xibin Song China	17	865 1.0×	272 0.5×	72 0.3×	100 0.5×	110 0.7×	34	1.2k

Countries citing papers authored by Melissa Mozifian

Since Specialization

Citations

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

Fields of papers citing papers by Melissa Mozifian

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Melissa Mozifian

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

All Works

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5 of 5 papers shown

1.

Mozifian, Melissa, et al.. (2021). Shaping Rewards for Reinforcement Learning with Imperfect Demonstrations using Generative Models. 6628–6634. 8 indexed citations

2.

Höfer, Sebastian, Kostas E. Bekris, Ankur Handa, et al.. (2021). Sim2Real in Robotics and Automation: Applications and Challenges. IEEE Transactions on Automation Science and Engineering. 18(2). 398–400. 81 indexed citations

3.

Mozifian, Melissa, Juan Camilo Gamboa Higuera, David Meger, & Gregory Dudek. (2019). Learning Domain Randomization Distributions for Transfer of Locomotion Policies.. arXiv (Cornell University). 3 indexed citations

4.

Ku, Jason S., Melissa Mozifian, Jungwook Lee, Ali Harakeh, & Steven L. Waslander. (2018). Joint 3D Proposal Generation and Object Detection from View Aggregation. 1–8. 1022 indexed citations breakdown →

5.

Mozifian, Melissa, et al.. (2018). Deep Learning a Quadrotor Dynamic Model for Multi-Step Prediction. 2454–2459. 27 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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