Teg Alam

487 citations
30 papers · 232 · h-index 9

Impact in

Papers in

Teg Alam

28 papers receiving 221 citations

Peers

Teg Alam
Comparison fields: 5 of 75
  • Health Information Management 24
  • Neurology 36
  • Health Informatics 4
  • Management Science and Operations Research 30
  • Computer Networks and Communications 51
Replace Yadala Sucharitha with:
Yadala Sucharitha India
C. Rohith Bhat India
Mudita Uppal India
Hemn Barzan Abdalla China
Augusto Júnio Guimarães Brazil
D Rajeswari India
Nirmal Adhikari United Kingdom
Kiran Sree Pokkuluri India
Rishika Yadav India
T Devi. India
Teg Alam relative to Yadala Sucharitha India Yadala Sucharitha's profile →
Citations per field
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Yadala Sucharitha · 1×
Citations per year

Countries citing papers authored by Teg Alam

Since Specialization
Citations

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

Fields of papers citing papers by Teg Alam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Teg Alam, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Teg Alam Line = papers co-authored together Teg Alam links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202347
2 202333
3 202320
4 202218
5 202116
6 201916
7 202310
8 20229
9 20248
10 20237
11 20227
12 20235
13 20195
14 20214
15 20223
16 20193
17 20223
18 20213
19 20242
20 20242

About Teg Alam

Teg Alam is a scholar working on Management Science and Operations Research, Computer Networks and Communications, Artificial Intelligence, Electrical and Electronic Engineering and Control and Systems Engineering, having authored 30 papers that have together received 232 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (6 papers), Forecasting Techniques and Applications (5 papers), Optimization and Mathematical Programming (5 papers), Energy Efficient Wireless Sensor Networks (3 papers), Stock Market Forecasting Methods (3 papers), Energy Load and Power Forecasting (3 papers), Internet of Things and AI (3 papers) and Market Dynamics and Volatility (3 papers). The work is most often cited by research in Health Information Management (24 citations), Neurology (36 citations), Health Informatics (4 citations), Management Science and Operations Research (30 citations) and Computer Networks and Communications (51 citations). Teg Alam has collaborated with scholars based in Saudi Arabia, Pakistan and South Korea. Frequent co-authors include Amjad Rehman, Tanzila Saba, Khalid Haseeb, Ali AlArjani, Gwanggil Jeon, Faten S. Alamri, Muhammad Mujahid, Suliman Mohamed Fati, Jaime Lloret and Wejdan Deebani. Their work appears in journals such as Sustainability, IEEE Access, Urban Climate, Cognitive Computation and Indian Journal of Science and Technology.

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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