I am a researcher with the Adaptive Systems and Interaction Group at Microsoft Research, Redmond. These days I am focusing on Aerial Informatics and Robotics. I am interested in building intelligent and autonomous flying agents that are safe and enable applications that can positively influence our society. The core technology builds upon cutting edge research in machine intelligence, robotics and human-centered computation in order to enable an entire fleet of flying robots that range from micro-UAVs to commercial jetliners. Various application scenarios include Weather Sensing, Monitoring for Precision Agriculture, Safe Cyber-Physical Systems etc.

More broadly, I am interested in Machine Learning, Quantum Computation and Computer Vision with applications in User Modelling, Affective Computing and HCI scenarios. I did a PhD at the MIT Media Lab and my Doctoral thesis looked at building Discriminative Models for Pattern Recognition with incomplete information (semi-supervised learning, imputation, noisy data etc.). A significant part of that work involved automatic analysis of non-verbal behavior (e.g. Facial Action Analysis, see Master’s thesis) and physiological responses. The earliest part of my research career tackled the problem of photorealistic facial animations.
I am also an avid aviator and hold FAA Commercial Pilot certificate (SEL), FAA Flight Instructor certificate (Airplane Single Engine and Instrument Airplane). I am an active amateur aircraft builder and recently finished building an RV-8 Aircraft (see : RV-8 build blog ).


Aerial Informatics and Robotics Platform

Bridging the simulator-to-reality gap with Aerial Informatics and Robotics platform Machine learning is becoming an increasingly important artificial intelligence approach to building autonomous and robotic systems. One of the key challenges with machine learning is the need for many samples — the amount of data needed to learn useful behaviors is prohibitively high. In addition, the robotic system is often non-operational during the training phase. This requires debugging to occur in real-world experiments with an unpredictable robot. The…

Windflow: Airplanes as Vast Sensor Network

The best available weather forecasts in the United States—from the federal government’s Winds Aloft program—have been based largely on data from instrumented weather balloons released twice a day, providing forecasts for 176 stations across the United States. Winds Aloft is often not accurate and uses time and fuel resources. The Windflow project explores the research question: Could airplanes in flight be employed as a vast sensor network to determine atmospheric conditions? Could data available today be used…

Safe Autonomous Flight Everywhere

The goal of this project is to build a generalized vehicle-agnostic system that can provide safety guarantees in the face of an uncertain world. We are defining what “safe” means, and building a theoretical framework that treats uncertainty in perception and control systems a key design parameter.

FarmBeats: AI & IoT for Agriculture

Established: May 14, 2015

Several studies have demonstrated the need to significantly increase the world’s food production by 2050. However, there is limited amount of additional arable land, and water levels have also been receding. Although technology could help the farmer, its adoption is limited because the farms usually do not have power, or Internet connectivity, and the farmers are typically not technology savvy. We are working towards an end-to-end approach, from sensors to the cloud, to solve the…





The Activity Platform
Helen Wang, Alexander Moshchuk, Michael Gamon, Mona Haraty, Shamsi Iqbal, Eli T. Brown, Ashish Kapoor, Chris Meek, Eric Chen, Yuan Tian, Jaime Teevan, Mary Czerwinski, Susan Dumais, in USENIX 15th Workshop on Hot Topics in Operating Systems (HotOS XV), May 8, 2015, View abstract, Download PDF


Mining Text Snippets for Images on the Web
Anitha Kannan, Simon Baker, Krishnan Ramnath, Juliet Fiss, Dahua Lin, Lucy Vanderwende, Rizwan Ansary, Ashish Kapoor, Qifa Ke, Matt Uyttendaele, Xin-Jing Wang, Lei Zhang, in KDD '14 Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, ACM Press, August 24, 2014, View abstract, Download PDF