Arush Kaushal | Machine Learning | Young Scientist Award Published on 22/10/202422/10/2024 by ScienceFather Arush Kaushal | Machine Learning | Young Scientist Award Mr. Arush Kaushal , Jaypee University of Information Technology, Solan, India. Arush Kaushal is a dedicated Assistant Professor at OPIT (Open Institute of Technology), specializing in Data Science and Machine Learning. With a robust academic background, including a Ph.D. in Computer Science, he has extensive teaching experience at various institutions, including Jaypee University and Chandigarh University. Arush is passionate about leveraging technology for societal impact, as demonstrated by his research in landslide prediction and earthquake detection using machine learning techniques. His commitment to education and innovation is reflected in his roles as a coding tutor and research intern. Publication profile Scopus Education Ph.D. (CSE) Jaypee University of Information Technology, Solan, HP (08/2021 – Present) M.Tech (CSE) Jaypee University of Information Technology, Solan, HP (07/2019 – 06/2021) B.Tech (CSE) Jaypee University of Information Technology, Solan, HP (07/2015 – 05/2019) Experience Assistant Professor OPIT (Open Institute of Technology) (08/2024 – Present) Coding Tutor Tutorpedia (05/2024 – 08/2024) Teaching Assistant Jaypee University of Information Technology (03/2023 – Present) Assistant Professor Chandigarh University (01/2022 – 10/2022) Software Engineer NSDF (National Skill Development Forum) (08/2021 – 01/2022) Research Intern Jaypee University of Information Technology (07/2020 – 07/2021) Suitability For The Award Arush Kaushal is a dedicated researcher and educator in the field of Computer Science and Engineering, with significant contributions to Machine Learning and Artificial Intelligence. His academic journey, combined with practical experience and research achievements, positions him as a strong candidate for the Young Scientists Award. Professional Development () Arush Kaushal is actively engaged in professional development, focusing on enhancing his skills in Machine Learning, Data Science, and Computer Vision. He has taught various courses, including Python and Artificial Intelligence, while also developing innovative solutions for real-time landslide prediction and earthquake detection. His dedication to teaching and research is reflected in his active participation in academic conferences, where he has published papers on landslide susceptibility detection. Arush is committed to fostering collaboration and knowledge-sharing in the field, continually striving for excellence in both education and research. Research Focus Arush Kaushal’s research focuses primarily on applying Machine Learning and Deep Learning techniques to environmental challenges, particularly in landslide prediction and earthquake detection. His innovative projects aim to enhance early warning systems using advanced data analytics and sensor networks, showcasing the potential of technology in mitigating natural disasters. By exploring classifiers in conjunction with object detectors, Arush contributes to the growing field of intelligent systems, aiming for societal benefits through his findings. His work highlights the intersection of technology and environmental safety, striving to make a meaningful impact on communities vulnerable to natural hazards. Awards and Honors () IEEE Conference Landslide Susceptibility Detection Using ResNet IEEE Conference Threshold Based Real-Time Landslide Prediction System Using Low-Cost Sensor Networks Publications Exploiting the synergy of SARIMA and XGBoost for spatiotemporal earthquake time series forecasting Cited by: 0 | Published in: 2024 Threshold Based Real-Time Landslide Prediction System Using Low-Cost Sensor Networks Cited by: 0 | Published in: 2023 Landslide Susceptibility Detection Using ResNet Cited by: 1 | Published in: 2023
Sheng-Lung Peng | Artificial Intelligence | Best Researcher Award Published on 19/10/202419/10/2024 by ScienceFather Sheng-Lung Peng | Artificial Intelligence | Best Researcher Award Prof. Sheng-Lung Peng, School of Innovative Design and Management at National Taipei University of Business, Taiwan . Sheng-Lung Peng is a Professor at the Department of Creative Technologies and Product Design, and Dean of the School of Innovative Design and Management at National Taipei University of Business, Taiwan. With a BS in Mathematics and an MS/PhD in Computer Science, he is a prominent figure in algorithm design, bioinformatics, and artificial intelligence. He holds multiple honorary and adjunct professor roles in Taiwan, China, and India, and is a leader in various computing associations. He has also edited and reviewed for leading journals. His work bridges academic innovation and real-world applications. Publication profile Orcid Education and Experience BS in Mathematics – National Tsing Hua University MS in Computer Science and Information Engineering – National Chung Cheng University PhD in Computer Science – National Tsing Hua University Honorary Professor – Beijing Information Science and Technology University Visiting Professor – Ningxia Institute of Science and Technology, China Adjunct Professor – National Dong Hwa University, Taiwan & Kazi Nazrul University, India Honorary Adjunct Professor – Sir Padampat Singhania University & Baroda University, India Suitability for The Award Dr. Sheng-Lung Peng’s extensive academic and professional achievements make him a strong candidate for the Best Researcher Award. His contributions to the fields of algorithm design, artificial intelligence, bioinformatics, and data mining demonstrate a profound impact on both academic research and practical applications. Professional Development () Dr. Sheng-Lung Peng has played a pivotal role in shaping computational education and research globally. He is the President of the Taiwan Computer Programming Contest and the Association of Algorithms and Computation Theory, as well as the Co-director of the ICPC Asia Pacific. In his editorial work, he has contributed to numerous top-tier journals like IEEE Internet of Things Magazine and Computers and Electrical Engineering. His leadership in the fields of cloud computing and information literacy, coupled with his involvement in international academic collaborations, reflects his commitment to advancing global computing knowledge. Research Focus Sheng-Lung Peng’s research interests lie at the intersection of algorithm design, artificial intelligence, bioinformatics, combinatorics, data mining, and networking. His work focuses on creating efficient algorithms to solve complex problems in these fields. His innovations have contributed significantly to advancements in bioinformatics, helping analyze biological data more effectively, and artificial intelligence, improving machine learning models and data processing. His contributions in combinatorics and data mining have expanded the frontiers of knowledge in both theoretical and applied domains. Awards and Honors () Honorary Professor – Beijing Information Science and Technology University Visiting Professor – Ningxia Institute of Science and Technology, China President – Association of Taiwan Computer Programming Contest Co-director – ICPC Asia Pacific Adjunct Professor – Sir Padampat Singhania University, Baroda University, India Director – Institute of Information and Computing Machinery Supervisor – Chinese Information Literacy Association Publication Privacy-Preserving Authentication Based on PUF for VANETs – Future Internet, 2024. Cited by: N/A On the d-Claw Vertex Deletion Problem – Algorithmica, 2024. Cited by: N/A SAHA: An SDN Enabled Fog Architecture for Healthcare Applications – Conference Paper, 2024. Cited by: N/A Model Compression Algorithm via Reinforcement Learning and Knowledge Distillation – Mathematics, 2023. Cited by: N/A Depth Map Super-Resolution Based on Semi-Couple Deformable Convolution Networks – Mathematics, 2023. Cited by: N/A A Novel Channel Pruning Compression Algorithm Combined with an Attention Mechanism – Electronics, 2023. Cited by: N/A A Compact Parallel Pruning Scheme for Deep Learning Model and Its Mobile Instrument Deployment – Mathematics, 2022. Cited by: 4 Adaptive Aggregate Stereo Matching Network with Depth Map Super-Resolution – Sensors, 2022. Cited by: 7 Smart and Future Applications of Internet of Multimedia Things (IoMT) Using Big Data Analytics – Sensors, 2022. Cited by: 10 A Novel Fusion Pruning Algorithm Based on Information Entropy Stratification and IoT Application – Electronics, 2022. Cited by: 9