Mohammad Kachuee

820 total citations · 1 hit paper
18 papers, 556 citations indexed

About

Mohammad Kachuee is a scholar working on Artificial Intelligence, Biomedical Engineering and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Mohammad Kachuee has authored 18 papers receiving a total of 556 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 4 papers in Biomedical Engineering and 2 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Mohammad Kachuee's work include Machine Learning and Data Classification (4 papers), Non-Invasive Vital Sign Monitoring (3 papers) and Data Stream Mining Techniques (2 papers). Mohammad Kachuee is often cited by papers focused on Machine Learning and Data Classification (4 papers), Non-Invasive Vital Sign Monitoring (3 papers) and Data Stream Mining Techniques (2 papers). Mohammad Kachuee collaborates with scholars based in United States and Iran. Mohammad Kachuee's co-authors include Mahdi Shabany, Mohammad Mahdi Kiani, Hoda Mohammadzade, Majid Sarrafzadeh, Kimmo Kärkkäinen, Chenglin Hong, Ian W. Holloway, Sung‐Jin Lee, Dongwon Jung and James C. Leiter and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Biomedical Engineering and Journal of Medical Internet Research.

In The Last Decade

Mohammad Kachuee

15 papers receiving 535 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.

Cuffless Blood Pressure Estimation Algorithms for Continuous Health-Care Monitoring

2016 445 citations Mohammad Kachuee, Mohammad Mahdi Kiani et al. IEEE Transactions on Biomedical Engineering profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mohammad Kachuee United States	6	448	393	232	45	40	18	556
Drew A. Birrenkott United States	5	492 1.1×	353 0.9×	207 0.9×	22 0.5×	54 1.4×	8	577
Mohammad Mahdi Kiani Iran	4	617 1.4×	552 1.4×	332 1.4×	19 0.4×	61 1.5×	6	691
Kilin Shi Germany	13	440 1.0×	245 0.6×	194 0.8×	20 0.4×	32 0.8×	27	563
P. Kostka Poland	10	227 0.5×	174 0.4×	85 0.4×	32 0.7×	31 0.8×	45	333
Christine L. Tsien United States	7	191 0.4×	125 0.3×	250 1.1×	50 1.1×	19 0.5×	9	384
Yong Bai China	12	289 0.6×	272 0.7×	359 1.5×	34 0.8×	69 1.7×	47	628
Sven Schellenberger Germany	10	362 0.8×	196 0.5×	165 0.7×	16 0.4×	23 0.6×	20	467
Tero Hurnanen Finland	13	401 0.9×	411 1.0×	128 0.6×	14 0.3×	42 1.1×	29	557
Zeng-Ding Liu China	10	318 0.7×	283 0.7×	143 0.6×	10 0.2×	34 0.8×	14	393
Abdolrahim Kadkhodamohammadi United Kingdom	10	171 0.4×	119 0.3×	148 0.6×	28 0.6×	23 0.6×	15	304

Countries citing papers authored by Mohammad Kachuee

Since Specialization

Citations

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

Fields of papers citing papers by Mohammad Kachuee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mohammad Kachuee

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

All Works

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18 of 18 papers shown

1.

Kachuee, Mohammad, et al.. (2024). LLM-based Frameworks for API Argument Filling in Task-Oriented Conversational Systems. 419–426. 1 indexed citations

2.

Jung, Dongwon, et al.. (2024). Planning and Editing What You Retrieve for Enhanced Tool Learning. 975–988.

3.

Kachuee, Mohammad, et al.. (2023). Constrained Policy Optimization for Controlled Self-Learning in Conversational AI Systems. 43–52. 2 indexed citations

4.

Kachuee, Mohammad, et al.. (2022). Domain-Aware Contrastive Knowledge Transfer for Multi-domain Imbalanced Data. 25–36. 3 indexed citations

5.

Kachuee, Mohammad, et al.. (2022). Scalable and Robust Self-Learning for Skill Routing in Large-Scale Conversational AI Systems. 1–8. 1 indexed citations

6.

Kachuee, Mohammad, et al.. (2021). Leveraging Social Media Activity and Machine Learning for HIV and Substance Abuse Risk Assessment: Development and Validation Study. Journal of Medical Internet Research. 23(4). e22042–e22042. 22 indexed citations

7.

Kachuee, Mohammad, et al.. (2021). Decentralized Knowledge Transfer on Edge Networks for Detecting Cancer in Images. 898. 1–5. 3 indexed citations

8.

Kachuee, Mohammad. (2020). Opportunistic Learning: Algorithms and Methods for Cost-Sensitive and Context-Aware Learning. eScholarship (California Digital Library).

9.

Kachuee, Mohammad, et al.. (2020). Generative Imputation and Stochastic Prediction. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44(3). 1278–1288. 16 indexed citations

10.

Kachuee, Mohammad, et al.. (2020). Target-Focused Feature Selection Using Uncertainty Measurements in Healthcare Data. 1(3). 1–17. 6 indexed citations

11.

Kachuee, Mohammad, et al.. (2019). Nutrition and Health Data for Cost-Sensitive Learning.. arXiv (Cornell University). 4 indexed citations

12.

Kachuee, Mohammad, et al.. (2019). Opportunistic Learning: Budgeted Cost-Sensitive Learning from Data Streams. International Conference on Learning Representations. 3 indexed citations

13.

Kachuee, Mohammad, et al.. (2018). Dynamic Feature Acquisition Using Denoising Autoencoders. IEEE Transactions on Neural Networks and Learning Systems. 30(8). 2252–2262. 14 indexed citations

14.

Kachuee, Mohammad, Lisa Moore, Ruyi Huang, et al.. (2017). An Active Learning Based Prediction of Epidural Stimulation Outcome in Spinal Cord Injury Patients Using Dynamic Sample Weighting. 478–483. 4 indexed citations

15.

Kachuee, Mohammad, et al.. (2017). Non-invasive blood pressure estimation using phonocardiogram. arXiv (Cornell University). 1–4. 28 indexed citations

16.

Kachuee, Mohammad, et al.. (2017). Sport analytics platform for athletic readiness assessment. 2006. 156–159. 1 indexed citations

17.

Kachuee, Mohammad, et al.. (2017). Context-aware feature query to improve the prediction performance. 838–842. 3 indexed citations

18.

Kachuee, Mohammad, Mohammad Mahdi Kiani, Hoda Mohammadzade, & Mahdi Shabany. (2016). Cuffless Blood Pressure Estimation Algorithms for Continuous Health-Care Monitoring. IEEE Transactions on Biomedical Engineering. 64(4). 859–869. 445 indexed citations breakdown →

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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