Bimal Kumar Dora | Engineering | Best Researcher Award

Mr. Bimal Kumar Dora | Engineering | Best Researcher Award

PhD at Visvesvaraya National Institute of Technology Nagpur, India

Bimal Kumar Dora is an emerging researcher in electrical engineering with a strong focus on power system optimization and renewable energy integration. Currently pursuing a PhD at Visvesvaraya National Institute of Technology, his research addresses critical challenges in developing a global electricity grid by integrating advanced machine learning and meta-heuristic algorithms. He has contributed significantly to academic literature through multiple publications in reputed international journals and conferences, emphasizing innovative solutions such as hybrid optimization techniques and robust algorithmic frameworks. His work bridges traditional power systems with modern computational methods, demonstrating both theoretical insight and practical application. Alongside his research, he actively participates in workshops and seminars that further enhance his expertise in control, power, and electric drives. His dedication is evidenced by prestigious fellowships and continuous professional development. Dora’s interdisciplinary approach and commitment to solving complex energy problems make him a promising candidate for future advancements in sustainable power systems.

Professional Profile 

Education

Bimal Kumar Dora’s academic journey reflects a dedicated and robust foundation in electrical engineering and research methodologies. He began his studies with a Diploma in Electrical Engineering from Odisha School of Mining Engineering, where he built his fundamental technical skills. Subsequently, he earned a Bachelor’s degree in Electrical Engineering from Gandhi Institute for Technological Advancement, further solidifying his expertise in the field. His academic progression continued with a Master of Technology from the National Institute of Technology Sikkim, where he specialized in Control, Power, and Electric Drives, achieving an outstanding CGPA and engaging in research on power system optimization. Currently, he is pursuing a PhD at Visvesvaraya National Institute of Technology, focusing on the global electricity grid and integrating innovative approaches in machine learning and meta-heuristic algorithms. This comprehensive educational background has equipped him with both theoretical knowledge and practical skills necessary for addressing complex challenges in sustainable energy systems.

Professional Experience

Bimal Kumar Dora’s professional experience exemplifies high-level research and practical applications in the electrical engineering domain. As a dedicated researcher, he has contributed to multiple international journals and conference proceedings, showcasing his work on power system optimization, renewable energy integration, and advanced algorithm development. His work has earned international acclaim. His research projects involve developing innovative hybrid algorithms such as the Exchange Market based Butterfly Optimization Algorithm, tested on standard IEEE systems and real-world power grids. Dora’s experience extends to collaborating with renowned academic institutions and industry experts, enhancing the translational impact of his work. In addition, he has participated in various workshops and seminars focused on control systems, power electronics, and emerging technologies. His technical proficiency in programming tools like Python and MATLAB reinforces his ability to tackle complex engineering challenges. Through professional development and engagement in cutting-edge research, he remains a key asset to the sustainable energy sector.

Research Interest

Mr. Bimal Kumar Dora’s research interests lie at the intersection of power system optimization, renewable energy integration, and advanced computational techniques. His work primarily focuses on developing efficient algorithms to tackle complex challenges in modern electrical grids, including the integration of renewable energy sources into a global electricity grid. He employs machine learning, meta-heuristic, and soft computing methods to design and implement innovative solutions for generation expansion planning and optimal reactive power dispatch. His exploration of hybrid optimization techniques—such as the Exchange Market based Butterfly Optimization Algorithm—demonstrates his commitment to enhancing system reliability and efficiency. By integrating traditional power system engineering with contemporary data-driven methodologies, his research addresses both theoretical and practical aspects of sustainable energy systems. This multidisciplinary approach not only contributes to academic literature but also offers tangible benefits for industry applications, making his work highly relevant in the evolving landscape of energy management and smart grid technologies.

Award and Honor

Throughout his academic and research career, Mr. Dora has received significant recognition for his dedication and innovative contributions. Notably, he qualified in the GATE examination in 2018, which paved the way for prestigious scholarships and fellowships. His academic excellence was further acknowledged through the AICTE GATE Scholarship awarded by MHRD during his M. Tech studies, reinforcing his capability in rigorous research and problem-solving. Currently, his potential is recognized with the MHRD Research Fellowship, an honor that supports his PhD work at Visvesvaraya National Institute of Technology. These awards not only underscore his technical proficiency and research acumen but also reflect his commitment to pushing the boundaries of electrical engineering. Such accolades serve as a testament to his ability to innovate and lead in the field of sustainable energy solutions, earning him respect and admiration among his peers and mentors.

Research Skill

Mr. Bimal Kumar Dora exhibits a robust set of research skills that are fundamental to his success as an emerging scholar in electrical engineering. His technical expertise spans a wide array of programming and simulation tools, including Python, MATLAB, and Octave, which he adeptly applies to model complex power systems and optimize performance. Proficient in using specialized software such as QGIS, MiPower, and Power World, he efficiently conducts simulations and analyses that support his research hypotheses. Additionally, his familiarity with real-time simulators like Typhon HIL and the Real-Time Transmission Line Simulator enhances his ability to test theoretical models under practical conditions. His skills extend to academic writing and presentation, supported by his proficiency in LATEX and MS Office. This comprehensive toolkit not only allows him to conduct innovative experiments and develop hybrid algorithms but also ensures that his findings are communicated effectively through high-impact publications and presentations at international conferences.

Conclusion

Bimal Kumar Dora demonstrates significant promise as a researcher with a strong foundation in innovative and interdisciplinary work. His solid academic record, impactful publications, and technical proficiency make him a compelling candidate for the Best Researcher Award. Addressing areas such as leadership in collaborative projects and extending the societal impact of his research could further elevate his profile. Overall, his achievements and ongoing commitment to advancing power system optimization and renewable energy integration mark him as a deserving contender for this recognition.

Publications Top Noted

Inverse Thresholding to Spectrogram for the Detection of Broken Rotor Bar in Induction Motor
Title: Inverse Thresholding to Spectrogram for the Detection of Broken Rotor Bar in Induction Motor
Authors: S Halder, S Bhat, BK Dora
Year: 2022
Citation Count: 18

An Enhanced Pathfinder Algorithm Based MCSA for Rotor Breakage Detection of Induction Motor
Title: An Enhanced Pathfinder Algorithm Based MCSA for Rotor Breakage Detection of Induction Motor
Authors: S Halder, BK Dora, S Bhat
Year: 2022
Citation Count: 15

Optimal Reactive Power Dispatch Problem Using Exchange Market Based Butterfly Optimization Algorithm
Title: Optimal Reactive Power Dispatch Problem Using Exchange Market Based Butterfly Optimization Algorithm
Authors: BK Dora, A Rajan, S Mallick, S Halder
Year: 2023
Citation Count: 14

Start-up Transient Analysis Using CWT and Ridges for Broken Rotor Bar Fault Diagnosis
Title: Start-up Transient Analysis Using CWT and Ridges for Broken Rotor Bar Fault Diagnosis
Authors: S Halder, S Bhat, B Dora
Year: 2023
Citation Count: 14

Solution of Reactive Power Dispatch Problems Using Enhanced Dwarf Mongoose Optimization Algorithm
Title: Solution of Reactive Power Dispatch Problems Using Enhanced Dwarf Mongoose Optimization Algorithm
Authors: BK Dora, S Bhat, S Halder, M Sahoo
Year: 2023
Citation Count: 13

A Solution to the Techno-Economic Generation Expansion Planning Using Enhanced Dwarf Mongoose Optimization Algorithm
Title: A Solution to the Techno-Economic Generation Expansion Planning Using Enhanced Dwarf Mongoose Optimization Algorithm
Authors: BK Dora, S Bhat, S Halder, I Srivastava
Year: 2022
Citation Count: 8

A Solution to Multi Objective Stochastic Optimal Power Flow Problem Using Mutualism and Elite Strategy Based Pelican Optimization Algorithm
Title: A Solution to Multi Objective Stochastic Optimal Power Flow Problem Using Mutualism and Elite Strategy Based Pelican Optimization Algorithm
Authors: BK Dora, S Bhat, S Halder, I Srivastava
Year: 2024
Citation Count: 6

Optimum Scheduling and Dispatch of Power Systems with Renewable Integration
Title: Optimum Scheduling and Dispatch of Power Systems with Renewable Integration
Authors: A Rajan, BK Dora
Year: 2022
Citation Count: 5

Prediction of Broken Rotor Bar in Induction Motor Using Spectral Entropy Features and TLBO Optimized SVM
Title: Prediction of Broken Rotor Bar in Induction Motor Using Spectral Entropy Features and TLBO Optimized SVM
Authors: S Halder, S Bhat, B Dora
Year: 2022
Citation Count: 3

An Enhanced Path Finder Algorithm for the Estimation of the Stator Current Envelope to Detect Rotor Bar Breakage in an Induction Motor
Title: An Enhanced Path Finder Algorithm for the Estimation of the Stator Current Envelope to Detect Rotor Bar Breakage in an Induction Motor
Authors: S Halder, BK Dora, S Bhat
Year: 2024
Citation Count: 2

Jun Dai | Engineering | Best Researcher Award

Assoc. Prof. Dr. Jun Dai | Engineering | Best Researcher Award

Associate Professor at Beijing institute of technology, China

Dr. Jun Dai is a distinguished researcher whose work has significantly advanced the fields of microfabrication, superconducting devices, and microsystem dynamics. He has built a robust reputation through his innovative research and diverse expertise in smart materials and MEMS technologies. Over the course of his career, Dr. Dai has secured 15 patents, authored 16 refereed journal articles, and delivered more than 30 technical presentations at both national and international conferences. His research is backed by multiple prestigious national projects, including those funded by the National Natural Science Foundation of China and the National Key R&D Program of China, which attest to his leadership and vision in addressing complex engineering challenges. By consistently pushing the boundaries of technology, Dr. Dai has made enduring contributions that benefit academic institutions, industry partners, and the broader scientific community, setting a high standard for excellence and innovation. His exemplary record consistently inspires future researchers worldwide.

Professional Profile 

Education

Dr. Jun Dai’s academic journey laid a robust foundation for his innovative career in engineering and technology. He earned his master’s degree in Mechatronical Engineering from Beijing Institute of Technology in 2010, where he developed a strong background in system dynamics and smart materials. Building on this expertise, he pursued a Ph.D. in Mechanical Engineering at the University of Tokyo, graduating in 2013. His doctoral research, which centered on microfabrication, superconducting devices, and focused-ion-beam chemical vapor deposition, showcased his ability to tackle complex engineering challenges with precision and creativity. Throughout his studies, Dr. Dai was recognized with prestigious awards and scholarships, including support from the China National Scholarship and the China Scholarship Council, affirming his academic excellence. This rigorous educational experience not only honed his technical skills but also instilled a passion for research and innovation that continues to drive his groundbreaking contributions to science and technology. Inspiring his future.

Professional Experience

Dr. Jun Dai’s professional journey is marked by rapid career progression and significant contributions to academia and industry. Beginning his career as a lecturer at Beijing Institute of Technology in 2013, he quickly demonstrated exceptional research and teaching capabilities, leading to his promotion to Associate Professor in 2018. His experience as a visiting researcher at the University of Tokyo in 2015 and 2019 further enriched his international perspective and collaborative skills. Dr. Dai has led high-profile research projects funded by prestigious organizations such as the National Natural Science Foundation of China and the National Key R&D Program of China, underscoring his leadership and innovation. In addition to his research accomplishments, he contributes to the academic community through roles on technical program committees, session chair positions, and as an evaluation expert for major funding bodies. His professional experience reflects a commitment to excellence, interdisciplinary collaboration, and innovation, driving future technological progress.

Research Interest

Dr. Jun Dai’s research interests focus on the integration of microscale engineering and advanced materials science, addressing fundamental challenges in device miniaturization and smart system design. His work spans microfabrication, superconducting devices, and focused-ion-beam chemical vapor deposition, enabling the creation of innovative nanoscale components. Dr. Dai is passionate about exploring the dynamics of microsystems, where the interplay between thermal, electrical, and mechanical fields can be harnessed for enhanced device performance. His research projects include developing thermally driven MEMS optical switches and investigating energy conversion mechanisms in rotary magnetorheological actuators. In addition, he is involved in research on nanoresonator coupling with superconducting circuits and the design of intelligent control systems for high-speed magnetic liquid seals. Through this interdisciplinary approach, Dr. Dai aims to push the boundaries of microelectromechanical systems, contributing both theoretical insights and practical solutions that advance modern engineering applications. His innovative approach continues to inspire new developments and collaborative research efforts.

Award and Honor

Dr. Jun Dai has been recognized with numerous awards and honors that reflect his exceptional contributions to engineering research and innovation. Throughout his career, he has received prestigious accolades, including the China National Scholarship from the China Scholarship Council during his doctoral studies and the JASSO Follow-up Research Fellowship, which recognized his promising research potential. These honors affirm his commitment to excellence and his role as a leading innovator in microfabrication, superconducting devices, and MEMS technology. His recognition extends beyond national boundaries, as international collaborations and accolades have further underscored his impact on the global research community. Dr. Dai’s award portfolio not only celebrates his technical achievements but also highlights his leadership, creative problem-solving, and dedication to advancing microsystem dynamics. These awards serve as a testament to his outstanding research capabilities and inspire both peers and emerging scientists to pursue groundbreaking work in modern engineering disciplines, earning further international prestige.

Research Skill

Dr. Jun Dai demonstrates an impressive array of research skills that combine rigorous theoretical analysis with innovative experimental techniques. His proficiency in microfabrication, particularly using focused-ion-beam chemical vapor deposition, allows him to develop advanced superconducting nanodevices with exceptional precision. Dr. Dai’s expertise spans multiple disciplines, including mechanical engineering, materials science, and electronics, enabling him to tackle complex problems in microsystems and smart material-based devices. He excels in designing controlled experiments, utilizing state-of-the-art instrumentation, and employing sophisticated data analysis methods to validate his hypotheses. His ability to lead large-scale, multidisciplinary projects and secure funding from prestigious bodies such as the National Natural Science Foundation of China is a testament to his research acumen. Furthermore, his strong communication skills are evident in his extensive publication record and international conference presentations, which reflect his commitment to advancing scientific knowledge and fostering collaboration across diverse research fields, demonstrating mastery in innovative research techniques successfully.

Conclusion

Dr. Jun Dai presents a compelling case for the Best Researcher Award. His strong academic credentials, innovative research portfolio, impressive publication and patent record, and significant professional service mark him as an outstanding contributor to his field. With minor enhancements in collaborative efforts, mentorship, and thematic diversification, his already exemplary record positions him as a highly suitable candidate for the award.

Publications Top Noted

Publication 1:
Authors: Wenwu Wang; Zeyu Ma; Qi Shao; Jiangwang Wang; Leixin Wu; Xiyao Huang; Zilu Hu; Nan Jiang; Jun Dai; Liang HE
Year: 2024
Citation: “Multi-MXene assisted large-scale manufacturing of electrochemical biosensors based on enzyme-nanoflower enhanced electrodes for the detection of H₂O₂ secreted from live cancer cells,” Nanoscale, 2024, DOI: 10.1039/d4nr01328j

Publication 2:
Authors: Kai Yang; Zhe Zhu; Xin He; Ruiqi Song; Xiaoqiao Liao; Leixin Wu; Yixue Duan; Chuan Zhao; Muhammad Tahir; Jun Dai et al.
Year: 2024
Citation: “High-performance zinc metal anode enabled by large-scale integration of superior ion transport layer,” Chemical Engineering Journal, July 2024, DOI: 10.1016/j.cej.2024.152114

Publication 3:
Authors: Zeyu Ma; Wenwu Wang; Yibo Xiong; Yihao Long; Qi Shao; Leixin Wu; Jiangwang Wang; Peng Tian; Arif Ullah Khan; Wenhao Yang et al.
Year: 2024
Citation: “Carbon Micro/Nano Machining toward Miniaturized Device: Structural Engineering, Large‐Scale Fabrication, and Performance Optimization,” Small, July 19, 2024, DOI: 10.1002/smll.202400179

Publication 4:
Authors: Haitian Long; Song Tian; Qiulei Cheng; Lingfei Qi; Jun Dai; Yuan Wang; Ping Wang; Sheng Liu; Mingyuan Gao; Yuhua Sun
Year: 2024
Citation: “Highly durable and efficient power management friction energy harvester,” Nano Energy, May 2024, DOI: 10.1016/j.nanoen.2024.109363

Publication 5:
Authors: Tairong Zhu; Tong Wu; Zheng Gao; Jianwen Wu; Qiaofeng Xie; Jun Dai
Year: 2024
Citation: “Anti-sedimentation mechanism of rotary magnetorheological brake integrating multi-helix microstructure,” International Journal of Mechanical Sciences, March 2024, DOI: 10.1016/j.ijmecsci.2024.108980

Publication 6:
Authors: Jun Dai; Changlei Feng; Jin Xie; Mingyuan Gao; Tao Zhen
Year: 2023
Citation: “Design and Control of an Analog Optical Switch Based on the Coupling of an Electrothermal Actuator and a Mass–Spring System,” IEEE/ASME Transactions on Mechatronics, 2023, DOI: 10.1109/tmech.2023.3238109

Publication 7:
Authors: Shuai Yang; Yumei Li; Ling Deng; Song Tian; Ye Yao; Fan Yang; Changlei Feng; Jun Dai; Ping Wang; Mingyuan Gao
Year: 2023
Citation: “Flexible thermoelectric generator and energy management electronics powered by body heat,” Microsystems & Nanoengineering, August 24, 2023, DOI: 10.1038/s41378-023-00583-3