Mr. Xiaoyin Zheng | Computer Vision Awards | Best Researcher Award

Mr. Xiaoyin Zheng | Computer Vision Awards | Best Researcher Award

Mr. Xiaoyin Zheng, XMotors.ai, United States

Mr. Xiaoyin Zheng is a skilled Computer Vision Algorithm Engineer at XMotors.ai, where he focuses on integrating deep learning for advanced cabin monitoring and driver state analysis. With an M.S. in Engineering Technology from Purdue University and a Bachelor’s in Automotive Engineering from Wuhan University of Technology, Xiaoyin excels in Python, C, C++, and MATLAB/Simulink. His technical expertise encompasses computer vision and deep learning, particularly in object classification, detection, and tracking. Xiaoyinā€™s notable research includes autonomous vehicle simulators and lithium battery estimation, and he has achieved recognition with a first prize at the GM Tech Center competition. Additionally, his experience as a Graduate Teaching Assistant at Purdue University underscores his dedication to advancing engineering education and technology.

šŸŒ Professional Profile:
Google Scholar

šŸŽ“ Education:

Xiaoyin Zheng earned his M.S. in Engineering Technology from Purdue University, specializing in robotics and self-driving technology. He also holds a Bachelor’s in Automotive Engineering from Wuhan University of Technology.

šŸ”¬ Technical Skills:

Xiaoyin is proficient in Python, C, C++, and MATLAB/Simulink. His expertise includes computer vision and deep learning, with a focus on object classification, detection, segmentation, tracking, and model acceleration.

šŸ’¼ Professional Experience:

Xiaoyin is currently a Computer Vision Algorithm Engineer at XMotors.ai, where he integrates deep learning into cabin monitoring systems and improves driver state monitoring through advanced data processing. Previously, he interned as a Mechanical Engineer at Along Aircraft Manufacturing Company, where he worked on airplane mechanical parts and fly test approvals.

šŸ”¬ Research Experience:

His research includes developing simulators for autonomous vehicle dynamics and lithium battery state-of-charge estimation using extended Kalman filtering. He also contributed to designing a foldable personal mobility device, winning first prize at the GM Tech Center competition.

šŸ“š Teaching Experience:

As a Graduate Teaching Assistant at Purdue University, Xiaoyin taught Automated Manufacturing Processes and Applied Statics, guiding students in CNC operations, CAD design, and fundamental engineering concepts.

šŸ† Achievements:

Xiaoyin’s innovative work in robotics and autonomous systems, coupled with his successful research and teaching roles, highlights his commitment to advancing engineering technology and education.

Publication Top Notes:

Lithium battery soc estimation based on extended kalman filtering algorithm
  • Year: 2018
  • Citations: 27
Multi-scale fractal characteristics of the pore system in low-permeability conglomerates from the junggar basin
  • Year: 2023
  • Citations: 2
Anything in Any Scene: Photorealistic Video Object Insertion
  • Year: 2024
A Minimal Set of Parameters Based Depth-Dependent Distortion Model and Its Calibration Method for Stereo Vision Systems
  • Year: 2024

 

 

 

Mr. Sanket Kachole | Computer Vision | Best Researcher Award

Mr. Sanket Kachole | Computer Vision | Best Researcher Award

Mr. Sanket Kachole, Kingston University, United Kingdom

āœØ Mr. Sanket Kachole is a seasoned researcher and data scientist with a rich background in neuromorphic vision and robotics. His Ph.D. journey was marked by expertise in data collection, annotation, and advanced model training, evident in his publications on Generative Neural Networks, Transformers, Multi-modal networks, Graph Neural Networks, and Spiking Neural Networks. From a Research Assistant at Kingston University to a Data Scientist at Santander Group, Sanket has consistently driven innovation using machine learning, computer vision, and NLP. His accolades include the prestigious Best Paper award at a CVPR workshop, highlighting his impactful contributions to the field. šŸ§ šŸ¤–

šŸŽ“Education :Ā 

šŸ“š Sanket Kachole is a trailblazer in the field of Artificial Intelligence, having pursued his Ph.D. in the subject at Kingston University, United Kingdom, from 2020 to 2023. His doctoral research delved into the realm of neuromorphic vision systems, with a focus on advancing autonomous perception in robotics. The culmination of his academic journey showcased in his thesis titled “Advancing Autonomous Perception in Robotics through Neuromorphic Vision Systems.” Prior to his Ph.D., Sanket earned his M.Sc. in Advanced Engineering from Kingston University (2017ā€“2019), where his dissertation explored a computer vision approach to monitoring the activity and well-being of honeybees. šŸŽ“šŸ¤–šŸ

šŸŒ Professional Profiles :Ā 

Google Scholar

Linkedin

šŸ† Awards and Achievement :

šŸŒ Sanket Kachole’s stellar career is punctuated by noteworthy achievements and accolades. In 2023, he clinched the prestigious Best Paper Award at the CVPR Event based Vision Workshop in Vancouver, Canada, showcasing his outstanding contributions to the field. His adept presentation skills were further recognized with the Best Oral Presentation Award at the ECE Conference hosted by Kingston University. Sanket’s commitment to cutting-edge research has been acknowledged through significant funding awards, including the Distinguished Research Achievement and Funding Award, as well as the Faculty Research Student Conference and Training Fund, both bestowed by Kingston University. šŸ†šŸ“„šŸ’”

šŸ§  Research Interests šŸ”¬šŸŒ :

šŸ”¬ Sanket Kachole’s passion lies at the intersection of cutting-edge technologies, with a primary focus on Artificial Intelligence, Robotics, Computer Vision, and Machine Learning. His research interests reflect a dynamic exploration of the realms where intelligent systems and computational algorithms converge, driving innovation in fields crucial to the future. šŸ¤–šŸ‘ļøā€šŸ—ØļøšŸ§ 

Google Scholar Metrics:

  • All Time:
    • Citations: 16 šŸ“–
    • h-index: 3 šŸ“Š
  • Since 2018:
    • Citations: 16 šŸ“–
    • h-index: 3 šŸ“Š

šŸ‘Øā€šŸ« A prolific researcher with significant impact and contributions in the field, as evidenced by citation metrics. šŸŒšŸ”¬

Publications ( Top Note ) :

1.Ā  A Neuromorphic Dataset for Object Segmentation in Indoor Cluttered Environment

Published: 2023, Journal: arXiv preprint, Cited By: 6

2.Ā  Event augmentation for contact force measurements

Published: 2022, Journal: IEEE Access, Cited By: 6

3.Ā  A computer vision approach to monitoring the activity and well-being of honeybees

Published: 2020, Journal: Intelligent Environments 2020: Workshop Proceedings of the 16th, Cited By: 3

4.Ā  Bimodal SegNet: Instance Segmentation Fusing Events and RGB Frames for Robotic Grasping

Published: 2023, Journal: arXiv preprint

5.Ā  Asynchronous Bioplausible Neuron for Spiking Neural Networks for Event-Based Vision

Published: 2023, Journal: arXiv preprint

6.Ā  Asynchronous events-based panoptic segmentation using graph mixer neural network

Published: 2023, Journal: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

7.Ā  Special Purpose Machine for 3-D Bowl feeder welding

Published: 2017

8.Ā  3 Dimensional Welding SPM / Path Tracker

Published: 2016, Journal: International Journal Of Design And Manufacturing Technology