Tutorials

Amit Ranjan Trivedi is an associate professor in the department of electrical and computer engineering at the University of Illinois at Chicago (UIC). Trivedi was awarded Sigma Xi best Ph.D. thesis award from Georgia Tech, IEEE Electron Device Society Fellowship, NSF CAREER Award, and best paper award at IEEE AICAS. His research interests include compute-in-memory and neuromorphic technologies. He has more than 100 publications in referred journals and conferences

Title: The Third Dimension of Technology Scaling: Co-designing for Direct Functionality Embedding in a Device
Abstract:  This talk explores a novel approach to achieving enhanced scalability of AI models within ultra-low-power systems. As AI models continue to grow exponentially in size and complexity to address increasingly diverse use cases, the limitations of transistor scaling have become apparent. While techniques like 3D and heterogeneous integration offer an interim solution by opening a second scaling dimension, the exponential growth of machine learning models necessitates a fundamental rethinking of acceleration strategies. We present an innovative direction: device-based computing, where key functionalities of AI models are directly embedded into devices, such as building circuits in a device and architectures in a circuit, through co-design of hardware and models. Starting from memristors that encapsulate entire multiply-accumulate (MAC) units within a single device to Gaussian transistors enabling reasoning functions, we delve into the underlying currents of these emerging approaches. We present them systematically as a cohesive concept, ultimately revealing a third dimension of scalability. This new paradigm paves the way for achieving higher functionality within constrained area and power budgets, offering transformative pathways for AI acceleration.

Gerhard Klimeck is the Elmore Chaired Professor of Electrical and Computer Engineering at Purdue University and leads two research centers in Purdue’s Discovery Park. He is also Vice President for Academic Information Technology and Deputy CIO. Previously he worked at the central research Laboratory of Texas Instruments and NASA/JPL/Caltech. His research interest is in computational nanoelectronics, high performance computing, and data analytics. He helped to create nanoHUB.org, the largest virtual nanotechnology user facility serving that served over 15 million users. He led the teams who developed the NEMO software tools.  Dr. Klimeck is a fellow of the Institute of Physics (IOP), the American Physical Society (APS), the Institute of Electrical and Electronics Engineers (IEEE), the American Association for the Advancement of Science (AAAS), and the German Humboldt Foundation. He has published over 525 printed scientific articles; he has been recognized for his co-invention of a single-atom transistor, quantum mechanical modeling theory, and simulation tools. His NEMO5 software has been used since 2015 at Intel to design nano-scaled design transistors. The nanoHUB team was recently recognized by a top 100 by R&D award – Making simulation and data pervasive.

Title: nanoHUB and Chipshub Tutorial
Abstract:  Over 250,000 nanoHUB users have run over 7 million simulations in Apps mostly focused on semiconductor devices and materials modeling. nanoHUB created nano-Apps before Apple created Apps for the iPhone and made scientific codes usable for a much larger user group.  Most scientific tools strive to be comprehensive in solving “any” simulation problem in a specific problem range.  That comprehensiveness limits the use to experts, who require extensive training.  nanoHUB has instead focused on delivering a spectrum of Apps (over 700 now) that individually have a limited capability focused on a PN-junction, MOSFET, or nanowire while the underlying tool could of course solve a much wider set of problems.   We assembled some of these Apps that are essential for specific courses into small sets such as ABACUS (crystals, bandstructure, drift-diffusion, pn-junctions, BJTs, MOScaps, MOSFETs) [1].  The usability results are stunning.  Our user analytics prove that over half of the simulation users participate in structured education through homework/project assignments.   We can identify classroom sizes and detailed tool usage [2,3]. We can begin to build mind-maps of design explorations and assess depth of explorations for individuals and classes. While parts of academia struggled to innovate curricula, we have measured the median first-time App insertion into a class to be less than six months.  Over 180 institutions have utilized nanoHUB in their curriculum innovation in over 3,600 classes.   Over 1 million nanoHUB visitors explore lectures and tutorials annually.  Based on this community presence we have expanded nanoHUB towards chip design.   Chipshub.org deliver online modeling, simulation, virtual environments, and lectures for the US initiative on workforce development and research funded by the US CHIPSact.    Commercial chip design vendors are partnering with Chipshub to host professional chip and semiconductor design software.  This presentation will overview some of the nanoHUB impact metrics.  In the tutorial a brief overview of ABACUS will be given and the audience may request other tool demonstrations or exploration.

[1] https://nanohub.org/groups/abacus ABACUS – Assembly of Basic Applications for Coordinated Understanding of Semiconductors.  A one-stop-shop for teaching and learning semiconductor fundamentals.

[2] Krishna Madhavan, Michael Zentner, Gerhard Klimeck, “Learning and research in the cloud”, Nature Nanotechnology 8, 786–789 (2013)

[3] TEDx Talk, Klimeck, “Mythbusting Scientific Knowledge Transfer with nanoHUB.org”, https://www.youtube.com/watch?v=PK2GztIfJY4 .

Bonnie L. Gray is a Professor in the School of Engineering Science (ENSC) at Simon Fraser University (SFU) in Canada, a Fraser Health Authority affiliated researcher, and on the board of the Vancouver Medical Device Development Center (MDDC). Dr. Gray has over 140 peer-reviewed journal and conference publications, and has given more than 30 invited, keynote, and plenary presentations at international conferences, in the areas of novel materials and fabrication techniques for biomedical and microfluidic devices and systems; development of flexible and wearable microfluidic and biosensor technologies; point-of-care instruments; and chip-based biological cell sorting and trapping methods. Dr. Gray is a dedicated mentor and the 2014 recipient of the SFU Dean of Graduate Studies Award for Excellence in Supervision. Dr. Gray was the Chapter Chair for the Vancouver IEEE Electron Devices Society (EDS) from 2007-2017, and organizer of two mini-colloquia in 2012 and 2017. She is on the Editorial Boards of PLOS One as well as the IOP Journal of Micromechanics and Microengineering. She chaired the SPIE Conference on Microfluidics, BioMEMS, & Medical Microsystems from 2014-2024, is a General co-Chair for IEEE Nano 2025, and on the local organizing committee for IEEE Sensors 2025. She is very active in organization and program committees for conferences sponsored by the IEEE Nanotechnology and Sensors Councils; and in EDI initiatives, including the IEEE Women in Electron Devices (WiEDS) Steering Committee and a member of Women of Wearables (WoW).

Title: Nanotechnology applications in wearables
Abstract:  The use of nanotechnology has advanced the fields of microfluidics, biosensors, and flexible electronics, resulting in devices and systems with new principles of operation, improved performance, and increased portability. The field of wearable devices has adopted many of these advances and tailored them to meet the specific needs of wearables, including reliable electronic-tissue interfaces, increased comfort, reduced weight, integration with flexible substrates or textiles, and compact design. Such advances have resulted in highly portable real-time sensing and actuating systems that can be worn on the body, and used to detect and monitor disease and medical conditions, promote human-machine interaction, detect physiological movement, and monitor health biomarkers. We investigate how nanotechnology, especially functional nanomaterials and nanofabrication techniques, can be applied to the development of wearable systems, including smart textiles and other flexible system platforms. We investigate how nanomaterials and nanofabrication can be applied to improve the performance of small actuators for wearable microfluidics devices and haptics, to develop new highly flexible wearable biosensors and sensor systems, and as the basis for other devices such as wearable human-machine interfaces.

Murty Polavarapu is the President of IEEE Society on Social Implications of Technology and Secretary of IEEE Electron Devices Society. He is engaged in the development of advanced semiconductor memory and logic products tailored for the defense and aerospace sectors, with a particular focus on space applications. In addition, Murty serves as the Managing Director of the Virginia Microelectronics Consortium, where he fosters collaboration between academic institutions and the microelectronics industry in Virginia.

With over twenty years of active volunteer service in IEEE, Murty has held various positions at the Chapter, Section, Region, MGA, Technical Activities (TA), IEEE-USA, and IEEE levels. He currently serves on several committees, including the IEEE Global Policy Caucus, IEEE PSPB/TAB Products and Services Committee, MGA Geographic Unit Operations Support Committee and the Continuing Education Committee of EA.

He holds eleven patents and has received many awards, including the BAE Systems Chairman’s Silver Award, Dominion Semiconductor President’s Award (Toshiba), Lockheed Martin Executive Award, IBM Outstanding Technical Achievement Award, and IBM Invention Achievement Award.

Murty earned his Master’s degree in Electrical Engineering from Howard University and a Master’s in Technology Management from the University of Pennsylvania.

Title: An Overview of IEEE – Advancing Technology for Humanity
Abstract:  The Institute of Electrical and Electronics Engineers (IEEE) is the world’s largest technical professional organization dedicated to advancing technology for the benefit of humanity. With over 400,000 members in more than 160 countries, IEEE fosters innovation through a vast network of technical societies, geographic units, humanitarian initiatives, conferences, publications, and educational programs. 

IEEE’s Technical Societies and Councils cover a diverse range of disciplines, including power and energy, communications, robotics, computing, aerospace, and biomedical engineering. Councils such as Nanotechnology Council address the interdisciplinary topics. These societies and councils disseminate cutting edge technical knowledge through peer reviewed publications and provide specialized resources for professionals and researchers. 

Beyond technology, IEEE is committed to humanitarian activities through programs like IEEE Smart Village, IEEE SIGHT (Special Interest Group on Humanitarian Technology), and EPICS in IEEE. These initiatives empower communities worldwide by applying engineering solutions to pressing social challenges, such as access to clean energy, healthcare, and education. 

A key pillar of IEEE’s impact is its standards development activities. The IEEE Standards Association (IEEE SA) oversees the creation of globally recognized technical standards, including Ethernet (IEEE 802.3) and Wi-Fi (IEEE 802.11). These standards enable interoperability, drive technological progress, and support industries ranging from telecommunications to artificial intelligence and smart grids.

IEEE’s geographic activities support its global reach, with over 340 local sections and 2,700 student branches that engage members at the grassroots level. Regional events, networking opportunities, and leadership development programs strengthen professional communities and collaboration. 

The organization plays a pivotal role in knowledge dissemination through conferences and publications. IEEE hosts over 2,000 conferences annually, bringing together researchers and industry experts. Its digital library, IEEE Xplore, contains millions of peer-reviewed articles, technical papers, and standards, serving as a premier resource for global innovation. 

IEEE also fosters lifelong learning through its **educational activities**, offering continuing education, certification programs, and STEM outreach initiatives. IEEE Learning Network (ILN) and IEEE TryEngineering inspire future generations and equip professionals with essential skills. 

This talk provides an insightful overview of IEEE’s multifaceted contributions, highlighting its role in shaping technology and driving positive societal impact.

Gina Adam is an associate professor with the Electrical and Computer Engineering department at the George Washington University. Her group works on the development of emerging non-volatile memory devices and novel hardware foundations that will enable new ways of neuro-inspired computing. She received her Ph.D. in electrical and computer engineering from the University of California Santa Barbara in 2015 and was a research scientist at the Romanian National Institute for Research and Development in Microtechnologies and a visiting scholar at École Polytechnique Fédérale de Lausanne before joining GWU. She was the recipient of an International Fulbright Science and Technology award in 2010, a Mirzayan fellowship at the National Academy of Engineering in 2012, a H2020 Marie Sklodowska-Curie grant from the European Commission in 2016, a NSF CRII award in 2020, the AFOSR Young Investigator and the NSF CAREER awards in 2023 and the DOE Early Career Research award in 2024.

Title: Memristor synapses: from the nanoscale to the system-level prototyping
Abstract:  Training of artificial intelligence systems is expected to consume massive amounts of computing resources in the coming decades at significant financial and environmental costs. New hardware alternatives are necessary to keep up with the increasing demand in complexity and energy efficiency in this sector. Emerging analog memory devices, like resistive switching technology (ReRAM or memristor) have shown potential for the compact and efficient implementation of artificial synapses for neuro-inspired computing. However, prototyping a neural network system with these nanoscale devices is not an easy task given their issues related to manufacturability, reliability and yield. This tutorial describes the steps in the design, fabrication and CMOS integration of oxide-based memristor switches and their applicability for neural network systems. Integrated arrays with 20,000 of these nanoscale devices will be shown. A novel mixed-signal prototyping platform called DAFFODIL, was designed as part of our collaboration for benchmarking memristive neural networks based on these arrays. Results on neural network inference will be shown on a multitude of pre-trained ternary weight solutions for classification. A fault-tolerant algorithm, called layer ensemble averaging, will also be discussed and experimentally demonstrated. Moreover, the complementary DAFFODIL simulation model will be shown to accurately predict the experimental hardware performance, showcasing the effectiveness of the proposed system for hardware-software co-design. Our long-term vision is to make this system open and accessible to support metrology and benchmarking efforts. This end-to-end prototyping platform aims to bring the device research and computer engineering communities closer together towards advancing the field of hardware neural networks based on emerging synaptic nanodevices.

Eleonore Vissol-Gaudin is a Senior Researcher in Data Governance at Fujitsu Research of Europe (FRE), within the Data Security Research Group. Prior to FRE, she was a Research Fellow in the Department of Materials Science and Engineering at Nanyang Technological University and member of the Hip lab. In that position, she investigated the development of data-driven modelling of dynamical systems, specifically the dynamics of DNA unfolding, as well as integrating machine learning into experimental materials science workflows. She got her PhD from Durham University in the UK, working on the development of unconventional computing devices. She is heavily involved in AI for Science initiatives and is co-organiser of the Machine Learning for Multiscale Processes at ICLR 2025 and in the scientific committee of the International AI4X conference. She has worked on the organisation of the AI for Science and Nobel Turing Challenge Conference 2024, along with 14 domain-specific AI for Science workshops in Singapore. She has been associate editor and reviewer for the IEEE Nanotechnology Council flagship conference IEEE NANO 2024 and chaired sessions at IEEE NANO2024 and the Singapore MRS’ ICMAT2023.

Title: Integrating AI into Materials Discovery: From Simulation to Experimental Workflows
Abstract: Artificial intelligence (AI) is transforming the landscape of materials discovery, accelerating computational simulations, optimising experimental workflows, and enabling data-driven breakthroughs. This tutorial aims to provide introduction to AI-driven methodologies in materials science, along with open-source tools to support researchers entering the field. The first part of the tutorial will explore AI-enhanced simulation techniques such as Machine learning (ML)-accelerated density functional theory (DFT), which aims to reduce computational costs while maintaining the accuracy of quantum mechanics calculations. The Materials Project Database, a widely used resource for materials informatics, will be introduced, along a critical discussion of its advantages and limitations. To conclude this part, the concept of physics-informed neural networks (PINNs) will be briefly examined. The second part will delve into AI within experimental workflows. One of the most commonly used algorithm for such workflows is Bayesian Optimisation (BO). This part of the tutorial will outline the working principles of BO, assess its strengths and limitations, and highlight emerging alternative approaches. Finally, the tutorial will quickly look into the future of self-driving labs, and the feasibility of truly closed-loop experimental systems within in the context of materials science and nanoelectronics.

Jackie Sharp is a senior mechanical engineer and mechatronics section supervisor with a demonstrated history of work including electromechanical design and rapid prototyping. In her day job she primarily is based in mechanical design and analysis, developing everything from radio housings to wearables to aircraft payloads. She is passionate about empowering the next generation of engineers through global STEM education and hands-on problem-solving, volunteering for various programs such as APL STEM Academy, Maryland MESA, and FIRST Robotics. She was a recent Fulbright Specialist Grant recipient working to modernize engineering education in Uzbekistan. She received a B.S. and M.S. in mechanical engineering from The University of Pittsburgh and is pursuing a PhD part-time at the University of Pittsburgh. She is a member of SME as well as chair of the Early Career Engineering Programming Committee and active member for ASME.

Title: Beyond the Lab Coat: Exploring Jobs You Didn’t Know You Were Qualified For
Abstract: Nanotechnology is constantly evolving with our ever changing world. This interactive session guides researchers through the process of identifying career opportunities outside their immediate field of study. Learn how to map your core competencies, decode job descriptions in adjacent industries, and find unexpected roles where your deep knowledge of materials and nanoscale science gives you a competitive edge.

Attila Bonyár is a full professor and head of the Nanotechnology and Sensorics Research Group at the Department of Electronics Technology, Faculty of Electronics Engineering and Informatics, Budapest University of Technology and Economics.

He was elected to serve in the Hungarian Academy of Sciences (HAS) Electron Devices and Electronics Technology Scientific Committee for three terms (in 2017, 2021 and 2023), and is currently an elected member of the HAS General Assembly.

He is a senior IEEE member since 2021 and actively serves in many international committees. He is the chair of the Nanopackaging Technical Committee (TC-11) of IEEE NTC since 2022 (vice-chair since 2020). He is AdCom member of IEEE NTC (Electronics Packaging Society representative) and chapter coordinator for Region 8 since 2020. He is a chair of the local IEEE Hungary&Romania EPS&NTC joint chapter since 2019 and advisor of the local student branch chapter since 2022. He is a Steering Committee member for two IEEE conferences (IEEE-SIITME since 2014 and IEEE-ISSE since 2017), and a Technical Committee member for several other major IEEE conferences (NANO, NMDC, ESTC).

He co-authored 190 publications, including 84 journal papers. His H-index is 24, with more than 2200 independent citations. His current research activities are focused on the development of optical biosensor technologies utilizing plasmonics, low-dimensional nanomaterials, nanocomposites, and nanometrology.

Title: Surface plasmons are collective electron oscillations, excited by electromagnetic radiation in metallic nanoparticles or thin films. In the case of nanoparticles, plasmon resonance grants unique optical properties to the nanoparticles, which have high sensitivity to the surrounding medium’s refractive index, making them functional for sensing purposes. Recent developments in the fabrication technologies of plasmonic nanomaterials enable their effective utilization in advanced bioanalytical concepts, such as localized surface plasmon resonance imaging (LSPRi), which promises the possibility of high-throughput biomolecule sensing integrated into miniaturized point-of-care (PoC) devices. The tutorial will introduce the theory and basics of biosensors and plasmonic sensing, the most common measurement configurations, and metrics to benchmark the performance of plasmonic sensors, and fabrication technologies to realize high-throughput biosensing with nanomaterial systems.