Ms. Preeti Shakya | Gas Sensor | Best Researcher Award

Posted on by ScienceFather

Ms. Preeti Shakya | Gas Sensor | Best Researcher Award 

Ms. Preeti Shakya, Malaviya National Institute of Technology Jaipur, India

Preeti Shakya is a dedicated researcher in nanotechnology, currently affiliated with the Materials Research Centre at Malaviya National Institute of Technology (MNIT) Jaipur. She specializes in nanoscale materials and device design, with a particular focus on gas sensor development using MEMS technology and advanced 2D materials. Her research expertise spans synthesis and characterization of nanomaterials such as graphene oxide (GO), reduced graphene oxide (rGO), MoS₂, MoSe₂, WSe₂, and CNT-based composites. Proficient in advanced characterization techniques including FTIR, UV-Vis spectroscopy, BET surface area measurement, FE-SEM, HR-TEM, and XPS, she actively contributes to the development of next-generation sensing devices. Preeti holds a B.Tech in Electronics and Communication Engineering from Rajasthan Technical University, an M.Tech in Nanotechnology from University College of Engineering, RTU Kota, and is pursuing a Ph.D. at MNIT Jaipur. Her research interests extend to gas sensors, supercapacitors, batteries, nanofabrication, and the development of novel intelligent material systems. Passionate about advancing gas sensor technology, she is committed to creating innovative solutions that have a lasting impact on the field.

Professional Profile:

ORCID

SCOPUS

Summary of Suitability for Best Researcher Award  

Preeti Shakya demonstrates a strong background in nanotechnology, particularly in the development of gas sensors using MEMS technology and advanced nanomaterials. Her expertise in synthesis, fabrication, and characterization of nanoscale materials, along with her proficiency in advanced research software and instrumentation, makes her a strong contender for the Best Researcher Award.

📚 Education

  • 🎓 Doctor of Philosophy (Ph.D.) – Materials Research Centre, Malaviya National Institute of Technology Jaipur (CGPA: 8.1)
  • 🎓 M.Tech (Nanotechnology) – University College of Engineering, RTU Kota (79%)
  • 🎓 B.Tech (Electronics and Communication Engineering) – Rajasthan Technical University (75.75%)
  • 🏫 All India Senior Secondary School Examination (2011) – R.B.S.E (72.92%)
  • 🏫 All India Secondary School Examination (2009) – C.B.S.E (61.61%)

💼 Work Experience

🔬 Nanotechnology Researcher – Specializing in:

  • Gas sensor development using MEMS technology
  • Synthesis of nanomaterials (GO, rGO, MoS₂, MoSe₂, WSe₂, CNT, rGO-CNT composites)
  • Electronic devices (Gas Sensors, Supercapacitors, Batteries)
  • Advanced characterization techniques (FTIR, UV-Vis, FE-SEM, HR-TEM, XPS, Raman spectroscopy)
  • Nanofabrication & research instrumentation development

🏆 Achievements, Awards & Honors

🌟 Recognized researcher in nanotechnology with expertise in advanced materials
🏅 Published research in gas sensors and sensing materials
🎖️ Contributions to MEMS-based gas sensor development using 2D materials
🏆 Active participation in national & international research projects

Publication Top Notes:

Charge storage kinetics of interconnected MnO<sub>2</sub> nano-needles/reduced graphene oxide composite for high energy density quasi-solid-state sodium ion asymmetric supercapacitor

Unraveling the Pseudocapacitive Charge Storage Mechanism of NiCo<sub>2</sub>O<sub>4</sub> Nanoflakes for Advanced Quasi Solid-State Hybrid Supercapacitor

Electrochemical Study of Reduced Graphene Oxide for Supercapacitor Application

Exploring Eco-friendly Nanocellulose-Based Hydrogel Membranes as Flexible and Biocompatible Electrolyte in Supercapacitors

Ultrathin and Flexible Gas Sensor Based on Monolayer Graphene for Environmental Monitoring

 

Prof. Dr. Weidong Jiao | Smart Detection | Best Researcher Award

Posted on by ScienceFather

Prof. Dr. Weidong Jiao | Smart Detection | Best Researcher Award 

Prof. Dr. Weidong Jiao, Zhejiang Normal University, China

Dr. Weidong Jiao was born in Wafangdian, Liaoning, China, in 1970. He received his B.E. and M.E. degrees in Safety Engineering and Mechanical Engineering from Gansu University of Technology in 1992 and 2001, respectively, and earned his Ph.D. in Mechanical Engineering from Zhejiang University in 2004. From 2004 to 2009, he served as a Professor in the Mechanical Engineering Department at Jiaxing University. Since 2013, he has been a Professor at the School of Engineering, Zhejiang Normal University. Dr. Jiao has authored over 100 research articles and holds approximately 20 invention patents. His research focuses on smart testing and signal processing, mechanical dynamics, and condition monitoring and fault diagnosis of mechanical equipment. He also serves as an Editor for the Journal of Vibration, Measurement & Diagnosis.

Professional Profile:

SCOPUS

Summary of Suitability for Best Researcher Award – Prof. Weidong Jiao

Prof. Weidong Jiao is a highly qualified candidate for the Best Researcher Award, based on his extensive contributions to mechanical engineering, fault diagnosis, and intelligent signal processing. His strong research background, innovative work, and leadership in academia make him a worthy contender for this prestigious recognition.

🎓 Education:

  • B.E. in Safety Engineering – Gansu University of Technology, Lanzhou (1992)
  • M.E. in Mechanical Engineering – Gansu University of Technology, Lanzhou (2001)
  • Ph.D. in Mechanical Engineering – Zhejiang University, Hangzhou (2004)

💼 Work Experience:

  • Professor, Mechanical Engineering Department, Jiaxing University (2004–2009)
  • Professor, School of Engineering, Zhejiang Normal University (Since 2013)

🏆 Achievements & Contributions:

  • 📚 Published over 100 research articles
  • 🔬 Invented approximately 20 innovations
  • 🛠️ Expertise in smart testing, signal processing, mechanical dynamics, condition monitoring, and fault diagnosis
  • 📝 Editor of Journal of Vibration, Measurement & Diagnosis

🏅 Awards & Honors:

  • 🎖️ Recognized for contributions in mechanical engineering and diagnostics
  • 🏅 Honored for advancements in fault diagnosis and condition monitoring
  • 🔍 Acknowledged for outstanding research and academic contributions in mechanical dynamics

Publication Top Notes:

Compact multiphysics coupling modeling and analysis of self-excited vibration in maglev trains

Deep learning in industrial machinery: A critical review of bearing fault classification methods

Recursive prototypical network with coordinate attention: A model for few-shot cross-condition bearing fault diagnosis

Double attention-guided tree-inspired grade decision network: A method for bearing fault diagnosis of unbalanced samples under strong noise conditions

Cross-Conditions Fault Diagnosis of Rolling Bearing Based on Transitional Domain Adversarial Network