Bipin Kumar | Earth and Planetary Sciences | Best Researcher Award

Dr. Bipin Kumar | Earth and Planetary Sciences | Best Researcher Award

Indian Institute of Tropical Meteorology | India

Author Profile

Scopus

Early Academic Pursuits

Dr. Bipin Kumar's academic journey began with a Bachelor of Science in Physical Sciences from the University of Allahabad in 1995, followed by a Master of Science in Mathematics from IIT Kanpur in 1998. He then pursued an MS in Research (Mathematics) at the National University of Singapore in 2006, focusing on computational methods for phase-field models. His quest for deeper expertise led him to earn a Ph.D. in Computing from Dublin City University in 2009, with a thesis on high-performance computing for multiphase fluid flows.

Professional Endeavors

Dr. Kumar’s career spans over two decades, encompassing roles in academia, research institutions, and industry. His notable positions include:

  • Scientist and Research Guide at IITM, Pune, India.
  • Associate Professor at Savitribai Phule Pune University.
  • Visiting Scientist at NCAR, Boulder, USA, and Visiting Faculty at McGill University, Canada.
  • Associate Faculty at the International Center for Theoretical Sciences, Bengaluru, India.
  • Scientist at Max-Planck-Institute for Meteorology, Germany.

He has held various teaching and research positions, contributing to advancements in high-performance computing, data science, and atmospheric physics.

Contributions and Research Focus

Dr. Kumar's research is centered around:

  • Data Science and AI/ML: Developing parallel Python routines and deep learning algorithms for weather forecasting, data downscaling, fire forecasting, and more.
  • Atmospheric Physics: Studying cloud droplet and aerosol dynamics using DNS.
  • High-Performance Computing (HPC): Enhancing parallel code for CFD problems, 3D visualization, and parallel I/O optimization.
  • Numerical Linear Algebra: Creating parallel algorithms for solving large linear systems of equations.

Accolades and Recognition

Dr. Kumar has received several prestigious awards:

  • DCU Teaching Excellence Nominee Award (2008)
  • Microsoft Postgraduate Research Scholarship (Ireland, 2007-08)
  • DCU Dean’s Connect Scholarship (Ireland, 2006-09)
  • NUS Research Scholarship (Singapore, 2004-06)
  • CSIR Senior Research Fellowship (India, 2004)

Impact and Influence

Dr. Kumar’s work has significantly influenced fields such as HPC, data science, and atmospheric physics. His contributions to developing computational methods for complex fluid flows and forecasting systems have advanced our understanding of cloud dynamics and weather patterns. His research has impacted both theoretical and practical aspects of meteorology and data analysis.

Legacy and Future Contributions

Dr. Kumar aims to broaden his impact through continued research and teaching. By leveraging his expertise in HPC, data science, and cloud microphysics, he aspires to address critical challenges in earth science and contribute to the development of innovative solutions for climate and environmental issues.

 

   Publications

  • Deep learning-based bias correction of ISMR simulated by GCM
    Authors: Sumanta Chandra Mishra Sharma, Bipin Kumar, Adway Mitra, Subodh Kumar Saha
    Journal: Atmospheric Research
    Year: 2024

 

  • Harnessing deep learning for forecasting fire-burning locations and unveiling PM2.5 emissions
    Authors: Gaikwad, S., Kumar, B., Yadav, P.P., Rao, S.A., Ghude, S.D.
    Journal: Modeling Earth Systems and Environment
    Year: 2024

 

  • Machine learning based quantification of VOC contribution in surface ozone prediction
    Authors: Kalbande, R., Kumar, B., Maji, S., Rathore, D.S., Beig, G.
    Journal: Chemosphere
    Year: 2023

 

  • On the modern deep learning approaches for precipitation downscaling
    Authors: Kumar, B., Atey, K., Singh, B.B., Nanjundiah, R.S., Rao, S.A.
    Journal: Earth Science Informatics
    Year: 2023

 

  • A modified deep learning weather prediction using cubed sphere for global precipitation
    Authors: Singh, M., Acharya, N., Patel, P., Nanjundiah, R.S., Niyogi, D.
    Journal: Frontiers in Climate
    Year: 2023

 

 

 

 

 

 

Akash Sharma | Engineering | Best Researcher Award

Mr. Akash Sharma | Engineering | Best Researcher Award

Malaviya National Institute of Technology | India

Author Profile

Scopus

Early Academic Pursuits 🎓

Mr. Akash Sharma’s academic journey began with a solid foundation in Electrical Engineering. He earned his Bachelor of Technology (B-Tech) in Electrical Engineering from Arya College of Engineering & IT, RTU Kota in 2016, achieving a commendable 68.5%. He further pursued a Master of Technology (M-Tech) in Power Systems from Malaviya National Institute of Technology (MNIT), Jaipur in 2021, with a CGPA of 7.72. His quest for knowledge continued as he completed his PhD in Power Systems at MNIT, Jaipur in 2022, with a CGPA of 7.6. His doctoral research focused on the performance analysis of smart grids, utilizing data-driven methods and machine learning.

Professional Endeavors 💼

Mr. Sharma's professional experience includes diverse roles. He served as a guest faculty at the College of Dairy Science and Technology, Jobner, from 2021 to 2022, where he contributed to the academic environment. Prior to this, he worked as a Graduate Engineer Trainee (GET) at IRB Infrastructure Ltd., handling electrical aspects of various plants and overseeing staff welfare. Additionally, Mr. Sharma gained valuable experience as a Public Relations Officer (PRO) with Indian Business Pages in 2016.

Contributions and Research Focus 🔍

Mr. Sharma's research is centered on the performance analysis of smart grids, integrating deep learning and machine learning techniques. His PhD work emphasizes cybersecurity in energy consumption, aiming to develop advanced models for detecting and mitigating cyber-attacks on smart grid infrastructures. His work also explores the seamless integration of renewable energy sources and optimization of smart grid performance. He has published a notable research paper on voltage profile enhancement using FACTS devices and has worked on solar tracking systems.

Accolades and Recognition 🏅

While Mr. Sharma has not yet received major awards, his active participation in co-curricular activities and his impactful research reflect his dedication. His work on smart grids and renewable energy has been well-received in academic circles, demonstrating his commitment to advancing the field of electrical engineering.

Impact and Influence 🌟

Mr. Sharma's contributions to smart grid technology and renewable energy integration are shaping the future of power systems. His work in enhancing grid performance and addressing cybersecurity concerns is crucial in the evolving landscape of energy management. His involvement in both academic and professional settings highlights his influence on the next generation of engineers and researchers.

Legacy and Future Contributions 🚀

Looking ahead, Mr. Sharma's ongoing research and professional activities will continue to impact the field of electrical engineering. His focus on smart grids and renewable energy positions him to contribute significantly to advancements in these areas. As he builds on his experiences and research, he is poised to leave a lasting legacy in the realm of power systems and sustainable energy solutions.

 

Publications

  • Title: Anomaly detection in smart grid using optimized extreme gradient boosting with SCADA system
  • Authors: Sharma, A., Tiwari, R.
  • Journal: Electric Power Systems Research
  • Year: 2024

 

  • Title: Load Shedding Technique for Maintaining Voltage Stability
  • Authors: Sharma, P.K., Sharma, A., Tiwari, R.
  • Journal: Lecture Notes in Electrical Engineering
  • Year: 2024

 

 

 

 

Sasank V.V.S | Computer Science | Best Researcher Award

Assist Prof Dr. Sasank V.V.S | Computer Science | Best Researcher Award

K L University | India

Author Profile

Scopus

Early Academic Pursuits

Dr. Sasank V.V.S. exhibited a strong academic foundation from the outset. He completed his secondary education at Jassver English Medium School in 2007 with a First Class distinction, scoring 72.66%. He continued to excel in his Intermediate studies at Mega Junior College, graduating in 2009 with an 84.1% mark, also achieving First Class. His academic journey progressed to higher education at Gitam Institute of Technology, GITAM University, where he obtained his B.Tech in Information Technology in 2013 with a CGPA of 8.15, earning a Distinction. He further advanced his education with an M.Tech in Computer Science and Technology from the same institution, graduating in 2016 with a remarkable 9.11 CGPA, securing the top rank in his department. Dr. Sasank completed his Ph.D. at K.L. University in 2023, marking a significant milestone in his academic career.

Professional Endeavors

Dr. Sasank has a rich professional background in both academia and industry. He began his teaching career as a Teaching Assistant in the CSE Department at Gitam University from October 2015 to April 2016. He then served as an Assistant Professor at the Lendi Institute of Engineering & Technology, VIZIANAGARAM, from June 2016 to April 2017. Following this, he joined Anil Neerukonda Institute of Technology & Sciences (ANITS) as an Assistant Professor and Placement Officer from June 2017 to April 2019. He has been affiliated with K L University since July 2019, initially in the CSE Department and later in the CSIT Department, where he also served as the ERP Registration In-charge. His teaching repertoire includes subjects such as DBMS, Software Engineering, Computer Architecture & Organization, Term Paper, UI/UX Design, and DevOps.

Contributions and Research Focus

Dr. Sasank's research primarily focuses on advanced topics in computer science and engineering. His areas of interest include brain tumor classification, real-time traffic management using IoT and machine learning techniques, and the evolution of modern women in literature. He has published a significant number of papers in reputed journals, including  SCI papers and several Scopus-indexed articles. His notable publications include works on hybrid deep neural networks, automatic tumor growth prediction, and brain tumor classification using modified kernel-based softplus extreme learning machines. Additionally, he has guided numerous B.Tech and M.Tech project batches, contributing to the academic growth of his students.

Accolades and Recognition

Dr. Sasank has received several accolades for his academic and research achievements. He was the top ranker in his M.Tech program at Gitam University in 2016. He has published 18 papers, including SCI, Scopus, and WOS-indexed journals, and has contributed to two book chapters. His innovative research has led to the publication of two patents: one on real-time traffic management using IoT and machine learning techniques, and another on the evolution of modern women in Manju Kapur’s novels. Additionally, he has earned global certifications, including Google Associate Cloud Engineer and AWS Cloud Practitioner, and has presented his research at various international conferences.

Impact and Influence

Dr. Sasank's contributions to the field of computer science and engineering have had a significant impact on both academic and practical applications. His research on brain tumor classification and real-time traffic management has potential real-world implications, advancing the fields of medical imaging and smart city technologies. As an educator, he has influenced many students through his teaching and mentorship, guiding them in their academic and research endeavors.

Legacy and Future Contributions

Dr. Sasank's ongoing research and academic activities are expected to leave a lasting legacy in the field of computer science and engineering. His contributions to brain tumor classification and IoT-based traffic management are poised to influence future research and development in these areas. As he continues to publish and present his work, Dr. Sasank is likely to inspire and mentor the next generation of engineers and researchers, ensuring continued innovation and excellence in his field.

 

Notable Publications

Prostate cancer classification using adaptive swarm Intelligence based deep attention neural network 2024

Effective Segmentation and Brain Tumor Classification Using Sparse Bayesian ELM in MRI Images 2023

Hybrid deep neural network with adaptive rain optimizer algorithm for multi-grade brain tumor classification of MRI images 2022 (14)

An automatic tumour growth prediction based segmentation using full resolution convolutional network for brain tumour 2022 (27)

Hate Speech & Offensive Language Detection Using ML &NLP 2022 (4)

 

 

 

 

Debapriya Banik | Computer Science | Best Researcher Award

Dr. Debapriya Banik | Computer Science | Best Researcher Award

ICFAI University | India

Author profile

Scopus

Orcid

Google Scholar

Early Academic Pursuits

Dr. Debapriya Banik embarked on his academic journey with a solid foundation in secondary and higher secondary education at Holy Cross School in Agartala, achieving commendable scores in both ICSE and ISC examinations. His passion for Computer Science led him to pursue a Bachelor of Technology (B.Tech) in Computer Science and Engineering at the National Institute of Technology Agartala, where he graduated with a CGPA of 7.59. His pursuit of higher education continued at Tripura University, where he excelled in his Master of Technology (M.Tech) in Computer Science and Engineering, earning a gold medal for securing the highest percentage. Dr. Banik's academic endeavors culminated in a Doctor of Philosophy (Ph.D.) in Computer Science and Engineering from Jadavpur University, where he focused on developing computer-aided techniques for the early prediction of colorectal cancer based on diagnostic image analysis.

Professional Endeavors

Dr. Banik's professional career is marked by diverse and impactful roles in academia and industry. He began his career as a consultant at Polaris Financial Technology Ltd in Chennai, gaining valuable industry experience. Transitioning to academia, he served as a Junior Research Fellow (JRF) on a DBT Twinning Project at Jadavpur University, working on techniques for pain management and breast cancer using IR imaging. He then became a Senior Research Fellow (SRF)-Direct at Jadavpur University under the sponsorship of the Council for Scientific and Industrial Research, Government of India. His academic career continued to flourish as he took on roles as an Assistant Professor at Techno India in Kolkata and later at ICFAI University in Tripura, where he currently teaches in the Department of Computer Science & Engineering.

Contributions and Research Focus

Dr. Banik's research has significantly contributed to the field of computer science, particularly in medical image analysis. His Ph.D. thesis focused on developing computer-aided techniques for the early prediction of colorectal cancer, leveraging diagnostic image analysis. Additionally, he has worked on the design and development of techniques for pain management and breast cancer using IR imaging. His innovative research approaches have not only advanced the field but also provided practical solutions for critical medical challenges. Dr. Banik's work is characterized by a strong focus on applying machine learning and computational techniques to enhance diagnostic accuracy and efficiency.

Accolades and Recognition

Dr. Banik's academic excellence and research contributions have earned him numerous awards and recognitions. He was awarded a gold medal for his outstanding performance in M.Tech at Tripura University. He received the DST-Inspire fellowship from the Department of Science and Technology, Government of India, and the North Eastern Council (NEC) Scheme fellowship for postgraduate studies. Dr. Banik secured the first position in the Workshop on Machine Learning for Medical Image Analysis (WMLMIA) - Fetal Ultrasound Censor (FUC) Grand Challenge, organized by the Department of Electrical Engineering at IIT Kharagpur. Additionally, he had the opportunity for a short-term research visit to the Medical University of Vienna, Austria, sponsored by DST, Government of India, where he worked on developing a computer-assisted diagnosis system for segmenting and detecting abnormalities and diseases under the supervision of Prof. Christian Kollman.

Impact and Influence

Dr. Banik's work has had a profound impact on the field of medical image analysis, particularly in the early detection and management of diseases such as colorectal and breast cancer. His research has paved the way for more accurate and efficient diagnostic tools, improving patient outcomes and contributing to the advancement of medical technology. As an educator, he has influenced and mentored numerous students, fostering a new generation of computer science professionals who are equipped with cutting-edge knowledge and skills.

Legacy and Future Contributions

Dr. Banik's legacy lies in his dedication to advancing the field of computer science through innovative research and his commitment to education. His work continues to inspire researchers and students alike, and his contributions to medical image analysis have set a high standard for future research in the field. Looking ahead, Dr. Banik aims to further his research on computer-aided diagnosis systems, exploring new applications and techniques to address emerging challenges in healthcare. His future contributions are expected to continue making significant strides in improving diagnostic accuracy and patient care through advanced computational methods.

 

Notable Publications

Robust medical and color image cryptosystem using array index and chaotic S-box 2024

dHBLSN: A diligent hierarchical broad learning system network for cogent polyp segmentation 2024

2pClPr: A Two-Phase Clump Profiler for Segmentation of Cancer Cells in Fluorescence Microscopic Images 2023 (2)

RBECA: A regularized Bi-partitioned entropy component analysis for human face recognition 2022 (1)

LwMLA-NET: A Lightweight Multi-Level Attention-based NETwork for Segmentation of COVID-19 Lungs Abnormalities from CT Images 2022 (39)

 

 

 

Elaheh Yaghoubi | Energy | Best Researcher Award

Dr. Elaheh Yaghoubi | Energy | Best Researcher Award

Karabuk University | Turkey

Author profile

Scopus

Orcid

Early Academic Pursuits

Dr. Elaheh Yaghoubi's academic journey began with an Associate's degree in Electrical Engineering from University College of Rouzbahan, Iran, where she graduated with a GPA of 3.5. She then pursued a Bachelor's degree in Electrical Engineering at Aryan Institute of Science and Technology University, Iran, achieving a perfect GPA of 4. Following this, she completed her Master's degree in Electrical Engineering at Islamic Azad University in Qaemshahr, Mazandaran, Iran, again with a perfect GPA of 4. Her Master's thesis focused on developing a routing algorithm for a proposed topology for a grid on a large-scale chip to detect errors. Dr. Yaghoubi is currently a Ph.D. candidate in Electronic and Electrical Engineering at Karabuk University in Turkey, where she is working on her thesis titled "Optimal power control of grid-connected distributed generation in a hierarchical framework based on Model Predictive Control."

Professional Endeavors

Dr. Yaghoubi has a diverse professional background that complements her academic achievements. From 2015 to 2018, she served as a Senior Manager at Kati Kabl Tabarestan Factory in Mazandaran, Iran, where she was responsible for quality assurance, inspecting products to ensure high quality, and troubleshooting technical issues. She then worked as a Senior Manager at Rico Electronics Company in Mazandaran, Iran, overseeing product quality assurance and implementing design modifications. From 2019 to 2021, she worked as a Website Designer at WebCore Company in Mazandaran, designing front-end interfaces with HTML, CSS, and JavaScript, and back-end systems with PHP and Laravel. Currently, Dr. Yaghoubi is a Principal Researcher at the Power Electrical Developing Advanced Research (PEDAR) group, focusing on investigation, teaching, and designing.

Contributions and Research Focus

Dr. Yaghoubi's research interests are broad and interdisciplinary, encompassing power system analysis, power system stability, power management, microgrids, smart grids, renewable energies, model predictive controllers (MPC), artificial neural networks, machine learning, deep learning, plasmonic applications, and nano-electronic devices. Her current research work involves optimal power control of grid-connected distributed generation using model predictive control, a topic that is crucial for the advancement of smart grids and renewable energy systems. She has also contributed to the understanding and development of routing algorithms for large-scale chips and has experience in quality control and product management in industrial settings.

Accolades and Recognition

Throughout her academic and professional career, Dr. Yaghoubi has been recognized for her excellence and contributions. She successfully passed her Ph.D. qualification exam with a perfect grade of 4 out of 4. Her consistent academic performance, marked by perfect GPAs during her Bachelor's and Master's studies, reflects her dedication and expertise in her field.

Impact and Influence

Dr. Yaghoubi's work has had a significant impact on both academic and industrial fields. Her research on smart grids, optimization techniques, and model predictive control contributes to the development of more efficient and reliable power systems. Her practical experience in quality control and product management ensures that her research is grounded in real-world applications and industrial standards.

Legacy and Future Contributions

Dr. Yaghoubi's legacy lies in her interdisciplinary approach to electronic and electrical engineering, integrating theoretical research with practical applications. Her work in power systems, renewable energy, and advanced control techniques positions her as a key contributor to the future of smart grid technology and sustainable energy solutions. As she continues her research and professional activities, Dr. Yaghoubi is likely to make further significant contributions to the field, driving innovation and excellence in electronic and electrical engineering.

 

Notable Publications

A systematic review and meta-analysis of machine learning, deep learning, and ensemble learning approaches in predicting EV charging behavior 2024

A systematic review and meta-analysis of artificial neural network, machine learning, deep learning, and ensemble learning approaches in field of geotechnical engineering 2024

Controlling and tracking the maximum active power point in a photovoltaic system connected to the grid using the fuzzy neural controller 2023 (1)

Tunable band-pass plasmonic filter and wavelength triple-channel demultiplexer based on square nanodisk resonator in MIM waveguide 2022 (9)

Triple-channel glasses-shape nanoplasmonic demultiplexer based on multi nanodisk resonators in MIM waveguide 2021 (11)

 

 

 

Yunyoung Nam | Computer Science | Best Researcher Award

Prof. Yunyoung Nam | Computer Science | Best Researcher Award

Soonchunhyang University | South Korea

Author Profile

Scopus

Early Academic Pursuits

Prof. Yunyoung Nam began his academic journey with a focus on Information and Communication. He achieved significant recognition early in his career, earning the Presidential Award for Excellence in Graduate School of Information and Communication in both 2003 and 2007. He also received the Dasan Fellowship from Ajou University in 2000, demonstrating his potential and commitment to his field from the start.

Professional Endeavors

Prof. Nam's professional career is marked by a series of progressive roles in academia and research. He served as a Senior Researcher at the Ubiquitous Convergence Research Institution from 2007 to 2010, followed by multiple postdoctoral positions at Stony Brook University-SUNY and Worcester Polytechnic Institute. He transitioned to academia as a Research Assistant Professor at Ajou University before joining Soonchunhyang University, where he has held positions as Assistant Professor, Associate Professor, and currently, Professor since 2023.

Contributions and Research Focus

Prof. Nam's research interests span a wide range of cutting-edge topics, including multimedia information retrieval, digital signal processing, machine learning methods for multimedia applications, and biomedical engineering. His contributions to these fields are substantial, with notable projects such as the development of a 3D deep-learning-based diagnosis platform for retinal disease, and a smartphone-based diagnosis and referral platform for chronic diseases. His research has been supported by prestigious organizations, including the National Research Foundation (NRF) and the Ministry of Science, ICT, and Future Planning (MSIP).

Accolades and Recognition

Throughout his career, Prof. Nam has been recognized for his exceptional contributions to research and academia. He has received the Presidential Award for Best Researcher at Soonchunhyang University three times (2015, 2018, 2020), highlighting his sustained excellence in research. Additionally, he was included in the 2011 edition of Who's Who in America, further acknowledging his influence and impact in his field.

Impact and Influence

Prof. Nam's impact extends beyond his research contributions. As an educator, he has taught a wide range of courses at Soonchunhyang University, including C#, AI, algorithms, data structure, discrete mathematics, and software engineering. His commitment to teaching and mentorship has influenced many students and upcoming researchers. Moreover, his membership in several professional associations such as IEEE and the Korea Information Processing Society, and his editorial roles in various journals, underscore his active involvement in the academic community.

Legacy and Future Contributions

Prof. Nam's legacy is defined by his relentless pursuit of knowledge and innovation in multimedia applications and biomedical engineering. His research projects, such as the RNA Innovation Human Resources Project for the Hyper-connected Convergence Industry, and the training of experts for the intelligent home care industry, are paving the way for future advancements. As he continues to lead and innovate, Prof. Nam's future contributions are expected to significantly influence both academic research and practical applications in his areas of expertise.

 

Notable Publications

Localization and grading of NPDR lesions using ResNet-18-YOLOv8 model and informative features selection for DR classification based on transfer learning 2024

Novelty of Different Distance Approach for Multi-Criteria Decision-Making Challenges Using q-Rung Vague Sets 2024

Federated Learning for Computational Offloading and Resource Management of Vehicular Edge Computing in 6G-V2X Network 2024 (5)

A gamified cognitive behavioral therapy for Arabs to reduce symptoms of depression and anxiety: A case study research 2024

Sleep Posture Classification Using RGB and Thermal Cameras Based on Deep Learning Model 2024

 

 

 

Lin Guo | Computer Science | Excellence in Innovation Award

Mr. Lin Guo | Computer Science | Excellence in Innovation Award

Huazhong University of Science and Technology | China

Author Profile

Scopus

Early Academic Pursuits

Mr. Lin Guo embarked on his academic journey with a strong foundation in Computer Science and Technology at Zhengzhou University, where he graduated with distinction as one of the top students. Building on this success, he pursued postgraduate studies in Artificial Intelligence at Huazhong University of Science and Technology, demonstrating a keen interest in advanced technologies and research methodologies.

Professional Endeavors

Mr. Guo's professional career is marked by significant contributions in the field of artificial intelligence and computer vision. His internship at Megvii Technology's Shanghai Research Institute focused on developing cutting-edge algorithms for AVP parking semantic mapping, addressing challenges in SLAM optimization and multi-frame fusion mapping. His role as a key engineer underscored his ability to innovate and implement complex solutions in real-world applications.

Contributions and Research Focus

Lin Guo has made substantial contributions to the field through his research publications and project involvements. His research spans point cloud registration, 3D registration efficiency, and advanced methods in SLAM and VIO positioning. His work on optimizing point cloud feature learning and overcoming feature ambiguity in different reference systems has been acknowledged for its innovation and practical relevance.

Accolades and Recognition

His academic achievements and research prowess have been recognized with numerous honors, including being an Outstanding Graduate of Henan Province and receiving prestigious scholarships from Zhengzhou University and Huazhong University of Science and Technology. His contributions to accepted and submitted papers in leading conferences and journals highlight his growing influence in the academic community.

Impact and Influence

Lin Guo's research has made a significant impact on the fields of computer vision and robotics, particularly in enhancing the accuracy and efficiency of point cloud registration and SLAM technologies. His methods have set benchmarks in performance on diverse datasets, demonstrating their applicability across indoor and outdoor environments.

Legacy and Future Contributions

Looking ahead, Lin Guo aims to continue pushing the boundaries of artificial intelligence and robotics. His future contributions are expected to further advance state-of-the-art techniques in SLAM optimization, 3D registration, and autonomous systems. By bridging theoretical insights with practical applications, he seeks to foster advancements that positively impact industries and society at large.

 

Notable Publications

Learning compact and overlap-biased interactions for point cloud registration 2024

SC 2-PCR++: Rethinking the Generation and Selection for Efficient and Robust Point Cloud Registration 2023 (9)

One-Inlier is First: Towards Efficient Position Encoding for Point Cloud Registration 2022 (5)

 

 

Vishnu Dharssini A.C | Engineering | Best Researcher Award

Ms. Vishnu Dharssini A.C | Engineering | Best Researcher Award

Thiagarajar College of Engineering | India

Author Profile

Scopus

Orcid

Google Scholar

Early Academic Pursuits

Ms. Vishnu Dharssini A.C has consistently demonstrated a passion for knowledge and excellence in her academic journey. Her pursuit of higher education in Electrical and Electronics Engineering began at Thiagarajar College of Engineering, Madurai, where she excelled academically. She was awarded a Silver Medal as the Best Outgoing Student of the Year 2021. Her dedication and outstanding performance were further recognized through awards for her achievements in the Anna University semestral examinations for two consecutive years, 2017 and 2018.

Professional Endeavors

Ms. Dharssini's professional endeavors are marked by her dedication to research and development in the field of Electrical and Electronics Engineering. She has engaged in various innovative projects, such as the simulation and analysis of a standalone microgrid for grid stability and modeling energy demand for an educational institution. Her current work focuses on an IoT-based demand side management and control scheme for smart grids. Additionally, she has gained valuable industrial exposure through her involvement in projects and collaborations.

Contributions and Research Focus

Ms. Dharssini has made significant contributions to the field of Electrical and Electronics Engineering, particularly in smart grid and renewable energy technologies. She is also exploring the burgeoning fields of machine learning and deep learning. Her research is supported by her proficiency in tools and software such as MATLAB, ETAP, Power World Simulator, Grafana, HOMER, DIG SILENT Power Factory Software, and PARAMICS. Her dedication to research is evident from her publications, which include two book chapters, seven conference papers, and five journal articles.

Accolades and Recognition

Ms. Dharssini's academic and research excellence have been widely recognized. In June 2023, she was selected for the "International Young Scientist Awards" under the category of "Best Researcher Award." Her commitment to continuous learning and skill enhancement is evident from her participation in numerous courses during the COVID-19 lockdown, including over five IEEE courses and five Coursera courses. Her efforts were further acknowledged when she received the "Savitha" scheme fellowship from Thiagarajar Research Fellowship in June 2022.

Impact and Influence

Ms. Dharssini's impact extends beyond her research contributions. She has actively participated in international conferences, where she has presented her work and engaged with the global academic community. Her involvement in initiatives such as the "Science and Technology Capacity Building for Industrial Needs" by the Tamil Nadu Council for Science and Technology in Chennai in 2019 highlights her commitment to applying her knowledge for industrial and societal benefits.

Legacy and Future Contributions

Ms. Vishnu Dharssini A.C's legacy in Electrical and Electronics Engineering is marked by her rigorous research, academic excellence, and dedication to continuous learning. As she continues her career, her contributions to smart grid technology, renewable energy systems, and the integration of machine learning in engineering are anticipated to advance the field significantly. Her ongoing research and professional endeavors promise to leave a lasting impact on the scientific community and pave the way for future innovations.

 

Notable Publications

Three-tier integrated demand-supply energy management for optimized energy usage in institutional building 2024

Smart Energy Source Management in a Commercial Building Microgrid 2024

An Investigation on Static Reconfiguration of Solar Photovoltaic Panels by Adopting Arithmetic Array Modelling 2023 (1)

Deployment of IoT-Based Smart Demand-Side Management System with an Enhanced Degree of User Comfort at an Educational Institution 2023 (4)

Energy Pattern Classification and Prediction in an Educational Institution using Deep Learning Framework 2022 (5)

 

 

Hafiz Muhammad Naveed | Economics, Econometrics and Finance | Best Research Award

Dr. Hafiz Muhammad Naveed | Economics, Econometrics and Finance | Best Research Award

Shenzhen University | China

Author Profile

Scopus

Google Scholar

Early Academic Pursuits

Dr. Hafiz Muhammad Naveed began his academic journey with a Bachelor (Hons) in Economics & Finance from the School of Economics, Islamia University, Bahawalpur (IUB), Pakistan, achieving a CGPA of 3.01/4.00. His dissertation focused on the impact of Foreign Direct Investment on Pakistan's economic growth, indicating an early interest in economic factors affecting national development. He continued his studies with a Master of Philosophy (M.Phil) in Business Administration, specializing in Finance, from the National College of Business Administration & Economics (NCBA&E), Lahore, Pakistan, with a CGPA of 3.5/4.0. His dissertation analyzed the impact of power shortages on capital flight in Pakistan.

Professional Endeavors

Dr. Naveed's teaching career started as a lecturer in Economics at the Punjab Group of Colleges, Fort Abbas Campus, Pakistan, from 2017 to 2019. He later became an English Teacher Assistant (ETA) and a Teaching Management Assistant (TMA) at Jiangsu University, China, from 2019 to 2023. During his tenure at Jiangsu University, he taught various subjects and assisted in writing academic papers for international journals. His excellence in teaching was recognized with an Excellent Teacher Award.

Contributions and Research Focus

Dr. Naveed's research primarily revolves around machine learning, deep learning, financial risk management, green finance, renewable energy, and environmental risk assessment. His PhD dissertation focused on financial system modeling using deep intelligent networks for financial predictions and assessments. He has authored several high-impact research publications, including: assessing the nexus between currency exchange rate returns, currency risk hedging, and international investments using intelligent networks; estimating the influence of the COVID-19 pandemic on financial markets with artificial neural networks; evaluating connectedness between currency risk hedging and firm value through deep neural networks; and analyzing the impact of the Russia-Ukraine War and COVID-19 on stock markets of G20 nations.

Accolades and Recognition

Dr. Naveed has received numerous awards and honors, including the 1st class presidential scholarship every year during his Ph.D. at Jiangsu University, China, due to his outstanding academic performance and social activities.

Impact and Influence

Dr. Naveed's work in integrating advanced computational techniques with financial analysis has significant implications for financial risk management and economic forecasting. His contributions to understanding the impacts of global crises, such as the COVID-19 pandemic and the Russia-Ukraine War, on financial markets have provided valuable insights for policymakers and investors.

Legacy and Future Contributions

Dr. Naveed's ongoing research and forthcoming publications, such as the financial modeling system using deep neural networks for financial risk assessments and green finance analysis, highlight his commitment to advancing the field of financial engineering. His work on sustainable development and environmental quality protection reflects his dedication to addressing global challenges through innovative research.

 

Notable Publications

Assessing the nexus between currency exchange rate returns, currency risk hedging and international investments: Intelligent network-based analysis 2024

The role of environmental knowledge, policies and regulations toward water resource management: A mediated-moderation of attitudes, perception, and sustainable consumption patterns 2024 (1)

Artificial neural network (ANN)-based estimation of the influence of COVID-19 pandemic on dynamic and emerging financial markets 2023 (11)

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Rudresh Dwivedi | Computer Science | Best Researcher Award

Assist Prof Dr. Rudresh Dwivedi | Computer Science | Best Researcher Award

Netaji Subhas University of Technology | India

Author Profile

Scopus

Orcid

Early Academic Pursuits

Dr. Rudresh Dwivedi's academic journey began with a Bachelor of Technology in Computer Science & Engineering from ICFAI University, Dehradun, India. He graduated in 2010 with a CGPA of 6.63/10. He then pursued a Master of Technology in Electrical Engineering from the National Institute of Technology (NIT), Raipur, India, graduating in 2013 with a CGPA of 8.63/10. His thesis, supervised by Dr. Narendra D. Londhe, focused on the classification of EEG-based multiclass motor imagery movements. Dr. Dwivedi furthered his academic career with a Ph.D. in Computer Science and Engineering from the Indian Institute of Technology (IIT), Indore, India, completing his doctoral studies in 2019 under the supervision of Dr. Somnath Dey. His Ph.D. thesis titled "Unimodal and Multimodal Biometric Verification Using Cancelable Iris and Fingerprint Templates" earned him a CGPA of 9.25/10.

Professional Endeavors

Dr. Dwivedi's professional career is marked by a blend of academic and industry experiences. His career commenced as a Software Engineer at Mars Web Solution, Bangalore, India, from August 2010 to March 2011. Transitioning to academia, he served as an Assistant Professor at NMIMS University, Maharashtra, India, in 2013. Following this, he was a Research Assistant at IIT Indore for a SERB-DST project focused on efficient cancelable template generation methods for fingerprint and iris biometrics. He then joined Pandit Deendayal Petroleum University (PDPU), Gandhinagar, Gujarat, India, as an Assistant Professor from July 2019 to August 2021. Currently, Dr. Dwivedi is an Assistant Professor in the Computer Science & Engineering Department at Netaji Subhas University of Technology, Dwarka, Delhi, India.

Contributions and Research Focus

Dr. Dwivedi has made significant contributions to the fields of biometrics, machine learning, and computer vision. His research has primarily focused on developing novel approaches for cancelable iris and fingerprint template generation, rotation-invariant iris code generation, and privacy-preserving biometric systems. He has also explored score-level and hybrid fusion schemes for protected multimodal biometric verification and secure communication systems using fingerprint-based cryptographic techniques. Additionally, his work on BCI (Brain-Computer Interface) systems has advanced the classification of EEG signals and the development of motor imagery-based systems.

Accolades and Recognition

Throughout his career, Dr. Dwivedi has received numerous awards and recognitions. These include the Third Prize at the Fifth IDRBT Doctoral Colloquium in 2015, the MHRD TA Fellowship for his Ph.D. studies, a Summer Research Fellowship at IIT Delhi in 2012, and a high percentile in the GATE 2011 exam, which secured him an MHRD TA Fellowship for his M.Tech. studies. He has also been awarded the State Meritorious Student Award and the National Talent Search Examination Scholarship during his early academic years.

Impact and Influence

Dr. Dwivedi's research has had a substantial impact on the field of biometric security, particularly in developing methods for protecting biometric templates. His work on cancelable biometrics and secure communication systems has contributed to enhancing privacy and security in biometric applications. His publications in esteemed journals and conferences have garnered attention and citations, reflecting his influence in the academic community.

Legacy and Future Contributions

Dr. Dwivedi's legacy is marked by his innovative contributions to biometric security and machine learning. His ongoing research continues to push the boundaries of these fields, promising further advancements in secure biometric systems and AI-based solutions. As a dedicated educator and researcher, Dr. Dwivedi's future contributions are anticipated to significantly impact both academia and industry, fostering the development of more secure and efficient biometric technologies.

 

Notable Publications

An efficient ensemble explainable AI (XAI) approach for morphed face detection 2024

Explainable AI (XAI): Core Ideas, Techniques and Solutions 2022 (161)

A Leaf Disease Detection Mechanism Based on L1-Norm Minimization Extreme Learning Machine 2021 (10)

A fingerprint based crypto-biometric system for secure communication 2019 (20)

Score-level fusion for cancelable multi-biometric verification 2019 (25)