Dong-Bin Kwak | Mechanical Engineering | Best Researcher Award

Dong-Bin Kwak | Mechanical Engineering | Best Researcher Award

Assist. Prof. Dr Dong-Bin Kwak, Seoul National University of Science and Technology, South Korea

Assist. Prof. Dr. Dong-Bin Kwak ๐ŸŽ“๐Ÿ”ฌ is a dedicated mechanical engineer specializing in nanoparticle engineering and filtration systems. He earned his Ph.D. from the University of Minnesota ๐Ÿซ (2017-2023) and his B.Sc. summa cum laude ๐ŸŽ–๏ธ from Hanyang University (2011-2017). Currently, he is an Assistant Professor at Seoul National University of Science and Technology ๐Ÿ“š, leading the Nanoparticle Engineering Laboratory. His cutting-edge research focuses on air filtration, hydrosol measurements, and heat sink optimization ๐Ÿ’จโš™๏ธ. Dr. Kwak is a recipient of the Young Scientist Award ๐Ÿ† and the AFS Fellowship. He has authored impactful publications and delivered numerous invited talks globally ๐ŸŒ.

Publication Profile

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Education

Assist. Prof. Dr. Dong-Bin Kwak is an accomplished mechanical engineer with an impressive academic journey ๐Ÿ“š. He earned his Ph.D. in Mechanical Engineering from the University of Minnesota, Twin Cities, USA (Sep. 2017 – Jan. 2023) ๐ŸŒ๐Ÿ”ง. Prior to this, he completed his Bachelor of Science in Mechanical Engineering with summa cum laude honors at Hanyang University, Seoul, Korea (Mar. 2011 – Feb. 2017) ๐ŸŒŸ๐Ÿ’ผ. His dedication to excellence and innovation has marked his academic and professional endeavors ๐Ÿ’ก. With expertise in mechanical engineering and a global education, Dr. Kwak continues to make impactful contributions to the field ๐Ÿ› ๏ธ๐Ÿ“ˆ.

Research and Project Experience

Assist. Prof. Dr. Dong-Bin Kwak is an esteemed Assistant Professor at Seoul National University of Science and Technology, leading the Nanoparticle Engineering Laboratory (NEL) ๐ŸŽ“. His research spans air filtration systems ๐Ÿ’จ, CMP-slurry filtration ๐ŸŒŽ, and nanoparticle measurement ๐Ÿ”ข, supported by LG and Samsung Electronics. Dr. Kwak optimizes filtration efficiency under varying humidity ๐ŸŒช and temperature โ˜€๏ธ and pioneers AI-based heat sink designs ๐Ÿงฎ. With expertise from roles at Onto Innovation ๐ŸŒŸ and the University of Minnesota, he advanced automated optical inspection ๐Ÿ‘๏ธ and contamination control ๐Ÿ’ง. His work also explores COVID-19 ventilation optimization ๐Ÿฆ  and electrospun nanofiber filtration. Dr. Kwak is a trailblazer in environmental and thermal engineering ๐Ÿซ๐Ÿ”„.

Awards

Assist. Prof. Dr. Dong-Bin has earned numerous prestigious accolades ๐Ÿ† throughout his academic and professional journey. He received the Young Scientist Award from KSMPE in Dec. 2024 ๐Ÿงช and the AFS Fellowship twice (2019, 2023) ๐ŸŒ. Notably, he was honored with the Mechanical Engineering Fellowship and Honorary Hanyang Study Abroad Scholarship (2017-2018) ๐Ÿ“š. His excellence began early, winning the National Engineering Fully Funded Scholarship (2011-2017) ๐Ÿ› ๏ธ and multiple awards at Hanyang University, including the Presidentโ€™s List Scholarship ๐Ÿฅ‡. His achievements span Best Design ๐Ÿ…, Capstone Chief Award ๐ŸŽ“, and Excellence Awards in competitions ๐Ÿ—๏ธ. He also received the Best Tutor Award for Engineering Mathematics ๐Ÿ“.

Collaborations & Teaching ๐Ÿ“šย 

Assist. Prof. Dr. Dong-Bin Kwak fosters innovation through impactful collaborations with industry giants like Samsung and LG ๐Ÿค๐Ÿ’ก. His commitment to nurturing future leaders is evident through his mentorship of undergraduate students ๐ŸŽ“โœจ. Dr. Kwak has shared his expertise as a professor at Seoul National University of Science and Technology ๐Ÿซ๐Ÿ‡ฐ๐Ÿ‡ท and as a course instructor at the University of Minnesota ๐Ÿ“š๐Ÿ‡บ๐Ÿ‡ธ. These roles highlight his dedication to academic growth and knowledge dissemination ๐Ÿ“–๐Ÿง‘โ€๐Ÿซ. By bridging academia and industry, Dr. Kwak continues to drive technological advancements and inspire the next generation of innovators ๐Ÿš€๐Ÿ”ฌ.

Research Focus

Assist. Prof. Dr. Dong-Bin Kwak’s research focuses on thermal management systems, nanoparticle behavior, and nanofiber filtration technology ๐Ÿ”ฌ๐ŸŒก๏ธ. His studies include improving nanofiber filter performance ๐Ÿงต๐Ÿ”, modeling inverse heat conduction for irregular structures ๐Ÿ—๏ธ๐Ÿ”ฅ, and optimizing radial heat sinks with triangular fins for efficient cooling ๐ŸŒ€โ„๏ธ. Dr. Kwak also investigates nanoparticle transport, deposition, and pressure drop across sharp-bent tubes and membranes, contributing to filtration efficiency and thermal sciences ๐Ÿงช๐Ÿ“Š. His interdisciplinary work advances air quality, heat transfer, and filtration systems, addressing real-world challenges in energy and environmental engineering ๐ŸŒโš™๏ธ. His findings aid in optimizing industrial systems and cutting-edge filtration technologies ๐Ÿญโœจ.

Publication top notes

Nanofiber filter performance improvement: nanofiber layer uniformity and branched nanofiber

Inverse heat conduction modeling to predict heat flux in a hollow cylindrical tube having irregular cross-sections

Cooling performance of a radial heat sink with triangular fins on a circular base at various installation angles

Numerical investigation of nanoparticle deposition location and pattern on a sharp-bent tube wall

Optimization of the radial heat sink with a concentric cylinder and triangular fins installed on a circular base

Natural convection flow around heated disk in cubical enclosure

Characterization of colloidal nanoparticles in mixtures with polydisperse and multimodal size distributions using a particle tracking analysis and electrospray-scanningย โ€ฆ

Influence of colloidal particles with bimodal size distributions on retention and pressure drop in ultrafiltration membranes

Experimental study of nanoparticle transport and penetration efficiency on a sharp-bent tube (elbow connection)

Modeling pressure drop values across ultra-thin nanofiber filters with various ranges of filtration parameters under an aerodynamic slip effect

 

 

Sandeep Jain | Engineering and Technology | Best Researcher Award

Sandeep Jain | Engineering and Technology | Best Researcher Award

Dr Sandeep Jain, Sungkyunkwan University, Republic of Korea, South Korea

Dr. Sandeep Jain is a metallurgical engineer and researcher with expertise in machine learning applications in alloy design, lightweight materials, and high-entropy alloys. He holds a Ph.D. (2023) and M.Tech. (2017) from IIT Indore and a B.E. in Mechanical Engineering (2013). Currently a Postdoctoral Researcher at Sungkyunkwan University, South Korea, Dr. Jain focuses on designing multicomponent alloys and optimizing manufacturing processes. He has published extensively, including works on machine learning-driven phase prediction and flow stress modeling. Dr. Jain is a guest editor, reviewer for leading journals, and recipient of prestigious awards like the Global Best Achievement Award 2024. ๐Ÿงช๐Ÿค–๐ŸŒ

Publication Profile

Orcid

Education

Dr. Sandeep Jain is a dedicated scholar with a robust academic background in engineering. ๐ŸŽ“ He earned his Ph.D. (2017-2023) and M.Tech (2015-2017) in Metallurgical Engineering and Materials Science from the prestigious Indian Institute of Technology Indore, achieving impressive CGPAs of 8.67 and 8.75, respectively. ๐Ÿ“˜โœจ His journey in engineering began with a B.E. in Mechanical Engineering from MBM Engineering College, Jodhpur (2009-2013), where he secured a commendable 68% score. ๐Ÿ”ง๐Ÿ“š Dr. Jainโ€™s academic excellence reflects his passion for materials science and mechanical engineering, laying a solid foundation for impactful contributions to his field. ๐Ÿš€๐Ÿ”ฌ

Research Experience

Dr. Sandeep Jain, currently a Postdoctoral Researcher at Sungkyunkwan University, South Korea ๐Ÿ‡ฐ๐Ÿ‡ท, specializes in designing lightweight multicomponent alloys and optimizing injection molding processes using machine learning ๐Ÿค–. As a Research Associate at IIT Delhi ๐Ÿ‡ฎ๐Ÿ‡ณ, he analyzed the mechanical and creep behavior of Ni-based superalloys and pioneered sustainable rose gold plating methods ๐ŸŒŸ. His tenure at IIT Indore included designing lightweight Ni-based alloys and conducting advanced phase equilibria studies ๐Ÿ”ฌ. Dr. Jainโ€™s expertise extends to simulation tools like ANSYS Fluent, XRD, and EBSD, contributing to innovative and sustainable material development ๐ŸŒ.

Teaching Experience

Dr. Sandeep Jain has an extensive teaching background in materials science and engineering. As a Teaching Assistant at the Indian Institute of Technology Indore (Dec 2017โ€“Nov 2022 and July 2015โ€“June 2017), he contributed to courses like Solidification and Phase Field Modelling, Computational Methods for Materials, and Physical Metallurgy. His expertise also spans practical modules, including Mechanical Workshop, Casting and Welding Lab. Earlier, he served as a Guest Faculty at Govt. Engineering College, Ajmer (Aug 2013โ€“June 2014), teaching Material Science, Engineering Mechanics, Strength of Materials, and more. Dr. Jainโ€™s dedication to education blends technical knowledge with hands-on experience. ๐ŸŽ“๐Ÿ› ๏ธ๐Ÿ“š

Awards / Fellowships

Dr. Sandeep Jain has earned prestigious accolades for his outstanding achievements in academia and research. In 2024, he was honored with the Global Best Achievement Awards ๐ŸŽ–๏ธ๐ŸŒŸ, recognizing his contributions to his field. His academic journey has been supported by prestigious fellowships, including the Ph.D. Fellowship ๐Ÿง‘โ€๐ŸŽ“๐Ÿ“š and the M.Tech. Fellowship ๐ŸŽ“๐Ÿ”ฌ, both awarded by the Ministry of Human Resource Development (MHRD), Government of India. These honors highlight his dedication, innovation, and excellence in advancing knowledge and contributing to societal progress. Dr. Jain’s achievements continue to inspire and set benchmarks for aspiring scholars worldwide. ๐Ÿš€๐Ÿ“–

Research Focus

Dr. Sandeep Jain’s research focuses on the development and application of machine learning techniques to predict mechanical properties in lightweight alloys and high entropy alloys. His studies include hardness prediction, flow stress, phase prediction, and the influence of processing methods like friction stir processing. These investigations aim to enhance the performance of advanced materials such as Al-Mg-based alloys and CoCrFeNiV high entropy alloys. His work bridges the gap between experimental studies and computational simulations, contributing valuable insights into alloy design and optimization. ๐ŸŒŸ๐Ÿ”๐Ÿ“Š

Publication Top Notes

A Machine Learning Perspective on Hardness Prediction in Advanced Multicomponent Al-Mg Based Lightweight Alloys