Launched in October 2020, the MIT and Accenture Convergence Initiative for Business and Expertise underscores the methods wherein business and expertise can collaborate to spur innovation. The five-year initiative goals to attain its mission by means of analysis, training, and fellowships. To that finish, Accenture has as soon as once more awarded 5 annual fellowships to MIT graduate college students engaged on analysis in business and expertise convergence who’re underrepresented, together with by race, ethnicity, and gender.
This yr’s Accenture Fellows work throughout analysis areas together with telemonitoring, human-computer interactions, operations analysis, AI-mediated socialization, and chemical transformations. Their analysis covers a big selection of tasks, together with designing low-power processing {hardware} for telehealth purposes; making use of machine studying to streamline and enhance enterprise operations; bettering psychological well being care by means of synthetic intelligence; and utilizing machine studying to know the environmental and well being penalties of complicated chemical reactions.
As a part of the applying course of, pupil nominations had been invited from every unit inside the College of Engineering, in addition to from the Institute’s 4 different colleges and the MIT Schwarzman Faculty of Computing. 5 distinctive college students had been chosen as fellows for the initiative’s third yr.
Drew Buzzell is a doctoral candidate in electrical engineering and laptop science whose analysis issues telemonitoring, a fast-growing sphere of telehealth wherein info is collected by means of internet-of-things (IoT) related units and transmitted to the cloud. At present, the excessive quantity of data concerned in telemonitoring — and the time and power prices of processing it — make knowledge evaluation troublesome. Buzzell’s work is concentrated on edge computing, a brand new computing structure that seeks to handle these challenges by managing knowledge nearer to the supply, in a distributed community of IoT units. Buzzell earned his BS in physics and engineering science and his MS in engineering science from the Pennsylvania State College.
Mengying (Cathy) Fang is a grasp’s pupil within the MIT College of Structure and Planning. Her analysis focuses on augmented actuality and digital actuality platforms. Fang is growing novel sensors and machine elements that mix computation, supplies science, and engineering. Shifting ahead, she is going to discover matters together with tender robotics strategies that may very well be built-in with garments and wearable units and haptic suggestions with the intention to develop interactions with digital objects. Fang earned a BS in mechanical engineering and human-computer interplay from Carnegie Mellon College.
Xiaoyue Gong is a doctoral candidate in operations analysis on the MIT Sloan College of Administration. Her analysis goals to harness the facility of machine studying and knowledge science to scale back inefficiencies within the operation of companies, organizations, and society. With the assist of an Accenture Fellowship, Gong seeks to seek out options to operational issues by designing reinforcement studying strategies and different machine studying strategies to embedded operational issues. Gong earned a BS in honors arithmetic and interactive media arts from New York College.
Ruby Liu is a doctoral candidate in medical engineering and medical physics. Their analysis addresses the rising pandemic of loneliness amongst older adults, which results in poor well being outcomes and presents notably excessive dangers for traditionally marginalized folks, together with members of the LGBTQ+ neighborhood and other people of coloration. Liu is designing a community of interconnected AI brokers that foster connections between person and agent, providing psychological well being care whereas strengthening and facilitating human-human connections. Liu acquired a BS in biomedical engineering from Johns Hopkins College.
Joules Provenzano is a doctoral candidate in chemical engineering. Their work integrates machine studying and liquid chromatography-high decision mass spectrometry (LC-HRMS) to enhance our understanding of complicated chemical reactions within the setting. As an Accenture Fellow, Provenzano will construct upon current advances in machine studying and LC-HRMS, together with novel algorithms for processing actual, experimental HR-MS knowledge and new approaches in extracting structure-transformation guidelines and kinetics. Their analysis may pace the tempo of discovery within the chemical sciences and advantages industries together with oil and fuel, prescription drugs, and agriculture. Provenzano earned a BS in chemical engineering and worldwide and international research from the Rochester Institute of Expertise.
