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)

 

 

Merve Asiler | Computer Science | Best Researcher Award

Ms. Merve Asiler | Computer Science | Best Researcher Award

Middle East Technical University | Turkey

Author Profile

Orcid

Googler Scholar

Early Academic Pursuits

Ms. Merve Asiler's academic journey began with an impressive performance at Yıldırım Beyazıt Science High School in Ankara, Turkey, where she graduated at the top of her class. She continued her education at the Middle East Technical University (METU) in Ankara, Turkey, earning dual bachelor's degrees in Computer Engineering and Mathematics. During her undergraduate studies, she developed a strong interest in algorithms, computer organization, operating systems, and computer graphics. She pursued her Master’s degree in Computer Engineering at METU, specializing in Big Data and Graph Databases, and is currently working towards her Ph.D. in Computer Engineering with a focus on Computer Graphics, Computational Geometry, and Digital Geometry Processing.

Professional Endeavors

Merve Asiler has accumulated extensive professional experience in both academia and industry. She has worked as a Research and Teaching Assistant at METU, where she has contributed to various courses, including Introduction to Computer Engineering Concepts, C Programming, Algorithms, and Computer Engineering Design. Her industry experience includes roles as a Software Developer at Accelerate Simulation Technologies, Turkish Aerospace, and Kale Yazilim. These roles involved developing software for unmeshed CAD geometries, engaging in modeling and simulation activities, and handling complex queries in large graph databases using Neo4j.

Contributions and Research Focus

Ms. Asiler's research primarily revolves around computer graphics, computational geometry, and digital geometry processing. Her Ph.D. research focuses on geometric kernel computation in 3D space, developing algorithms that outperform current methods for kernel computation. Her Master's research involved developing BB-Graph, a new subgraph isomorphism algorithm for querying big graph databases. This work was done in collaboration with Kale Yazilim and demonstrated significant performance improvements over existing algorithms.

Accolades and Recognition

Ms. Asiler has been recognized for her academic excellence with a GPA of 3.93/4.00 in her Ph.D. studies and 3.71/4.00 in her Master's program. She has published significant research papers, including a study on 3D geometric kernel computation in polygon mesh structures and a subgraph isomorphism algorithm for querying big graph databases. Her work has been published in reputable journals like Computers & Graphics and the Journal of Big Data.

Impact and Influence

Ms. Asiler's contributions to computer science, particularly in the areas of computer graphics and big data, have had a significant impact on both academia and industry. Her research on geometric kernels and graph databases has advanced the understanding and application of these complex areas. As a teaching assistant, she has influenced and mentored numerous students, preparing original programming assignments and supervising student projects.

Legacy and Future Contributions

Looking ahead, Ms. Asiler plans to leverage her expertise in mesh kernels to explore novel solutions for non-self-intersecting shape interpolation and star-shape decomposition problems. Her future contributions are likely to continue pushing the boundaries of computational geometry and computer graphics, benefiting both academic research and practical applications in various industries. With her strong foundation and ongoing commitment to research, Ms. Asiler is poised to make lasting contributions to the field of computer science.

 

Notable Publications

3D geometric kernel computation in polygon mesh structures 2024

HyGraph: a subgraph isomorphism algorithm for efficiently querying big graph databases 2022 (3)