Editor-in-Chief and Editors

Dr. Jeanne Bickford has had a long and wide-ranging career first as a member of IBM’s technical Staff in various scientific and managerial roles, and most recently as a Distinguished Member of the Technical Staff at Globalfoundries. Her experience spans the range of manufacturing, product design, new product introduction and device design. She has authored/co-authored 30 conference/journal papers in the area of design for manufacturing and has 87 issued US patents, one issued China patent, and one issued Japan patent. Dr. Bickford has also served as a guest associate editor for these Transactions for the last 2 years, managing papers associated with the annual ASMC Conference. Her extensive experience will allow her to contribute in the areas of Yield Modeling and Analysis and Factory Modeling.

Martin W. Braun is a Technologist in Intel Corporation’s Technology Development Analytics and Technology Automation department.  Since joining Intel in 2004, Martin has delivered innovative algorithmic solutions for run-to-run control, image analysis, fault detection and classification, mid-range planning, and supply chain management.  These have been applied in various manufacturing areas to include wafer fabrication, assembly/test operations, substrate fabrication, and interfactory material transport.  Prior to joining Intel, Martin was a Technologist at Texas Instrument’s Kilby Center from 2001-2004, developing run-to-run control and fault detection algorithms for the wafer lithography and etch processes.  Martin has published over 40 papers/articles in various conferences and journals, and cowrote two book chapters.  He received his MSE and PhD (2001) degrees from Arizona State University.

Dragan Djurdjanovic obtained his B.S. in Mechanical Eng. and in Applied Mathematics in 1997 from the Univ. of Nis, Serbia, his M.S. in Mechanical Eng. from the Nanyang Technological Univ., Singapore in 1999, and his M.S. in Electrical Eng. (Systems) and Ph.D. in Mechanical Eng. in 2002 from the Univ. of Michigan, Ann Arbor. His research interests include advanced quality and process control in multistage manufacturing systems, intelligent proactive maintenance techniques and applications of advanced signal processing in biomedical engineering. He was the director of the recently graduated NSF Industry-University Cooperative Research Center (I-UCRC) on Intelligent Maintenance Systems at The University of Texas at Austin and is Associate Director of the NSF Engineering Research Center on Nanomanufacturing Systems (NASCENT Center). He co-authored 70 journal publications, 9 book chapters and more than 30 refereed conference publications. He is a Fellow of the International Society for Engineering Asset Management, Associate Member of the International Academy for Production Research (CIRP) and is the recipient of several prizes and recognitions, including the 2018 August-Wilhelm Scheer Visiting Professorship from Technical University of Munich, 2006 Outstanding Young Manufacturing Engineer Award from the Society of Manufacturing Engineers (SME) and 2005 Teaching Incentive Award from the Department of Mechanical Engineering of the University of Michigan.

Mircea V. Dusa is an ASML Fellow and a founding member of ASML’s Technology Development Center. He has over 40 years of experience in semiconductor industry encompassing manufacturing, development and research, starting from mask making to stepper and metrology engineering. Currently, he works on exploratory imaging solutions for advanced lithography tools seeking integration of exposure tools functionality to non-lithography tool components, from layout design, to photomask, patterning processes and associated metrology and control techniques. Prior to ASML, he was in various engineering positions at National Semiconductor/Fairchild Research Center, SEEQ Technology, ST Microelectronics, Zygo Corporation. He has over 200 publications and holds two dozen US patents in lithography and metrology sciences on topics ranging from DTCO, imaging, overlay and CD control and patterning processes. He is an active member of SPIE, where he chaired the Advanced Lithography Symposium between 2013-2016, Optical Microlithography Conference between 2008-2011 and International Working Group for Photolithography. From 2008 to today, Mircea is teaching SPIE’s special course on Multi Patterning Principles and Applications. He is a member of IEEE and a SPIE Fellow. Dr. Dusa graduated with a BS in Electrical Engineering, MS in Solid State Physics from University of Bucharest in Romania and holds a Ph.D. degree in Applied Optics from the same university.

Dr. Feng Ju is an associate professor with the School of Computing and Augmented Intelligence at Arizona State University. He received a B.S. degree from Shanghai Jiao Tong University in 2010, and an M.S. degree in electrical and computer engineering and Ph.D. degree in industrial and systems engineering from the University of Wisconsin Madison in 2011 and 2015, respectively. His current research interests include sensing, modeling and optimization of manufacturing systems and additive manufacturing processes. He has been a recipient of multiple awards, including Dr. Hamed K. Eldin Outstanding Early Career IE in Academia Award, SME Outstanding Young Manufacturing Engineer Award, Best Paper Awards in IISE Transactions and IFAC MIM, and Best Student Paper Award in IEEE CASE.

Dongchan Kim received the B.S. degree from Seoul National University, Seoul, South Korea, the M.S. and Ph.D. degrees majoring in physical chemistry from KAIST(Korea Advanced Institute of Science and Technology), Taejon, South Korea. After doing the post doctoral study in department of chemistry at University of North Carolina at Chapel Hill, NC, USA, he joined Samsung Electronics as a senior process engineer in 2000. Since then, he has spent his career working in various semiconductor fields - chemical vapor deposition, integration management and yield control, dry etching, and equipment development, etc. From 2006 to 2007, he was a Samsung assignee to IMEC, Leuven, Belgium. He continued the career as a Principal Engineer at Samsung Semiconductor R&D Center.(2007-2016) After Advanced Micro-Fabrication Equipment Inc.(AMEC) as a senior director(2016-2022), he works for ASML Korea as a Senior Account Manager.(2022-) He has about 25ea of publications and presentations. He was a keynote speaker for several symposiums such as APCPST 2012, DPS 2013, and ICMAP 2014. He also has about 50 patents worldwide as the 1st author or co-author.

Dr. Chia-Yen Lee is currently a professor in the Department of Information Management, National Taiwan University. He received Ph.D. degree from the Dept. of Industrial and Systems Engineering at Texas A&M University, USA. His research interests include productivity and efficiency analysis, manufacturing data science, intelligent manufacturing systems, and stochastic optimization with applications to semiconductor manufacturing, TFT-LCD, energy and pollutant, fastener, petrochemical industries, etc. He serves as associate editor for IEEE Transactions on Semiconductor Manufacturing and IEEE Transactions on Automation Science and Engineering. His research works appear in European Journal of Operational Research, IEEE Transactions on Power Systems, IEEE Transactions on Engineering Management, Journal of Environmental Management, and Applied Soft Computing, etc. He received the 2021 Outstanding Research Award from Ministry of Science and Technology (MOST) of Taiwan, the 2018 Kwoh-Ting Li Technology & Literature Lectureships Award of Distinguished Young Scholars from NCKU-Delta Electronics, the 2017 Ta-You Wu Memorial Award of Distinguished Young Scholars from MOST, Outstanding Young Scholar Grants (2014, 2017, 2022) from MOST, the 17th Best Practice Paper Award from the Asia Pacific Industrial Engineering and Management Systems Conference (APIEMS 2016), the 2016 Outstanding Young Industrial Engineer Award from the Chinese Institute of Industrial Engineers (CIIE 2016).

Dr. Jun Haeng Lee received his B.S., M.S., and Ph.D. degrees in electrical engineering from Korea Advanced Institute of Science and Technology (KAIST) in 1999, 2001, and 2005, respectively. He worked for 2 and half years at KDDI R&D Labs from 2005. Since he joined Samsung Electronics in 2009, he has been working on various R&D projects including neuromorphic sensors and chips, motion recognition, spiking neural network and its learning algorithms, efficient deep network for neural processors, deep learning algorithms for industrial applications. He worked as a visiting researcher at the Institute of Neuroinformatics, the University of Zurich and ETH Zurich, from 2015 to 2017. He is currently a VP of Technology and the head of Machine Learning Tech Unit at Samsung Advanced Institute of Technology (SAIT) of Samsung Electronics. His activities include developing machine learning and deep learning algorithms for semiconductor manufacturing and leading related projects.

Lars Mönch is a Full Professor in the Department of Mathematics and Computer Science at the University of Hagen, Germany. He received a master’s degree in applied mathematics and a Ph.D. in the same subject from the University of Göttingen, Germany. He also holds a habilitation degree in information systems from the Technical University of Ilmenau. His current research interests are in simulation-ba­sed production control of semiconductor wafer fabrication fa­cilities, applied optimization and artificial intelligence appli­cations in manufacturing, logistics, and service operations. He is a member of GI (German Chapter of the ACM), GOR (German Operations Research Society), SCS, and INFORMS. Prof. Mönch served as an Associate Editor for IEEE Transactions on Automation Science and Engineering from 2008-2012.

Dr. Mahadeva Iyer Natarajan is currently Director of Product Development Quality and Reliability at Allegro Microsystems, and has held technical and management positions at Globalfoundries (USA), Chartered Semiconductor (Singapore), Silterra (Malaysia), IMEC (Belgium) and IME (Singapore). His experience and interests span the range of supporting product reliability issues across product design, manufacturing and customer support. He is the author of more than 90 technical publications and holds 40 patents, and will support us in the areas of Yield Modeling and Analysis and Yield Enhancement.

Gian Antonio Susto (S'11-M'16) received the M.S. degree (cum laude) in control systems engineering and the Ph.D. in Information Engineering from the University of Padova, Padova, Italy, in 2009 and 2013. He is currently Assistant Professor at University of Padova. He is also a co-founder at Statwolf Ltd. He has been a visiting student at the University of California, San Diego (2008-09), and at National University of Ireland Maynooth (NUIM) (2012), an Intern Researcher at Infineon Technologies Austria AG, Villach, Austria (2011) and post-doctoral associate at NUIM (2013). During his career, his awards include the IEEE-CASE Best Student Conference Paper Award (2011), IEEE/SEMI-ASMC Best Student Paper Award (2012) and IEEE-MSC Best Student Paper Award (2012). His research interests include manufacturing data analytics, machine learning, gesture recognition and natural language processing. He is the author of more than 40 technical publications, and his knowledge of data science and analytics will significantly enhance our Factory Modeling area.