Advanced Intelligence Software Lab
The Advanced Intelligence Sofware lab (or AIS lab for short) is located at Gyte building in Purdue University Northwest. The lab is focusing on public safety-related projects with doctoral, MS-level students, and undergradautes.
Research Interests
My research interests are in the area of robust deep/machine learning, text mining, data privacy and security, and information quality, and cloud computing. For all Publications, see Google Scholar and
ResearchGate
Research Devices
The AIS lab has two GPU machines with 80 cores, 200 GB memory, 6 TB data storages.The lab is dedicated to anlzying audio datasets and image datasets with deep learning and statistical learning approaches.
Robust Deep Learning(Selected publications)
- Dai, Wei, Daniel Berleant. Discovering Limitations of Image Quality Assessments with Noised Deep Learning Image Sets," 2022 IEEE International Conference on Big Data (Big Data), Osaka, Japan, 2022, pp. 3735-3744, doi: 10.1109/BigData55660.2022.10020507
- Dai, Wei, Daniel Berleant. "Benchmarking robustness of deep learning classifiers using two-factor perturbation" 2021 IEEE International Conference on Big Data (Big Data), Orlando, FL, USA, 2021, pp. 5085-5094, doi: 10.1109/BigData52589.2021.9671976.
- Dai, Wei, and Ningning Wu. "Profiling Essential Professional Skills of Chief Data Officers Through Topic Modeling Algorithms." in Americas Conference on Information Systems ,2017. # A Top Conference in Information Management Field.
Information Quality (Selected publications)
Data Privacy of Internet of Things (IoT)
Cloud Computing (Selected publications)
- Dai, Wei and his research team is developing Distributed Time Sync Simulation . So far, the simulation has triggered many positive interests at academic. Note that the simulation is 100% math models, graphic algorithms, and distribution algorithms. On October 4th, 2023, David research team introduced the simulation at Purdue University, West Lafayette
- Dai, Wei co-authored a paper named HCoop: A Cooperative and Hybrid Resource Scheduling for Heterogeneous Jobs in Clouds was just accepted by the 14th IEEE International Conference on Cloud Computing Technology and Science, October 2023.
- Jiagang Liu, Ju Ren, Wei Dai, Deye Zhang, Pude Zhou, Yaoxue Zhang, Geyong Min, Noushin Najjari. "Online Multi-Workflow Scheduling under Uncertain Task Execution Time in IaaS Clouds." IEEE Transactions on Cloud Computing, 2019. # A Top Journal in the Computer Science.
Selected Research Grants
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[Role: PI] Chicago Quantum Hub, "Quantum Computing Cloud Credits", $500, Period: October 2024- January 2025
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[Role: PI] Indiana Space Grant Consortium (NASA-control), "Using Satellite Images and Acoustic Sensors for Improving Public Safety with Deep Learning Models", $17,000, Period: May 2024- May 2025
- [Role: PI] Provost Grant, Purdue University Northwest, “Gunshot Detection for public security”, Project Period: April 2023 - May 2025
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[Role: PI] Blakemore Family Business Fellowship, “An Online Cybersecurity Course for 100 Family Business Owners: A Proposal” $2,000, Period: October 2021
- [Role: PI] Google (GCP Research Credits), “Aerial Images and Artificial Intelligence for Optimized Soybean Breading”, Total Award: $5,000. Project Period: November 2019 – December 2020. Collaborators: Pengyin Chen (University of Missouri-Columbia)
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[Role: PI] Southeast Missouri State University (Internal), A Self-Defense Web Application with Informed Caches, Total Award: $500. Project Period: October 2019 – December 2020
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TruckXi Company,California, USA, Industry Research Grant, $3,500 2015
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UA Little Rock, Academic Travel Awards, $1,000 2016-2018
SELECTED AWARD
Academia
- Excellence in Research Award in College of College of Engineering and Sciences, 2024, Purdue University Northwest
Excellence in Research Award in Information Science, 2017, UA Little Rock
- The first place and the third place Research Awards at UALR Student Research and Creative Works EXPO in 2017, UA Little Rock
- Honorable Mention Award at UALR Student Research and Creative Works EXPO, 2016, UA Little Rock
Industry
- Industrial Awards in EIT Open House, 2017, UA Little Rock
- Best IBM Customer Service Award in 2014;
- IBM Excellent Instructor Prize in 2011 and 2012, respectively
- IBM Outstanding Employee in 2009 and 2012, respectively
- IBM South China Technical Talent Award in 2009, 2011, and 2012, respectively