Chengbo Tian | Wearable Electronics | Research Excellence Award

Mr. Chengbo Tian | Wearable Electronics | Research Excellence Award

Nanjing University of Aeronautics and Astronautics | China

Chengbo Tian is a Ph.D. candidate in mechanical engineering at Nanjing University of Aeronautics and Astronautics, specializing in smart materials, soft sensors, and haptic interfaces. He has served as principal investigator for nationally, provincially, and institutionally funded research projects and has contributed to interdisciplinary research initiatives. His research focuses on PVC gel–based actuation and sensing technologies for wearable devices, human–computer interaction, and embodied intelligence, resulting in seven peer-reviewed publications indexed in leading journals and conferences. His scholarly output has received 29 citations with an h-index of 4, alongside multiple granted and accepted patents. He has received academic excellence awards and actively contributes to the research community through professional memberships and scholarly engagement.

Citation Metrics (Scopus)

29
20
16
12
8
4
0

Citations

29

Documents

7

h-index

4

Citations

Documents

h-index

View ResearchGate View Scopus Profile

Featured Publications

Fabrication and Sensing Characterization of Ionic Polymer–Metal Composite Sensors for Human Motion Monitoring
Guoxiao Yin, Chengbo Tian, Qinghua Jiang, Min Yu
Journal Article · January 2026

Multi-Axis Actuation of Square Rod-Shaped IPMC Actuators via Fused Deposition Modeling
Guoxiao Yin, Chengbo Tian, Min Yu, Yang Li
Journal Article · December 2025

Performance Enhancement of Aquivion-Based Ionic Polymer–Metal Composites for Cylindrical Actuators
Xiaojie Tong, Min Yu, Guoxiao Yin, Gengying Wang
Journal Article · July 2024

Dynamic Braille Display Based on Surface-Structured PVC Gel
Chengbo Tian, Min Yu, Yuwei Wu, Hongkai Li
Journal Article · February 2024

Dr. Swarup Ghosh | Energy Harvesting & Self-Powered Systems | Best Researcher Award

Dr. Swarup Ghosh | Energy Harvesting & Self-Powered Systems | Best Researcher Award

Assistant Professor | SR University | India

Dr. Swarup Ghosh is an Assistant Professor and Assistant Dean (Research) at the School of Computer Science and Artificial Intelligence, SR University, specializing in computational materials science, condensed matter physics, and AI-driven materials discovery. He earned his Ph.D. in Science from Jadavpur University with a focus on first-principles calculations, following an M.Sc. in Physical Sciences and a B.Sc. in Physics. Dr. Ghosh previously served as a Postdoctoral Research Associate at Jadavpur University and as a faculty member at Sammilani Mahavidyalaya, contributing to advanced computational materials research and student mentorship. His work spans density functional theory, molecular dynamics, many-body perturbation theory, electronic structure simulations, and machine-learning-enabled materials design, resulting in publications in high-impact journals and presentations at prestigious scientific forums. His research includes breakthroughs in 2D and nanomaterials, thermoelectrics, photovoltaics, spintronics, and catalytic systems, emphasizing data-centric scientific innovation. He has been honored with national research fellowships, merit-based academic distinctions, and awards for research excellence, while also serving as a reviewer for reputed international journals and participating in professional training programs and conferences. He maintains a strong scholarly impact, demonstrated by 245 citations, an h-index of 9, and an i10-index of 9, underscoring his growing influence in computational materials science and interdisciplinary research.

Profile: Google Scholar

Featured Publications

Swarup Ghosh*, Predicting photovoltaic efficiency of two-dimensional Janus materials for solar energy harvesting: A combined first-principles and machine learning study. Solar Energy Materials and Solar Cells, Accepted.

Swarup Ghosh*, First-principles study on structural, electronic, optical and photovoltaic properties of Sc₂C-based Janus MXenes for solar cell applications. Materials Today Communications, Accepted.

Swarup Ghosh, Predicting band gaps of ABN₃ perovskites: An account from machine learning and first-principles DFT studies. RSC Advances, Accepted.