Dr. Sajal Halder, Charels Sturt University, Australia
👨💻 Dr. Sajal Halder is a pioneering figure in computer engineering, earning his Doctor of Philosophy (PhD) from RMIT University in December 2022. His groundbreaking thesis on “Itinerary Recommendation based on Deep Learning” showcases his commitment to pushing the boundaries of knowledge in travel technology. Under the mentorship of A/Prof Jeffrey Chan and Prof. Xiuzhen Zhang, he made significant contributions to the intersection of deep learning and travel recommendations. Holding a Master of Engineering with an outstanding CGPA of 4.23/4.30 from Kyung Hee University, South Korea, Dr. Halder’s early research delved into “Supergraph based Periodic Behaviors Mining in Dynamic Social Networks.” Currently serving as a Research Fellow at Charles Sturt University, he leads innovative projects in cybersecurity, developing a groundbreaking metadata-based model. Dr. Halder’s expertise spans machine learning, deep learning, and software security, reflecting a dedication to shaping the future of technology. 🚀🔒
🎓 Education :
🎓 Dr. Sajal Halder is a trailblazer in the field of computer engineering, culminating his academic journey with a Doctor of Philosophy (PhD) from the School of Computing Technologies at the Royal Melbourne Institute of Technology (RMIT) University in December 2022. His groundbreaking thesis, “Itinerary Recommendation based on Deep Learning,” reflects his commitment to pushing the boundaries of knowledge. Under the guidance of A/Prof Jeffrey Chan and Prof. Xiuzhen Zhang, Dr. Halder contributed significantly to the intersection of deep learning and travel recommendations. Prior to his doctoral achievements, he earned a Master of Engineering from Kyung Hee University, South Korea, with a remarkable CGPA of 4.23/4.30 (95.25%). His master’s thesis, supervised by Prof. Young-Koo Lee, delved into “Supergraph based Periodic Behaviors Mining in Dynamic Social Networks,” showcasing his early prowess in innovative research. Dr. Halder’s academic odyssey exemplifies a commitment to excellence and exploration in the dynamic landscape of computer engineering. 🌐👨🎓
🌐 Professional Profiles :
Google Scholar
Scopus
Orcid
Linkedin
Github
🏗️ Experience :
👨💼 Dr. Sajal Halder brings his expertise to the forefront as a Research Fellow at Charles Sturt University, Wagga Wagga, NSW, Australia, since December 2022. In this role, he has spearheaded the development of a groundbreaking metadata-based model for detecting malicious and benign packages within the NPM repository. Dr. Halder’s innovative approach includes the introduction of two sets of features, namely easy to manipulate (ETM) and difficult to manipulate (DTM), where manipulating DTM relies on long-term planning and monotonic properties. The verification of feature selection effectiveness through various machine learning and deep learning techniques demonstrates his commitment to robust model development. Notably, his work extends to analyzing algorithm performance under metadata manipulation and proposing enhanced metadata adversarial attack-resistant algorithms, showcasing Dr. Halder’s dedication to advancing the field of cybersecurity. 🔍🛡️
🧠 Research Interests 🔬🌐 :
🔍 Dr. Sajal Halder’s research interests form a dynamic intersection of cutting-edge technologies. With a focus on Machine Learning and Deep Learning, he delves into the realms of artificial intelligence, exploring innovative approaches to data analysis and pattern recognition. His expertise extends to the critical domain of Software Security, where he contributes to the development of robust systems resilient against modern cyber threats. Additionally, Dr. Halder is engaged in advancing Recommendation Systems, aiming to enhance user experience and personalization through intelligent algorithms. His multifaceted research portfolio exemplifies a commitment to shaping the future of technology across diverse domains. 🤖🔒
📚 Publication Impact and Citations :
Scopus Metrics:
- 📝 Publications: 24 documents indexed in Scopus.
- 📊 Citations: A total of 222 citations for his publications, reflecting the widespread impact and recognition of Dr. Sajal Halder’s research within the academic community.
Google Scholar Metrics:
- All Time:
- Citations: 358 📖
- h-index: 12 📊
- i10-index: 14 🔍
- Since 2018:
- Citations: 291 📖
- h-index: 11 📊
- i10-index: 12 🔍
👨🏫 A prolific researcher with significant impact and contributions in the field, as evidenced by citation metrics. 🌐🔬
Publications Top Notes :
1. Predicting students yearly performance using neural network: A case study of BSMRSTU
Published Year: 2016
Journal/Conference: 5th International Conference on Informatics, Electronics and Vision
Cited By: 56
2. Movie recommendation system based on movie swarm
Published Year: 2012
Journal/Conference: Second international conference on cloud and green computing
Cited By: 35
3. Supergraph based periodic pattern mining in dynamic social networks
Published Year: 2017
Journal/Conference: Expert Systems with Applications
Cited By: 34
4. An efficient hybrid system for anomaly detection in social networks
Published Year: 2021
Journal/Conference: Cybersecurity
Cited By: 31
5. Exploring significant heart disease factors based on semi-supervised learning algorithms
Published Year: 2018
Journal/Conference: International Conference on Computer, Communication, Chemical, Material Engineering
Cited By: 25
6. Smart disaster notification system
Published Year: 2017
Journal/Conference: 4th International Conference on Advances in Electrical Engineering
Cited By: 23
7. Transformer-based multi-task learning for queuing time aware next POI recommendation
Published Year: 2021
Journal/Conference: Pacific-Asia Conference on Knowledge Discovery and Data Mining
Cited By: 20
8. Smart CDSS: Integration of social media and interaction engine (SMIE) in healthcare for chronic disease patients
Published Year: 2015
Journal/Conference: Multimedia Tools and Applications
Cited By: 20
9. Link prediction by correlation on social network
Published Year: 2017
Journal/Conference: 20th International Conference of Computer and Information Technology
Cited By: 16
10. An efficient approach of identifying tourist by call detail record analysis
Published Year: 2016
Journal/Conference: International Workshop on Computational Intelligence
Cited By: 13