The phenomenal improvement in the capabilities of modern smartphones, and the underlying `App' store model of software distribution, has fundamentally changed the mobile computing landscape and also led to several interesting research problems. Two of the major ones that we are interested in are energy management (to improve battery lifetime) and addressing privacy on mobile platforms. We have for example, developed program analysis for 3rd party Apps running on modern smartphone OSes which can cause un-necessary battery drain due to developer error. We have also built a tool that verifies Android apps for the absence of energy sapping bugs. We are now exploring ways to crowd source app behavior to identify and mitigate causes of abnormal battery drain at runtime. The second aspect of mobile computing that we are very interested in is privacy, specifically for apps that collect and often share user data such as location, contacts, often unknown to users. We are exploring holistic end to end solutions for helping developers as well as user manage privacy on iOS and Android by combining techniques such as static analysis, runtime monitoring, crowdsourcing and machine learning. We are building on our ProtectMyPrivacy platform for both iOS and Android with over 200K downloads and tens of thousands of daily active users. We are exploring multiple research directions such as understanding user perception and bias towards privacy, effectiveness of crowdsourcing, improving effectiveness of privacy prompts, inferring purpose of privacy sensitive data access and its use, and also understanding the motivations behind privacy breaching apps and the entire ecosystem.