Work with thought leaders and academic experts in Hardware and Architecture

I am dedicated and passionate about inspiring and engaging my students in an effective learning process to generate new knowledge, do innovations, engage in technology transfer, and enhance human capital through interdisciplinary and collaborative research for the well-being of academia, industry, and society.

Seasoned Ph.D. in Biotechnology with a robust background in plant biology, environmental biotechnology, molecular biology, microbiology, physiology, and biochemical analysis. Demonstrated proficiency in sample collection, laboratory analysis, meticulous data analysis, and comprehensive documentation and reporting. Bringing a wealth of experience and a commitment to excellence, I am dedicated to advancing my skills and making a significant impact in the field.

T. Osswald is Hoeganaes Professor of Materials at the University of Wisconsin-Madison, where he has been a faculty member since 1989. Osswald received the PhD in Mechanical Engineering from the University of Illinois at Urbana-Champaign in 1987, the MS in Mechanical Engineering from the South Dakota School of Mines and Technology in 1982, and the BS in Mechanical Engineering from the South Dakota School of Mines and Technology in 1981. Before joining the UW-Madison faculty, Osswald was a Humboldt Fellow at the Rheinisch Westfalische Technische Hochschule Aachen. Osswald’s research interests are in the areas of processing-structure-property relationships for metals and composites, with a focus on powder metallurgy and metal injection molding. His research has been supported by the National Science Foundation, the Department of Energy, the US Army Research Office, and industry. Osswald is a Fellow of ASM International and the American Academy of Mechanics, and he has received the Extrusion Division Award, the Powder Metallurgy Division Award, and the Distinguished Teaching Award from TMS.

• Expertise in image and video processing, machine vision, machine learning, digital signal processing, deep learning and pattern recognition algorithm development. • Expertise of production quality C/C++, Python language implementation including for real-time and multiple including embedded platforms. • Experience of working for start-ups and global companies. • Over 50 scientific publications and patents. Specialties: AI, image/video processing, computer vision, machine vision, deep learning, pattern recognition, machine learning, data science, software engineering, embedded software, real-time systems, motor control, Python, C/C++, R and MATLAB programming, software development, object oriented, Linux, Windows, algorithms, Agile development.

**Results-driven AI leader with 20+ years of success spearheading model development and optimization initiatives in the energy industry and academia. Proven track record in leveraging computational data science, scientific machine learning, and AI to drive breakthrough physics-data solutions and deliver tangible business value. Adept at translating complex scientific concepts into robust AI models. Skilled in numerical simulation, scientific machine learning, and bilingual communication to optimize project outcomes.**

**Research Expertise** Computer architecture, high-performance parallel processing, computer systems performance analysis, approximate computing, computing with emerging technologies, and storage systems. **Biographical summary** David J. Lilja received a Ph.D. and an M.S., both in Electrical Engineering, from the [University of Illinois at Urbana-Champaign,](http://www.uiuc.edu/) and a B.S. in Computer Engineering from [Iowa State University](http://www.iastate.edu/) in Ames. He is Professor Emeritus of [Electrical and Computer Engineering](http://www.ee.umn.edu/) at the [University of Minnesota](http://www.umn.edu/) in Minneapolis. He previously served as a member of the graduate faculties in [Computer Science](http://www.cs.umn.edu/), [Scientific Computation](http://www.scicomp.umn.edu/), and [Data Science](http://datascience.umn.edu//).  He served ten years as the head of the ECE department at the University of Minnesota, worked as a research assistant at the Center for Supercomputing Research and Development at the [University of Illinois,](http://www.uiuc.edu/) and as a development engineer at [Tandem Computers Incorporated](http://www.tandem.com/) in Cupertino, California.  He received a [Fulbright](http://www.fulbright.org/) Senior Scholar Award to visit the University of Western Australia and was a visiting Professor at the University of Canterbury in Christchurch, New Zealand. He has chaired and served on the program committees of numerous conferences.  He was elected a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) and a Fellow of the American Association for the Advancement of Science (AAAS) for contributions to the statistical analysis of computer performance. He also is a registered Professional Engineer.

I am passionate about solving big problems with scientific and computational tools. A highly experienced applied mathematician working in academia (faculty) and industry (consulting), with 15+ years of research and teaching expertise in inverse problems, signal processing, and data science. A highly-skilled software engineer and analyst/architect with 6+ years of experience as a technical lead in professional software development.

Dr. Athul Prasad received his MBA from MIT where he was a Sloan Fellow, M.Sc. (Tech.) (with distinction) and D.Sc. (Tech) from Aalto University, B.Tech (with distinction) from University of Kerala, and is also a graduate of the year-long executive management (LEAD) program from Stanford University's Graduate School of Business. He was with Nokia from 2014-2023 and is currently with Samsung based out of Mountain View, CA. He has coauthored over 40 peer reviewed scientific publications and has written a book on 5G "End-to-End Mobile Communications: Evolution to 5G," McGraw-Hill, Aug. 2020. He's also the co-inventor of over 90 patents.

I am a Researcher at the University of Campinas - Unicamp. I received both B.Eng. degree in Automation and Control Engineering and M.Sc. degree in Electrical Engineering from the Pontifical Catholic University of Rio Grande do Sul - PUCRS in 2016 and 2018, respectively. I received my Ph.D. degree in Electrical Engineering from Unicamp in 2022. My current research interests include digital communications systems, adaptive DSP, and machine learning.

I hold a PhD Eng. degree in computer science. I am a graduate of the Polish-Japanese Academy of Information Technology in Warsaw, POLAND. Currently, I am associate professor at the Cathedral of Multimedia at the same university. I lead and conduct scientific projects and research related to natural language processing and machine learning based on statistical methods and neural networks. I eagerly take up IT challenges and engage in interesting interdisciplinary projects, in particular related to HCI, UX, medicine, and psychology. In addition, as my profession, I have worked as a lecturer at the Warsaw School of Photography, and as an IT trainer. My specialties as a teacher are primarily deep learning, machine learning, natural language processing, computational linguistics, multimedia, HCI, UX, mobile applications, HTML 5, Adobe applications, and server products from Apple and Microsoft. As far as my didactic work is concerned, I lead classroom studies at the faculty of computer science and at the new media art department of the Polish-Japanese Academy of Information Technology and, in the past, I have also directed classes and lectures at the Warsaw School of Photography & Graphic Design. I am also an expert at the Polish National Agency for Academic Exchange, a member of the Polish Information Processing Society, and a member of the Polish Telemedicine and eHealth Society with Bene Meritus honor. Finally, I am a certified Microsoft, Apple, Adobe, w3schools, and EITCA specialist as well as being the Author of many scientific monographs and specialized IT books related to machine learning, administration of servers, and multimedia. I also engage as an editor of various specialized IT web portals such as in4.pl, pclab.pl, and e-biotechnologia.pl where I am author of training materials, guides, and hardware reviews. Some of my articles have also been published in iCoder Magazine and Komputer Świat magazine.

**Education** Ruben Del-Rio-Ruiz is an electrical engineer specializing in biomedical engineering. He completed his B.S. in Electrical Engineering at the Universidad de Deusto in 2013 and pursued his M.S. in Telecommunications Engineering with a focus on Flexible RF Electronics at the same university, graduating in 2015. Recently, Ruben obtained his Ph.D. in Engineering for the Information Society and Sustainable Development from the University of Deusto in 2021, concentrating on wearable Antennas design and Propagation properties. **Experience** Throughout his academic journey, Ruben has garnered extensive experience in the field of telecommunications, with a specific emphasis on textile planar antenna design and in-body comunications. He has worked as a Research Assistant and a PhD Student at the University of Deusto. Additionally, he served as a Postdoctoral Scholar at Tufts University, where he combined his prior research acumen with the development of biomedical devices for rapid diagnosis and treatment of diseases. More specifically, he has protrotyped a variaty of ingestible devices as a tool to better understand the gut microbiome. **Purpose** Ruben's research is centered on creating innovative and sustainable solutions for biomedical devices. He has disseminated his findings through publications in various peer-reviewed journals and presentations at international conferences. Committed to advancing non-intrusive biomedical devices, their safety, and sustainable development, Ruben is dedicated to utilizing his knowledge and skills for this purpose.

Experienced academic and researcher specializing in data science and computer vision, with a proven track record in academia and industry. Proficient in Computer Vision, Machine Learning, and Image Processing, with published many works recognized by over 1000 citations in peer-reviewed publications. Proven ability to collaborate effectively within multidisciplinary teams to tackle complex problems and deliver innovative solutions.  Advocate for teamwork, effective communication, and mentorship.