The story of Genghis Khan has until now been spliced together through a collection of almost entirely secondary source text. It has become understood that throughout his rule, he had introduced an alphabet and central currency, united a kingdom of warring tribes, and had conquered the majority of the known world creating an influence that stretched from Poland to Japan, leaving a legacy of unsurpassed proportions. Yet the sources of this history have decidedly originated from the fearful pens of his enemies. The mystery that surrounded his death and burial during the summer of 1227 still eludes the world today. His tomb remains undiscovered, a time capsule into the days of birth of the modern world.

The Valley of the Khans project is an international collaboration between the University of California at San Diego, the Mongolian Academy of Science and the International Association for Mongol Studies, and the National Geographic Society to perform a high-tech, non-invasive remote sensing investigation for the tomb of Genghis Khan. It is funded in part by the NGS/Waitt Institute for Discovery, the National Geographic Expeditions Council, UC San Diego, and Industry and private support.

The goal of the project is to identify the site of Genghis Khan's Tomb using noninvasive methodologies utilizing technologies ranging from aerial and satellite imaging, human computation, non-invasive geophysical surveying such as ground penetrating radar, magnetometry and electro-magnetometry and 3D data visualization. By providing a physical location for the site through these non-invasive tools the project will enable protective measures through organizations such as UNESCO World Heritage for long-term sustainable conservation.


The goal of this research is to develop human computation concepts that efficiently harness the power human perception on a massive scale and combine that collective human response with machine learning. This effort, motivated by the satellite and aerial remote sensing component of the Valley of the Khans Project, has allowed us to test theories of a new age in the human/computer relationship.

Human Computation, often referred to as Crowdsourcing, is an emerging field of computer science in which problems are approached by engaging large numbers of participants, knowingly or unknowingly, to participate in collective initiatives through innovative online platforms.

Harnessing the efforts of millions of people working toward a singular goal presents a major challenge that is becoming increasing relevant as virtual networks such as Facebook and MySpace open the possibility of massive collective initiatives. Concurrently, computation requirements are evolving beyond questions with discrete answers; fields like computer-vision are reaching the limits of a computer-only approach. Combining these two trends this proposal investigates a revolutionary concept with wide ranging applications (e.g. real-time imagery emergency response, defense intelligence, conservation, basic science, global education) and transformative impact in all areas of computation. Utilizing the collective human experience for active machine learning will define the path through which the digital world evolves.

Tomnod (Mongolian for "big eye") was founded in 2009 out of the success of the Valley of the Khans (VOTK) Project by Albert and three other members of the VOTK Project team: Shay Har-Noy, Luke Barrington, and Nathan Ricklin. Three years later, Tomnod was acquired by the company DigitalGlobe while incubating at EvoNexus.[8] Tomnod uses online map interfaces that engage many people to each view and tag a small section of a large area on the planet. In 2011 Tomnod cooperated with the UNHCR to locate refugee camps in Somalia.[9] Users were asked to use satellite images to count the shelters of refugees. Other projects include searching for the tomb of Genghis Khan,[10] mapping damage after Typhoon Haiyan,[5] and searching for Malaysia Airlines Flight 370 where 8 million people participated in the online search through imagery data.

Lin, A.Y.M., Huynh, A., Lanckriet, A., Barrington, L. (2014) Crowdsourcing the Unknown: The Satellite Search for Genghis Khan, PloS One 9 (12).
Lin, A.Y.M., Huynh, A., Barrington, L., Lanckriet, G. Search and Discovery in Human Computation. In Handbook of Human Computation, Springer- New York (2013), pp.171-186.
Levy, T.E., Smith, N.G., Najjar, M., DeFanti, T.A., Kuester, F.and Lin, A.Y.M. (2012) Cyber-Archaeology in the Holy Land: The Future of the Past. Washington, D.C.: Biblical Archaeology Society eBook
Huynh, A., Lin, A.Y.M. (2013) Mobile Analysis of Large Temporal datasets for Exploration and Discovery. 2013 Digital Heritage Conference Proceedings.
Huynh, A., Ponto, K., Lin, A.Y.M. (2013) Visual Analytics of Inherently Noisy Crowdsourced Data on Ultra High Resolution Displays. 2013 IEEE Aerospace Conference Proceedings.
Huynh, A. and Lin, A.Y.M. (2012) Connecting the Dots: Triadic Clustering of Crowdsourced Data to Map Dirt Roads. Proceedings of the 21st International Conference on Pattern Recognition.
Levy, T.E., Smith, N.G., Najjar, M., DeFanti, T.A., Kuester, F.and Lin, A.Y.M. (2012) Cyber-Archaeology in the Holy Land: The Future of the Past. Washington, D.C.: Biblical Archaeology Society eBook
Lin, A.Y.M., Novo, A., Har-Noy, S., Ricklin, N., Stamatiou, K. (2011). Combining GeoEye-1 Satellite Remote Sensing , UAV Aerial Imaging, and Geophysical Surveys in Anomaly Detection Applied to Archaeology IEEE J-STARS, vol 4, page 870-876.
Lin, A. Y.M., Novo, A., Weber, P.P., Morelli, G., Goodman, D., Schulze, J. (2011) A Virtual Excavation: Combining 3D Immersive Virtual Reality and Geophysical Surveying, International Symposium on Visual Computing, ISVC 2011, Part II, LNCS 6939, pp. 229–238.
Lin, A.Y.M. (2010) ”The search for Genghis Khan: Using modern tools to hunt for an ancient past” Aerospace Conference, 2010 IEEE , vol., no., pp.1-2.