David Williamson
CEO & President
David Williamson is the president and Chief Executive Officer of the HomeWorld Educational Resources. He is a geologist and has 22 years of working experience in oil and gas industry. He has strong passion in Earth science and environmental education. He has a rich experience in project and company management. Dave has strong project and business management skills. Also, he is a domain expert and has MS degrees in geographic information sciences (GIS) and geosciences. David Williamson will serve as the key coordinator with the UTD research team and the project manager for EasyVille educational content preparation, materials reviewer, and the organizer of the review camp.
Zachary Clowdus
Secretary
Zach enjoys the research process and using my geoscience knowledge to educate others on interesting topics. He likes coming up with creative solutions to complicated problems and collaborating with a team to produce a great finished product as efficiently and effectively as possible.
Steve (Zhongjie) Zheng
Treasurer & Technology Director
Zhongjie Zheng is a technical consultant in the HomeWorld Educational Resources. He is a Senior Software Engineer at Splunk and was a software development engineer at Amazon. He has 8 years of online platform and mobile software engineering experience. He is specialized in UI control, 3D rendering, Unity, and OpenGL, and familiar with CesiumJS, which is an open source JavaScript library for creating world-class 3D globes and maps and its extended product Cesium Ion is one of the primary resources that we will use to develop the EasyVille. He has a MS degree in computer science. Zhongjie Zheng will serve as the primary technical leader of the EasyVille development.
Ning Wang, Ph.D.
Research and Development Director
Ning Wang is an interdisciplinary researcher and academic leader specializing in data science, learning science, and human-centered computing. He currently serves as a Complex Data Interaction Research Fellow with the National Center for Science and Engineering Statistics (NCSES), where he contributes to the development of next-generation data visualization tools and AI-powered systems that enhance access to complex scientific data for researchers, policymakers, and the public.
Dr. Wang holds a Ph.D. in Sustainable Earth Systems Science, with additional training in geology, geophysics, computer science, and science education. His work focuses on advancing how individuals engage with complex information systems through data visualization, AI, and innovative learning environments.
Through his combined efforts in research, academic leadership, network building, and grant development.
Dr. Wang serves as a board leader for research at HomeWorld Educational Resources advancing complex systems learning, sustainability education, and workforce readiness in the age of artificial intelligence. In this role, he has built and led collaborative networks across research and doctoral institutions, guided research initiatives, and supported grant development efforts to expand interdisciplinary programs and partnerships.
He also serves as an Adjunct Professor at the University of Texas at Dallas, where he designed and teaches project-based courses that integrate science, storytelling, and technology. His academic leadership emphasizes interdisciplinary collaboration, experiential learning, and mentoring students from diverse backgrounds to develop research, communication, and innovation skills.
Dr. Wang is committed to strengthening connections across research and doctoral universities and advancing collaborative, data-informed approaches to addressing complex societal challenges.
Ali N. Salman, Ph.D.
AI Solution Expert
Dr. Ali Salman is a Research Scientist at ARRAY INNOVATION and his research specializes in facial expression recognition and privacy-preserving AI. His work combines computer vision, federated learning, and unsupervised adaptation to develop personalized, real-time emotion recognition models that operate securely on-device. He has extensive experience in data collection (MSP-Podcast, MSP-GEO, MSP-Face, NaturalVoices) as well as text-to-speech (TTS) and voice conversion (VC) on wild data, advancing natural and adaptable AI systems.
Skilled in:
-Facial Expression Recognition (FER): Specializing in both static and dynamic FER with robust, privacy-focused solutions.
-Privacy-Preserving AI: Developing models that safeguard user data through on-device processing and federated learning.
-Federated Learning: Implementing decentralized, adaptive models that continuously improve across devices.
-Unsupervised Adaptation: Enhancing model personalization without manual labels through pseudo-labeling techniques.
-Computer Vision: Advanced image and video processing, including style disentanglement and landmark-based feature extraction.
-Text-to-Speech (TTS) & Voice Conversion (VC): Extensive experience with TTS and VC systems, particularly using wild data.
-Data Collection & Curation: Managed large-scale datasets (MSP-Podcast, MSP-GEO, MSP-Face, NaturalVoices) for emotion and speech recognition research as well as TTS and VC.
-Generative AI and deep learning model development links:
Github: https://github.com/3loi
HuggingFace: https://huggingface.co/3loi
Scholar: https://scholar.google.com/citations?user=BOX8bpAAAAAJ&hl=en
Seong-Gyun Leem, Ph.D.
AI Solution Expert
Dr. Leem is a research scientist at Meta Reality Labs working on advancing text-to-speech systems for smart-glasses. He obtained Ph.D. degree in Electrical Engineering from UT Dallas in 2024, with research focused on noise-robust speech/video emotion recognition. He is interested in solving real-world challenges in applied machine learning, including:
1) noisy data filtering and curation
2) training robust models with noisy signals and subjective labels
3) model evaluation under subjective conditions.
He has published 20+ research papers, achieving 300+ citations and h-index 10+.
For publication details, please visit my Google Scholar profile: https://scholar.google.com/citations?user=JKiiu20AAAAJ&hl=en&oi=ao
