Arash Termehchy

Arash Termehchy is an Associate Professor in the Department of Electrical Engineering and Computer Science at Oregon State University's College of Engineering. His research focuses on data-centric systems, including machine learning on structured/heterogeneous data, human-data interaction, and scalable/robust reasoning systems. He leads the IDEA Lab and teaches courses such as CS 549 (Scalable Reasoning & ML), CS 540 (Database Management Systems), and CS 440 (Database Management Systems). His work has been recognized with awards like the 2019 ACM SIGMOD Research Highlight Award and multiple Best Paper selections.

Termehchy holds a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign. His research spans data cleaning methods for ML, scalable relational learning, and systems for translational biomedicine (e.g., RTX-KG2). He explores how users' data focus evolves during visual analysis and develops adaptive visualization techniques like ShiftScope. His work emphasizes practical applications of AI in data systems, including entity augmentation, query generation, and model consistency through declarative constraints.

Key contributions include Schema-independent relational learning (Castor), variational databases, and the Data Exploration Game framework. His research bridges theoretical foundations (e.g., logical scalability of learning algorithms) with real-world systems (e.g., Universal-DB for graph analytics). Current projects address challenges in handling incomplete data, scalable schema mappings, and human-in-the-loop data exploration.

• Education:
  • Ph.D., Computer Science, University of Illinois at Urbana-Champaign
• Labs/Teams: IDEA Lab (Investigating Data-centric AI & Exploratory Analytics)
• Grants: NSF III Collaborative Research on Similarity Metrics (2014), Yahoo! Key Scientific Challenges (2011)