Career Profile
My primary research areas include artificial intelligence, machine learning, advanced autonomy, neuro-symbolic systems, automated planning and acting, cognitive architectures, reinforcement learning, motion planning, hierarchical task planning, and goal reasoning.
Experiences
Conduct research and develope autonomy algorithms for underwater vehicles.
Conduct research and develop systems in goal reasoning, cognitive architectures, theory of mind and automated planning applied toward a range of autonomous systems for DARPA.
Investigated autonomous agents operating in dynamic environments.
Developed an interface between the MIDCA cognitive architecture and a Baxter humanoid robot.
Studied the relationship between Perception, Planning, and Interpretation.
Conducted research in areas of cloud computing, big data and machine learning in distributed frameworks.
Worked on an approach to scale up existing Euclidean embedding algorithms for Big Data.
Developed a customized online shopping store using Grails and My SQL.
Developed a Valuation system to estimate share prices of banks.
Developed an Excel Add-in that shows on-line trading information.
Developed a duplex WCF service that pushes new data to subscribed clients.
Developed apps to read utility meters remotely using varied technologies (GPRS, etc.)
Publications
- Dannenhauer, Z. A. “Anticipation in Dynamic Environments; Knowing What to Monitor.” Doctoral dissertation, Wright State University, College of Engineering and Computer Science, Dayton.
- [AIC-18] Dannenhauer, Z. A., & Cox, M. T. (2018). “Rationale-based Perceptual Monitors.” In AI Communications Journal 31.2, pp. 197–212.
- [ACS-17] Cox, M. T., & Dannenhauer, Z. A. (2017). “Perceptual goal monitors for cognitive agents in changing environments.” In The Fifth Annual Conference on Advances in Cognitive Systems (pp. 1-16). Palo Alto, CA: Cognitive Systems Foundation.
- [FLAIRS-17] Dannenhauer, Z. A., & Cox, M. T. (2017).“Rationale-based visual planning monitors for cognitive systems.” In V. Rus & Z. Markov (Eds.), Proceedings of the 30th International FLAIRS Conference (pp. 182-185). Palo Alto, CA: AAAI Press.
- [IJCAI-16 Goal Reasoning Workshop] Alavi, Z. and Cox, M.T. (2016). “Rationale-based Visual Planning Monitors.” In Working Notes of the 4th Workshop on Goal Reasoning. New York, IJCAI-16.
- [AAAI-16] Cox, M. T., Alavi, Z., Dannenhauer, D., Eyorokon, V., & Munoz-Avila, H. (2016). “MIDCA: A metacognitive, integrated dual-cycle architecture for self-regulated autonomy.” Proceedings of the 30th AAAI Conference on Artificial Intelligence. Palo Alto, CA: AAAI Press.
- [CLOUD-15] Alavi, Z., Sharma, S., Zhou, L., & Chen, K. (2015, June). “Scalable Euclidean Embedding for Big Data.” In Cloud Computing (CLOUD), 2015 IEEE 8th International Conference on (pp.773-780). IEEE.
- [VLDB-14] Alavi, Z., Zhou, L., Powers, J., &Chen, K. (2014). “RASP-QS: Efficient and Confidential Query Services in the Cloud.” Proceedings of the VLDB Endowment, 7(13).
- [ICCAE-10] Rahbarinia, B., Pedram, M. M., Arabnia, H., & Alavi, Z. (2010, February). “A multi-objective scheme to hide sequential patterns.” In Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on(Vol. 1, pp. 153-158). IEEE.
- [EJSR-10] Djahantighi, F. S., Feizi-Derakhshi, M. R., Pedram, M. M., & Alavi, Z. (2010). “An effective algorithm for mining users behaviour in time-periods.” European Journal of Scientific Research, 40(1), 81-90.
Projects
( Video of MIDCA Controlling a Robot ); In this demo, someone makes a change in the world while Baxter is planning. Using plan monitors, Baxter can observe the change and adapt its plan for the new situation.
Skills
Professional Activities
Organizer for the 4th Integrating Planning, Acting, and Execution (IntEx) and 8th Goal Reasoning (GR) held at ICAPS-2020
Served as a reviewer for IJCAI-16 GR Workshop, AAAI-16, ACS-17, and ICAPS-19.