Ms. Akarshani Amarasinghe | Artificial Intelligence | Young Scientist Award

Lecturer at University of Sri Jayewardenepura, Sri Lanka

M.C. Akarshani Amarasinghe is an accomplished academic and researcher pursuing a PhD in Computer Engineering at the University of Sri Jayewardenepura, Sri Lanka. With a strong background in machine learning, image processing, and drone technology, her work focuses on innovative solutions for public health and agriculture. She has contributed to impactful research projects, such as identifying dengue mosquito breeding sites via drones and optimizing pesticide usage in arable lands. Alongside her research, Akarshani has extensive teaching experience, is a mentor for Google Summer of Code, and holds several prestigious awards for her research excellence.

Publication profile

scholar

🎓 Higher Education

01.2024 – Present PhD in Computer Engineering, Faculty of Engineering, University of Sri Jayewardenepura, Sri Lanka Supervisors: Dr. Udaya Wijenayake, Prof. K.L. Jayaratne Research: Path planning algorithm for achieving multiple goals.. 2011 – 2016. BSc (Hons) in Computer Science, University of Colombo School of Computing, Sri Lanka Second Class Upper Division (3.25/4 – Four-Year Program)

🔬 Recent Research

D4D (Drone for Dengue) Sustainable Computing Research Group, University of Colombo School of Computing. Research on machine learning and image processing for identifying dengue mosquito breeding sites via drone images. Advisors: Prof. T.N.K. De Zoysa, Dr. C.I. Keppitiyagama. 2017 – Present GitHub Project

🧑‍🏫 Teaching Experience

03.02.2020 – Present Lecturer, Department of Computer Engineering, Faculty of Engineering, University of Sri Jayewardenepura, Sri Lanka Subjects: Operating Systems, Data Mining, Natural Language Processing, Quality Engineering, Compilers.01.01.2019 – 31.01.2020 Assistant Lecturer, Department of Computer Science and Software Engineering, Sri Lanka Institute of Information Technology Subjects: Software Engineering Concepts, Programming, Distributed Systems. 01.02.2018 – 30.12.2018 Assistant Lecturer, University of Colombo School of Computing Subjects: Programming Using C, Data Structures, Operating Systems. 2018 Visiting Lecturer, National Institute of Business Management, Sri Lanka Subject: Image Processing. 02.01.2018 – 01.02.2018 Instructor, University of Colombo School of Computing

🏅 Awards and Achievements

2023 Student Research Project of the Year at the National ICT Awards, NBQSA 2023. 2022 Best Paper in AI and ML Track, ICARC 2022. 2019 N2Women Travel Grant to attend ACM SenSys 2019. 2017 N2Women Travel Grant to attend MobiSys Women’s Workshop

🏢 Professional Service

2023 – Present Treasurer, Past Pupils’ Association, Sadhu Daham Pasala, Sri Lanka. 2015 – Present Committee Member, Thumbowila Api Welfare Society. 2012 – 2016 Committee Member, AIESEC Colombo – South

Publication

Identifying mosquito breeding sites via drone images
Authors: C Suduwella, A Amarasinghe, L Niroshan, C Elvitigala, K De Zoysa, …
Conference: Proceedings of the 3rd Workshop on Micro Aerial Vehicle Networks, Systems
Year: 2017
Citations: 29

A machine learning approach for identifying mosquito breeding sites via drone images
Authors: A Amarasinghe, C Suduwella, C Elvitigala, L Niroshan, RJ Amaraweera, …
Conference: Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems
Year: 2017
Citations: 15

Suppressing dengue via a drone system
Authors: A Amarasinghe, C Suduwella, L Niroshan, C Elvitigala, K De Zoysa, …
Conference: 2017 Seventeenth International Conference on Advances in ICT for Emerging Regions
Year: 2017
Citations: 15

A swarm of crop spraying drones solution for optimizing safe pesticide usage in arable lands
Authors: A Amarasinghe, VB Wijesuriya, D Ganepola, L Jayaratne
Conference: Proceedings of the 17th Conference on Embedded Networked Sensor Systems
Year: 2019
Citations: 10

A path planning algorithm for an autonomous drone against the overuse of pesticides
Authors: A Amarasinghe, VB Wijesuriya, L Jayaratne
Conference: 2021 10th International Conference on Information and Automation for Sustainability
Year: 2021
Citations: 5

Drones vs dengue: a drone-based mosquito control system for preventing dengue
Authors: A Amarasinghe, VB Wijesuriya
Conference: 2020 RIVF International Conference on Computing and Communication Technologies
Year: 2020
Citations: 4

Stimme: a chat application for communicating with hearing impaired persons
Authors: A Amarasinghe, VB Wijesuriya
Conference: 2019 14th Conference on Industrial and Information Systems (ICIIS)
Year: 2019
Citations: 4

✅ Conclusion

M.C. Akarshani Amarasinghe is an excellent candidate for the Research for Young Scientist Award. Her innovative contributions to drone technology for health and agriculture, leadership roles, and technical skills make her stand out. With continued expansion of her research portfolio and international exposure, she has the potential to achieve even greater recognition in the future.

Dr. Weihua Liu| AI | Best Researcher Award

Dr at AthenaEyesCO., LTD. China

With extensive contributions to academia and industry, I’ve authored over 20 influential papers and filed more than 80 patents, underscoring my commitment to innovation at the intersection of AI and healthcare. My career spans leadership in national science foundation projects and pioneering advancements in medical imaging and diagnostic technologies.

Profile

Orcid

🎓Education

Post-Doctoral Research Beijing Institute of Technology, School of Medical Technology (Nov 2021 – Jun 2024) Co-supervisor: Chen Duanduan, Focus: Construction and Application of Medical Multi-modal Large Models. PhD in Computer Science Beijing Institute of Technology, School of Computer Science (Sep 2014 – Jun 2021) Supervisor: Liu Xiabi Dissertation: “Deep Network Structure and Its Learning Method Based on Pulmonary Nodule Detection and Lung Parenchyma Segmentation”. Bachelor’s and Master’s Degrees Changsha University of Science and Technology, School of Computer and Communication Engineering Bachelor’s Degree in Computer Science and Technology (Sep 2002 – Jun 2006), Master’s Degree in Software Engineering and Theory (Graduated Jun 2009), Research Focus: Image Processing and Pattern Recognition

🔬Research Projects

National Natural Science Foundation of China Project: Research on Intelligent Assessment Method for Stroke Risk Based on High-Risk Carotid Plaque-Complex Blood Flow Image Feature Analysis (2023-2026). Beijing Natural Science Foundation Project: Research on the Model of Acute Respiratory Distress Syndrome Assisted Diagnosis and Treatment Based on AI and Data Mining (2023-2026). Changsha Major Science and Technology Special Project Research and Application of Trustworthy Intelligent Vision Key Technologies in 5G Environment (2020-2023)

🚀 Professional Experience:

As an AI Algorithm Scientist at 3M’s Beijing Research and Development Center, I spearheaded the development of the BAX framework, a unified cross-platform AI deployment system widely adopted in biometric intelligence systems globally.

💡 Patents:

I’ve filed over 80 patents, showcasing my innovations in areas like multimodality-based medical models, facial recognition, and medical identity authentication.

🌟 Research Expertise:

With a profound focus on AI and healthcare intersections, I bring extensive theoretical knowledge in biometric technology, physiological and psychological computing, and medical assistant diagnosis.

Publications Top Notes 📝

Shape-margin knowledge augmented network for thyroid nodule segmentation and diagnosis
- Year: 2024
- Authors: Liu, Weihua; Lin, Chaochao; Chen, Duanduan; Niu, Lijuan; Zhang, Rui; Pi, Zhaoqiong
- Source: Computer Methods and Programs in Biomedicine

A pyramid input augmented multi-scale CNN for GGO detection in 3D lung CT images
- Year: 2023
- Authors: Liu, Weihua; Liu, Xiabi; Luo, Xiongbiao; Wang, Murong; Han, Guanghui; Zhao, Xinming; Zhu, Zheng
- Source: Pattern Recognition

Stone needle: A general multimodal large-scale model framework towards healthcare
- Year: 2023
- Authors: Liu, Weihua; Zuo, Yong
- Source: arXiv preprint arXiv:2306.16034

Contraction Mapping of Feature Norms for Data Quality Imbalance Learning
- Year: 2022
- Authors: Liu, Weihua; Liu, Xiabi; Li, Huiyu; Lin, Chaochao
- Source: Available at SSRN 4250246

Integrating lung parenchyma segmentation and nodule detection with deep multi-task learning
- Year: 2021
- Authors: Liu, Weihua; Liu, Xiabi; Li, Huiyu; Li, Mincan; Zhao, Xinming; Zhu, Zheng
- Source: IEEE Journal of Biomedical and Health Informatics

A new three-stage curriculum learning approach for deep network based liver tumor segmentation
- Year: 2020
- Authors: Li, Huiyu; Liu, Xiabi; Boumaraf, Said; Liu, Weihua; Gong, Xiaopeng; Ma, Xiaohong
- Source: 2020 International Joint Conference on Neural Networks (IJCNN)

URDNet: a unified regression network for GGO detection in lung CT images
- Year: 2020
- Authors: Liu, Weihua; Ren, Yuchen; Li, Huiyu
- Source: Wireless Communications and Mobile Computing

Content-sensitive superpixel segmentation via self-organization-map neural network
- Year: 2019
- Authors: Wang, Murong; Liu, Xiabi; Soomro, Nouman Q; Han, Guanhui; Liu, Weihua
- Source: Journal of Visual Communication and Image Representation

Hybrid resampling and multi-feature fusion for automatic recognition of cavity imaging sign in lung CT
- Year: 2019
- Authors: Han, Guanghui; Liu, Xiabi; Zhang, Heye; Zheng, Guangyuan; Soomro, Nouman Qadeer; Wang, Murong; Liu, Weihua
- Source: Future Generation Computer Systems

Akarshani Amarasinghe | Artificial Intelligence | Young Scientist Award