Technology platforms are emerging as a new kind of workplace: from crowdwork to ‘peer economy’ platforms. This project uses ethnographic methods to address questions such as: Who are the workers on these platforms? What are their work practices? How do they differ from traditional labor? How is the complex relationship between workers, customers, platform provider, and the algorithms they create, experienced? What does all this imply for designing more equitable and sustainable markets for work?
We consider various scheduling problems that arise in large clusters.
Supersingular Isogeny Diffie Hellman Library
A lattice-based cryptography library
Several studies have demonstrated the need for the world’s food production to double by 2050. However, there is limited amount of additional arable land, and water levels have also been receding at a fast rate. 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 problem.
Homomorphic Encryption (HE) refers to a special type of encryption technique that allows for computations to be done on encrypted data, without requiring access to a decryption key.
holoportation is a new type of 3D capture technology that allows high quality 3D models of people to be reconstructed, compressed, and transmitted anywhere in the world in real-time. When combined with mixed reality displays such as HoloLens, this technology allows users to see and interact with remote participants in 3D as if they are actually present in their physical space. Communicating and interacting with remote users becomes as simple as face to face communication.
Video has become ubiquitous on the Internet, broadcasting channels, as well as that captured by personal devices. This has encouraged the development of advanced techniques to analyze the semantic video content for a wide variety of applications, such as video highlight detection, video summarization, object detection, action recognition, semantic segmentation, and so on.
A service to enable interactive search experiences within structured data via natural language inputs.
We are designing programming languages for building safe and reliable asynchronous systems. The languages are based on the programming idiom of communicating state machines. They offer first-class support for writing safety and liveness specifications as well as building abstract models of code. They offer systematic testing capabilities that exhaustively (in the limit) tests all possible executions of the program, weeding out even hard-to-find concurrency bugs.
IVy is a research tool intended to allow interactive development of protocols and their proofs of correctness. It also provides a platform for developing and experimenting with automated proof techniques. In particular, IVy provides interactive visualization of automated proofs, and supports a use model in which the human protocol designer and the automated tool interact to expose errors and prove correctness.
Friendships are dynamic. In this project, we uncover the dynamics of tie strength and online social interactions in terms of various aspects, such as reciprocity, temporality, and contextually. Based upon these dynamics, we build a learning to rank framework to predict social interactions in online social networks.
One out of four people in the world have experienced mental illness at some point in their lives. DiPsy is a digital psychologist presented as a personalized chatbot, who can evaluate, diagnose, treat and study users' mental processes through natural conversations.
We are developing a system for the acquisition, transmission and display of real-time 3D digital content. Our goal is to enable live, immersive 3D communications and entertainment experiences. Our strategy is to acquire the 3D signal within a cubical volume. We represent this signal using high resolution colored voxels, and have created algorithms for acquisition, encoding, decoding, streaming, and display of this voxel data designed specifically for modern massively data-parallel GPUs.
We are inundated with data. Resources to analyze the data are finite and expensive. Approximate answers allow us to explore much larger amounts of data than otherwise possible given available resources. Reducing the cost, if doable for a large fraction of the complex queries that run on this data, is of strategic importance because the savings can be re-invested into more sophisticated algorithms or be used as a key differentiator for analytics-as-a-service offerings.
Room2Room is a life-size telepresence system that leverages projected augmented reality to enable co-present interaction between two remote participants. We enable a face-to-face conversation by performing 3D capture of the local user with color + depth cameras and projecting their virtual copy into the remote space at life-size scale. This creates an illusion of the remote person’s presence in the local space, as well as a shared understanding of verbal and non-verbal cues (e.g., gaze).
BLE Angle of Arrival (AoA) system that can locate a commercial mobile device with high accuracy at distances over a dozen meters.
Image is becoming a popular media for user communications on social networks. Then, it comes to be a natural requirement to enable chatbot to chat on images besides textual inputs. Based on MS XiaoIce(微软小冰), we explore the direction of image chat and iterate several rounds to enhance her talkative ability for images.
Dogs are human's close friends on the planet, there were estimated to be 400 million dogs in the world from hundreds of varied breeds. As the large number of breeds, it is hard for normal users to recognize most of them. Hereby, we developed a dog recognizer to assist users to know more about dogs.
We are developing new techniques to efficiently deliver content and services over large-scale cloud infrastructure
In the field of computer science, large-scale experimentation on users is not new: there have been many efforts in both the public and private sectors to analyze users and to create experimental conditions to provoke changes in their behavior. However, new autonomous and semi-autonomous systems for experimentation, driven by techniques from AI and machine learning, raise important questions for the field. Many of these questions are about the social and ethical implications of these systems.
Labs: New York
PACORA (Performance-Aware Convex Optimization for Research Allocation) is a resource allocation framework for general-purpose operating and cloud systems, which is designed to provide responsiveness guarantees to a simultaneous mix of high-throughput parallel, interactive, and real-time applications in an efficient, scalable manner in order to improve efficiency without sacrificing responsiveness or performance.
Click-through data accumulated by search engine where rich connections between images and semantics have been built via the massive user clicks. The data comes free when search engine freely provides service to users, and naturally scales up to million scale even billion scale. Unlike dedicatedly constructed datasets, click-through data is noisy, unstructured and unbalanced. Under this project, we are targeting effectively using click-through data to solve image understanding problems.
This project aims at applying recent deep learning methods for conversational understanding tasks such as Cortana.
The capability of managing personal photos is becoming crucial. In this work, we have attempted to solve the following pain points for mobile users: 1) intelligent photo tagging, best photo selection, event segmentation and album naming, 2) speech recognition and user intent parsing of time, location, people attributes and objects, 3) search by arbitrary queries.