Nirav Bhatt | Analysis | Best Researcher Award

Dr. Nirav Bhatt | Analysis | Best Researcher Award

Associate Professor at CHARUSAT, India

Dr. Nirav H. Bhatt is an accomplished academic and researcher with a Ph.D. in AI/ML from CHARUSAT. He has over 15 years of experience in teaching, mentoring, and research. Dr. Bhatt has guided more than 50 students, both at the Master’s and Bachelor’s levels, and is recognized as a top-performing mentor by NPTEL. His research, which focuses on low-latency processing and data analytics, has been presented at prestigious international conferences and published in renowned journals. He has also conducted expert talks and seminars on big data and database systems at multiple institutions. Dr. Bhatt has received numerous awards, including recognition from AICTE and Texas Instruments, and has played a pivotal role in promoting NPTEL courses in regional languages. With technical expertise in machine learning, cloud computing, and data science, he continues to contribute significantly to both academia and industry.

Professional Profile 

Education

Dr. Nirav H. Bhatt has a strong academic foundation with a Ph.D. in AI/ML from CHARUSAT, completed in 2022. Prior to his doctorate, he earned a Master’s degree in Computer Engineering (M.E.C.E.) from DDU in 2009 with a score of 66.33%, and a Bachelor’s degree in Information Technology (B.E.I.T.) from Gujarat University in 2006, where he scored 63.76%. He also holds a Diploma in Information Technology (D.I.T.) from TEB, which he completed in 2003 with an impressive score of 71.62%. His academic journey reflects a consistent dedication to computer science and technology. Dr. Bhatt’s doctoral thesis focused on a novel approach for low-latency processing in stream data, further contributing to the field of AI and machine learning. His educational achievements are complemented by certifications such as Microsoft Certified MTA in Database Fundamentals, highlighting his expertise and ongoing commitment to professional growth.

Professional Experience

Dr. Nirav H. Bhatt has over 15 years of professional experience in academia and research. Since 2008, he has been a faculty member at Charotar University of Science and Technology (CHARUSAT), where he currently serves as the Head of the Department of AI-ML and an Associate Professor. During his tenure, Dr. Bhatt has significantly contributed to the development of the AI/ML curriculum and research programs. He has also held a position as an Assistant Professor at C. U. Shah College of Engineering and Technology for a year. Dr. Bhatt has played a pivotal role as a mentor, guiding over 50 students in computer science and receiving recognition as a top-performing mentor by NPTEL. Additionally, he has conducted expert talks, seminars, and online courses in areas such as big data analytics and database systems. His experience extends to industry training with leading organizations, strengthening his practical knowledge in machine learning, cloud computing, and data science.

Research Interest

Dr. Nirav H. Bhatt’s research interests primarily lie in the fields of Artificial Intelligence (AI), Machine Learning (ML), Big Data, and Data Science. His work focuses on developing innovative solutions for low-latency processing in stream data, with an emphasis on enhancing the efficiency and scalability of data-driven systems. Dr. Bhatt’s doctoral research, which introduced a novel approach to stream data processing, has contributed significantly to advancing the understanding of real-time data analytics. His expertise also extends to cloud platforms such as Google Cloud and AWS, where he explores the integration of machine learning algorithms in cloud environments to handle large-scale data processing. Additionally, he is passionate about data visualization, the application of AI in database systems, and the development of intelligent systems for big data analytics. His research is aimed at solving practical challenges in academia and industry, particularly in optimizing data processing and machine learning models for real-world applications.

Award and Honor

Dr. Nirav H. Bhatt has received numerous awards and honors in recognition of his contributions to academia and research. Notably, he has been awarded by AICTE and Texas Instruments for fostering collaboration between government, academia, and industry, particularly through his coordination of the “TI Embedded System Design using MSP430” MOOC in 2021. Dr. Bhatt has also been recognized for his consistent excellence as a mentor, earning the title of Top Performing Mentor by NPTEL for several consecutive years (2016–2020). His leadership in Swayam-NPTEL courses has garnered multiple accolades, including recognition for his translation work in regional languages for courses such as “Fundamentals of Database Systems” and “Programming in C.” Additionally, he was awarded Best Research Paper Presentation at the SSIC-2019 International Springer Conference and received multiple certifications for his contribution to the CHARUSAT NPTEL Local Chapter, achieving AAA and AA grades over several years. These awards highlight his dedication to education and research.

Conclusion

Dr. Nirav H. Bhatt is an exceptional candidate for the Best Researcher Award. His academic achievements, extensive contributions to the field of AI and ML, as well as his mentoring roles, distinguish him as a leader in both research and education. His awards, recognition by NPTEL, and commitment to research make him a deserving nominee. However, focusing on expanding his international collaborations and enhancing the practical impact of his research could propel him to even greater heights in the academic community. Based on his accomplishments and contributions, he shows a strong potential to receive the Best Researcher Award.

Publications Top Noted

  • Smart systems and IoT: Innovations in computing
    Authors: AK Somani, RS Shekhawat, A Mundra, S Srivastava, VK Verma
    Year: 2020
    Citation: 35
  • A survey on comparative study of wireless sensor network topologies
    Authors: J Soparia, N Bhatt
    Year: 2014
    Citation: 33
  • Performance comparison of different sorting algorithms
    Authors: P Prajapati, N Bhatt, N Bhatt
    Year: 2017
    Citation: 21
  • Ranking of classifiers based on dataset characteristics using active meta learning
    Authors: N Bhatt, A Thakkar, A Ganatra, N Bhatt
    Year: 2013
    Citation: 13
  • Survey and evolution study focusing comparative analysis and future research direction in the field of recommendation system specific to collaborative filtering approach
    Authors: A Patel, A Thakkar, N Bhatt, P Prajapati
    Year: 2019
    Citation: 11
  • An efficient approach for low latency processing in stream data
    Authors: N Bhatt, A Thakkar
    Year: 2021
    Citation: 10
  • A review of soft computing techniques for time series forecasting
    Authors: A Sanghani, N Bhatt, NC Chauhan
    Year: 2016
    Citation: 10
  • Survey on Anonymization in Privacy Preserving Data Mining
    Authors: F Presswala, A Thakkar, N Bhatt
    Year: 2015
    Citation: 7
  • Experimental Analysis on Processing of Unbounded Data
    Authors: N Bhatt, A Thakkar
    Year: 2019
    Citation: 6
  • Proceedings of the international conference on ismac in computational vision and bio-engineering 2018 (ismac-cvb)
    Authors: D Pandian, X Fernando, Z Baig, F Shi
    Year: 2019
    Citation: 6
  • A survey on issues of data stream mining in classification
    Authors: R Jani, N Bhatt, C Shah
    Year: 2018
    Citation: 6
  • Deep learning: a new perspective
    Authors: N Bhatt, N Bhatt, P Prajapati
    Year: 2017
    Citation: 6
  • Algorithm selection via meta-learning and active meta-learning
    Authors: N Bhatt, A Thakkar, N Bhatt, P Prajapati
    Year: 2020
    Citation: 5
  • Query expansion for effective retrieval from microblog
    Authors: S Patel, N Bhatt, C Shah
    Year: 2017
    Citation: 5
  • A survey of information retrieval on microblog
    Authors: S Patel, N Bhatt, C Shah
    Year: 2017
    Citation: 5

Prof. Dae-Geun Hong| Data-driven analysis and optimization Awards | Best Researcher Award

Prof. Dae-Geun Hong| Data-driven analysis and optimization Awards | Best Researcher AwardMr. AMBUDHI SHUKLA | Nitride Amplifier Awards | Best Researcher Award

Prof. Dae-Geun Hong , Pohang University of Science & Technology (POSTECH) , South Korea

Muhammad Hilal is a dedicated and accomplished academic professional with a strong background in physics and chemical engineering. Born on March 4, 1991, in Pakistan, he holds permanent residency in the Republic of Korea. Hilal’s academic journey includes earning a Bachelor of Science in Physics from Abdul Wali Khan University, followed by a Master of Sciences in Applied Physics from Ghulam Ishaq Khan Institute of Engineering Sciences and Technology (GIKI), and ultimately a Doctor of Philosophy (PhD) in Chemical Engineering from Dongguk University, Seoul, where he achieved an outstanding GPA of 4.21/4.50. His postgraduate research and teaching experience have been notably impactful, culminating in his current position as an Assistant Professor at Sejong University, Seoul, South Korea.

Hilal’s research interests span the synthesis of advanced materials such as 2D materials (MXene, Graphene, MoS2), metal oxides, and polymers, focusing on applications like wearable technology, gas sensing, and glucose monitoring. He has secured significant research funding from prestigious institutions like the National Research Foundation of Korea (NRF) and has received numerous awards recognizing his academic achievements, including Best Research Awards during his doctoral studies. Hilal’s career is characterized by a strong commitment to academic excellence, innovative research, and impactful teaching, making him a key contributor to the field of chemical engineering and materials science. 🌱

Professional Profile:

Scopus

Google Scholar

Orcid

Research Focus

Dr. Hilal’s research interests encompass the synthesis and characterization of advanced materials, including 2D materials like MXene, Graphene, and MoS2, as well as metal oxides and polymers. His work extends to the development of hybrid solar cells, electrochemical sensors for glucose and pH monitoring, gas sensors, and energy storage technologies such as supercapacitors and Zn Ion batteries.

Professional Experience

Currently serving as an Assistant Professor at Sejong University in Seoul, South Korea, Dr. Hilal is actively engaged in teaching undergraduate courses on semiconductor device processing and technology, alongside conducting cutting-edge research on 2D materials for wearable technology applications.

Previously, Dr. Hilal held positions as a Research Professor at Korea University and a Postdoctoral Researcher at Dongguk University, where he led research projects focused on nanomaterials for glucose and pH sensing, as well as the development of 2D materials for gas sensing technology.

Achievements and Grants

Dr. Hilal’s contributions have been recognized with prestigious awards, including the Best Research Award from Dongguk University. He has secured substantial research grants from the National Research Foundation of Korea (NRF) to support his innovative work in materials science and sensor technology.

Teaching Experience

With a passion for education, Dr. Hilal has mentored and taught undergraduate students in courses related to semiconductor technology, sensor electronics, and signal processing. His dedication to academic excellence is reflected in his previous roles as a Graduate Assistant at the GIK Institute, where he facilitated courses in mechanics and electricity & magnetism.

Muhammad Hilal is committed to advancing scientific knowledge, fostering innovation, and preparing the next generation of engineers and researchers in the field of chemical engineering and materials science. 🌱

Publication Top Notes:

Newly Design Porous/Sponge Red Phosphorus@Graphene and Highly Conductive Ni2P Electrode for Asymmetric Solid State Supercapacitive Device With …

Citation – 47

Significant improvement in the photovoltaic stability of bulk heterojunction organic solar cells by the molecular level interaction of graphene oxide with a PEDOT: PSS …

Citation – 45

A dual-functional flexible sensor based on defects-free Co-doped ZnO nanorods decorated with CoO clusters towards pH and glucose monitoring of fruit juices and human fluids

Citation – 26

Improving the conductivity of PEDOT: PSS to nearly 1 million S/m with graphene on an ITO-glass substrate

Citation – 23

Interface engineering of G-PEDOT: PSS hole transport layer via interlayer chemical functionalization for enhanced efficiency of large-area hybrid solar cells and their charge …

Citation – 23