Ameer Haj-Ali

685 total citations
10 papers, 266 citations indexed

About

Ameer Haj-Ali is a scholar working on Electrical and Electronic Engineering, Hardware and Architecture and Information Systems. According to data from OpenAlex, Ameer Haj-Ali has authored 10 papers receiving a total of 266 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Electrical and Electronic Engineering, 4 papers in Hardware and Architecture and 3 papers in Information Systems. Recurrent topics in Ameer Haj-Ali's work include Advanced Memory and Neural Computing (6 papers), Ferroelectric and Negative Capacitance Devices (5 papers) and Parallel Computing and Optimization Techniques (4 papers). Ameer Haj-Ali is often cited by papers focused on Advanced Memory and Neural Computing (6 papers), Ferroelectric and Negative Capacitance Devices (5 papers) and Parallel Computing and Optimization Techniques (4 papers). Ameer Haj-Ali collaborates with scholars based in Israel, United States and Ecuador. Ameer Haj-Ali's co-authors include Shahar Kvatinsky, Rotem Ben-Hur, Nimrod Wald, Ronny Ronen, Debjyoti Bhattacharjee, Ion Stoica, Krste Asanović, Qijing Huang, William S. Moses and John Wawrzynek and has published in prestigious journals such as IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on Circuits and Systems I Regular Papers and IEEE Micro.

In The Last Decade

Ameer Haj-Ali

10 papers receiving 259 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ameer Haj-Ali Israel	8	197	67	64	47	46	10	266
Rotem Ben-Hur Israel	7	255 1.3×	95 1.4×	40 0.6×	38 0.8×	28 0.6×	10	300
Hanbo Sun China	9	252 1.3×	31 0.5×	44 0.7×	95 2.0×	36 0.8×	22	338
Geoffrey Ndu United Kingdom	5	252 1.3×	40 0.6×	97 1.5×	96 2.0×	60 1.3×	7	340
Fatemeh Tehranipoor United States	11	117 0.6×	37 0.6×	148 2.3×	75 1.6×	30 0.7×	30	244
Pravin Mane India	6	393 2.0×	129 1.9×	90 1.4×	34 0.7×	35 0.8×	18	430
S. Mourad United States	10	268 1.4×	31 0.5×	165 2.6×	37 0.8×	73 1.6×	57	356
Fatemeh Tehranipoor United States	9	201 1.0×	88 1.3×	251 3.9×	52 1.1×	26 0.6×	12	312
Abusaleh Jabir United Kingdom	10	232 1.2×	44 0.7×	88 1.4×	102 2.2×	17 0.4×	66	310
Song Bian Japan	11	126 0.6×	16 0.2×	67 1.0×	145 3.1×	24 0.5×	58	306

Countries citing papers authored by Ameer Haj-Ali

Since Specialization

Citations

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

Fields of papers citing papers by Ameer Haj-Ali

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ameer Haj-Ali. 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 Ameer Haj-Ali. The network helps show where Ameer Haj-Ali may publish in the future.

Co-authorship network of co-authors of Ameer Haj-Ali

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

All Works

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10 of 10 papers shown

Haj-Ali, Ameer, Qijing Huang, William S. Moses, et al.. (2020). AutoPhase: Juggling HLS Phase Orderings in Random Forests with Deep Reinforcement Learning. arXiv (Cornell University). 2. 70–81. 5 indexed citations

Li, Bin, Ren Wang, Charlie Tai, et al.. (2020). RLDRM: Closed Loop Dynamic Cache Allocation with Deep Reinforcement Learning for Network Function Virtualization. 335–343. 10 indexed citations

Zheng, Lianmin, Wu Zhao, Cody Hao Yu, et al.. (2020). Ansor: Generating high-performance tensor programs for deep learning. 863–879. 24 indexed citations

Haj-Ali, Ameer, Nesreen K. Ahmed, Theodore L. Willke, et al.. (2019). Deep Reinforcement Learning in System Optimization.. arXiv (Cornell University). 2 indexed citations

Ben-Hur, Rotem, et al.. (2019). SIMPLER MAGIC: Synthesis and Mapping of In-Memory Logic Executed in a Single Row to Improve Throughput. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 39(10). 2434–2447. 76 indexed citations

Haj-Ali, Ameer, et al.. (2019). Supporting the Momentum Training Algorithm Using a Memristor-Based Synapse. IEEE Transactions on Circuits and Systems I Regular Papers. 66(4). 1571–1583. 12 indexed citations

Huang, Qijing, Ameer Haj-Ali, William S. Moses, et al.. (2019). AutoPhase: Compiler Phase-Ordering for HLS with Deep Reinforcement Learning. 308–308. 16 indexed citations

Haj-Ali, Ameer, Rotem Ben-Hur, Nimrod Wald, Ronny Ronen, & Shahar Kvatinsky. (2018). Not in Name Alone: A Memristive Memory Processing Unit for Real In-Memory Processing. IEEE Micro. 38(5). 13–21. 29 indexed citations

Haj-Ali, Ameer, Rotem Ben-Hur, Nimrod Wald, Ronny Ronen, & Shahar Kvatinsky. (2018). IMAGING: In-Memory AlGorithms for Image processiNG. IEEE Transactions on Circuits and Systems I Regular Papers. 65(12). 4258–4271. 39 indexed citations

10.

Haj-Ali, Ameer, Rotem Ben-Hur, Nimrod Wald, & Shahar Kvatinsky. (2018). Efficient Algorithms for In-Memory Fixed Point Multiplication Using MAGIC. Zenodo (CERN European Organization for Nuclear Research). 1–5. 53 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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