oneAPI Innovators
Abedalmuhdhi Almomany, Yarmouk University
Abedalmuhdi Almomany received his bachelor of science degree in computer engineering from Yarmouk University. In 2017, he joined the Department of Computer Engineering, College of Engineering at Yarmouk University where he serves as an assistant professor. His research interests include reconfigurable computing, parallel processing, and embedded systems.
Abhishek Nandy, Dynopii
Abhishek Nandy is the cofounder of Dynopii. He has a bachelor of technology degree and a curious mind. An experienced speaker, Abhishek has presented his work at many large conferences and premier education institutes in India. He has also authored books on reinforcement learning, Unity* machine learning, leap motion, and game engines.
Adam Milton-Barker, Innov8 Digital Media* LTD & Peter Moss Leukemia MedTech Research
Adam uses oneAPI technologies to develop open source classifiers for leukemia detection and other medical technology (MedTech) projects as part of his nonprofit, Peter Moss Leukemia MedTech Research. He uses oneAPI in other projects within his company and personal life, such as for facial recognition and natural linguistics.
Aleksandar Ilic, Universidade de Lisboa
Aleksandar Ilic is an associate professor at the Instituto Superior Técnico (IST), Universidade de Lisboa, and a senior researcher of the INESC-ID, Portugal. He contributed to more than 50 scientific publications. Aleksandar's research includes high-performance and energy-efficient computing, and modeling of heterogeneous systems.
Akshay Bhuvaneswari Ramakrishnan
Akshay works at Hitachi Energy as a data engineer. With a strong passion for machine learning and AI, he possesses extensive experience and expertise in these cutting-edge technologies. As a part of Intel® Innovators and an Intel® Ambassador, Akshay has won numerous hackathons and serves as a mentor for startups. His research contributions include many papers and two books.
Alessandro Faria, Oiti Technologies
Alessandro is a speaker, researcher, and founder of Oiti Technologies. Since 1984, he has worked with many technologies including Linux*, biometrics, computer vision, and GPUs. Alessandro invented the Certiface technology. He is an ambassador of openSUSE Linux* in Latin America, and is a member of the Open Source Foundation for Application Security (OWASP) and Mozillians. Allesandro contributes to the OpenCV library and open source software that includes being a maintainer of librealsense in openSUSE Linux.
Ali Mustufa Shaikh, Postman* Inc.
As someone who is passionate about machine learning, Ali enjoys sharing his knowledge and creating practical machine learning projects. He focuses on the CPPE-5 (medical personal protective equipment) dataset. Additionally, he teaches over 2,000 individuals about the Intel® Edge AI Certification and has trained more than 50,000 people in various technology areas.
Aniket Kumar, Pulsar
Aniket uses the power of oneAPI to propel innovation throughout his professional endeavors. His diverse portfolio of projects includes Monte Carlo simulations, fractal explorations, Rubik's Cube* solutions, and pioneering the development of blockchain solutions using Data Parallel C++ (DPC++).
Anusha Chinchanooru Ashoka, Lam Research
Anusha is passionate software engineer with a drive for innovation and a deep curiosity for exploring new technologies. Anusha is skilled in developing robust solutions through years of experience at Lam Research* and Honeywell*, and is committed to diversity and inclusion to create a meaningful social impact.
Arun GK
Arun is adept at tasks involving electronics and computer science and is considering building a career in those fields. He is passionate about the complex ways that AI and IoT intertwine to make life better. Arun's interests mainly lie in the automotive and energy engineering fields.
Bharathi Athinarayanan, IQVIA
Bharathi is an IT professional with more than 18 years of demonstrated knowledge in leading high-end technology and software development across diversified teams. He has extensive experience in the fields of AI, machine learning, emerging technology research, patenting, prototyping, and more. He holds more than 75 certifications with specializations in AI, machine learning, and startup innovation and strategy.
Chandra J
Dr. Chandra J is a researcher turned academician working in the field of AI and machine learning on applications in areas like sudden cardiac arrest, lung cancer, autism, and emotional intelligence. She works with genomics and all kinds of medical images (MRI, CT scan, PET, fMRI, and sMRI) where efficient machine learning algorithms are implemented using Intel oneAPI for model implementation.
Clay Breshears, Self Employed
Dr. Clay Breshears has been involved with parallel computation and programming for almost 40 years. He is the author of The Art of Concurrency: A Thread Monkey's Guide to Writing Parallel Applications, published by O'Reilly Media (2009). Clay is rewriting the example codes from his book with Data Parallel C++ (DPC++). He is working towards DPC++ implementations of The Game of Life* and Japanese logic puzzles.
Clemente Giorio, Deltatre*
Clemente is a multifaceted technology enthusiast, researcher, and innovator who has transformed his passion for science and technology into a remarkable career. As a community speaker, he delivers talks about oneAPI, DPC++, and the OpenVINO™ toolkit. As part of his senior research and development engineer role at Deltatre*, Clemente has been spearheading an exciting migration project transitioning an existing (internal) software written in CUDA* (from NVIDIA*) to SYCL* that's compiled using the Intel® oneAPI DPC++ Compiler. Additionally, he's using the capabilities of the Intel® Distribution of OpenVINO™ toolkit to achieve optimized inference on pose estimation and body segmentation.
Deepthi AJ, Codeyoung
In Deepthi's professional life, she has used oneAPI to develop an electrocardiogram (ECG) automated diagnosis application, integrating optimized building blocks from Intel like Intel® Extension for Scikit-learn*, XGBoost, daal4py, and so on. This initiative aims to enhance healthcare access for underserved communities, ensuring timely and accurate cardiac assessments. Additionally, she is actively engaged in a generative AI project, exploring innovative applications in the field.
Dev Aryan Khanna
Dev specializes in implementing advanced AI techniques and using Intel oneAPI libraries, including Intel® oneAPI Deep Neural Network Library (oneDNN) and Intel® oneAPI Data Analytics Library (oneDAL), to encourage innovation in healthcare. His work focuses on optimizing deep learning models to enhance disease detection, contributing to significant advancements in the field.
Elakkiya R
Using the transformative capabilities of oneAPI in her professional journey, Elakkiya is immersed in projects that span diverse domains. From advancing lung-image-quality assessment and diagnosis to pioneering sign-language-generation technologies, Elakkiya's work intersects innovation in healthcare and accessibility. Additionally, Elakkiya develops LLMs tailored for role-playing applications, pushing the boundaries of natural language understanding and interaction.
Felix LeClair
Felix is an open source engineer focused on high-performance computing (HPC), Single Instruction Multiple Data (SIMD), and SYCL. He specializes in optimizing software performance and enabling developers to make the most of cutting-edge hardware technologies, like CPUs, GPUs, or FPGAs.
Felix is focused on accelerating OpenBLAS and FFmpeg* for Intel® Advanced Vector Extensions 512 to make reduced precision types more accessible for classical compute. He is passionate about open source software and believes that collaboration and knowledge sharing are key to advancing HPC.
Harsh Verma, CTO, Glocol Networks
Dr. Harsh Verma is a technology leader and the recipient of an award of excellence for extraordinary contribution to technology by Northern Essex Community College (NECC, an association of the state chief information officers [CIO] in the US), and a Best of California Award for IT collaboration. He received the Future Worlds Exemplary Leadership Award in 2019. Harsh works on using oneAPI and the OpenVINO toolkit for a strategic traffic intersection project in collaboration with the US Department of Transportation (DOT) Volpe Center.
Ian Peitzsch, University of Pittsburgh & SHREC
Ian is a PhD student at the University of Pittsburgh working in the National Science Foundation (NSF) Center for Space, High-Performance, and Resilient Computing (SHREC). His research focuses on accelerating hyperdimensional computing on various hardware platforms.
Ibraheem Khan
Ibraheem's project explores the interpretability of Kolmogorov-Arnold Networks (KAN). The project uses oneAPI to enhance the efficiency of training and testing workloads on Intel® Developer Cloud. As a recent graduate and current computer vision engineer interested in LLMs and deep learning in general, Ibraheem is uncovering new insights and optimizations in these fields.
Istvan Reguly, Pázmány Péter Catholic University (PPCU)
Istvan is an associate professor at PPCU Faculty of Information Technology and Bionics (ITK) teaching parallel programming on modern CPUs, GPUs, and supercomputers. His research focuses on developing tools for scientists that make it easier to express what they want to solve, and then automating the process of efficiently mapping to today's and tomorrow's heterogeneous architectures.
James Bickerstaff, University of Pittsburgh & SHREC
James received his bachelor of science in computer engineering from the University of Pittsburgh and is now a second-year PhD student. He is a member of the NSF SHREC research lab. His primary research focus is accelerating high-throughput applications using FPGAs with oneAPI.
Jamjala Narayanan Swathi
Dr. Jamjala Swathi's research focuses on computer vision projects for CCTV surveillance systems. She is working on a project to detect dangerous objects and suspicious activities captured via CCTV to alert security guards or concerned officials. Jamjala uses Intel oneAPI and OpenVINO toolkit in this project to recognize faces and objects in the scene and classify the scene as suspicious or normal.
Jehferson Mello, Self Employed
Jehferson is an enthusiast who is keen on widening the scope of heterogeneous computing and parallelization and is excited about open source and standards.
Besides taking advantage of the power of technologies such as Threading Building Blocks (TBB) and Intel® Implicit SPMD Program Compiler (Intel® ISPC), he is keenly interested in SYCL as the standard for heterogeneous compute and DPC++. Jehferson's ToyBrot project is a test-bed and showcase for these types of technology to help others make decisions about how to proceed on their own projects.
Juan Fumero
Juan is the lead architect of the TornadoVM project, a parallel programming framework for offloading Java* programs into hardware accelerators such as GPUs, FPGAs and multicore CPUs. TornadoVM runs as a plug-in to existing OpenJDK* distributions. The project also contains a just-in-time (JIT) compiler and a runtime system to automatically orchestrate and optimize programs by running on multiple accelerators. TornadoVM uses libraries and APIs from the Intel® toolkit, such as oneDNN and Intel® oneAPI Math Kernel Library (oneMKL) libraries, for the acceleration of deep learning and linear algebra operators, and the Level Zero API as a bridge between Java applications and the GPU drivers.
Kalpana Shanmugam
Kalpana collaborates with the Education team at KG Institutions to enhance the skills of students and faculty members according to industry standards for AI, machine learning, and deep learning. There is a particular emphasis on LLM projects that use Retrieval Augmented Generation (RAG). Kalpana uses Intel toolkits powered by oneAPI to explore the algorithmic behavior of various machine learning and deep learning models, conducting experiments with extensive datasets to evaluate runtime and memory performance. Intel Developer Cloud is invaluable to this work for its high-computation tasks and digital library. These pioneering insights consolidate information discovery and analysis into a single workflow, enabling faster and more comprehensive decision-making at a moment's notice.
Karthika Subbaraj
Karthika is a passionate teacher and practices research by learning and sharing knowledge in Computational Social Science and Open Source Intelligence (OSINT).
Kazi Haque, Dynopii
Kazi has close to a decade of experience working with AI- and IoT-based applications. He started his journey at Infosys* and now creates and nurtures multiple tech startups. Kazi works on the Intel toolkit for enterprise application integration and evangelizes and contributes to the oneAPI community by taking part in more than 100 workshops and training programs, including national-level hackathons.
Kris Rowe, Argonne Leadership Computing Facility
Kris is an assistant computational scientist in the Performance Engineering Group at Argonne National Laboratory’s Leadership Computing Facility. His research focuses on performance portability, and optimization of high-order finite and spectral element methods for computational science and engineering applications. This work makes extensive use of DPC++ (the oneAPI implementation of SYCL), as well as the Intel® oneAPI DPC++/C++ and Intel® Fortran compilers, Intel® oneAPI Math Kernel Library, and tools like Intel® Advisor and Intel® VTune™ Profiler.
Kris holds a PhD in applied mathematics from the University of Waterloo and was a postdoctoral research associate at Cornell University.
Laxmi Narayanan G
Laxmi is the head of automation for a large engineering services company. He works on multiple deep learning engagements with an emphasis on image analytics and computer vision. Also, as a visiting faculty member at Indian Institute of Management (IIM), he enables students to build intelligent applications using the oneAPI platform.
Luke Kljucaric, University of Pittsburgh and Center for Space, High-Performance, and Resilient Computing (SHREC)
Luke is a PhD student in the electrical and computer engineering department at the University of Pittsburgh. He is the lead student of the Reconfigurable Systems group in the National Science Foundation (NSF) Center at SHREC under Dr. Alan George. His research focuses on analyzing machine learning architectures and developing scalable, low-latency accelerators with neuromorphic technology. Much of his research focuses on using SYCL and oneAPI for accelerated FPGA development and studying the efficacy of high-level design tools.
Marcel Breyer, University of Stuttgart
Marcel is a PhD student at the University of Stuttgart in the Scientific Computing department. After working on a performance-portable implementation of a well-known algorithm in his master thesis, his research now covers a broader field of performance portability. This research includes new applications of SYCL as one possibility to achieve performance portability between different hardware. His main focus is a performance-portable implementation of a Least Squares Support Vector Machine (LS-SVM).
Muthuramalingam Akila
Dr. Muthuramalingam Akila spent 29 years in education and IT. She is a chief executive officer at KSR Educational Institutions, Tiruchengode. Muthuramalingam holds a bachelor of engineering and master of engineering in computer science and engineering and a PhD in computer science. She was awarded several leadership and educational honors.
Muthuramalingam researches machine learning, AI, visual computing, and biometric and bioinformatics applications. Her commitment to innovation is evident in patents she holds for waste treatment, stock market prediction, and IoT system efficiency enhancement.
Oluwatosin Odubanjo, University of A Coruña
Oluwatosin develops mathematical and computational solutions for physical applications. Her work uses OpenMP*, DPC++, and Python* from the Intel® oneAPI Base & HPC Toolkit and AI Tools to develop these solutions across Intel CPUs and GPUs.
Osman El-Ghotmi
At the University of Ottawa, Osman's research group actively develops and maintains a high-performance modern numerical framework for the solution of hyperbolic partial differential equations (PDE). He uses SYCL to extend and scale an implementation of a higher-order numerical technique to target hardware accelerators on large heterogeneous computing facilities. Osman is also the founding contributor and lead developer of the PySYCL project. PySYCL is an open source Python interface for SYCL that enables Python applications to use SYCL functionalities for heterogeneous computing. PySYCL abstracts away the complexities of GPU programming and provides users with an easier-to-use numerical library.
Owen Lucas, University of Pittsburgh & SHREC
Owen graduated from the University of Pittsburgh with a bachelor of science in computer engineering. He is a PhD student at the NSF SHREC at the University of Pittsburgh working under Dr. Alan George. His research focuses on using reconfigurable computing to accelerate bioinformatics applications with oneAPI.
Peter Darveau, Hexagon Technology Inc.
Peter is an experienced technology partner with Intel who provides scientific computing leadership in a community of engineers, scientists, and researchers across Canada for machine learning and AI applications. He regularly conducts HPC workshops and writes scientific papers related to best and recommended computing practices. As an Intel® Certified Instructor in machine learning using oneAPI, Peter's students have confidence that they can rely on oneAPI framework to continuously improve their computing and coding efficiency. His contribution also provides reassurance that, as Intel® Innovators, they have connections to the oneAPI community to support any unique needs and provide continuous improvement feedback of the toolsets.
Peter Ma, SiteMana
Peter Ma is cofounder at SiteMana, an AI company that predicts anonymous visitor purchasing intent. He’s also part of the Intel® Software Innovator, TED speaker, and Techstars* alumni. Peter used oneAPI for predicting the purchasing intent of anonymous visitors and employed the Intel® Developer Cloud for generating large language model (LLM) emails, and enhancing email and ad retargeting strategies.
Prajwal Kumar
Prajwal is an AI and machine learning professional. He has over two years of experience in solving complex problems and driving data-driven decisions that take advantage of Intel toolkits to achieve meaningful business outcomes with a solid foundation in big data analytics, machine learning, computer vision, LLMs, and neural networks. Intel oneAPI technology helped him to accelerate AI and HPC workloads that improved return on investments.
Prakash Arumugam
Dr. Prakash Arumugam uses technology to improve patient outcomes and access to care. The work involves developing innovative solutions that enhance diagnostics, treatment, and patient monitoring, ultimately leading to more personalized and effective healthcare interventions. His research focuses on early prediction of diabetes mellitus and detecting breast cancer and brain tumors. In education, he is dedicated to exploring how technology can enhance learning experiences and make education more accessible and inclusive. Prakash believes that by taking advantage of the power of technology, we can create more engaging and effective learning environments that cater to diverse learner needs.
Prashant R. Nair
Dr. Prashant R. Nair's research focuses on using AI, machine learning, and analytics for Industry 4.0, smart healthcare, and smart education domains. Representative projects in progress include developing a smart healthcare system for Indian healthcare using IoT, AI, and blockchain. He is also engaged in popularizing and evangelizing oneAPI among the academic community not only in his university but also in other institutions.
Rafael Asenjo, University of Malaga
Rafael is a professor of Computer Architecture at the University of Malaga, Spain. He was a visiting scholar and visiting research associate at the University of Illinois in Urbana-Champaign and a research visitor at the IBM* Thomas J. Watson Research Center and at Cray* Inc.
He has used TBB since 2008 and over the last 10 years, Rafael has focused on productively exploiting heterogeneous chips that use TBB as the orchestrating framework. He coauthored the latest book on TBB (open access). Rafael has been using oneAPI since its release to contribute in the heterogeneous (CPU, GPU, and FPGA) parallelization of irregular codes considering energy consumption and programmability.
Ricardo Menotti, Federal University of São Carlos (UFSCar)
Ricardo is an associate professor in the Department of Computer Science at the UFSCar. He uses oneAPI to develop accelerators for various applications using FPGAs. Previously, Ricardo did this manually using a hardware description language (HDL) and researched high-level synthesis (HLS) techniques. He is also interested in CPUs and GPUs to accelerate HPC applications.
Ritwik Murali
Dr. Ritwik Murali's research revolves around the fast-developing world of cybersecurity, meta-heuristic algorithms for search and optimization, neuroevolution, and computing education. He enjoys guiding students toward building software products for academic and in-house requirements. Apart from academic research, Ritwik mentors and trains students for various Capture the Flag hacking contests, hackathons, product development projects, and generic competitions.
Sameer Shende, University of Oregon
Sameer is a research professor and the director of the Performance Research Laboratory at the University of Oregon, and the president and director of ParaTools Inc. He has contributed to the TAU Performance System*, Program Database Toolkit (PDT), HPC Linux, and Extreme-scale Scientific Software Stack (E4S). Sameer's research interests include software stacks, runtime systems, performance instrumentation, compiler optimizations, measurement, and analysis tools for HPC.
Sagaya Aurelia
Sagaya is associated with the Computer Science department at Christ University. She completed her bachelor of engineering in 2000, master of technology in 2002, and PhD in 2019. She has published several research papers in journals and spoken at conferences. The Global Mission of the United Nations Global Compact awarded her the Peace Leader and Peace Educator award. Her research interests include human-computer interaction, augmented reality, and virtual reality.
Sivraj P
Sivraj works with embedded systems and IoT design to develop solutions for a variety of fields, including smart grids, intelligent transportation systems, automotive systems, electric vehicles (EV), and robotics. He uses machine learning approaches to develop intelligent services like energy management, net-zero microgrids and buildings, smart traffic management systems, Advanced Driver Assistance Systems (ADAS), smart EV charging infrastructures, self-navigating robots, and collaborative robotic arms. He guides students in advanced studies across these domains.
Srie Vidhya Janani
Srie is working as an assistant professor for computer science and engineering at Anna University Regional Campus, Madurai. She is adopting Intel oneAPI for all projects and research works. She has published multiple articles in top-class reputed journals, and is currently guiding three research scholars and completed two research scholars for their PhDs.
Tamer Mahmoud
Tamer is an enterprise leader, information and communications technology (ICT) technologist, and industry expert. For over 25 years, he has been leading, managing, and performing research, development, and implementation of technologically challenging systems in a wide range of domains.
Tamer is researching and developing methods and tools for future software development, focusing on performance, large code-base management, and unified models targeting multiplatforms, among other objectives.
Dr. T S Murugesh
Dr. T S Murugesh a seasoned professor, researcher, author, mentor, speaker, and hackathon enthusiast who has more than 23 years experience in academia. The versatility of oneAPI by means of appropriate theory and practical implementation with the latest tools in machine learning has been presented in a simple yet effective way in the book, Machine Learning with oneAPI, and in the research article, Enhancing Multiclass Classification of Knee Osteoarthritis Severity Grades Using oneDNN, that caters to everyone’s needs to understand the power of optimization.
Usha Rengaraju
Usha currently heads the data science research at Exa Protocol and is the world’s first woman triple Kaggle* Grandmaster. She specializes in deep learning and probabilistic graphical models. Usha has won many awards and consistently participates as a mentor, judge, and evangelist for many oneAPI events.
Yan Luo, University of Massachusetts Lowell
Professor Yan Luo leads the Advanced Computer Architecture and Network Systems Laboratory (ACANETS) at the University of Massachusetts Lowell. His goal is to address the challenges in cyberphysical systems and data-driven analytics for high-impact applications in the fields of healthcare, environmental and structural monitoring, and computer networking.
Yan's current research projects at ACANETS include embedded acoustic sensor networks, novel systems for biosensing, data-driven network traffic analytics, and medical image processing. Using oneAPI and Intel Developer Cloud, he teaches heterogeneous computing to undergraduate and graduate students to broaden the scope of computer engineering curriculum and to make them workforce-ready with advanced computing technologies.
Yuri Winche Achermann
Yuri is an aerospace engineer turned entrepreneur spinning off a deep research project in Germany into a startup. He participated in projects with NASA* and Michigan Institute of Technology's (MIT) GeneSys, and worked for data consulting company Artefact and Fraunhofer Institute for Production Technology.
Zhibo Li
Zhibo is a research assistant at the University of Edinburgh who is working on integrating collection skeletons and algorithmic skeletons for use in heterogeneous environments (including GPUs and FPGAs) through oneAPI. Based on the collection skeletons proposed in his prior research, where the programmer can specify data collections with the properties without knowing the implementation details, the extension of collection skeletons enables programmers to apply algorithmic skeletons to these property-based specifications of data collections. Additionally, property checks against the algorithmic skeletons will be performed at compile time. Successful checks result in generating parallel algorithmic skeletons optimized for heterogeneous running.