Dr. Nadeem Tariq Beigh | Bio-Inspired Robot Design | Best Researcher Award

Khalifa University | United Arab Emirates

Dr. Nadeem Tariq Beigh is an Indian Researcher and postdoctoral fellow at the smart and intelligent sensors lab, department of mechanical and nuclear engineering, Khalifa University, Abu Dhabi. With a Ph.d. in electrical engineering from the Indian Institute of Technology Delhi, he has established himself as a rising scholar in sustainable sensing, self-powered systems, mems/nems, and energy harvesting. His research emphasizes the design and development of dual piezoelectric/triboelectric nanocomposites, micro/nano energy harvesters, and intelligent sensor systems integrated with machine learning for smart health care and industry 5.0 applications. Dr. Beigh has previously served as a research fellow at nanyang technological university, singapore, and a research assistant at iit delhi, contributing to several high-impact projects funded by dst, Bio-Inspired Robot Design fit, and international collaborations. He has authored 33 research documents, accumulated 239 citations from 152 scholarly works, and holds an h-index of 8, reflecting his growing influence in advanced materials and micro-energy systems research. His interdisciplinary expertise bridges electrical, mechanical, and materials engineering, driving innovations in sustainable, flexible, and intelligent sensor technologies that advance the frontiers of smart electronics and self-powered devices.

Profiles: Scopus | Orcid

Featured Publications

Beigh, N. T., & Alcheikh, N. (2025, October 8). Vapor-induced porosity in graphene/PDMS: A scalable route to high-performance pressure sensors. Microsystems & Nanoengineering.

Amara, H., Beigh, N. T., & Alcheikh, N. (2025, September 17). Smart resonant micro-sensor and micro-actuator: High-performance, wide-range bi-axial magnetic sensitive/insensitive micro-device for multifunctional sensing applications. Microsystems & Nanoengineering.

Alcheikh, N., Amara, H., & Beigh, N. T. (2025, May 5). Smart resonant micro-sensor and micro-actuator: High-performance, wide-range bi-axial magnetic sensitive/insensitive micro-device for multifunctional sensing applications.

Singh, S., Beigh, N. T., Gupta, P., Mallick, D., & Goswami, A. (2025, April). Polarity-dependent surface charge retention on CYTOP fluoropolymer for durable TENG applications. Applied Materials Today.

Beigh, N. T. (2025, March 19). High-performance MEMS magnetic sensor based on a smart tunable resonator. In Proceedings of the 2025 IEEE 38th International Conference on Micro Electro Mechanical Systems (MEMS). IEEE.

Ms. Tamanna | Neural Networks for Robot Control | Best Researcher Award

Goethe University, Frankfurt | Germany

Tamanna is a Ph.d. researcher at Goethe University, Frankfurt, Germany, specializing in geochemistry with a focus on integrating data science and machine learning into geo-scientific research. Her work aims to bridge the gap between traditional geoscience and modern computational methodologies by leveraging data-driven approaches to analyze complex geochemical systems. She holds a bs-ms degree in earth and environmental sciences from the Indian institute of science education and research, Bhopal. her expertise spans elemental and isotopic geochemistry, geospatial analysis, statistical modeling, and predictive analytics for geochemical processes. She is proficient in programming and data visualization using python, Neural Networks for Robot Control, matlab, qgis, and arcgis. Tamanna has authored two research documents with approximately one citation and an h-index of 1 for those publications; overall, her author-level record includes 99 citations and an h-index of 6, according to google scholar. Beyond her technical skills, she is actively involved in interdisciplinary research that combines quantitative methods, laboratory work, and field investigations to enhance the understanding of earth’s chemical evolution. fluent in english and hindi, with working knowledge of german, she represents the next generation of data-driven geoscientists.

Profile: Orcid

Featured Publications

Tamanna, Hezel, D. C., & Marschall, H. R. (2025, October). MRMinerals and MineralTD: Machine‐Readable Mineral Formula and Compositions Data Set for Data‐Driven Research. Geoscience Data Journal.

Tamanna, Hezel, D. C., Srivastava, N., & Faber, J. (2025, August 13). Using machine learning for automatic rock classification. American Mineralogist.