NRT Core Faculty
Arthi Jayaraman (PI, NRT director) has expertise in the development and use of molecular models, theory, simulation (using HPC), and DS towards the design of novel polymers. She has extensive collaborations with experimentalists in academia, industry, and national labs. Given her research expertise in soft materials, polymers, high-performance computing, and data science, and her regular interdisciplinary interactions with chemists, computer scientists, mechanical engineers, and biologists, who use different technical vocabulary, she understands the graduate training needs and the current training gaps in graduate programs involving the cultural and communication barriers that challenge such interdisciplinary interactions. Through such interdisciplinary interactions, the graduate students and postdocs trained in her research laboratory have gone on to become successful researchers in industry, national laboratories, and academia. She also has extensive experience teaching core and elective classes to both undergraduate and graduate students over the last 12+ years. One of these course relevant to this NRT is a graduate elective on ‘Molecular modeling and simulation of soft materials’.
In her past role as director of graduate program in Chemical and Biomolecular Engineering, she learned how graduate programs could better integrate students’ technical training and professional skills development and how the success of graduate students is closely linked to their advisor(s)’s involvement in their mentoring. These observations motivate her to lead this NRT program focused on graduate education and mentoring. Lastly, Jayaraman’s role as Associate Editor for Macromolecules (2019 – present) and Deputy Editor (2021- present) for the new open access journal on Polymers from the American Chemical Society (ACS Polymers Au) gives her an understanding of current challenges of data sharing and access in the publishing world, which she will also share with the graduate trainees in this NRT.
Rudolf Eigenmann (co-PI, NRT Executive Committee member) is an expert in compiler optimization, programming methodologies, and performance evaluation for HPC, as well as the design of cyberinfrastructure. His past experiences include participation in NSF-Combined Research-Curriculum Development (CRCD) and service as Program Director in the NSF’s Office of Advanced Cyberinfrastructure. Prof. Eigenmann serves as the PI, along with Prof. Jayaraman, Prof. Wu and two other co-PIs, on an NSF MRI grant that has brought UD its newest supercomputer DARWIN which will be leveraged for NRT CDST-MIDAS’s convergent research projects and some of the educational efforts. Prof. Eigenmann also offers a relevant course for NRT trainees – ‘High-Performance Computing (HPC) 101’ – this is an introductory course to HPC and DS that students across the disciplines take to learn basic principles, terminology, and technology needed to develop and run efficient computational and data science applications. Prof. Eigenmann has also been organizing HPC+Data Science lunch meetings which may be relevant for NRT trainees to consider attending. His graduate training experience also builds on activities at his previous position at Purdue University, where he co-directed an interdisciplinary graduate program in computational science and engineering and initiated a corresponding DS focused program.
Cathy Wu (co-PI, NRT Executive Committee member) is an expert in bioinformatics and computational biology, genomic informatics, natural language processing, semantic computing, deep learning, and cyberinfrastructure. She established the UD Center for Bioinformatics and Computational Biology (CBCB) in 2009 to foster collaborative research with over 70 affiliate faculty from across the university and the region. The Center is the home of the interdisciplinary Bioinformatics Data Science (BDS) PhD, Bioinformatics Master’s, and graduate certificate programs, now with more than 60 students. She is the founding Director of the Data Science Institute (DSI) that serves to catalyze and coordinate data science activities at UD, connecting researchers across seven colleges to foster multidisciplinary research collaborations. Prof. Wu has received grants with significant mentoring effort, such as NSF IGERT grant and several NIH Diversity/Re-Entry Supplement grants. She has been a mentor in the NRMN and has participated in the Culturally Aware Mentoring (CAM) study. She has served on the Board on Research Data and Information of the National Research Council (NRC) and was an early adopter of the FAIR data sharing principles.
Kristi Kiick (co-PI, NRT Executive Committee member) is an expert in the synthesis, characterization, and application of protein, peptide, and self-assembled materials for applications in tissue engineering, drug delivery, and bioengineering. Her past service as Deputy Dean for interdisciplinary programs and partnerships for 3 years led to strategic partnerships between UD and Brookhaven national laboratory (BNL), which we will leverage for NRT internships. She currently serves on the editorial board on Molecular Systems Design and Engineering, a journal aligned with the NRT themes of “development or use of statistical or machine learning methodologies for molecular design; and integrated artificial intelligence and automated robotics in experimental science”. She currently serves as the chairperson for the BME department at UD.
Prof. Kiick has trained and mentored diverse research teams (averaging 10 graduate students, 2 postdoctoral researchers, and 2-3 UG researchers per year) over the past five years. Trainees meet with Kiick formally on a biweekly basis, as a full group on a weekly basis, and as sub-groups on a biweekly basis. As a Fulbright Scholar in the UK, Kiick has also initiated development of 4+1 MS programs in bio/pharmaceuticals, and in exchange opportunities for UD UGs in MSE and BME.
Sunita Chandrasekaran (co-PI, NRT Technical Training co-Director) is an expert in HPC, parallel computing, programming models/abstractions, and connecting their tools to domain sciences (e.g., bioinformatics, atmospheric research). Chandrasekaran, with co-author Dr. Guido Juckeland (member of our NRT IAC), has published an edited textbook on OpenACC for Programmers: Concepts and Strategies and has organized GPU Hackathons. Prof. Chandrasekaran also plans to offer a graduate level ‘Parallel programming and data science’ elective based on the success and impact of an undergraduate core course led Chandrasekaran and Stephen F. Siegel from CIS. This course is expected to cover the fundamentals of parallel concepts, patterns, methodologies, and programming models used for parallelization, parallelization of both multicore systems and systems with accelerators and will be expanded to integrate NRT training by studying programming challenges from soft materials domain scientists.
Marianthi Ierapetritou(NRT Technical Training co-Director) is an expert in ML and mathematical modeling of process operations, focusing on pharmaceutical manufacturing, and energy and sustainability process modeling and operations. Prior to joining UD, she served as chair of her department and Associate Vice President for the Promotion of Women in Science, Engineering, and Mathematics at Rutgers University. She is currently developing new graduate courses/modules that apply DS concepts and techniques towards chemical engineering problems. Prof. Ierapetritou has been an active educator and mentor for 18 Ph.D. students, 5 masters and 10 UG student theses in the past five years. She has also served as a thrust leader and test bed coordinator for a successful NSF-ERC focusing on Structured Organic Particulate Systems and in this effort mentored 10 PhD and Master students and hosted 1-2 UG students yearly in her lab getting experience in this interdisciplinary area of research.
Joshua Enszer (NRT Professional Development co-Director) is an expert in pedagogy, teaching and learning, gamification and game-based learning, development of engineering curriculum, and chemical process safety education. He serves as an academic consultant for the AIChE Center for Chemical Process Safety and is a member of the Advisory Board of the UD Center for Teaching and Assessment of Learning (CTAL). Prof. Enszer will serve as the advisor for trainees who opt to do the pedagogical training and teaching fellowship during their NRT traineeship. He has been involved in the Teaching Fellowship program in CBE since 2016 and has mentored graduate students who have served as teaching fellows. He guides the training fellows through this program in preparing for lectures for two weeks of the assigned course, effective modes of delivery of lectures and incorporation of in-class active learning techniques, going over the evaluation post-lectures, and outlining steps for improvement of the teaching fellow as an instructor. Outside this fellowship program, he supervises about 20 graduate students each year as they serve as teaching assistants for lab and lecture courses in the department of chemical and biomolecular engineering.
Laure Kayser (NRT Professional Development co-Director) is an expert in synthesis and characterization of soft organic electronics (conjugated polymers) for biological applications; she leads an interdisciplinary research group working at the intersection of organometallic chemistry, polymer synthesis, and materials and device engineering. Her joint appointments in two colleges (Arts & Sciences and Engineering) brings a unique perspective of differences and similarities in graduate training in these colleges. Her role as a member of the steering committee member for the UD (NIH Training program) Chemistry-Biology Interface (CBI) program will also be useful in translating their successful training practices into our program. Prof. Kayser mentors an interdisciplinary and diverse research group of five graduate students from MSE and CBC at UD since Fall 2019. Individual and group meetings are held weekly to track progress toward the graduate degree and discuss career opportunities and goals. She is also a faculty trainer and a member of the steering committee for the NIH-funded Chemistry-Biology Interface graduate training program. As part of this program, her focus is on outreach, diversity, and community support. She has also taken courses on effective mentoring including the CAM workshop.
Austin Brockmeier(NRT Technical Training co-Director) is an expert in data science, machine learning, and signal processing, with a focus on the design of statistical models, numerical optimization, and data mining algorithms. He brings in a unique expertise having developed and applied DS approaches to analyze data from a wide range of disciplines: biomedical engineering, neuroscience, and natural language processing. Relevant to this NRT program are his recent experiences in the Inclusive Teaching Professional Development Workshop Series at UD, UD College of Engineering Diversity Working Group, as well as launching the DSI’s Data Science Community Hour. Prof. Brockmeier has also developed a graduate course in machine learning (ML) that combines the three foundational fields of data science(DS): mathematics, statistics, and computer science, and introduces students to the review of current literature and semester-long independent research projects with peer review. He currently mentors a group of four PhD students and one master’s student.