Graduate Student Research Assistant
Current
Ann Arbor, Michigan, United States
𝐏𝐫𝐨𝐣𝐞𝐜𝐭: 𝐑𝐞𝐚𝐥-𝐓𝐢𝐦𝐞 𝐍𝐮𝐦𝐞𝐫𝐢𝐜𝐚𝐥 𝐃𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐭𝐢𝐚𝐭𝐢𝐨𝐧 (𝐑𝐓𝐍𝐃), 𝐅𝐮𝐧𝐝𝐞𝐝 𝐛𝐲 𝐅𝐨𝐫𝐝 (𝐟𝐮𝐧𝐝𝐢𝐧𝐠 𝐨𝐟 $115𝐊)𝘓𝘦𝘥 𝘵𝘩𝘦 𝘤𝘰𝘭𝘭𝘢𝘣𝘰𝘳𝘢𝘵𝘪𝘰𝘯 𝘸𝘪𝘵𝘩 𝘍𝘰𝘳𝘥’𝘴 𝘦𝘯𝘨𝘪𝘯𝘦𝘦𝘳𝘴 𝘵𝘰 𝘥𝘦𝘷𝘦𝘭𝘰𝘱 𝘢 𝘩𝘪𝘨𝘩-𝘢𝘤𝘤𝘶𝘳𝘢𝘤𝘺 𝘙𝘛𝘕𝘋 𝘢𝘭𝘨𝘰𝘳𝘪𝘵𝘩𝘮 𝘤𝘳𝘪𝘵𝘪𝘤𝘢𝘭 𝘧𝘰𝘳 𝘍𝘰𝘳𝘥’𝘴 𝘪𝘯-𝘩𝘰𝘶𝘴𝘦 𝘢𝘶𝘵𝘰𝘯𝘰𝘮𝘰𝘶𝘴 𝘷𝘦𝘩𝘪𝘤𝘭𝘦 𝘵𝘦𝘤𝘩𝘯𝘰𝘭𝘰𝘨𝘺, 𝘴𝘱𝘦𝘤𝘪𝘧𝘪𝘤𝘢𝘭𝘭𝘺 𝘵𝘢𝘳𝘨𝘦𝘵𝘪𝘯𝘨 𝘵𝘩𝘦 𝘤𝘰𝘮𝘱𝘭𝘦𝘹 𝘤𝘩𝘢𝘭𝘭𝘦𝘯𝘨𝘦 𝘰𝘧 𝘢𝘶𝘵𝘰𝘯𝘰𝘮𝘰𝘶𝘴 𝘧𝘳𝘦𝘦𝘸𝘢𝘺 𝘮𝘦𝘳𝘨𝘪𝘯𝘨• Developed a pioneering RTND algorithm, achieving a 52% increase in accuracy in sensor data differentiation over industry norms, establishing a new standard; led to the publication of 1 journal and 2 first-author conference papers• Delivered research findings to a multi-disciplinary audience at American Control Conference (ACC), one of the leading control conferences with 1300+ attendees𝐏𝐫𝐨𝐣𝐞𝐜𝐭: 𝐒𝐞𝐧𝐬𝐨𝐫-𝐅𝐚𝐮𝐥𝐭 𝐃𝐞𝐭𝐞𝐜𝐭𝐢𝐨𝐧, 𝐅𝐮𝐧𝐝𝐞𝐝 𝐛𝐲 𝐭𝐡𝐞 𝐍𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐒𝐜𝐢𝐞𝐧𝐜𝐞 𝐅𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧 (𝐟𝐮𝐧𝐝𝐢𝐧𝐠 𝐨𝐟 $75𝐊)𝘙𝘦𝘢𝘭-𝘵𝘪𝘮𝘦 𝘥𝘦𝘵𝘦𝘤𝘵𝘪𝘰𝘯 𝘰𝘧 𝘴𝘦𝘯𝘴𝘰𝘳 𝘮𝘢𝘭𝘧𝘶𝘯𝘤𝘵𝘪𝘰𝘯𝘴 𝘪𝘴 𝘤𝘳𝘪𝘵𝘪𝘤𝘢𝘭 𝘧𝘰𝘳 𝘱𝘳𝘦𝘦𝘮𝘱𝘵𝘪𝘷𝘦𝘭𝘺 𝘱𝘳𝘦𝘷𝘦𝘯𝘵𝘪𝘯𝘨 𝘤𝘢𝘵𝘢𝘴𝘵𝘳𝘰𝘱𝘩𝘪𝘤 𝘧𝘢𝘪𝘭𝘶𝘳𝘦𝘴 𝘪𝘯 𝘢𝘶𝘵𝘰𝘯𝘰𝘮𝘰𝘶𝘴 𝘷𝘦𝘩𝘪𝘤𝘭𝘦𝘴 & 𝘢𝘪𝘳𝘤𝘳𝘢𝘧𝘵• Introduced an innovative algorithm to detect and identify sensor faults, breakthrough enabled by innovative work in RTND• Submitted a first-author paper to leading control and system journal, currently undergoing peer review