Question 1

Which countries lead Smart Systems and Machine Learning research?

Accepted Answer

By volume, India and Indonesia publish the most (1.4k and 136 works in 2022-now).

Question 2

Which institutions lead Smart Systems and Machine Learning research?

Accepted Answer

By volume in 2022-now, Saveetha University publishes the most Smart Systems and Machine Learning research, followed by SRM Institute of Science and Technology and Chitkara University.

Question 3

Who are the leading researchers in Smart Systems and Machine Learning?

Accepted Answer

The most-cited researchers publishing on Smart Systems and Machine Learning include Seyedali Mirjalili and Witold Pedrycz.

Question 4

Where is Smart Systems and Machine Learning research done?

Accepted Answer

The largest centres of Smart Systems and Machine Learning research in 2022-now are Chennai (India), Bengaluru (India), Dehra Dūn (India) and Coimbatore (India). Among places with at least 20 works in it, it is an unusually large share of all research in Dehra Dūn, Phagwāra and Vijayawada.

Question 5

Where is the best place to study Smart Systems and Machine Learning?

Accepted Answer

Among universities, judged by research, Mangalore University, Saveetha University and Lovely Professional University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

Question 6

Is Smart Systems and Machine Learning research growing?

Accepted Answer

Output in 2022-2025 was 166% higher than in 2018-2021, peaking in 2024. The fastest-growing topics are Smart Systems and Machine Learning.

Question 7

What are the most cited papers in Smart Systems and Machine Learning?

Accepted Answer

The most cited paper in Smart Systems and Machine Learning is "Artificial Intelligence (AI) applications for COVID-19 pandemic" (Raju Vaishya, Mohd Javaid, Ibrahim Haleem Khan et al., 2020), with 1,535 citations. Next come "Recommendation systems: Principles, methods and evaluation" (1,325) and "Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models" (1,187).