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Boston is a fantastic student-oriented city, home to some of the best universities in the world.\u003C/p>\u003Cp style=\"margin-left:0px;\">The summer season is especially lively as MERL and Boston are teeming with researchers and visitors from all over the world.\u003C/p>","2024-12-03T21:20:01.452Z","2024-12-03T21:20:50.687Z","2024-12-03T21:20:50.679Z","113",{"id":1156,"name":1157,"alternativeText":15,"caption":15,"width":45,"height":815,"formats":15,"hash":1158,"ext":1159,"mime":866,"size":1160,"url":1161,"previewUrl":15,"provider":22,"provider_metadata":15,"createdAt":1162,"updatedAt":1162},83,"thumbnail_Mitsubishi_Electric_Logo_1_d2184a4b4a.jpg","thumbnail_Mitsubishi_Electric_Logo_1_d2184a4b4a_eb7080ac38",".jpg",7.31,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/thumbnail_Mitsubishi_Electric_Logo_1_d2184a4b4a_eb7080ac38.jpg","2024-12-03T21:20:46.218Z",{"id":644,"variation":1142,"button":1164},[1165],{"id":499,"label":1145,"size":824,"color":825,"style":15,"icon":826,"iconPosition":827,"url":1166,"newWindow":15,"downloadable":15,"shape":15},"https://www.merl.com/","-84",{"id":351,"name":1169,"description":1170,"createdAt":1171,"updatedAt":1172,"publishedAt":1173,"url_path_id":1174,"logo":1175,"website":1182,"url_path":1186},"Quanser","\u003Cp style=\"margin-left:0px;\">About Quanser – \u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://acc2024.a2c2.org/sponsors-and-exhibitors/www.quanser.com\">\u003Cstrong>\u003Cu>www.quanser.com\u003C/u>\u003C/strong>\u003C/a>\u003C/p>\u003Cp style=\"margin-left:0px;\">Quanser is the world leader in innovative technology for engineering education and research. With a heritage in creating leading-edge platforms for controls, mechatronics, and robotics, Quanser has built a legacy over the past 35 years of transformational solutions that bring emerging technologies including autonomous robotics, IoT, self-driving, and virtual reality to students worldwide. Quanser is unique as the only commercial organization that offers a comprehensive, academically sound platform for delivering programs that push the boundaries of traditional engineering education and research. Through a wide network of academic partners and faculty equivalent researchers and course designers, Quanser works with institutions to solve the challenges of modern engineering as true colleagues as opposed to conventional vendors.\u003C/p>","2025-01-12T00:31:03.358Z","2025-01-12T00:31:05.327Z","2025-01-12T00:31:05.321Z","116",{"id":926,"name":1176,"alternativeText":15,"caption":15,"width":45,"height":1177,"formats":15,"hash":1178,"ext":1159,"mime":866,"size":1179,"url":1180,"previewUrl":15,"provider":22,"provider_metadata":15,"createdAt":1181,"updatedAt":1181},"thumbnail_Quanser_logo_low_res_011046dd52.jpg",82,"thumbnail_Quanser_logo_low_res_011046dd52_d4a8975404",2.32,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/thumbnail_Quanser_logo_low_res_011046dd52_d4a8975404.jpg","2025-01-12T00:30:28.544Z",{"id":203,"variation":1142,"button":1183},[1184],{"id":517,"label":1145,"size":824,"color":825,"style":15,"icon":826,"iconPosition":827,"url":1185,"newWindow":15,"downloadable":15,"shape":15},"https://www.quanser.com/","-86",{"id":338,"name":1188,"description":1189,"createdAt":1190,"updatedAt":1191,"publishedAt":1192,"url_path_id":1193,"logo":1194,"website":1220,"url_path":1224},"MathWorks","\u003Cp style=\"margin-left:0px;\">The MATLAB and Simulink product families are fundamental applied math and computational tools at the world's educational institutions. Adopted by more than 6,500 universities and colleges, MathWorks products accelerate the pace of learning, teaching, and research in engineering and science. MathWorks products also help prepare students for careers in industry worldwide, where the tools are widely used for data analysis, mathematical modeling, and algorithm development in collaborative research and new product development.  Application areas include data analytics, mechatronics, communication systems, image processing, computational finance, and computational biology.\u003C/p>","2025-01-12T00:33:31.600Z","2025-01-12T00:33:42.649Z","2025-01-12T00:33:42.643Z","117",{"id":1195,"name":1196,"alternativeText":15,"caption":15,"width":869,"height":1197,"formats":1198,"hash":1216,"ext":863,"mime":866,"size":1217,"url":1218,"previewUrl":15,"provider":22,"provider_metadata":15,"createdAt":1219,"updatedAt":1219},89,"large_Math_Works_Logo_1024x204_ffaa565ecf.jpeg",199,{"small":1199,"medium":1205,"thumbnail":1211},{"ext":863,"url":1200,"hash":1201,"mime":866,"name":1202,"path":15,"size":1203,"width":38,"height":1204},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/small_large_Math_Works_Logo_1024x204_ffaa565ecf_2b4cc396a3.jpeg","small_large_Math_Works_Logo_1024x204_ffaa565ecf_2b4cc396a3","small_large_Math_Works_Logo_1024x204_ffaa565ecf.jpeg",10.31,100,{"ext":863,"url":1206,"hash":1207,"mime":866,"name":1208,"path":15,"size":1209,"width":881,"height":1210},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/medium_large_Math_Works_Logo_1024x204_ffaa565ecf_2b4cc396a3.jpeg","medium_large_Math_Works_Logo_1024x204_ffaa565ecf_2b4cc396a3","medium_large_Math_Works_Logo_1024x204_ffaa565ecf.jpeg",16.94,149,{"ext":863,"url":1212,"hash":1213,"mime":866,"name":1214,"path":15,"size":1215,"width":45,"height":656},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/thumbnail_large_Math_Works_Logo_1024x204_ffaa565ecf_2b4cc396a3.jpeg","thumbnail_large_Math_Works_Logo_1024x204_ffaa565ecf_2b4cc396a3","thumbnail_large_Math_Works_Logo_1024x204_ffaa565ecf.jpeg",4.01,"large_Math_Works_Logo_1024x204_ffaa565ecf_2b4cc396a3",24.39,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/large_Math_Works_Logo_1024x204_ffaa565ecf_2b4cc396a3.jpeg","2025-01-12T00:33:26.907Z",{"id":164,"variation":1142,"button":1221},[1222],{"id":269,"label":1145,"size":824,"color":825,"style":15,"icon":826,"iconPosition":827,"url":1223,"newWindow":15,"downloadable":15,"shape":15},"https://www.mathworks.com/","-87",{"id":414,"name":1226,"description":1227,"createdAt":1228,"updatedAt":1229,"publishedAt":1230,"url_path_id":1231,"logo":1232,"website":1252,"url_path":1256},"MDPI","\u003Cp style=\"margin-left:0px;\">A pioneer in scholarly, open access publishing, MDPI has supported academic communities since 1996. Based in Basel, Switzerland, MDPI has the mission to foster open scientific exchange in all forms, across all disciplines. Our 437 diverse and open access journals, including 428 peer- reviewed journals and 9 conference journals, are supported by more than 295,000 academic experts who share our mission, values, and commitment to providing high-quality service for our authors. We serve scholars from around the world to ensure the latest research is freely available and all content is distributed under a Creative Commons Attribution License (CC BY).\u003C/p>","2025-01-12T00:35:15.712Z","2025-01-12T00:35:17.095Z","2025-01-12T00:35:17.087Z","118",{"id":1233,"name":1234,"alternativeText":15,"caption":15,"width":881,"height":1089,"formats":1235,"hash":1248,"ext":18,"mime":19,"size":1249,"url":1250,"previewUrl":15,"provider":22,"provider_metadata":15,"createdAt":1251,"updatedAt":1251},90,"medium_MDPI_company_logo_a8700b6065.png",{"small":1236,"thumbnail":1242},{"ext":18,"url":1237,"hash":1238,"mime":19,"name":1239,"path":15,"size":1240,"width":38,"height":1241},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/small_medium_MDPI_company_logo_a8700b6065_d9b3b3e019.png","small_medium_MDPI_company_logo_a8700b6065_d9b3b3e019","small_medium_MDPI_company_logo_a8700b6065.png",18.51,118,{"ext":18,"url":1243,"hash":1244,"mime":19,"name":1245,"path":15,"size":1246,"width":45,"height":1247},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/thumbnail_medium_MDPI_company_logo_a8700b6065_d9b3b3e019.png","thumbnail_medium_MDPI_company_logo_a8700b6065_d9b3b3e019","thumbnail_medium_MDPI_company_logo_a8700b6065.png",7.22,58,"medium_MDPI_company_logo_a8700b6065_d9b3b3e019",8.88,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/medium_MDPI_company_logo_a8700b6065_d9b3b3e019.png","2025-01-12T00:34:55.481Z",{"id":499,"variation":1142,"button":1253},[1254],{"id":139,"label":1145,"size":824,"color":825,"style":15,"icon":826,"iconPosition":827,"url":1255,"newWindow":15,"downloadable":15,"shape":15},"https://www.mdpi.com/","-88",{"id":131,"name":1258,"description":1259,"createdAt":1260,"updatedAt":1261,"publishedAt":1262,"url_path_id":1263,"logo":1264,"website":1278,"url_path":1282},"dSPACE","\u003Cp>dSPACE is a leading provider of simulation and validation solutions worldwide for developing networked, autonomous, and electrically powered vehicles. The company's range of end-to-end solutions are used particularly by automotive manufacturers and their suppliers to test the software and hardware components in their new vehicles long before a new model is allowed on the road. Not only is dSPACE a sought-after partner in vehicle development, but engineers also rely on our know-how at dSPACE when it comes to aerospace and industrial automation. Our portfolio ranges from end-to-end solutions for simulation and validation to engineering and consulting services as well as training and support. With approximately 2,200 employees worldwide, dSPACE is headquartered in Paderborn, Germany, has three project centers in Germany, and serves customers through regional dSPACE companies in the USA, the UK, France, Japan, China, Croatia, and South Korea.\u003C/p>","2025-01-17T15:21:12.931Z","2025-01-17T15:39:56.058Z","2025-01-17T15:39:56.051Z","324",{"id":209,"name":1265,"alternativeText":15,"caption":15,"width":1266,"height":1267,"formats":1268,"hash":1274,"ext":863,"mime":866,"size":1275,"url":1276,"previewUrl":15,"provider":22,"provider_metadata":15,"createdAt":1277,"updatedAt":1277},"dSPACE.jpeg",296,63,{"thumbnail":1269},{"ext":863,"url":1270,"hash":1271,"mime":866,"name":1272,"path":15,"size":1273,"width":45,"height":545},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/thumbnail_d_SPACE_c7242cae77.jpeg","thumbnail_d_SPACE_c7242cae77","thumbnail_dSPACE.jpeg",5.3,"d_SPACE_c7242cae77",6.34,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/d_SPACE_c7242cae77.jpeg","2025-01-17T15:20:09.191Z",{"id":517,"variation":1142,"button":1279},[1280],{"id":296,"label":1145,"size":824,"color":825,"style":15,"icon":826,"iconPosition":827,"url":1281,"newWindow":55,"downloadable":15,"shape":15},"https://www.dspace.com/en/inc/home.cfm","-294",{"id":396,"name":1284,"description":1285,"createdAt":1286,"updatedAt":1287,"publishedAt":1288,"url_path_id":1289,"logo":1290,"website":1298,"url_path":1302},"GM","\u003Cp>\u003Cspan style=\"background-color:oklch(100);color:oklch(0.200);\">We envision a future of zero crashes, zero emissions and zero congestion, and we have committed ourselves to leading the way toward this future. General Motors has been pushing the limits of transportation and technology for over 100 years. Today, we are in the midst of a transportation revolution. And we have the ambition, the talent and the technology to realize the safer, better and more sustainable world we want. As an open, inclusive company, we’re also creating an environment where everyone feels welcomed and valued for who they are. One team, where all ideas are considered and heard, where everyone can contribute to their fullest potential, with a culture based in respect, integrity, accountability and equality. Our team brings wide-ranging perspectives and experiences to solving the complex transportation challenges of today and tomorrow. At General Motors, innovation is our north star. As the first automotive company to mass-produce an affordable electric car, and the first to develop an electric starter and air bags, GM has always pushed the limits of engineering. We are General Motors. We transformed how the world moved through the last century. And we’re determined to do it again as we redefine mobility to serve our customers and shareholders and solve societal challenges.\u003C/span>\u003C/p>","2025-01-23T21:35:39.609Z","2025-01-23T21:35:41.629Z","2025-01-23T21:35:41.622Z","326",{"id":1291,"name":1292,"alternativeText":15,"caption":15,"width":1293,"height":1293,"formats":15,"hash":1294,"ext":863,"mime":866,"size":1295,"url":1296,"previewUrl":15,"provider":22,"provider_metadata":15,"createdAt":1297,"updatedAt":1297},96,"thumbnail_GM_logo_3a1557d988.jpeg",156,"thumbnail_GM_logo_3a1557d988_6554944dd1",4.34,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/thumbnail_GM_logo_3a1557d988_6554944dd1.jpeg","2025-01-23T21:35:08.017Z",{"id":269,"variation":1142,"button":1299},[1300],{"id":112,"label":1145,"size":824,"color":825,"style":15,"icon":826,"iconPosition":827,"url":1301,"newWindow":15,"downloadable":15,"shape":15},"https://www.gm.com/","-295",{"id":145,"name":1304,"description":1305,"createdAt":1306,"updatedAt":1307,"publishedAt":1308,"url_path_id":1309,"logo":1310,"website":1316,"url_path":1320},"Halliburton","\u003Cp style=\"margin-left:0px;\">Halliburton is one of the world’s leading providers of products and services to the energy industry. Founded in 1919, we create innovative technologies, products, and services that help our customers maximize their value throughout the life cycle of an asset and advance a sustainable energy future. We combine technology, services and execution expertise to assist our customers with hydrocarbons location, geological data management, drilling and formation evaluation, well construction and completion, and production optimization throughout the life of their asset.\u003C/p>","2025-02-27T02:37:33.554Z","2025-02-27T02:37:40.638Z","2025-02-27T02:37:40.630Z","334",{"id":1028,"name":1311,"alternativeText":15,"caption":15,"width":45,"height":388,"formats":15,"hash":1312,"ext":18,"mime":19,"size":1313,"url":1314,"previewUrl":15,"provider":22,"provider_metadata":15,"createdAt":1315,"updatedAt":1315},"thumbnail_Halliburton_Logo_5e3f947d01.png","thumbnail_Halliburton_Logo_5e3f947d01_7668326667",1.37,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/thumbnail_Halliburton_Logo_5e3f947d01_7668326667.png","2025-02-27T02:37:07.771Z",{"id":112,"variation":1142,"button":1317},[1318],{"id":552,"label":1145,"size":824,"color":825,"style":15,"icon":826,"iconPosition":827,"url":1319,"newWindow":15,"downloadable":15,"shape":15},"https://www.halliburton.com/","-300",{"id":302,"name":1322,"description":1323,"createdAt":1324,"updatedAt":1325,"publishedAt":1326,"url_path_id":1327,"logo":1328,"website":1361,"url_path":1365},"Franklin Open","\u003Cp style=\"margin-left:0px;\">\u003Cspan style=\"color:rgb(0,0,0);\">Franklin Open is a peer-reviewed, gold open-access journal that focuses on the fields of engineering and applied mathematics. Franklin Open is a partner journal to the longstanding Journal of The Franklin Institute, which has been publishing scientific research and discoveries for nearly 200 years. The journal was created to not only continue that legacy, but to provide a sustainable platform for new research to be widely disseminated from all voices in the scientific and academic communities. Franklin Open aims to publish high-quality manuscripts under such topics as, Complex Networks & Dynamic Systems, Control Engineering, Robotics & General Dynamic Systems, Energy & Power Systems, Information & Communications, Data Science & Artificial Intelligence, Neural Networks & Learning Systems, Speech, Image, & Signal Processing, and Epidemiology & Evolutionary Systems. We welcome new submissions as well as special issue proposals through our website. If you have any questions, please contact \u003C/span>\u003Ca href=\"mailto:franklinopen@fi.edu\">\u003Cspan style=\"color:rgb(70,120,134);\">\u003Cstrong>\u003Cu>franklinopen@fi.edu\u003C/u>\u003C/strong>\u003C/span>\u003C/a>\u003Cspan style=\"color:rgb(0,0,0);\">.\u003C/span>\u003C/p>","2025-02-27T15:57:53.785Z","2025-05-14T21:09:52.777Z","2025-02-27T15:57:55.775Z","335",{"id":1059,"name":1329,"alternativeText":15,"caption":15,"width":1330,"height":1331,"formats":1332,"hash":1357,"ext":1159,"mime":866,"size":1358,"url":1359,"previewUrl":15,"provider":22,"provider_metadata":15,"createdAt":1360,"updatedAt":1360},"Franklin Open LOGO.jpg",2480,688,{"large":1333,"small":1339,"medium":1345,"thumbnail":1351},{"ext":1159,"url":1334,"hash":1335,"mime":866,"name":1336,"path":15,"size":1337,"width":869,"height":1338},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/large_Franklin_Open_LOGO_0cecf262d9.jpg","large_Franklin_Open_LOGO_0cecf262d9","large_Franklin Open LOGO.jpg",28.72,277,{"ext":1159,"url":1340,"hash":1341,"mime":866,"name":1342,"path":15,"size":1343,"width":38,"height":1344},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/small_Franklin_Open_LOGO_0cecf262d9.jpg","small_Franklin_Open_LOGO_0cecf262d9","small_Franklin Open LOGO.jpg",11.2,139,{"ext":1159,"url":1346,"hash":1347,"mime":866,"name":1348,"path":15,"size":1349,"width":881,"height":1350},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/medium_Franklin_Open_LOGO_0cecf262d9.jpg","medium_Franklin_Open_LOGO_0cecf262d9","medium_Franklin Open LOGO.jpg",19.7,208,{"ext":1159,"url":1352,"hash":1353,"mime":866,"name":1354,"path":15,"size":1355,"width":45,"height":1356},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/thumbnail_Franklin_Open_LOGO_0cecf262d9.jpg","thumbnail_Franklin_Open_LOGO_0cecf262d9","thumbnail_Franklin Open LOGO.jpg",4.23,68,"Franklin_Open_LOGO_0cecf262d9",81.38,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/Franklin_Open_LOGO_0cecf262d9.jpg","2025-02-27T15:57:50.459Z",{"id":188,"variation":1142,"button":1362},[1363],{"id":757,"label":1145,"size":824,"color":825,"style":15,"icon":826,"iconPosition":827,"url":1364,"newWindow":15,"downloadable":15,"shape":15},"https://www.sciencedirect.com/journal/franklin-open","-301",{"id":644,"name":1367,"description":1368,"createdAt":1369,"updatedAt":1370,"publishedAt":1371,"url_path_id":1372,"logo":1373,"website":1404,"url_path":1408},"Lockheed Martin","\u003Cp>Headquartered in Bethesda, Maryland, Lockheed Martin, is a global security and aerospace company that employs approximately 116,000 people worldwide and is principally engaged in the research, design, development, manufacture, integration and sustainment of advanced technology systems, products, and services. We solve complex challenges, advance scientific discovery, and deliver innovative solutions to help our customers keep people safe. With a focus on the U.S. National Defense Strategy, we are developing, innovating, and integrating hypersonic capabilities that travel Mach 5 or more, directed energy that travels at the speed of light, and autonomous systems used for a variety of lifesaving military and commercial applications. \u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://lockheedmartin.com/aeronautics\">Lockheed Martin Aeronautics\u003C/a> develops high-performance combat, air mobility and reconnaissance and surveillance aircraft. We also provide world-class training, focused logistics support, and advanced targeting and navigation technologies to enable the right people with the right skills to be in the right place at the right time with the right information to accomplish their missions. \u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://lockheedmartin.com/space\">Lockheed Martin Space\u003C/a> builds satellites and spacecraft that do amazing things in space for government and commercial customers. Lockheed Martin-built satellites give earlier warning of severe weather, connect troops on the battlefield, and deliver GPS directions to a billion people worldwide. As we look to the future, we are driving innovations to help our customers do even more in orbit. That is why we are designing smarter satellites that operate like smartphones in the sky, with apps that can be updated in orbit so they can adapt as mission needs on the ground change. Within Lockheed Martin, the \u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://lockheedmartin.com/atl\">Advanced Technology Laboratories\u003C/a> is a research and development center for scientific advancement in the areas of autonomy, robotics, artificial intelligence, command & control, human-machine symbiosis, spectrum operations, hypersonics and cyber. Careers page: \u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://lockheedmartin.com/careers.\">https://lockheedmartin.com/careers.\u003C/a> \u003C/p>","2025-04-26T01:34:41.209Z","2025-07-02T17:07:12.122Z","2025-04-26T01:34:50.770Z","351",{"id":808,"name":1374,"alternativeText":15,"caption":15,"width":1375,"height":1376,"formats":1377,"hash":1400,"ext":863,"mime":866,"size":1401,"url":1402,"previewUrl":15,"provider":22,"provider_metadata":15,"createdAt":1403,"updatedAt":1403},"Lockheed-Martin-Logo-1200x214.jpeg",1200,214,{"large":1378,"small":1384,"medium":1389,"thumbnail":1395},{"ext":863,"url":1379,"hash":1380,"mime":866,"name":1381,"path":15,"size":1382,"width":869,"height":1383},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/large_Lockheed_Martin_Logo_1200x214_ccaa8c8794.jpeg","large_Lockheed_Martin_Logo_1200x214_ccaa8c8794","large_Lockheed-Martin-Logo-1200x214.jpeg",19.54,178,{"ext":863,"url":1385,"hash":1386,"mime":866,"name":1387,"path":15,"size":1388,"width":38,"height":1195},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/small_Lockheed_Martin_Logo_1200x214_ccaa8c8794.jpeg","small_Lockheed_Martin_Logo_1200x214_ccaa8c8794","small_Lockheed-Martin-Logo-1200x214.jpeg",8.38,{"ext":863,"url":1390,"hash":1391,"mime":866,"name":1392,"path":15,"size":1393,"width":881,"height":1394},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/medium_Lockheed_Martin_Logo_1200x214_ccaa8c8794.jpeg","medium_Lockheed_Martin_Logo_1200x214_ccaa8c8794","medium_Lockheed-Martin-Logo-1200x214.jpeg",14.23,134,{"ext":863,"url":1396,"hash":1397,"mime":866,"name":1398,"path":15,"size":1399,"width":45,"height":256},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/thumbnail_Lockheed_Martin_Logo_1200x214_ccaa8c8794.jpeg","thumbnail_Lockheed_Martin_Logo_1200x214_ccaa8c8794","thumbnail_Lockheed-Martin-Logo-1200x214.jpeg",3.43,"Lockheed_Martin_Logo_1200x214_ccaa8c8794",24.28,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/Lockheed_Martin_Logo_1200x214_ccaa8c8794.jpeg","2025-04-26T01:34:36.801Z",{"id":552,"variation":1142,"button":1405},[1406],{"id":358,"label":1145,"size":824,"color":825,"style":15,"icon":826,"iconPosition":827,"url":1407,"newWindow":55,"downloadable":15,"shape":15},"https://lockheedmartin.com/","-317",{"id":289,"name":1082,"description":1410,"createdAt":1411,"updatedAt":1412,"publishedAt":1413,"url_path_id":1414,"logo":1415,"website":1416,"url_path":1420},"\u003Cp style=\"margin-left:0px;\">SIAM publishes textbooks and monographs in print and electronic format. Visit our booth to browse our titles, all available at discounted conference pricing. SIAM partners with authors to publish books of outstanding quality and accessible pricing. If you’re interested in writing a book, please contact the SIAM Executive Editor \u003Ca href=\"mailto:greenspan@siam.org\">\u003Cstrong>\u003Cu>greenspan@siam.org\u003C/u>\u003C/strong>\u003C/a>\u003Cstrong>\u003Cu>.\u003C/u>\u003C/strong>\u003C/p>","2025-05-28T03:16:18.871Z","2025-05-28T03:18:49.090Z","2025-05-28T03:18:49.082Z","355",{"id":131,"name":1088,"alternativeText":15,"caption":15,"width":1089,"height":1090,"formats":15,"hash":1091,"ext":18,"mime":19,"size":1092,"url":1093,"previewUrl":15,"provider":22,"provider_metadata":15,"createdAt":1094,"updatedAt":1095},{"id":638,"variation":1142,"button":1417},[1418],{"id":433,"label":1145,"size":824,"color":825,"style":15,"icon":826,"iconPosition":827,"url":1419,"newWindow":55,"downloadable":15,"shape":15},"https://www.siam.org/Publications/Books","-320",{"pagination":1422},{"page":5,"pageSize":164,"pageCount":5,"total":289},{"id":177,"heading":482,"pageHeader":1424,"sections":1425},{"id":177,"description":15,"showPageHeader":55,"backgroundColor":58,"image":15},[1426,1435,1551],{"id":236,"__component":1427,"componentVariation":1428,"styles":15,"header":1429,"body":1432},"content.content","Content Image Left",{"id":164,"heading":1430,"prose":54,"lead":15,"eyebrow":15,"badge":15,"componentVariation":1431,"containerWidth":15,"image":15},"Presentation Schedule","Heading Center",{"id":1433,"title":15,"body":1434,"containerWidth":15,"buttonGroup":15,"media":15},55,"\u003Cp>The Plenary talk schedule is:\u003C/p>\u003Cul>\u003Cli>Tuesday, July 8: Maryam Fazel, 8:30-9:30am\u003C/li>\u003Cli>Wednesday, July 9: Elisa Franco, 8:30-9:30am; Mengdi Wang, 10-11am; Raffaello (Raff) D'Andrea, 7-8pm (\u003Ca target=\"_blank\" rel=\"noopener noreferrer\" href=\"https://acc2025.a2c2.org/public-presentation\">Public Presentation\u003C/a>)\u003C/li>\u003Cli>Thursday, July 10: George Pappas, 8:30-9:30am\u003C/li>\u003C/ul>",{"id":28,"__component":1436,"componentVariation":1437,"styles":15,"header":1438,"contactGroup":1440},"content.contacts","Contacts Carousel Card",{"id":203,"heading":1439,"prose":54,"lead":15,"eyebrow":15,"badge":15,"componentVariation":1431,"containerWidth":15,"image":15},"Speaker Biographies ",[1441],{"id":177,"groupTitle":15,"contacts":1442},[1443,1469,1502,1527],{"id":517,"contact":1444},{"id":131,"name":1445,"committee":15,"position":15,"affiliation":1446,"email":15,"biography":1447,"createdAt":1448,"updatedAt":1449,"url_path_id":1450,"contactPhoto":1451,"socialLinks":1465,"url_path":1468},"Maryam Fazel","University of Washington","\u003Cp>\u003Cspan style=\"color:rgb(33,33,33);font-family:Arial, Helvetica, sans-serif;\">Maryam Fazel is the Moorthy Family Professor of Electrical and Computer Engineering at the University of Washington, with adjunct appointments in Computer Science and Engineering, Mathematics, and Statistics. Maryam received a PhD from Stanford University and a BS from Sharif University of Technology in Iran. She is a recipient of the NSF Career Award, UWEE Outstanding Teaching Award, UAI conference Best Student Paper Award, and her paper on low-rank matrix estimation was selected by ScienceWatch as a Fast Breaking Paper (based on number of citations). She directs the Institute for Foundations of Data Science (IFDS), a multi-site NSF TRIPODS Institute. She is a Program Chair of ICML 2025, an Action Editor for Journal on Machine Learning Research, and serves on the Editorial board of the MOS-SIAM Book Series on Optimization. Her current research interests are in the area of optimization, machine learning, and control.\u003C/span>\u003C/p>","2024-02-13T16:35:30.875Z","2025-01-27T20:49:29.112Z","36",{"id":344,"name":1452,"alternativeText":15,"caption":15,"width":1453,"height":1001,"formats":1454,"hash":1461,"ext":1159,"mime":866,"size":1462,"url":1463,"previewUrl":15,"provider":22,"provider_metadata":15,"createdAt":1464,"updatedAt":1464},"mfazel.jpg",225,{"thumbnail":1455},{"ext":1159,"url":1456,"hash":1457,"mime":866,"name":1458,"path":15,"size":1459,"width":1460,"height":1293},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/thumbnail_mfazel_3ec0e6a3da.jpg","thumbnail_mfazel_3ec0e6a3da","thumbnail_mfazel.jpg",4.13,117,"mfazel_3ec0e6a3da",10.79,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/mfazel_3ec0e6a3da.jpg","2024-02-13T16:34:45.804Z",[1466],{"id":28,"url":1467,"platform":1145},"https://people.ece.uw.edu/fazel_maryam/","-29",{"id":269,"contact":1470},{"id":338,"name":1471,"committee":15,"position":15,"affiliation":1472,"email":15,"biography":1473,"createdAt":1474,"updatedAt":1475,"url_path_id":1476,"contactPhoto":1477,"socialLinks":1498,"url_path":1501},"Elisa Franco","University of California, Los Angeles","\u003Cp>\u003Cspan style=\"color:rgb(0,0,0);\">Elisa Franco is a Professor in Mechanical & Aerospace Engineering and Bioengineering at UCLA.  She received a Ph.D. in Control and Dynamical Systems from the California Institute of Technology, and a Ph.D. in Automation from the University of Trieste, Italy. The Franco group works on research problems at the intersection of mathematical modeling and DNA/RNA nanotechnology, with focus on the design and synthesis of biomolecular circuits and responsive materials. These projects are funded by the NSF, the DOE, the Sloan Foundation, and the Broad Stem Cell Research Center at UCLA. Prof. Franco is the recipient of an NSF CAREER award, a Rose Hills Foundation Young Investigator award, and is a Hellman Fellow. She is an active member of the IEEE Control Systems Society, and served in the Board of Governors and as Student Activities Chair.\u003C/span>\u003C/p>","2024-02-13T01:36:43.015Z","2024-02-13T16:41:49.347Z","34",{"id":407,"name":1478,"alternativeText":15,"caption":15,"width":1479,"height":1480,"formats":1481,"hash":1494,"ext":1159,"mime":866,"size":1495,"url":1496,"previewUrl":15,"provider":22,"provider_metadata":15,"createdAt":1497,"updatedAt":1497},"elisa_franco.jpg",581,643,{"small":1482,"thumbnail":1488},{"ext":1159,"url":1483,"hash":1484,"mime":866,"name":1485,"path":15,"size":1486,"width":1487,"height":38},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/small_elisa_franco_019b193b3b.jpg","small_elisa_franco_019b193b3b","small_elisa_franco.jpg",29.37,452,{"ext":1159,"url":1489,"hash":1490,"mime":866,"name":1491,"path":15,"size":1492,"width":1493,"height":1293},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/thumbnail_elisa_franco_019b193b3b.jpg","thumbnail_elisa_franco_019b193b3b","thumbnail_elisa_franco.jpg",4.8,141,"elisa_franco_019b193b3b",44.49,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/elisa_franco_019b193b3b.jpg","2024-02-13T01:38:44.310Z",[1499],{"id":101,"url":1500,"platform":1145},"https://www.seas.ucla.edu/francolab/","-27",{"id":139,"contact":1503},{"id":414,"name":1504,"committee":15,"position":15,"affiliation":1505,"email":15,"biography":1506,"createdAt":1507,"updatedAt":1508,"url_path_id":1509,"contactPhoto":1510,"socialLinks":1523,"url_path":1526},"George Pappas","University of Pennsylvania","\u003Cp>\u003Cspan style=\"color:rgb(33,33,33);\">George Pappas is the UPS Foundation Professor at the Department of Electrical and Systems Engineering at the University of Pennsylvania. He also holds a secondary appointment in the Departments of Computer and Information Sciences, as well as Mechanical Engineering and Applied Mechanics.  He currently serves as the Associate Dean for Research and Innovation in the School of Engineering and Applied Science and as the Director of the Raj and Neera Singh program in Artificial Intelligence. Pappas’s research focuses on control systems, robotics, autonomous systems, formal methods, and machine learning for safe and secure cyber-physical systems. He has received numerous awards, including the NSF PECASE, the Antonio Ruberti Young Researcher Prize, the George S. Axelby Award, the O. Hugo Schuck Best Paper Award, and the George H. Heilmeier Faculty Excellence Award. Pappas has mentored more than fifty students and postdocs, now faculty in leading universities worldwide. He is a Fellow of IEEE, IFAC, and was elected to the National Academy of Engineering in 2024.\u003C/span>\u003C/p>","2024-02-13T16:31:47.171Z","2025-01-11T22:27:13.039Z","35",{"id":656,"name":1511,"alternativeText":15,"caption":15,"width":1512,"height":1512,"formats":1513,"hash":1519,"ext":1159,"mime":866,"size":1520,"url":1521,"previewUrl":15,"provider":22,"provider_metadata":15,"createdAt":1522,"updatedAt":1522},"pappas-george.jpg",400,{"thumbnail":1514},{"ext":1159,"url":1515,"hash":1516,"mime":866,"name":1517,"path":15,"size":1518,"width":1293,"height":1293},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/thumbnail_pappas_george_8ed3321823.jpg","thumbnail_pappas_george_8ed3321823","thumbnail_pappas-george.jpg",4.9,"pappas_george_8ed3321823",25.24,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/pappas_george_8ed3321823.jpg","2024-02-13T16:31:41.727Z",[1524],{"id":5,"url":1525,"platform":1145},"https://www.georgejpappas.org/","-28",{"id":188,"contact":1528},{"id":302,"name":1529,"committee":15,"position":15,"affiliation":1530,"email":15,"biography":1531,"createdAt":1532,"updatedAt":1532,"url_path_id":1533,"contactPhoto":1534,"socialLinks":1547,"url_path":1550},"Mengdi Wang","Princeton University","\u003Cp>\u003Cspan style=\"color:rgb(33,33,33);\">Mengdi Wang is an associate professor at the Department of Electrical and Computer Engineering and Center for Statistics and Machine Learning at Princeton University. She is also affiliated with the Department of Computer Science, Princeton’s ML Theory Group. She was a visiting research scientist at DeepMind, IAS and Simons Institute on Theoretical Computer Science. Her research focuses on machine learning, reinforcement learning, generative AI, AI for science and intelligence system applications . Mengdi received her PhD in Electrical Engineering and Computer Science from Massachusetts Institute of Technology in 2013, where she was affiliated with the Laboratory for Information and Decision Systems and advised by Dimitri P. Bertsekas. Before that, she got her bachelor degree from the Department of Automation, Tsinghua University. Mengdi received the Young Researcher Prize in Continuous Optimization of the Mathematical Optimization Society in 2016 (awarded once every three years), the Princeton SEAS Innovation Award in 2016, the NSF Career Award in 2017, the Google Faculty Award in 2017,  and the MIT Tech Review 35-Under-35 Innovation Award (China region) in 2018, WAIC YunFan Award 2022, AACC’s Donald Eckman Award 2024. She serves as a Program Chair for ICLR 2023 and Senior AC for Neurips, ICML, COLT, associate editor for Harvard Data Science Review, Operations Research. Research supported by NSF, AFOSR, NIH, ONR, Google, Microsoft C3.ai, FinUP, RVAC Medicines.\u003C/span>\u003C/p>","2024-05-08T19:08:59.583Z","39",{"id":1247,"name":1535,"alternativeText":15,"caption":15,"width":1376,"height":1001,"formats":1536,"hash":1543,"ext":1159,"mime":866,"size":1544,"url":1545,"previewUrl":15,"provider":22,"provider_metadata":15,"createdAt":1546,"updatedAt":1546},"wang01-1.jpg",{"thumbnail":1537},{"ext":1159,"url":1538,"hash":1539,"mime":866,"name":1540,"path":15,"size":1541,"width":1542,"height":1293},"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/thumbnail_wang01_1_cb8417feb3.jpg","thumbnail_wang01_1_cb8417feb3","thumbnail_wang01-1.jpg",4.09,111,"wang01_1_cb8417feb3",11.53,"https://confcats-siteplex.s3.us-east-1.amazonaws.com/acc25/wang01_1_cb8417feb3.jpg","2024-05-08T19:06:28.243Z",[1548],{"id":120,"url":1549,"platform":1145},"https://ece.princeton.edu/people/mengdi-wang","-32",{"id":101,"__component":1552,"componentVariation":1553,"contactsVariation":1554,"styles":1555,"header":15,"sessionsGroup":1557},"content.sessions","Sessions Base","Card Contact Full",{"id":217,"edgeTop":57,"edgeBottom":57,"background":1556,"containerWidth":15},"base-50",[1558,1576,1595,1613],{"id":198,"groupTitle":15,"sessions":1559},[1560],{"id":101,"session":1561},{"id":28,"title":1562,"teaser":1563,"body":54,"createdAt":1564,"updatedAt":1565,"publishedAt":1566,"url_path_id":1567,"contacts":1568,"url_path":1575},"Policy Optimization Methods for Control","\u003Cp>\u003Cspan style=\"color:rgb(33,33,33);\">Policy Optimization methods enjoy wide practical use in Reinforcement Learning (RL) for applications ranging from robotic manipulation to game-playing, partly because they are easy to implement, and require only black-box access to the underlying model. This talk focuses on recent developments in policy optimization (a gradient-based approach for feedback control design) popularized by its success in RL. We describe\u003C/span>\u003Cspan style=\"color:black;\"> theoretical results on the optimization landscape, global convergence, and sample complexity of\u003C/span>\u003Cspan style=\"color:rgb(33,33,33);\"> policy optimization in several canonical continuous control problems, despite their nonconvexity in policy parameters, by exploiting structural properties such as the Polyak-Lojasiewicz (or gradient dominance) condition. This line of work attempts to bring control theory and RL closer, and has helped advance two recent trends: (1) use of control problems as benchmarks for less-understood RL algorithms, and (2) theoretically-sound use of RL-style methods in control. \u003C/span>\u003C/p>","2024-09-18T19:41:10.880Z","2025-05-04T20:51:00.434Z","2024-10-19T16:06:10.640Z","107",[1569],{"id":131,"name":1445,"committee":15,"position":15,"affiliation":1446,"email":15,"biography":1447,"createdAt":1448,"updatedAt":1449,"url_path_id":1450,"contactPhoto":1570,"socialLinks":1573,"url_path":1468},{"id":344,"name":1452,"alternativeText":15,"caption":15,"width":1453,"height":1001,"formats":1571,"hash":1461,"ext":1159,"mime":866,"size":1462,"url":1463,"previewUrl":15,"provider":22,"provider_metadata":15,"createdAt":1464,"updatedAt":1464},{"thumbnail":1572},{"ext":1159,"url":1456,"hash":1457,"mime":866,"name":1458,"path":15,"size":1459,"width":1460,"height":1293},[1574],{"id":28,"url":1467,"platform":1145},"-79",{"id":481,"groupTitle":15,"sessions":1577},[1578],{"id":120,"session":1579},{"id":101,"title":1580,"teaser":1581,"body":54,"createdAt":1582,"updatedAt":1583,"publishedAt":1584,"url_path_id":1585,"contacts":1586,"url_path":1594},"Dynamics and Control of Biomolecular Systems","\u003Cp style=\"text-align:justify;\">Biological cells are complex dynamic systems in which sensing, control, and actuation are orchestrated by networks of active molecules with coupled functions. Cells not only detect and process information, but also leverage that information to direct the assembly of physical structures, such as scaffolds, membranes, and organelles. A productive approach to understanding the design principles governing these multicomponent systems involves the constructive, bottom-up synthesis of biomolecules capable of performing dynamic tasks. Many challenges emerge when building such systems, such as parametric uncertainty, unintended interactions, and the breakdown of signaling modularity, which can be better understood by synthesis efforts outside the cell. I will discuss these challenges in the context of in vitro synthetic biology, which offers a simplified environment for constructing coupled biochemical reaction networks and self-assembling systems. I will begin by describing methods to design artificial nucleic acids (DNA and RNA) that drive the creation of signal generators and components that self-assemble into a variety of structural elements, like filamentous crystals and amorphous condensates. Next, I will explore how these signaling networks and self-assembled structures can be interconnected via the design of nucleic acid sequences, using computational tools to program their interactions. I will then discuss how pulse generators and oscillator circuits can regulate the formation and dissolution of self-assembled physical structures. I will also describe how these techniques have enabled the creation of dynamic, artificial organelles within living cells. These advances contribute to our broader goal of controlling physical matter through biomolecular reactions, paving the way for the development of intelligent biological materials that can sense and make decisions through embedded control programs.\u003C/p>","2024-09-18T19:41:37.404Z","2025-04-23T22:23:03.335Z","2024-10-19T16:06:05.378Z","108",[1587],{"id":338,"name":1471,"committee":15,"position":15,"affiliation":1472,"email":15,"biography":1473,"createdAt":1474,"updatedAt":1475,"url_path_id":1476,"contactPhoto":1588,"socialLinks":1592,"url_path":1501},{"id":407,"name":1478,"alternativeText":15,"caption":15,"width":1479,"height":1480,"formats":1589,"hash":1494,"ext":1159,"mime":866,"size":1495,"url":1496,"previewUrl":15,"provider":22,"provider_metadata":15,"createdAt":1497,"updatedAt":1497},{"small":1590,"thumbnail":1591},{"ext":1159,"url":1483,"hash":1484,"mime":866,"name":1485,"path":15,"size":1486,"width":1487,"height":38},{"ext":1159,"url":1489,"hash":1490,"mime":866,"name":1491,"path":15,"size":1492,"width":1493,"height":1293},[1593],{"id":101,"url":1500,"platform":1145},"-80",{"id":574,"groupTitle":15,"sessions":1596},[1597],{"id":177,"session":1598},{"id":177,"title":1599,"teaser":1600,"body":54,"createdAt":1601,"updatedAt":1602,"publishedAt":1603,"url_path_id":1604,"contacts":1605,"url_path":1612},"Control for A.I. Safety","\u003Cp>\u003Cspan style=\"color:rgb(33,33,33);\">The rapid proliferation of artificial intelligence (A.I.) and large language models (LLMs) is revolutionizing our world. However, as these systems increasingly find real-world applications in controlling physical systems—such as autonomous robots, self-driving cars, and other critical infrastructure—their potential to cause harm has escalated dramatically. This is due to large error rates, lack of robustness, hallucinations, as well as a new LLM attack known as jailbreaking.  Ensuring safety in safety critical contexts requires a paradigm shift from traditional A.I. development toward robust safety mechanisms. In this talk, I will explore how ideas from control theory can provide rigorous tools and frameworks for developing safety filters tailored towards control systems with deep learning in the loop and LLM-controlled robots, including VLA-controlled robots. By leveraging tools such as integrated quadratic constraints, temporal logic synthesis, and control barrier functions, I will address how our community can play a crucial role in designing A.I. safety systems that effectively mitigate risks while preserving the utility and adaptability of A.I. in real world applications.\u003C/span>\u003C/p>","2025-01-11T22:25:12.165Z","2025-01-11T22:25:33.708Z","2025-01-11T22:25:15.843Z","115",[1606],{"id":414,"name":1504,"committee":15,"position":15,"affiliation":1505,"email":15,"biography":1506,"createdAt":1507,"updatedAt":1508,"url_path_id":1509,"contactPhoto":1607,"socialLinks":1610,"url_path":1526},{"id":656,"name":1511,"alternativeText":15,"caption":15,"width":1512,"height":1512,"formats":1608,"hash":1519,"ext":1159,"mime":866,"size":1520,"url":1521,"previewUrl":15,"provider":22,"provider_metadata":15,"createdAt":1522,"updatedAt":1522},{"thumbnail":1609},{"ext":1159,"url":1515,"hash":1516,"mime":866,"name":1517,"path":15,"size":1518,"width":1293,"height":1293},[1611],{"id":5,"url":1525,"platform":1145},"-85",{"id":120,"groupTitle":15,"sessions":1614},[1615],{"id":5,"session":1616},{"id":5,"title":1617,"teaser":1618,"body":54,"createdAt":1619,"updatedAt":1620,"publishedAt":1621,"url_path_id":1622,"contacts":1623,"url_path":1630},"Controlled Generation for Large Foundation Models","\u003Cp>Recent advances in large foundation models, such as large language models (LLMs) and diffusion models, have demonstrated impressive capabilities. However, to truly align these models with user feedback or maximize real-world objectives, it is crucial to exert control over the decoding processes, in order to steer the distribution of generated output. In this talk, we will explore methods and theory for controlled generation within LLMs and diffusion models. We will discuss various modalities or achieving this control, focusing on applications such as alignment of LLM, accelerated inference, transfer learning, and diffusion-based optimizer.\u003C/p>\u003Cp> \u003C/p>","2024-09-18T17:27:49.887Z","2025-04-23T22:16:27.385Z","2024-09-18T17:27:51.428Z","106",[1624],{"id":302,"name":1529,"committee":15,"position":15,"affiliation":1530,"email":15,"biography":1531,"createdAt":1532,"updatedAt":1532,"url_path_id":1533,"contactPhoto":1625,"socialLinks":1628,"url_path":1550},{"id":1247,"name":1535,"alternativeText":15,"caption":15,"width":1376,"height":1001,"formats":1626,"hash":1543,"ext":1159,"mime":866,"size":1544,"url":1545,"previewUrl":15,"provider":22,"provider_metadata":15,"createdAt":1546,"updatedAt":1546},{"thumbnail":1627},{"ext":1159,"url":1538,"hash":1539,"mime":866,"name":1540,"path":15,"size":1541,"width":1542,"height":1293},[1629],{"id":120,"url":1549,"platform":1145},"-78",{"data":1632,"meta":1633},{"id":177,"heading":482,"createdAt":487,"updatedAt":488,"publishedAt":489,"url_path_id":490,"url_path":492,"contentType":84},{},1778851769437]