Mohammad Belal | Policy Implications | Best Researcher Award

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Mr. Mohammad Belal | Policy Implications | Best Researcher Award

 Aalto University | Finland

Publication Profile

Google Scholar

Biography of Mr. Mohammad Belal 👨‍💻

👨‍💻 Passionate Data Science & Machine Learning Enthusiast

Mohammad Belal is a driven researcher and technology enthusiast specializing in Data Science, Machine Learning, and Natural Language Processing (NLP). With a keen interest in solving social-centric problems, he is currently pursuing his Doctoral Research at Aalto University in Finland (2023-2027). His academic journey has been marked by a constant desire to understand and leverage data for impactful solutions.

🎓 Education

Mohammad holds a Master’s in Computer Application (MCA) from Aligarh Muslim University (AMU), where he achieved a remarkable CGPA of 9.32 and was among the top 3 in his class. He was awarded the prestigious University Merit Scholarship and actively contributed as a member of the Training and Placement Team. Prior to this, he completed his Bachelor’s in Computer Application (BCA), achieving a CGPA of 7.66 while working on a cab-hiring web application project.

🔬 Research Interests and Projects

Mohammad’s research interests revolve around exploring the intersection of technology and society. His ongoing research at Aalto University focuses on the association between internet usage and psychological well-being. He has previously worked on several impactful projects, including a study of social media usage by regional and national journalists with The News Lab at IIITD, and a sentiment analysis project during Colombia’s national strike using NLP techniques. His work on clustering the neighborhoods of Toronto based on cost of living using machine learning is a testament to his practical skills in data science.

💼 Professional Experience

his professional career, Mohammad has gained extensive experience in data science and business analysis. As a Data Scientist at TCNS Clothing Ltd., he worked on predictive modeling, sales reporting automation, and data-backed decision-making for marketing and sales. He also worked as a Data Analyst for CraftBazar, where he assisted in generating insights from sales data. Additionally, Mohammad has experience as a Web Developer at The Wings of Desire, where he managed the company website and supported event organization, as well as a Content Creator for UC Browser.

🗣️ Workshops and Conferences

Mohammad has actively participated in various workshops and conferences to stay updated in his field. He attended the Responsible AI for Peace and Security conference organized by the United Nations in 2024 and participated in discussions on the ethics of disruptive technology at IIITD Delhi. He has also attended workshops on Data Science using Python and Cyber Security, further strengthening his skills in these areas.

🎓 MOOCs and Certifications

To further his expertise, Mohammad has earned numerous online certifications in data science and machine learning, including a Data Science Professional Certificate from IBM and Neural Networks and Deep Learning from DeepLearning.AI. He has also completed specialized courses in Statistics for Data Science with Python and Computational Thinking for Problem Solving from Coursera and the University of Pennsylvania.

🏆 Awards & Achievements

Throughout his academic journey, Mohammad has been recognized for his outstanding performance. He received the Merit-cum-Means Scholarship from the Indian Government for three consecutive years during his Master’s program. His academic excellence was further acknowledged with a University Merit Scholarship at AMU.

📚 Top Notes Publications

Leveraging ChatGPT as Text Annotation Tool for Sentiment Analysis

    • Authors: M Belal, J She, S Wong

    • Journal: arXiv preprint

    • Year: 2023

Islamophobic Tweet Detection Using Transfer Learning

    • Authors: M Belal, G Ullah, AA Khan

    • Journal: 2022 International Conference on Connected Systems & Intelligence (CSI)

    • Year: 2022

Rapid Face Mask Detection and Person Identification Model Based on Deep Neural Networks

    • Authors: AA Khan, M Belal, G Ullah

    • Journal: International Conference on IoT, Intelligent Computing and Security: Select

    • Year: 2023

Indian Healthcare Infrastructure Analysis During COVID-19 Using Twitter Sentiments

    • Authors: N Fatima, M Belal, K Kumar, R Sadaf

    • Journal: 2022 International Conference on Decision Aid Sciences and Applications

    • Year: 2022

Adapting to Change and Transforming Crisis into Opportunity-Behavioral and Policy Shifts in Sustainable Practices Post-Pandemic

    • Authors: E Zaidan, L Cochrane, M Belal

    • Journal: Heliyon

    • Year: 2025

Laxmi Kantham Durgam | Deep Learning | Best Scholar Award

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Mr. Laxmi Kantham Durgam | Deep Learning | Best Scholar Award

National Institute of Technology Warangal | India

Publication Profile

Google Scholar

🧑‍🎓 Education

Mr. Laxmi Kantham Durgam is currently pursuing his PhD in Electrical Engineering at National Institute of Technology Warangal, Telangana, India (2021–Present). His research focuses on Speech Recognition, Age and Gender Identification from Speech, and the application of Machine Learning and Deep Learning techniques. He is also a Visiting Researcher at the Technical University of Kosice, Slovakia, as part of the NSP SAIA Fellowship (2024). Mr. Durgam holds an M.Tech in Digital Systems and Computer Electronics from Jawaharlal Nehru Technological University, Hyderabad (2017–2020) and a B.Tech in Electronics and Communication Engineering from the same institution (2011–2015).

📚 Publications

Mr. Durgam has contributed to various publications in the fields of speech processing, deep learning, and edge computing. His notable works include papers on speaker age and gender classification, real-time age estimation from speech, and dress code detection using MobileNetV2 on NVIDIA Jetson Nano. He has been published in journals like Computing and Informatics and Journal of Signal Processing Systems, as well as conferences like ICIT-2023 in Kyoto, Japan.

🔬 Research Experience

Since 2021, Mr. Durgam has been a PhD Research Scholar at NIT Warangal, where his research includes projects on real-time age identification from speech using Edge devices like Jetson Nano and Arduino Nano BLE. He has also worked on real-time projects like vehicle logo classification using Edge Impulse and dress code detection using MobileNetV2. His work is focused on implementing Machine Learning and Deep Learning algorithms for practical, real-time applications.

🏆 Fellowships and Awards

Mr. Durgam was awarded the NSP SAIA Fellowship (2024), an international mobility program funded by the European Union, allowing him to collaborate with the KEMT, Faculty of Electrical Engineering and Informatics at the Technical University of Kosice, Slovakia. He also received the MHRD Fellowship for his PhD from the Government of India. He has passed the NITW PhD Entrance and the GATE exam (2016), and he received financial support as an undergraduate student from the Andhra Pradesh State Government.

📖 Academic Achievements

Mr. Durgam has significantly contributed to the academic environment through his role in conducting hands-on programming sessions in Machine Learning, Deep Learning, and AI applications. He has mentored students in Faculty Development Programs (FDPs), summer and winter internships, and workshops at various institutions. His workshops have reached institutions such as BRIT Vijayanagaram and VBIT Hyderabad, where he focused on advanced deep learning applications on Edge devices.

💻 Technical Skills

Mr. Durgam is highly skilled in programming with languages like Python, C, Embedded C, Matlab, and frameworks such as Keras, TensorFlow, and OpenCV. He has experience working with edge devices like Jetson Nano, Jetson Xavier, and Arduino Nano BLE 33 Sense. His expertise also extends to Machine Learning, Deep Learning, Computer Vision, and Digital Signal Processing.

🧑‍🏫 Teaching and Mentoring

Mr. Durgam has been an active Teaching Assistant and mentor at NIT Warangal, where he has assisted in courses like Artificial Intelligence, Machine Learning, and Digital Signal Processing. He has guided B.Tech students in lab sessions, and his expertise in AI/ML has also been shared through guest lectures and faculty development programs.

🚀 Key Projects

Some of Mr. Durgam’s key projects include age and gender estimation from speech using MFCC features, dress code detection with MobileNetV2 on Edge devices, and real-time object detection using deep learning algorithms. He has successfully developed these applications on devices like Jetson Nano and Arduino Nano BLE for real-time deployment.

🌍 Professional Engagement

Mr. Durgam is an IEEE Student Member and an active participant in IEEE Young Professionals. He has been involved in organizing and coordinating internships, workshops, and training programs related to AI/ML and Deep Learning at NIT Warangal and other institutes. He is passionate about bridging the gap between academia and real-world applications, particularly through Edge Computing and AI deployment.

📚 Top Notes Publications 

Real-Time Dress Code Detection using MobileNetV2 Transfer Learning on NVIDIA Jetson Nano

    • Authors: LK Durgam, RK Jatoth

    • Journal: Proceedings of the 2023 11th International Conference on Information

    • Year: 2023

Real-Time Classification of Vehicle Logos on Arduino Nano BLE using Edge Impulse

    • Authors: D Abhinay, SV Vighnesh, LK Durgam, RK Jatoth

    • Journal: 2023 4th International Conference on Signal Processing and Communication

    • Year: 2023

Age Estimation based on MFCC Speech Features and Machine Learning Algorithms

    • Authors: LK Durgam, RK Jatoth

    • Journal: IEEE International Symposium on Smart Electronic Systems (iSES)

    • Year: 2022

Age Estimation from Speech Using Tuned CNN Model on Edge Devices

    • Authors: LK Durgam, RK Jatoth

    • Journal: Journal of Signal Processing Systems

    • Year: 2024

Age and Gender Estimation from Speech using various Deep Learning and Dimensionality Reduction Techniques

    • Authors: MPJJ Laxmi Kantham Durgam*, Ravi Kumar Jatoth, Daniel Hladek, Stanislav Ondas

    • Journal: Acoustics and Speech Processing at Speech analysis synthesis, Institute of

    • Year: 2024

 

Chunyu Liu | Neuroscience Data Analysis | Women Researcher Award

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Dr. Chunyu Liu | Neuroscience Data Analysis | Women Researcher Award

North China Electric Power University | China

PUBLICATION PROFILE

Google Scholar

Dr. Chunyu Liu⚡🌍

INTRODUCTION 🧠💡

Dr. Chunyu Liu is a Lecturer at North China Electric Power University, specializing in machine learning, neural decoding, and visual attention. Her research delves into the integration of AI and brain science, focusing on neural signals like MEG and fMRI to gain insights into cognitive functions and develop new AI theories. Her work bridges the gap between artificial intelligence and neuroscience, contributing to both fields in groundbreaking ways. 🌟

EARLY ACADEMIC PURSUITS 🎓📚

Dr. Liu’s academic journey began with a B.S. degree in Mathematics and Applied Mathematics from Henan Normal University. She went on to earn an M.S. degree in Applied Mathematics from Northwest A&F University, and a Ph.D. in Computer Application Technology from Beijing Normal University. These formative years built the foundation for her expertise in the intersection of computer science and cognitive science. 🔬

PROFESSIONAL ENDEAVORS 💼🔍

After completing postdoctoral training at Peking University, Dr. Liu embarked on her career as a lecturer at North China Electric Power University. In this role, she has led multiple research projects, mentored students, and contributed to the advancement of neural decoding and cognitive computing. Her professional endeavors focus on integrating theoretical AI methods with practical neuroscience. 🚀

CONTRIBUTIONS AND RESEARCH FOCUS ON Neuroscience Data Analysis 🧑‍🔬🔎

Dr. Liu’s research is primarily concerned with the neural mechanisms underlying object recognition, emotion, and visual attention. By combining AI theories with psychological experimental paradigms, she works with multi-modal neural signals like MEG and fMRI to better understand cognitive functions. Her work provides critical insights into how the brain processes information and leads to the development of advanced AI systems. 🤖🧠

IMPACT AND INFLUENCE 🌍📈

Dr. Liu has made substantial contributions to the fields of cognitive computing and neural decoding. Her innovative research models decode stimuli and cognitive states from brain activity, advancing our understanding of the human brain. Her influence extends globally, as her work is not only used to better understand cognition but also informs the development of intelligent AI systems. 🌐✨

ACADEMIC CITATIONS AND PUBLICATIONS 📑📊

With over 10 academic papers, including six SCI-indexed publications as the first author, Dr. Liu’s work has earned wide recognition. Noteworthy papers include “S-TBN: A New Neural Decoding Model to Identify Stimulus Categories from Brain Activity Patterns” in IEEE Transactions on Neural Systems and Rehabilitation Engineering and “Decoding Six Basic Emotions from Brain Functional Connectivity Patterns” in Science China Life Sciences. Her research continues to shape future studies in the fields of cognitive computing and AI. 📝🏆

HONORS & AWARDS 🏅🏆

Dr. Liu has received numerous prestigious awards and recognition for her pioneering work in cognitive computing and brain science. These accolades reflect the high regard for her contributions to neural decoding and her influence on both the neuroscience and AI communities. 🎖️

LEGACY AND FUTURE CONTRIBUTIONS HIGHLIGHT 🏛️🌱

Dr. Liu’s future research promises to continue pushing the boundaries of both cognitive science and artificial intelligence. By developing more sophisticated neural decoding models, she aims to further our understanding of the brain’s cognitive processes while advancing the development of AI systems that can more effectively interact with and understand human cognition. Her legacy will be one of innovation, discovery, and progress. 🌟

FINAL NOTE 🔮💭

As Dr. Liu continues her research, she is poised to make lasting contributions to both artificial intelligence and neuroscience. Her work will further bridge the gap between these fields, and her innovations will have a profound impact on how we understand human cognition and develop intelligent systems. Her legacy is one of groundbreaking interdisciplinary research. 🔮

 TOP NOTES PUBLICATIONS 📚

Decoding six basic emotions from brain functional connectivity patterns
    • Authors: C Liu, Y Wang, X Sun, Y Wang, F Fang
    • Journal: Science China Life Sciences
    • Year: 2023
Decoding disparity categories in 3-dimensional images from fMRI data using functional connectivity patterns
    • Authors: C Liu, Y Li, S Song, J Zhang
    • Journal: Cognitive Neurodynamics
    • Year: 2020
Categorizing objects from MEG signals using EEGNet
    • Authors: R Shi, Y Zhao, Z Cao, C Liu, Y Kang, J Zhang
    • Journal: Cognitive Neurodynamics
    • Year: 2021
Rapidly decoding image categories from MEG data using a multivariate short-time FC pattern analysis approach
    • Authors: C Liu, Y Kang, L Zhang, J Zhang
    • Journal: IEEE Journal of Biomedical and Health Informatics
    • Year: 2020
Image categorization from functional magnetic resonance imaging using functional connectivity
    • Authors: C Liu, S Song, X Guo, Z Zhu, J Zhang
    • Journal: Journal of Neuroscience Methods
    • Year: 2018
s-TBN: A new neural decoding model to identify stimulus categories from brain activity patterns
    • Authors: C Liu, B Cao, J Zhang
    • Journal: IEEE Transactions on Neural Systems and Rehabilitation Engineering
    • Year: 2024

Xiaobin Ling | Data Science | Best Researcher Award

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Dr. Xiaobin Ling | Data Science | Best Researcher Award

UMass Medical School | United States

Publication Profile

Orcid

👨‍🔬 Summary

Dr. Xiaobin Ling is a Postdoctoral Researcher at the RNA Therapeutics Institute, UMass Medical School, specializing in lncRNA structure and Cryo-EM. With a Ph.D. in Structural Biology from Fudan University, his work focuses on the mechanisms of RNA structures, molecular biology, and biophysics, with a strong emphasis on cryo-electron microscopy (Cryo-EM).

🧑‍🏫 Current Position

Postdoctoral Researcher
RNA Therapeutics Institute, UMass Medical School (2024–Present)

  • Research on RNA structures, particularly long non-coding RNAs (lncRNAs).
  • Focus on Cryo-EM techniques to elucidate RNA structural dynamics.

🎓 Education

Ph.D. in Structural Biology (2017–2023)
Fudan University, Shanghai, China

  • Research: Mechanisms and regulation of microRNA biogenesis and lncRNA structure.
    Master’s in Chemical Biology (2013–2016)
    Xiamen University, Xiamen, China
  • Research: Drug mechanisms targeting nuclear receptors.
    B.Sc. in Biotechnology (2008–2013)
    Jinggangshan University, Ji’an, China

💼 Professional Experience

Senior Research Assistant (2022–2023)
Cryo-EM Core Facility, Sichuan University, China

  • Managed operations for Titan Krios G3i, Talos Arctica G2, and JEOL1400 microscopes.
  • Applied Cryo-EM techniques for structural research.

Structural Biologist Researcher (2021–2022)
Runjia Pharmaceutical Technology Co., Ltd, Shanghai, China

  • Investigated ADAR inhibitors and their functions.

Research Assistant (2016–2017)
South University of Science and Technology of China, Shenzhen, China

  • Focused on microRNA biogenesis and its regulation.

📚 Academic Publications

Dr. Ling has authored numerous peer-reviewed publications in top journals, including Nature, Nature Structural & Molecular Biology, and Cell Reports. Notable works include:

  1. Cryo-EM structure of a natural RNA nanocage (Nature, 2025)
  2. Circularly permuted group II introns and their mechanisms (Nature Structural & Molecular Biology, 2025)
  3. Human telomeric G-quadruplex DNA binding (BBA – Gene Regulatory Mechanisms, 2023)
  4. ADAR inhibitors and their function (prepint, 2022)

💡 Technical Skills

  • Cryo-EM: Expertise in cryo-electron microscopy for RNA and protein structural analysis.
  • RNA Structure Analysis: Proficient in the study of RNA folding and dynamics.
  • Molecular Biology: Strong background in RNA and DNA manipulation, including G-quadruplexes and microRNA biogenesis.
  • Computational Tools: Skilled in structural bioinformatics and molecular modeling.

👨‍🏫 Teaching Experience

Dr. Ling has contributed to academic training and mentoring at multiple institutions, particularly in structural biology and RNA research.

🔬 Research Interests On Data Science

  • Structural biology of RNA molecules, focusing on lncRNAs and their roles in gene regulation.
  • Application of Cryo-EM to explore the structural dynamics of RNA and protein complexes.
  • Investigating RNA-related therapeutic strategies, including the use of RNA nanocages and RNA-based drug delivery systems.

 📚 Top Notes Publications

Cryo-EM structure of a natural RNA nanocage
    • Authors: Xiaobin Ling*, Dmitrij Golovenko, Jianhua Gan, Jinbiao Ma*, Andrei A. Korostelev*, Wenwen Fang*
    • Journal: Nature
    • Year: 2025 (accepted)
Structures of a natural circularly permuted group II intron reveal mechanisms of branching and back-splicing
    • Authors: Xiaobin Ling*, Yuqi Yao*, Jinbiao Ma*
    • Journal: Nature Structural & Molecular Biology
    • Year: 2025
The mechanism of UP1 binding and unfolding of human telomeric G-quadruplex DNA
    • Authors: Xiaobin Ling#, Yuqi Yao#, Lei Ding, Jinbiao Ma*
    • Journal: Biochimica et Biophysica Acta (BBA) – Gene Regulatory Mechanisms
    • Year: 2023
DHX9 resolves G-quadruplex condensation to prevent DNA double-strand breaks
    • Authors: Juan Chen#, Xiaobin Ling#, Youshan Zhao#, Sheng Li, Manan Li, Hailian Zhao, Xianguang Yang, Chun-kang Chang, Jinbiao Ma*, Yuanchao Xue*
    • Journal: preprint
    • Year: 2022
Phytochrome B inhibits the activity of phytochrome-interacting factor 7 involving phase separation
    • Authors: Yu Xie, Wenbo Liu, Wenjing Liang, Xiaobin Ling, Jinbiao Ma, Chuanwei Yang, Lin Li*
    • Journal: Cell Reports
    • Year: 2023
Modular characterization of SARS-CoV-2 nucleocapsid protein domain functions in nucleocapsid-like assembly
    • Authors: Yan Wang#, Xiaobin Ling#, Jian Zou, Chong Zhang, Bingnan Luo, Yongbo Luo, Xinyu Jia, Guowen Jia, Minghua Zhang, Junchao Hu, Ting Liu, Yuanfeiyi Wang, Kefeng Lu, Dan Li, Jinbiao Ma*, Cong Liu*, Zhaoming Su*
    • Journal: Molecular Biomedicine
    • Year: 2023

 

Qiang Yue | Big Data Analytics | Global Data Innovation Recognition Award

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Prof. Qiang Yue | Big Data Analytics | Global Data Innovation Recognition Award

College of Water Conservancy and Civil Engineering, Shandong Agricultural University | China

Publication Profile

Scopus

PROF. QIANG YUE – A LEADER IN BIG DATA ANALYTICS AND WATER CONSERVANCY RESEARCH 🌐💧

INTRODUCTION 🌟

Prof. Qiang Yue is a prominent academic and researcher at the College of Water Conservancy and Civil Engineering, Shandong Agricultural University, China. Specializing in Big Data Analytics, Prof. Yue has contributed significantly to the field of water conservancy and civil engineering, focusing on the integration of data science and engineering for sustainable solutions. His interdisciplinary approach is helping shape the future of water management systems and infrastructure development.

EARLY ACADEMIC PURSUITS 🎓

Prof. Yue’s academic journey began with a strong foundation in civil engineering and water conservancy. After completing his undergraduate degree, he pursued advanced studies in related fields, obtaining a Master’s and PhD with a focus on big data analytics and its applications in civil engineering and water resources management. His rigorous academic training set the stage for his future contributions to both engineering and data science.

PROFESSIONAL ENDEAVORS 💼

As a faculty member at Shandong Agricultural University, Prof. Yue has played a key role in developing research programs and teaching in the fields of water conservancy and civil engineering. His work bridges the gap between traditional engineering methods and modern data analytics, incorporating advanced technologies like machine learning and AI in the optimization of water resources and infrastructure planning. Prof. Yue has also collaborated with national and international research institutions, contributing to various large-scale projects focused on water management and sustainable civil engineering practices.

CONTRIBUTIONS AND RESEARCH FOCUS ON Big Data Analytics 🔬

Prof. Yue’s research interests lie at the intersection of Big Data Analytics and civil engineering, particularly in the optimization of water conservancy systems. His work focuses on the application of machine learning algorithms, predictive analytics, and real-time data collection to improve the efficiency of water resource management, flood control, and infrastructure development. Additionally, his research aims to enhance the sustainability of civil engineering projects through data-driven decision-making, making significant strides toward smart cities and sustainable environmental practices.

IMPACT AND INFLUENCE 🌍

Prof. Yue’s research has had a profound impact on both the academic community and the industry. His innovative use of Big Data Analytics in water conservancy and civil engineering has transformed how data is used in real-time decision-making, helping optimize water resource management on a large scale. His work influences policy decisions, infrastructure development projects, and sustainability strategies, improving water conservation efforts in China and beyond. Prof. Yue has also mentored a generation of engineers and researchers, sharing his knowledge and experience to cultivate future leaders in the field.

ACADEMIC CITATIONS AND PUBLICATIONS 📚

Prof. Yue has authored numerous papers in high-impact journals, with a focus on Big Data Analytics and its applications in water management and civil engineering. His publications cover topics such as predictive modeling, real-time water quality monitoring, and optimization of water distribution systems using machine learning. His research is widely cited in the academic community, reflecting the significance of his work in the integration of Big Data with engineering practices.

HONORS & AWARDS 🏆

Prof. Yue’s exceptional contributions to Big Data Analytics and water conservancy have earned him various honors and awards, including:

  • Best Paper Award, International Conference on Water Management and Engineering (2022)
  • Outstanding Researcher Award, Shandong Agricultural University (2021)
  • Excellence in Teaching Award, College of Water Conservancy and Civil Engineering (2020)
  • Innovation in Data Science Award (2019)

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Prof. Yue’s work is paving the way for the next generation of engineers who will rely on data analytics to create sustainable and efficient infrastructure solutions. His future contributions promise to further the development of smart cities, improve water resource management, and enhance the overall resilience of urban environments to climate change. As he continues to innovate and mentor young engineers, his legacy will endure, shaping the future of civil engineering and environmental sustainability.

FINAL NOTE 📌

Prof. Qiang Yue’s career has been defined by his commitment to applying cutting-edge technology to real-world problems in water conservancy and civil engineering. His research is reshaping how engineers and policymakers approach water management and sustainability. His ability to blend Big Data Analytics with traditional engineering disciplines is a testament to his vision for the future of infrastructure and environmental protection.

 TOP NOTES PUBLICATIONS 📚

Dynamic health prediction of plain reservoirs based on deep learning algorithms
    • Authors: Z., Zhu; Zhaohui, H.; Wu, Hao; Z., Zhang, Zhicheng; R., Wang, Rui; Q., Yue, Qiang
    • Journal: Engineering Applications of Artificial Intelligence
    • Year: 2025
Recognition and quantification of apparent damage to concrete structure based on computer vision
    • Authors: J., Liu, Jiageng; H., Sun, Hongyu; Q., Yue, Qiang; Y., Jia, Yanyan; S., Wang, Shaojie
    • Journal: Measurement: Journal of the International Measurement Confederation
    • Year: 2025

Diksha Kumar | Deep learning | Women Researcher Award

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Mrs. Diksha Kumar | Deep learning | Women Researcher Award

Ramrao Adik Institute of Technology (RAIT) | India

Publication Profile

Scopus
Orcid

BIOGRAPHY OF Mrs. Diksha Kumar 🌱📚

INTRODUCTION 🌍

Diksha Kumar is an accomplished research scholar with over 10 years of experience in higher education, currently pursuing her PhD in Computer Engineering at Ramrao Adik Institute of Technology (RAIT), India. Specializing in machine learning, deep learning, and generative AI, she has made significant strides in both research and innovation. She has secured funding for her research through a grant from Mumbai University, India, and holds a patent for an innovative aquatic animal-friendly ocean cleaning system. Through her research endeavors, Diksha has consistently pushed the boundaries of technology to contribute to a cleaner, smarter world. 🌍🔬

EARLY ACADEMIC PURSUITS 🎓

Diksha Kumar’s academic journey began with her intense passion for computer science and technology. As a student, she exhibited a deep curiosity and enthusiasm for computational methods and their real-world applications. Pursuing her undergraduate and master’s degrees, Diksha excelled in every academic pursuit, solidifying her foundation in computer engineering. Her rigorous academic training at Ramrao Adik Institute of Technology (RAIT) laid the groundwork for her current doctoral research, enabling her to delve into cutting-edge areas such as deep learning and machine learning.

PROFESSIONAL ENDEAVORS 👩‍💼

her professional career, Diksha Kumar has worked across various dimensions of academia and research. As a Research Scholar at RAIT, she has engaged in multiple industry-linked research projects. Her pioneering work in image classification and processing has garnered her attention in international academic circles. She has secured prestigious research grants and has become a member of the IEEE, further bolstering her professional credibility. Her practical contributions in the fields of AI and remote sensing have not only garnered attention but are making impactful changes in technology and environmental sustainability.

CONTRIBUTIONS AND RESEARCH FOCUS  ON  Deep learning 🔬

Diksha’s research work is marked by several innovative contributions to deep learning and AI. Her work on adapting Attention U-Net for image classification and combining it with XGBoost to enhance classification accuracy stands out. Additionally, she developed a hybrid model fusing VGG19 with XGBoost for improved image analysis. Moreover, her current focus on a novel cloud removal technique combining Homomorphic Filtering and Gamma Correction holds promise for enhancing image processing techniques. These contributions demonstrate her skill in addressing complex challenges in AI and image processing.

IMPACT AND INFLUENCE 🌟

Diksha Kumar’s research has had a substantial impact on both academia and industry. Her work, which fuses theoretical AI techniques with real-world applications, is paving the way for further advancements in image classification, remote sensing, and environmental protection. The patented aquatic animal-friendly ocean cleaning system showcases her commitment to using technology for environmental conservation, setting an example for researchers seeking to combine innovation with sustainability. Her pioneering work continues to inspire others in the research community and has led to significant strides in the application of deep learning to environmental issues.

ACADEMIC CITATIONS AND PUBLICATIONS 📑

Diksha Kumar has earned recognition through her impressive academic citations, reflecting the importance and relevance of her work. With a citation index of 19 and multiple publications in SCI and Scopus-indexed journals, her contributions to image processing, machine learning, and deep learning are well-regarded. Her academic output includes four journal articles, highlighting her prolific and impactful research work. Each publication has been a step forward in the development of AI-driven solutions that address both scientific and practical problems.

HONORS & AWARDS 🏆

Diksha’s commitment to excellence has earned her several accolades and recognitions in her field. Notably, she has been awarded a research grant from Mumbai University, which enabled her to pursue her innovative projects. Additionally, her research achievements are acknowledged through her patent for the aquatic animal-friendly ocean cleaning system. As she continues to make strides in her field, Diksha is a strong contender for the Women Researcher Award, which would recognize her outstanding contributions to research and technology.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Diksha Kumar’s legacy is being shaped by her relentless pursuit of excellence in research and her dedication to the practical applications of AI and deep learning. With future projects focused on advancing image processing techniques and addressing environmental issues, Diksha is positioning herself as a leader in these fields. Her future contributions will not only advance the frontiers of AI but also have a direct and positive impact on society, ensuring that her work continues to inspire and influence the next generation of researchers.

FINAL NOTE ✨

Diksha Kumar is a dynamic researcher whose work in AI, deep learning, and image classification is leaving a lasting impact on the academic and scientific communities. Her innovative solutions and commitment to using technology for the betterment of the environment showcase her ability to combine technical expertise with real-world challenges. As she moves forward with her PhD and her current research projects, Diksha’s work promises to make an even greater impact in the years to come.

TOP NOTES PUBLICATIONS 📚

AUXG: Deep Feature Extraction and Classification of Remote Sensing Image Scene Using Attention Unet and XGBoost
  • Authors: D.G. Kumar, Diksha Gautam, S.Z. Chaudhari, Sangita Zope
  • Journal: Journal of the Indian Society of Remote Sensing
  • Year: 2024

Kwang-Sig Lee | Artificial Intelligence | Excellence in Research

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Dr. Kwang-Sig Lee | Artificial Intelligence | Excellence in Research

Korea University Anam Hospital AI Center | South Korea

Publication Profile

Scopus

Google Scholar

INTRODUCTION 🧑‍🎓

Dr. Kwang-Sig Lee is a distinguished academician, research leader, and innovator specializing in the integration of medical and social informatics. Currently serving as Vice Center Chief at the AI Center of Korea University Anam Hospital, Dr. Lee’s groundbreaking research combines artificial intelligence with diverse datasets, such as genetic, image, numeric, and text data. His expertise in AI-driven systems has led to revolutionary work in healthcare, focusing on predictive AI models and multimodal machine learning. His work has earned significant recognition, influencing both academic circles and real-world medical applications.

EARLY ACADEMIC PURSUITS 🎓

Dr. Lee’s academic journey began at Kon Kuk University in Seoul, South Korea, where he earned a Bachelor’s degree in Economics and Physics (1994-1999), with a GPA of 3.52/4.00. He furthered his studies at Iowa State University (1999-2004), earning dual Master’s degrees in Economics and Sociology, graduating with a GPA of 3.69/4.00. Dr. Lee’s pursuit of advanced studies led him to Johns Hopkins University, where he obtained his Ph.D./MSE in Sociology and Applied Mathematics with a focus on health systems, securing a GPA of 3.63/4.00.

PROFESSIONAL ENDEAVORS 💼

Dr. Lee’s professional career spans across multiple prestigious institutions. At present, he holds the role of Vice Center Chief at Korea University’s AI Center in the Medical School. His previous roles include serving as a Research Associate Professor at the same institution, and Senior Research Fellow positions at various research agencies, including Acorn, Enliple, Agilesoda, and National Health Insurance Service. Dr. Lee has also worked as an Assistant Professor at Yonsei University and Sungkyunkwan University, contributing his expertise in preventive medicine and biostatistics.

CONTRIBUTIONS AND RESEARCH FOCUS ON ARTIFICIAL INTELLIGENCE 🧬

Dr. Lee’s contributions to the field of medical and social informatics are vast and impactful. His research primarily focuses on the application of artificial intelligence (AI) in healthcare, especially through the use of machine learning models, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Transformer models. His work explores the integration of genetic, image, numeric, and text data, thereby providing a more holistic approach to solving complex health-related challenges. Dr. Lee is known for his expertise in “Wide & Deep Learning,” a method that synthesizes multiple AI approaches to offer more powerful insights and predictive models.

IMPACT AND INFLUENCE 🌍

Dr. Lee’s innovative research has earned significant recognition both in academic and industrial circles. His work has been published in over 45 SCIE-indexed journals with a combined impact factor of 168. His Field-Weighted Citation Impact is 1.76, surpassing the average citation impact of KAIST in 2021. His expertise is frequently sought in both teaching and consultation, with Dr. Lee being an influential member of various academic committees. His ability to mentor graduate students and lead multidisciplinary research projects has significantly shaped the landscape of AI and healthcare.

ACADEMIC CITATIONS AND PUBLICATIONS 📚

Dr. Lee’s extensive publication record spans notable journals such as Cancers, European Radiology, International Journal of Surgery, and Journal of Medical Systems. His contributions have greatly impacted the scientific community, with a robust body of work related to medical AI, health informatics, and predictive modeling. In addition to his research articles, Dr. Lee has served as a guest editor for journals like Frontiers in Bioscience and Applied Sciences, as well as a reviewer for top-tier publications such as Nature Communications and Journal of Big Data.

HONORS & AWARDS 🏆

Throughout his academic career, Dr. Lee has been the recipient of numerous accolades, including full financial support during his tenure at Johns Hopkins University and Iowa State University. Additionally, he has been awarded for his academic excellence during his undergraduate studies at Kon-Kuk University. Dr. Lee’s consistent recognition for research excellence is evident from his impactful publications and active participation in the academic community, including his involvement in major research projects funded by government agencies.

FINAL NOTE ✨

Dr. Kwang-Sig Lee’s career is a testament to his dedication to advancing AI in medicine and social sciences. His expertise in combining machine learning with healthcare applications has paved the way for new innovations in predictive medicine, offering vital contributions to global healthcare systems. As he continues to lead research projects at the AI Center at Korea University, Dr. Lee’s legacy will be defined by his commitment to improving public health through cutting-edge technology and interdisciplinary research.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Dr. Lee’s future endeavors are poised to have a lasting impact on the fields of AI and healthcare. As the Vice Center Chief at one of the top medical schools, his work is expected to advance predictive healthcare models, fostering the development of more personalized and efficient healthcare solutions. With his expertise in “Wide & Deep Learning,” Dr. Lee is likely to continue influencing both the academic community and industry, shaping the future of AI-driven healthcare innovations.

TOP NOTES PUBLICATIONS 📚

Article: Graph Machine Learning With Systematic Hyper-Parameter Selection on Hidden Networks and Mental Health Conditions in the Middle-Aged and Old
  • Authors: K. Lee, Kwang-sig; B. Ham, Byung-joo
    Journal: Psychiatry Investigation
    Year: 2024
Article: A Machine Learning-Based Decision Support System for the Prognostication of Neurological Outcomes in Successfully Resuscitated Out-of-Hospital Cardiac Arrest Patients
  • Authors: S. Lee, Sijin; K. Lee, Kwang-sig; S. Park, Sang-hyun; S. Lee, Sung-woo; S. Kim, Sujin
    Journal: Journal of Clinical Medicine
    Year: 2024
Article: Clinical and Dental Predictors of Preterm Birth Using Machine Learning Methods: The MOHEPI Study
  • Authors: J. Park, Jung-soo; K. Lee, Kwang-sig; J. Heo, Ju-sun; K. Ahn, Ki-hoon
    Journal: Scientific Reports
    Year: 2024
Article: Explainable Artificial Intelligence on Safe Balance and Its Major Determinants in Stroke Patients
  • Authors: S. Lee, Sekwang; E. Lee, Eunyoung; K. Lee, Kwang-sig; S.B. Pyun, Sung Bom
    Journal: Scientific Reports
    Year: 2024

Omar Haddad | Artificial Intelligence | Best Researcher Award

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Dr. Omar Haddad l Artificial Intelligence | Best Researcher Award

MARS Research Lab, Tunisia

Author Profile

Google Scholar

🎓 Early Academic Pursuits

Dr. Omar Haddad began his academic journey with a solid foundation in mathematics, earning his Bachelor in Mathematics from Mixed High School, Tataouine North, Tunisia, in 2008. Building on this, he pursued a Fundamental License in Computer Science at the Faculty of Sciences of Monastir, University of Monastir, Tunisia, graduating with honors in 2012. He further honed his skills in advanced topics through a Research Master in Computer Science specializing in Modeling of Automated Reasoning Systems (Artificial Intelligence) at the same institution, completing his thesis on E-Learning, NLP, Map, and Ontology in 2016. This laid the groundwork for his doctoral studies in Big Data Analytics for Forecasting Based on Deep Learning, which he completed with highest honors at the Faculty of Economics and Management of Sfax, University of Sfax, Tunisia, in 2023.

💼 Professional Endeavors

Currently, Dr. Haddad is an Assistant Contractual at the University of Sousse, Tunisia, where he contributes to the academic and technological growth of the institution. He is a dedicated member of the MARS Research Laboratory at the University of Sousse, where he collaborates on cutting-edge projects in Artificial Intelligence and Big Data Analytics. His professional expertise extends to teaching across various levels, including preparatory, license, engineer, and master levels, with over 2,000 hours of teaching experience in state and private institutions.

📚 Contributions and Research Focus

Dr. Haddad’s research spans several transformative domains, including:

  • Artificial Intelligence (AI) and its application in solving complex problems.
  • Machine Learning (ML) and Deep Learning (DL) for advanced predictive modeling.
  • Generative AI and Large Language Models (LLMs) for innovation in Natural Language Processing (NLP).
  • Big Data Analytics for informed decision-making and forecasting.
  • Computer Vision for visual data interpretation and insights.

He has published three significant contributions in Q1 and Q2 journals and participated in Class C conferences, highlighting his commitment to impactful and high-quality research.

🌟 Impact and Influence

As a peer reviewer for prestigious journals like The Journal of Supercomputing, Journal of Electronic Imaging, SN Computer Science, and Knowledge-Based Systems, Dr. Haddad ensures the integrity and quality of academic contributions in his field. His work has influenced a diverse range of domains, from computer science education to applied AI, establishing him as a thought leader in his areas of expertise.

🛠️ Technical Skills

Dr. Haddad possesses a robust set of technical skills, including:

  • Proficiency in Deep Learning frameworks and Big Data tools.
  • Expertise in programming languages such as Python and C.
  • Knowledge of Database Engineering and algorithms.
  • Application of Natural Language Processing (NLP) in academic and industrial projects.

👨‍🏫 Teaching Experience

Dr. Haddad has an extensive teaching portfolio, covering a wide range of topics:

  • Database Engineering, Algorithms, and Programming, taught across license and engineer levels.
  • Advanced topics such as Big Data Frameworks, Foundations of AI, and Object-Oriented Programming.
  • Specialized courses on Information and Communication Technologies in Teaching and Learning.

His dedication to education is evident in his ability to adapt teaching strategies to different academic levels and institutional needs.

🏛️ Legacy and Future Contributions

Dr. Haddad’s legacy lies in his ability to bridge academia and industry through innovative research and teaching. As he continues to expand his expertise in Generative AI and LLMs, his future contributions will likely shape the next generation of intelligent systems and predictive analytics. His goal is to inspire students and researchers to harness the transformative potential of AI and Big Data to address global challenges.

🌐 Vision for the Future

Dr. Omar Haddad envisions a future where AI and Big Data technologies are seamlessly integrated into various sectors to enhance decision-making, foster innovation, and empower global communities. By combining his teaching, research, and technical skills, he aims to leave a lasting impact on the academic and technological landscape.

📖 Top Noted Publications
Toward a Prediction Approach Based on Deep Learning in Big Data Analytics
    • Authors: O. Haddad, F. Fkih, M.N. Omri
    • Journal: Neural Computing and Applications
    • Year: 2022
A Survey on Distributed Frameworks for Machine Learning Based Big Data Analysis
    • Authors: O. Haddad, F. Fkih, M.N. Omri
    • Journal: Proceedings of the 21st International Conference on New Trends in Intelligent Software Systems
    • Year: 2022
An Intelligent Sentiment Prediction Approach in Social Networks Based on Batch and Streaming Big Data Analytics Using Deep Learning
    • Authors: O. Haddad, F. Fkih, M.N. Omri
    • Journal: Social Network Analysis and Mining
    • Year: 2024
Big Textual Data Analytics Using Transformer-Based Deep Learning for Decision Making
    • Authors: O. Haddad, M.N. Omri
    • Journal: Proceedings of the 16th International Conference on Computational Collective Intelligence
    • Year: 2024

Feng Hu | Multi-modal feature recognition | Best Researcher Award

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Assoc Prof Dr. Feng Hu l Multi-modal feature recognition | Best Researcher Award

Communication University of China, China

Author Profile

Scopus

Early Academic Pursuits 🎓

Assoc. Prof. Dr. Feng Hu’s academic journey began with a deep interest in communication and information systems. He earned his Ph.D. in Communication and Information Systems from the prestigious Communication University of China (CUC), Beijing, in 2013. This educational foundation set the stage for his distinguished career in the fields of wireless communications, media convergence, and related technologies, shaping his future research and academic contributions.

Professional Endeavors and Contributions 🌐

Dr. Feng Hu is a prominent figure in the domain of 5G/6G wireless communications, and his professional journey has been marked by several key roles. Since December 2018, he has been an Associate Professor at Communication University of China and a master tutor, where he plays a significant role in mentoring future engineers and researchers. He has also been an active member of the Working Group of Radio, Film, and Television Administration for Wireless Interactive Radio and Television, as well as a member of the Working Group of 5G Broadcast. These positions have allowed him to contribute to the development and regulation of cutting-edge technologies in the media and communications sector.

Research Focus and Impact 🔬

Dr. Hu’s research interests lie in the development of transmitting and receiving techniques for 5G and 6G wireless communications. His work focuses on optimizing wireless communication systems, utilizing machine learning, and exploring optimization theory to enhance the efficiency and performance of modern communication technologies. His research has significant implications for the advancement of wireless communication systems, contributing to the global transition to next-generation technologies and improving communication capabilities in various sectors.

Technical Skills and Expertise ⚙️

Dr. Hu is highly skilled in the areas of wireless communications, machine learning, and optimization theory. His expertise includes developing novel algorithms and techniques for 5G/6G systems, addressing challenges in data transmission, signal processing, and system optimization. He is proficient in applying advanced mathematical models and machine learning approaches to improve communication systems’ performance, reliability, and security, making him a key player in advancing the state-of-the-art in wireless communications.

Teaching Experience and Mentorship 🍎

As an Associate Professor and master tutor, Dr. Hu is deeply involved in shaping the next generation of professionals in communication and information systems. He has taught a variety of undergraduate and graduate-level courses, imparting his knowledge in wireless communications, machine learning, and optimization. His mentorship extends beyond the classroom, guiding students in research and academic pursuits, while fostering a culture of innovation and critical thinking in the field of communications.

Legacy and Future Contributions 🌱

Dr. Hu’s legacy is rooted in his pioneering work in the development of 5G/6G wireless communication systems and his significant contributions to the academic and professional communities. Looking ahead, he aims to continue pushing the boundaries of wireless communication technologies, with a particular focus on optimizing next-generation communication networks and integrating machine learning approaches to improve system efficiencies. His future contributions will likely influence both academic research and practical implementations in the rapidly evolving fields of wireless communications and media convergence.

Academic Citations and Recognition 🏆

Dr. Feng Hu’s research has garnered recognition in top-tier academic journals and conferences in the fields of communication systems and wireless technology. His work has not only contributed to the scientific community but has also influenced industry practices and standards in wireless communication. He continues to be a sought-after figure in academic circles, providing valuable insights into the development of 5G/6G systems and machine learning applications in communications.

Professional Affiliations and Leadership 🌍

Dr. Hu is an active member of several esteemed organizations, including IEEE and the Society of Communications, where he holds the prestigious title of Senior Member. His involvement in key working groups related to wireless interactive radio and television and 5G broadcast further highlights his leadership in shaping the future of communication technologies. These affiliations enhance his ability to drive impactful research and contribute to the global dialogue on the future of communication systems.

Future Outlook and Innovation 🚀

With his vast expertise in wireless communication systems and emerging technologies, Dr. Hu’s future endeavors will focus on leading innovations in 6G communication systems, integrating artificial intelligence and machine learning to enhance system performance, and tackling the challenges posed by next-generation wireless networks. His ongoing research will play a critical role in shaping the future of global communication, advancing both academic theory and practical applications in the field.

 Top Noted Publications 📖

SDDA: A progressive self-distillation with decoupled alignment for multimodal image–text classification

Authors: Chen, X., Shuai, Q., Hu, F., Cheng, Y.
Journal: Neurocomputing
Year: 2025

EmotionCast: An Emotion-Driven Intelligent Broadcasting System for Dynamic Camera Switching

Authors: Zhang, X., Ba, X., Hu, F., Yuan, J.
Journal: Sensors
Year: 2024

 Asymptotic performance of reconfigurable intelligent surface assisted MIMO communication for large systems using random matrix theory

Authors: Hu, F., Zhang, H., Chen, S., Zhang, J., Feng, Y.
Journal: IET Communications
Year: 2024

Real-Time Multi-Service Adaptive Resource Scheduling Algorithm Based on QoE

Authors: Li, W., Li, S., Hu, F., Yin, F.
Conference: 2024 IEEE 12th International Conference on Information and Communication Networks, ICICN 2024
Year: 2024

5G RAN Slicing Resource Allocation Based on PF/M-LWDF

Authors: Hu, F., Qiu, J., Chen, A., Yang, H., Li, S.
Conference: 2024 4th International Conference on Computer Communication and Artificial Intelligence, CCAI 2024
Year: 2024

Vinod Kumar | Big Data Analytics | Best Researcher Award

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Assoc Prof Dr. Vinod Kumar | Big Data Analytics | Best Researcher Award

FLAME University, India

Author Profile

Google Scholar

🌱 Early Academic Pursuits

Assoc Prof Dr. Vinod Kumar began his academic journey with a strong foundation in Mechanical Engineering, earning a Bachelor’s degree from Haryana College of Technology & Management, Kaithal. He then transitioned into the realm of business, acquiring a Master of Business Administration (MBA) in Marketing from Chandigarh Business School. His intellectual pursuit culminated in a Ph.D. in Marketing from the prestigious Indian Institute of Technology (IIT) Roorkee. His doctoral thesis, titled “Assessing the Influence of Stakeholders on Sustainability Marketing Strategy,” focused on how various stakeholders shape the strategies for sustainable marketing.

💼 Professional Endeavors

Dr. Kumar’s professional trajectory spans over a decade in academia, with positions at renowned institutions. His current role as an Associate Professor at FLAME University in Pune, Maharashtra, marks the latest phase in a distinguished career. Prior to this, he held faculty positions at MICA, Ahmedabad, Symbiosis Institute of Business Management, and the Indian Institute of Information Technology, Lucknow, among others. Additionally, Dr. Kumar’s experience in industry as a Sales Executive and Water Treatment Specialist adds practical insight to his academic teaching. This mix of academia and industry experience enriches his approach to teaching and research.

📚 Contributions and Research Focus

Dr. Kumar’s research primarily focuses on Brand Management, Digital Marketing, Green Marketing, Digital Business Strategy, and Social Media Marketing. His interdisciplinary approach integrates traditional marketing principles with the evolving digital landscape. Notable research projects include studying the relationship between stakeholders and sustainability strategies, and he has contributed significantly to the literature on stakeholder identification in marketing. Dr. Kumar has published papers in high-impact journals such as Management Research Review and has been honored with the Emerald Literati Network Award for Excellence in 2017 for his outstanding research.

🌍 Impact and Influence

Through his academic and professional roles, Dr. Kumar has made a substantial impact in shaping the marketing landscape. His research has not only contributed to the academic body of knowledge but has also influenced industry practices. The recognition of his work through awards like the Best Paper Award at AMRIT-2020 and Emerald Literati Network Awards for Excellence reflects his significant influence in the marketing and digital business strategy domains. Additionally, his consulting project on Digital Marketing Strategies and Tools for God’s Grace Distributions showcases his practical expertise and ability to drive business transformation.

📑 Academic Cites and Recognition

Dr. Kumar’s research has garnered widespread recognition and citation in leading academic forums. His work on Sustainability Marketing and Stakeholder Analysis is widely referenced in marketing and sustainability studies. His recognition by various academic bodies, including the FIIB Business Review as a reviewer and the AIM-AMA Sheth Foundation Travel Grant, further solidifies his standing as an authority in his field.

💻 Technical Skills

Dr. Kumar possesses advanced proficiency in digital marketing tools, UI/UX Design, Social Media Marketing, and Data Analytics. His expertise in Digital Business Strategy enables him to leverage digital platforms effectively for both academic purposes and real-world business solutions. This technical expertise is integrated into his teaching, providing students with a modern, practical learning experience that blends theory with the latest industry practices.

🎓 Teaching Experience

Dr. Kumar has held teaching positions across multiple prestigious institutions, where he has designed and taught courses on Marketing Management, Digital Marketing, Brand Management, and Sales and Distribution Management. His role as the Founding Head of the Department at IIIT Lucknow enabled him to create a dynamic curriculum and research environment for future leaders in business management. His approach to teaching combines innovative strategies, a deep understanding of digital platforms, and a focus on practical application, which has been appreciated by students and colleagues alike.

🌟 Legacy and Future Contributions

As a respected academic, Dr. Kumar has not only imparted knowledge but has also shaped the future of marketing education. His research continues to evolve, with ongoing supervision of Ph.D. students, such as Ms. Isha Sharma and Mr. Vibhav Singh. Dr. Kumar’s legacy is built upon his commitment to enhancing the relevance of marketing education in the digital age and his contribution to sustainability marketing. His future contributions are likely to have a significant impact on both academic literature and industry practices in digital business strategy, making him a thought leader to watch in the coming years.

📖 Top Noted Publications 

Evolution of Sustainability as Marketing Strategy: Beginning of New Era
    • Authors: V Kumar, Z Rahman, AA Kazmi, P Goyal
    • Journal: Procedia-Social and Behavioral Sciences
    • Year: 2012
Sustainability Marketing Strategy: An Analysis of Recent Literature
    • Authors: V Kumar, Z Rahman, AA Kazmi
    • Journal: Global Business Review
    • Year: 2013
Examining Consumer-Brand Relationships on Social Media Platforms
    • Authors: NK Jain, S Kamboj, V Kumar, Z Rahman
    • Journal: Marketing Intelligence and Planning
    • Year: 2018
Stakeholder Identification and Classification: A Sustainability Marketing Perspective
    • Authors: V Kumar, Z Rahman, AA Kazmi
    • Journal: Management Research Review
    • Year: 2016
Why Export Competitiveness Differs Within Indian Textile Industry? Determinants and Empirical Evidence
    • Authors: R Dhiman, V Kumar, S Rana
    • Journal: Review of International Business and Strategy
    • Year: 2020
Investigating the Impact of Online Service Convenience on Customer Engagement, Attitude and Intention to Use Food Delivery Apps
    • Authors: V Vandana, S Kumar, V Kumar, P Goyal
    • Journal: International Journal on Food System Dynamics
    • Year: 2023