[{"id":2538,"date":"2025-05-31T14:36:53","date_gmt":"2025-05-31T21:36:53","guid":{"rendered":"https:\/\/r6.ieee.org\/scv-cs\/?p=2538"},"modified":"2025-06-01T20:50:11","modified_gmt":"2025-06-02T03:50:11","slug":"icads2025","status":"publish","type":"post","link":"https:\/\/r6.ieee.org\/scv-cs\/icads2025\/","title":{"rendered":"Agentic AI themed 4th International Conference on Applied Data Science (ICADS 2025)"},"content":{"rendered":"

\"\"<\/a><\/p>\n

 <\/p>\n

Date: July 17, 2025<\/strong><\/span><\/h1>\n

Join us for the Fourth International Conference on Applied Data Science (ICADS 2025), organized by the IEEE Computer Society of Santa Clara Valley. This virtual event brings together global innovators in data science to share cutting-edge research and practical applications.<\/p>\n

ICADS 2025 focuses on the latest advancements in GenAI<\/strong> and its real-world applications, offering a streamlined set of expert talks. This year, we\u2019re placing a special emphasis on Agentic AI<\/strong>, with five dedicated sessions exploring its potential to shape the future of applied data science. Join us virtually to connect with leading researchers and stay at the forefront of innovation\u2014all from the comfort of your home.<\/p>\n

 <\/p>\n

Registration<\/strong><\/span><\/a><\/p>\n

Schedule<\/strong><\/span><\/p>\n\n\n\n\n\n\n\n\n
Time<\/td>\nSession<\/td>\n<\/tr>\n
08:00 to 09 AM PST<\/td>\nAgentic AI: Redefining Autonomy in Intelligent Systems<\/td>\n<\/tr>\n
09:00 to 10:00 AM PST<\/td>\nThe Rise of Autonomous Intelligence: How AI Agents Are Redefining Science, Art, and Business<\/td>\n<\/tr>\n
10:00 am to 11:00 AM PST<\/td>\nFrom Algorithms to Agents: The Role of Agentic AI in Healthcare<\/td>\n<\/tr>\n
11:00 to 12:00 PM PST<\/td>\nTrustworthiness of Agentic AI<\/td>\n<\/tr>\n
12:00 to 01:00 PM PST<\/td>\nBeyond the Buzz: Defining Agentic AI Systems, Their Capabilities, and the Path Forward<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n
<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Speakers<\/strong><\/span><\/p>\n\n\n\n\n\n\n\n
\"\"<\/a><\/td>\n\n

Title: The Rise of Autonomous Intelligence: How AI Agents Are Redefining Science, Art, and Business<\/strong><\/p>\n

Abstract – <\/strong>In this talk, Kamer Ali Yuksel (Head of Agentic AI @ aiXplain) describes how LLM-driven agents are transforming autonomy across research, enterprise, and design. He shows that today\u2019s agents aren\u2019t just \u201csmart autocomplete\u201d but self-directed ideators, experimenters, analysts, and creators. Drawing on his recent publications, he argues that AI agents already deliver end-to-end autonomy: how aiXplain autonomously refine Agentic AI workflows via continuous LLM-driven feedback loops, ideate and implement enterprise Agentic AI use-cases, and derive actionable business insights from enterprise data\u2014producing executive-ready reports without human intervention.<\/p>\n

Situating this vision alongside industry milestones\u2014from DeepMind\u2019s AlphaEvolve to Google Research\u2019s AI Co-Scientist and Sakana\u2019s AI Scientist\u2014he demonstrates how AI Agents now drive original research, design and execute experiments, and draft manuscripts; and how he used this framework to power breakthroughs in quantitative finance by uncovering new risk-adjusted performance metrics, portfolio allocation strategies, and technical indicators. He will talk about autonomous creativity too: evolving GLSL shaders, generative art, and highly converting landing pages through user-driven interactive evolution or visual-LLM feedback.<\/p>\n

 <\/p>\n

Speaker Bio – <\/strong>Kamer Ali Yuksel is a distinguished AI leader and visionary computer scientist, recognized for his pioneering contributions to AI, ML, and Deep Learning over a career spanning more than two decades. He currently serves as the Head of Agentic AI as a Distinguished Scientist at aiXplain, a Silicon Valley-based no-code AI marketplace\/ecosystem and agentification framework founded by Hassan Sawaf, former Director of AI at eBay, Amazon, AWS, and Meta.
\nKamer’s previous leadership roles include Chief Data Scientist at Hawk:AI, where he pioneered anti-money laundering and fraud technologies receiving the FinTech Germany Award; and also at ConnectedLife GmbH, where he led the development of AI-powered health and smart living solutions, winning the EIT Health Wild Card Challenge. He continues to push the boundaries of innovation at aiXplain, shaping the future of enterprise Agentic AI technologies<\/span><\/td>\n<\/tr>\n

\"\"<\/a><\/td>\nTalk title: From Algorithms to Agents: The Role of Agentic AI in Healthcare<\/strong><\/p>\n

Abstract – <\/strong>The future of healthcare is not just digital\u2014it\u2019s intelligent. Agentic AI represents a paradigm shift in artificial intelligence, moving beyond static models and reactive systems to dynamic, autonomous agents capable of setting goals, making decisions, and adapting over time. Unlike traditional AI, which passively responds to inputs, agentic AI can plan, reason, and act in complex, real-world environments\u2014making it especially suited for the demands of modern healthcare.<\/p>\n

In this talk, we explore the emerging role of agentic AI in transforming clinical workflows, decision-making, and patient engagement. From autonomous patient monitoring and adaptive treatment planning to intelligent workflow orchestration, agentic systems have the potential to operate as active teammates to clinicians. We discuss the potential capabilities of agentic AI in learning continuously from patient data, suggesting personalized interventions, and coordinating across departments\u2014all while adapting in real time to new conditions or goals.<\/p>\n

We also discuss real-world application scenarios, including cases like oncology support agents that will be able to manage treatment pathways and virtual health assistants that will monitor chronic conditions at home. Alongside these innovations, we examine critical challenges such as explainability, safety, ethical oversight, and integration into existing clinical systems.<\/p>\n

Ultimately, agentic AI can offer a path toward more proactive, personalized, and scalable healthcare. This talk presents both the promise and the responsibilities of bringing agentic AI into mainstream healthcare\u2014shifting the role of AI from a passive tool to an active, intelligent partner.<\/p>\n

 <\/p>\n

Speaker Bio – <\/strong>Dr. Anuradha Kar is an Associate Professor in AI and Robotics at Aivancity Paris Cachan, France, where she teaches and mentors graduate students in deep learning, AI for health, computer vision, explainable AI, and human-computer interaction.<\/span><\/p>\n

She holds a Ph.D. in Electrical Engineering from the University of Galway, Ireland. Her research interests lie at the intersection of assistive technologies, digital health, generative AI, and the ethical and fair deployment of artificial intelligence.<\/p>\n

She has conducted research at several leading institutions, including the Institut Pasteur in Paris, where she focused on deep learning applications in drug discovery, and the Paris Brain Institute, where she worked on AI-driven analysis of Alzheimer\u2019s disease biomarkers. At the \u00c9cole normale sup\u00e9rieure de Lyon, she developed deep learning techniques for the analysis of 3D bio-imaging datasets.<\/p>\n

Anuradha is also an author of two liveProject series with Manning Publications (2021 and 2024), which delve into the use of deep learning and explainable AI in medical imaging workflows.<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\nTitle: Trustworthiness of Agentic AI<\/strong><\/p>\n

Abstract – <\/strong>In especially the last decade, developments in the field of AI caused transformative changes in the context of modern life. Although deep learning models of the early 2000s allowed enhanced solutions for real-world problems, generative AI models changed the rules of the game and placed AI in the middle of daily life.<\/p>\n

As a result, today\u2019s AI systems can deal with more complicated data-driven problems and support humans in many tasks\u2014including even the ones involving intellectual processes. Furthermore, such systems can ensure a networked solution flow through agentic use.<\/p>\n

However, one of the most important challenges exposed by such AI formation is trustworthiness. Because agentic AI, through generative and complicated architectures, results in black-box models, there is a critical need for research in ensuring trustworthiness.<\/p>\n

Moving from this fact, this speech will be about understanding the need for trustworthiness in Agentic AI and learning about the latest developments in ensuring it. The speech will discuss not only technical solution approaches but also our responsibilities to build human-compatible Agentic AI.<\/p>\n

In this context, the speech will also cover advancements in terms of AI policies regarding its management and safety.<\/p>\n

Speaker Bio – <\/strong>Dr. Utku Kose received the B.S. degree in 2008 from the Department of Computer Education at Gazi University, Turkey, as the faculty valedictorian. He received his M.S. degree in 2010 from Afyon Kocatepe University, Turkey, in the field of computer science, and his D.S.\/Ph.D. degree in 2017 from Selcuk University, Turkey, in the field of computer engineering.<\/span><\/p>\n

Between 2009 and 2011, he worked as a Research Assistant at Afyon Kocatepe University. He then served as a Lecturer and Vocational School Vice Director at the same university between 2011 and 2012. From 2012 to 2017, he worked as a Lecturer and Director of a Research Center at Usak University. He was an Assistant Professor at Suleyman Demirel University between 2017 and 2019, and an Associate Professor there from 2019 to 2024. Currently, he is a Full Professor at Suleyman Demirel University, Turkey.<\/p>\n

Dr. Kose has also taught at other higher education institutions such as Gazi University and Istanbul Arel University. He served as a Visiting Researcher at the University of North Dakota, USA (2023\u20132024), and holds the title of Honorary Professor of Artificial Intelligence at ITM (SLS) Baroda University, India.<\/p>\n

He has more than 350 publications, including articles, authored and edited books, proceedings, and technical reports. He serves on the editorial boards of many scientific journals and is one of the editors of the Biomedical and Robotics Healthcare (CRC Press) and Computational Modeling Applications for Existential Risks (Elsevier) book series.<\/p>\n

His research interests include artificial intelligence, machine ethics, AI safety, biomedical applications, optimization, chaos theory, distance education, e-learning, computer education, and computer science.<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\nTitle: Beyond the Buzz: Defining Agentic AI Systems, Their Capabilities, and the Path Forward<\/strong><\/p>\n

Abstract – <\/strong>Despite widespread discussion of AI agents across industry and academia, the field lacks consensus on fundamental questions: What exactly constitutes an agent? What problems can current agents realistically solve versus what remains beyond their reach? This talk addresses the clarity gap by examining current agent capabilities and limitations through real-world examples, and establishing concrete problem statements for researchers and practitioners. We’ll identify key research challenges including the need for standardized evaluation frameworks, improved planning mechanisms, and better techniques for agent-human collaboration. The goal is to move beyond the hype and provide a structured foundation for meaningful progress in agent development, complete with proposed benchmarks and a research roadmap that can guide the next generation of agent systems toward solving real-world problems effectively and safely.<\/p>\n

Speaker Bio –\u00a0<\/strong><\/span>Ranjitha Gurunath Kulkarni is a Senior ML Engineer at Dropbox with over a decade of experience in NLP-focused applied machine learning. At Dropbox, she plays a pivotal role in building next-generation AI systems, including a cutting-edge LLM-based Agents Platform and the question answering system powering Dropbox Dash. Prior to that, she worked at Microsoft, contributing to research and development in language modeling and speech recognition.<\/span><\/td>\n<\/tr>\n

\"\"<\/a><\/td>\nTitle: Agentic AI: Redefining Autonomy in Intelligent Systems<\/strong><\/p>\n

Abstract<\/strong> – Agentic AI is reshaping the boundaries of artificial intelligence by enabling systems that move beyond reactive responses to exhibit autonomy, initiative, and adaptability. These agents are capable of independently setting goals, planning multi-step actions, maintaining memory over time, and interacting intelligently with their environments. Underpinned by architectures that combine reasoning, perception, and feedback loops, agentic systems are increasingly deployed in domains such as software automation, robotics, and decision support. As their influence grows, so do the challenges\u2014ranging from safety and value alignment to transparency and collaboration. Agentic AI represents a foundational shift in how intelligent systems are designed and deployed, redefining autonomy for the next generation of AI.<\/p>\n

Speaker Bio – <\/strong><\/span>Dr. Soumen Biswas is a Senior Researcher in the Artificial Intelligence Research Group at Hitachi R&D India. His expertise spans artificial intelligence, computer vision, large language models (LLMs), and vision-language models (VLMs). He focuses on developing cutting-edge AI solutions tailored for industrial applications in domains such as manufacturing, healthcare, mobility, and smart infrastructure.<\/p>\n

Dr. Biswas has a strong track record of publications in reputed journals and international conferences. He serves as a reviewer for esteemed journals including IEEE Transactions on Circuits and Systems for Video Technology, Circuits, Systems, and Signal Processing (Springer), IET Image Processing, IET Signal Processing, Journal of Computational and Applied Mathematics (Elsevier), Optik \u2013 International Journal for Light and Electron Optics (Elsevier), ACM Transactions, and IEEE Access, among others.<\/p>\n

Beyond research, Dr. Biswas is actively involved in academic leadership and the AI research community. He has organized workshops and special sessions at major conferences such as ICMLA, IEEE Big Data, and IEEE AISP. He also serves on the Program Committees of various IEEE and Springer-sponsored international conferences. Dr. Biswas is a Senior Member of the IEEE.<\/p>\n

 <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 <\/p>\n

Organizers<\/strong><\/span><\/p>\n\n\n\n\n
\"\"<\/a><\/td>\n\"\"<\/a><\/td>\n<\/tr>\n
Dr Vishnu Pendyala<\/strong><\/a><\/td>\nRahul Raja<\/strong><\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 <\/p>\n

Previous Events<\/strong><\/span><\/p>\n

First International Conference on Applied Data Science (ICADS’22<\/a>)<\/p>\n

Second International Conference on Applied Data Science (ICADS’23<\/a>)<\/p>\n

Third International Conference on Applied Data Science (ICADS’24<\/a>)<\/p>\n

Contact Us<\/strong><\/span><\/p>\n

If you have any questions, please reach out to us at: link<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

  Date: July 17, 2025 Join us for the Fourth International Conference on Applied Data Science (ICADS 2025), organized by the IEEE Computer Society of Santa Clara Valley. This virtual… Read more →<\/span><\/a><\/p>\n","protected":false},"author":290,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[74,34,2,31],"tags":[],"class_list":["post-2538","post","type-post","status-publish","format-standard","hentry","category-2025-events","category-conferences","category-upcoming-events","category-webinar"],"_links":{"self":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts\/2538","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/users\/290"}],"replies":[{"embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/comments?post=2538"}],"version-history":[{"count":0,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts\/2538\/revisions"}],"wp:attachment":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/media?parent=2538"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/categories?post=2538"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/tags?post=2538"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":2468,"date":"2024-10-24T16:00:54","date_gmt":"2024-10-24T23:00:54","guid":{"rendered":"https:\/\/r6.ieee.org\/scv-cs\/?p=2468"},"modified":"2024-10-24T16:00:54","modified_gmt":"2024-10-24T23:00:54","slug":"quantitative-analysis-of-machine-learning-model-performance-and-the-need-to-consider-explainability-in-it","status":"publish","type":"post","link":"https:\/\/r6.ieee.org\/scv-cs\/quantitative-analysis-of-machine-learning-model-performance-and-the-need-to-consider-explainability-in-it\/","title":{"rendered":"Quantitative Analysis of Machine Learning Model Performance and the Need to Consider Explainability in It"},"content":{"rendered":"

Speaker: Dr. Vishnu S. Pendyala, San Jose State University
\n <\/a>
\nMeeting Date: Monday, December 30, 2024
\nTime: Checkin via Zoom for presentation at 7:00 PM (PST)
\nCost: none
\nReservations: events.vtools.ieee.org\/m\/442073 <\/a>
\nSummary:<\/strong> For a long time, the AI\/ML community relied on traditional evaluation metrics such as the confusion matrix, accuracy, precision, and recall for assessing the performance of machine learning models. However, the rapidly evolving field has been raising several ethical concerns, which calls for a more comprehensive evaluation scheme. In easy-to-understand language, this talk will delve into the quantitative analysis of model performance, emphasizing the critical importance of explainability. As ML models become increasingly complex and pervasive, understanding their decision-making processes is paramount. We’ll explore various performance metrics, their limitations, and the growing need for transparency. Topics covered include Cohen\u2019s Kappa Statistic, Matthew’s correlation coefficient (MCC), Confusion Matrix, Precision, Recall, G-measure, ROC Curve, Youden’s J statistic, Type II Adversarial attack, R-squared, LIME, SHAP, and more.
\n
\nBio: Vishnu S. Pendyala, <\/strong> PhD is a faculty member in Applied Data Science and an Academic Senator with San Jose State University, current chair of the IEEE Computer Society Santa Clara Valley Chapter, and IEEE Computer Society Distinguished Contributor. During his recent 3-year term as an ACM Distinguished Speaker and before that as a researcher and industry expert, he gave numerous (70+) talks in various forums such as faculty development programs, the 12th IEEE GHTC h5-index:14, h5-median:19, IEEE ANTS h5-index:15 h5-median:19, 11th and 12th IACC H5-Index: 606, H10-Index: 305, 10th ICMC H5-index: 10, h5-median: 15, IUCEE, to audiences at venues such as Stanford University, University of Bolton, Universidad de Ingenier\u00eda y Tecnolog\u00eda, Lima, Peru, IIIT Hyderabad, KREA, IIT Indore, IIIT Bhubaneswar. Some of these talks are available on YouTube and IEEE.tv. He is a senior member of the IEEE and has over two decades of experience in the software industry in the Silicon Valley, USA. His book, \u201cVeracity of Big Data,\u201d is available in several libraries, including those of MIT, Stanford, CMU, the US Congress and internationally. Two other books on machine learning and software development that he edited are also well-received and found a place in the US Library of Congress and other reputed libraries. Dr. Pendyala taught a one-week course sponsored by the Ministry of Human Resource Development (MHRD), Government of India, under the GIAN program in 2017 to Computer Science faculty from all over the country and delivered the keynote in a similar program sponsored by AICTE, Government of India in 2022. Dr. Pendyala recently served on the US government’s National Science Foundation (NSF) proposal review panel. He received the Ramanujan Memorial gold medal and a shield for his college at the State Math Olympiad.<\/p>\n","protected":false},"excerpt":{"rendered":"

— Machine Learning KPIs, Confusion Matrix, Precision, Recall, G-measure, ROC Curve, Youden’s J statistic, Type II Adversarial attack, R-squared, LIME, SHAP …<\/p>\n","protected":false},"author":78,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[69,31],"tags":[],"class_list":["post-2468","post","type-post","status-publish","format-standard","hentry","category-2024-events","category-webinar"],"_links":{"self":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts\/2468","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/users\/78"}],"replies":[{"embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/comments?post=2468"}],"version-history":[{"count":0,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts\/2468\/revisions"}],"wp:attachment":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/media?parent=2468"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/categories?post=2468"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/tags?post=2468"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":2465,"date":"2024-10-24T11:14:25","date_gmt":"2024-10-24T18:14:25","guid":{"rendered":"https:\/\/r6.ieee.org\/scv-cs\/?p=2465"},"modified":"2024-10-24T15:55:24","modified_gmt":"2024-10-24T22:55:24","slug":"2465-2","status":"publish","type":"post","link":"https:\/\/r6.ieee.org\/scv-cs\/2465-2\/","title":{"rendered":"Heterogeneous Integration for AI Architectures: Advanced Packaging Approaches"},"content":{"rendered":"

Organized by the Indiana Electronics Packaging Society Chapter<\/em>
\nSpeaker: Dr. Mukta Farooq, Distinguished Research Scientist, IBM (and IEEE Fellow)
\n <\/a>
\nMeeting Date: Friday, November 1, 2024
\nTime: Checkin via Zoom for presentation at 9:00 AM (PDT)
\nCost: none
\nReservations: events.vtools.ieee.org\/m\/440607 <\/a>
\nSummary:<\/strong> While silicon scaling has reached astonishing levels over the last half century, there has not been a corresponding level of scaling in electronics packaging technology. However, Artificial Intelligence (AI) architectures are now changing the landscape, increasingly moving us towards advanced packaging technology and Heterogeneous Integration (HI). What are these unique requirements of AI which are driving the need for HI? What are some of the unique challenges in semiconductor and packaging technologies that must be overcome to make this successful? This seminar will discuss key HI methods including interposers, fan out wafer level processing, silicon bridges, and 3D integration to see how they can be leveraged to achieve AI architectures.<\/p>\n

Bio: Dr. Mukta Farooq <\/strong> is an IBM Distinguished Research Scientist, and the 3D\/Heterogeneous Integration Technology Leader at IBM Research. She is an IEEE Fellow, an IEEE EDS Distinguished Lecturer, and winner of the 2023 EDS JJ Ebers Award. Mukta is a Distinguished Alumna of IIT-Bombay (India). Mukta is a metallurgist and materials scientist with expertise in Heterogeneous Integration for Chiplet Technology, CMOS BEOL, Lead-free Alloys, and Chip-Package Interaction. She has 244 granted US patents, 66 granted international patents, and is an IBM Lifetime Master Inventor and IBM Academy of Technology member. She has been invited to give keynote talks and teach short courses, and to write papers in her field of expertise. Mukta received her BS from IIT-Bombay, MS from Northwestern University, and PhD from Rensselaer Polytechnic Institute.<\/p>\n","protected":false},"excerpt":{"rendered":"

— scaling, unique challenges, interposers, WLP, silicon bridges, 2.5D, 3D …<\/p>\n","protected":false},"author":78,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[69,31],"tags":[],"class_list":["post-2465","post","type-post","status-publish","format-standard","hentry","category-2024-events","category-webinar"],"_links":{"self":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts\/2465","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/users\/78"}],"replies":[{"embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/comments?post=2465"}],"version-history":[{"count":0,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts\/2465\/revisions"}],"wp:attachment":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/media?parent=2465"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/categories?post=2465"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/tags?post=2465"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":2463,"date":"2024-10-24T11:01:50","date_gmt":"2024-10-24T18:01:50","guid":{"rendered":"https:\/\/r6.ieee.org\/scv-cs\/?p=2463"},"modified":"2024-11-12T18:59:56","modified_gmt":"2024-11-13T02:59:56","slug":"artificial-intelligence-driven-smart-digital-diagnostics-and-therapeutics-for-neurological-disorders","status":"publish","type":"post","link":"https:\/\/r6.ieee.org\/scv-cs\/artificial-intelligence-driven-smart-digital-diagnostics-and-therapeutics-for-neurological-disorders\/","title":{"rendered":"Artificial Intelligence Driven Smart Digital Diagnostics and Therapeutics for Neurological Disorders"},"content":{"rendered":"

Slides: AI-DTx Nov ’24 talk by Prof. Vir V. Phoha Slides<\/a><\/p>\n

Video: https:\/\/www.youtube.com\/watch?v=VE6NSrEfGyk<\/a><\/p>\n

Speaker: Prof. Vir Phoha, EE & CS, Syracuse University
\n <\/a>
\nMeeting Date: Monday, November 11, 2024
\nTime: Checkin via Zoom for presentation at 5:00 (PST)
\nCost: none
\nReservations: events.vtools.ieee.org\/m\/438778 <\/a>
\nSummary:<\/strong> Neurological disorders are a leading cause of disability and death worldwide. Early detection and efficient management of these disorders can provide significant health benefits. By providing real-time data-driven insights, AI-driven methods meet an urgent need for early detection and management of these disorders.
\nIn this talk, Prof. Phoha will present the potential of AI-driven early diagnosis and Digital Therapeutics (DTx) for neurological disorders. Using the unique properties of data generated through neurological anomalies and disorders, one can use AI methods such as transfer learning from existing knowledge; one-shot and few-shot learning for spiking and sparse data, and hidden Markov models to find underlying relationships and causes of malignant neurological disorders. The speaker will show how the generated data can be captured through smart wearables and phones, how uncovering relationships provides insights for digital rehabilitation, and how using augmented reality and virtual reality provides tremendous potential for cognitive therapy, psychiatric assessments, and rehabilitation. Prof. Phoha will outline a proof-of-concept smart diagnostics-enabled mirror and discuss security issues in smart diagnostics.<\/p>\n

Moderator:<\/strong> Dr. Vishnu S. Pendyala of San Jose State University (CS Chapter Chair)<\/p>\n


\nBio: Vir V. Phoha <\/strong> is currently a tenured full Professor of Electrical Engineering and Computer Science in the College of Engineering and Computer Science at Syracuse University, New York. His research interests include machine learning, nonlinear prediction, hidden pattern detection and correlation, and knowledge discovery and analysis. Professor Phoha has supervised 20 PhD students and 65 MS students. Professor Phoha is a Fellow of AAAS; AAIA; IEEE; NAI; and SDPS. He is an ACM Distinguished Scientist. He has won many research awards including the 2017 IEEE Region 1 Technical Innovation Award for contributions to Behavioral Biometrics.<\/p>\n","protected":false},"excerpt":{"rendered":"

— smart wearables, digital rehabilitation, augmented reality, virtual reality, cognitive therapy, psychiatric assessments, security issues in smart diagnostics …<\/p>\n","protected":false},"author":78,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[69,35,36,31],"tags":[],"class_list":["post-2463","post","type-post","status-publish","format-standard","hentry","category-2024-events","category-slides","category-video","category-webinar"],"_links":{"self":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts\/2463","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/users\/78"}],"replies":[{"embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/comments?post=2463"}],"version-history":[{"count":0,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts\/2463\/revisions"}],"wp:attachment":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/media?parent=2463"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/categories?post=2463"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/tags?post=2463"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":2454,"date":"2024-09-24T09:43:02","date_gmt":"2024-09-24T16:43:02","guid":{"rendered":"https:\/\/r6.ieee.org\/scv-cs\/?p=2454"},"modified":"2024-09-24T09:43:45","modified_gmt":"2024-09-24T16:43:45","slug":"energy-efficient-high-speed-avalanche-photo-diode-apd-optical-links-for-hpc-data-centers","status":"publish","type":"post","link":"https:\/\/r6.ieee.org\/scv-cs\/energy-efficient-high-speed-avalanche-photo-diode-apd-optical-links-for-hpc-data-centers\/","title":{"rendered":"Energy-Efficient High Speed Avalanche Photo Diode (APD) Optical Links for HPC, Data Centers"},"content":{"rendered":"

Speaker: Dr. Zhihong Huang, principal research scientist, Hewlett Packard Labs
\n <\/a>
\nMeeting Date: Thursday, December 12, 2024
\nTime: Checkin via WebEx for presentation at 12:00 noon (PST)
\nCost: none
\nReservations: events.vtools.ieee.org\/m\/435507 <\/a>
\nSummary:<\/strong> As AI and machine learning continue to advance rapidly, the demand for GPU and data center connectivity is escalating. Silicon photonics is emerging as a transformative solution for optical interconnects, offering cost-effective, high-volume optical interconnect solution. Current electrical and optical interconnect struggle to meet the power demand and connectivity driven by the needs of AI and cloud computing. At the LSIP group within Hewlett Packard Labs, we are focused on delivering low-power optical links capable of reaching beyond 1.6Tb\/s transmission with 200+ Gb\/s per lane. In this presentation, I will discuss our efforts in developing high speed silicon photonics optical interconnects, including utilizing high speed Si(Ge) avalanche photodiodes to realize energy-efficient optical links.
\n
\nBio: Zhihong (Joan) Huang <\/strong> is a principal research scientist at Hewlett Packard Labs. At LSIP group within Hewlett Packard Labs (HPE Labs), she leads the research and development of high-sensitivity, low-energy silicon optical transceivers and integrated photonic networks for data centers and high-performance computing. She focuses on photonics device innovation, photonic link and CMOS transceiver co-design and photonic link optimization to enable 200+ Gb\/s high-speed Si photonics optical links for AI cloud environments, data centers, and high-performance computing. Her passion is centered on implementing integrated Si photonics to sensing, photonic neural network, high-speed optical interconnects and chip-to-chip connectivity. Zhihong has obtained her B.S. degree from Peking University, and her M.S. and Ph.D. degrees in Electrical Engineering from the University of Texas at Austin. She has authored and coauthored over 170+ journal and conference papers, 40+ granted patents and with two dozen pending.<\/p>\n","protected":false},"excerpt":{"rendered":"

— high-performance & AI computing, SiPho, optical interconnects, low power, 1.6Tb\/s, Si(Ge) …<\/p>\n","protected":false},"author":78,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[31],"tags":[],"class_list":["post-2454","post","type-post","status-publish","format-standard","hentry","category-webinar"],"_links":{"self":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts\/2454","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/users\/78"}],"replies":[{"embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/comments?post=2454"}],"version-history":[{"count":0,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts\/2454\/revisions"}],"wp:attachment":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/media?parent=2454"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/categories?post=2454"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/tags?post=2454"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":2452,"date":"2024-09-24T09:33:46","date_gmt":"2024-09-24T16:33:46","guid":{"rendered":"https:\/\/r6.ieee.org\/scv-cs\/?p=2452"},"modified":"2024-09-24T09:36:30","modified_gmt":"2024-09-24T16:36:30","slug":"ama-data-privacy-gautam-kamath","status":"publish","type":"post","link":"https:\/\/r6.ieee.org\/scv-cs\/ama-data-privacy-gautam-kamath\/","title":{"rendered":"AMA (Ask me Anything) on Data Privacy, Machine Unlearning, and more with Prof. Gautam Kamath"},"content":{"rendered":"

Speaker: Prof. Gautam Kamath, University of Waterloo (and Faculty Member at the Vector Institute)
\nModerator: Dr. Vishnu Pendala, San Jose State University
\n <\/a>
\nMeeting Date: (day), (date\/month), 2021
\nTime: Checkin via Zoom for presentation at 6:00 (PDT)
\nCost: none
\nReservations: events.vtools.ieee.org\/m\/431191 <\/a>
\nSummary:<\/strong> After a brief introduction highlighting issues and solutions for data privacy in machine learning settings, Prof. Gautam Kamath will answer your questions related to data privacy, machine unlearning, research, academia, career advice, and anything in between. You may review his work and thoughts on Google Scholar at scholar.google.com\/citations?user=MK6zHkYAAAAJ&view_op=list_works&sortby=pubdate <\/a>, and on YouTube at www.youtube.com\/results?search_query=gautam+kamath<\/a> and generally on the Internet.
\nPlease submit your questions in advance:
\n — via Twitter by using the hashtag, #KamathAMA and tagging @vishnupendyala
\n — emailing vspendyala(at)hotmail(dot)com with #KamathAMA in the subject
\n — during your registration on Zoom
\nSelected questions will be answered by Prof. Kamath during the session. Audience may be able to ask follow-up questions during the session using the Zoom Chat system.<\/p>\n


\nBio: Gautam Kamath <\/strong> is an Assistant Professor at the David R. Cheriton School of Computer Science at the University of Waterloo, and a Canada CIFAR AI Chair and Faculty Member at the Vector Institute. He has a B.S. in Computer Science and Electrical and Computer Engineering from Cornell University and an M.S. and Ph.D. in Computer Science from the Massachusetts Institute of Technology. He is interested in reliable and trustworthy statistics and machine learning, including considerations such as data privacy and robustness. He was a Microsoft Research Fellow, as a part of the Simons-Berkeley Research Fellowship Program at the Simons Institute for the Theory of Computing. He serves as an Editor in Chief of Transactions on Machine Learning Research and is the program committee co-chair of the 36th International Conference on Algorithmic Learning Theory (ALT 2025). He is the recipient of several awards, including the Caspar Bowden Award for Outstanding Research in Privacy Enhancing Technologies, a best paper award at the Forty-first International Conference on Machine Learning (ICML 2024), and the Faculty of Math Golden Jubilee Research Excellence Award.<\/p>\n","protected":false},"excerpt":{"rendered":"

— IEEE Day event, research, directions, issues and solutions, career advice …<\/p>\n","protected":false},"author":78,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[31],"tags":[],"class_list":["post-2452","post","type-post","status-publish","format-standard","hentry","category-webinar"],"_links":{"self":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts\/2452","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/users\/78"}],"replies":[{"embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/comments?post=2452"}],"version-history":[{"count":0,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts\/2452\/revisions"}],"wp:attachment":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/media?parent=2452"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/categories?post=2452"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/tags?post=2452"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":2389,"date":"2024-07-25T09:24:30","date_gmt":"2024-07-25T16:24:30","guid":{"rendered":"https:\/\/r6.ieee.org\/scv-cs\/?p=2389"},"modified":"2024-07-25T10:45:52","modified_gmt":"2024-07-25T17:45:52","slug":"hot-chips-2024","status":"publish","type":"post","link":"https:\/\/r6.ieee.org\/scv-cs\/hot-chips-2024\/","title":{"rendered":"Hot Chips 2024 Conference (Hybrid)"},"content":{"rendered":"

IEEE Computer Society’s Technical Committee on Microprocessors and Microcomputers <\/em>
\n <\/a>
\nDates: Sunday – Tuesday, August 25-27, 2024
\nLocation: Memorial Auditorium, Stanford University (and via Zoom)
\nCost: $160 for members ($200 non-members) — includes breakfast, lunch and coffee breaks. Early registration discount through Friday, August 2nd
\nInformation, and to register: https:\/\/hotchips.org <\/a><\/p>\n

Summary:<\/strong>
\nTutorials: Sunday, August 25
\nConference: Monday & Tuesday, August 26-27
\n
\nTutorials: Overview of AI in Chip Design<\/strong> (NVIDIA); Higher Data Center Compute Density<\/strong> (Supermicron); Thermal challenges of Edge Devices<\/strong> (Qualcomm); Applications for Thermo-electric Cooling<\/strong> (Phononic) and others.<\/p>\n

Presentations: Snapdragon X Elite Qualcomm Oryon CPU<\/strong> (Qualcomm); Lunar Lake<\/strong> (Intel); 5GHz IBM Z Processor and AI Inferencing Accelerator <\/strong> (IBM); An AI Compute ASIC with Optical Attach <\/strong> (Broadcom) plus Poster Session and many others — see full Program. <\/p>\n","protected":false},"excerpt":{"rendered":"

— Attend In-Person at Stanford, or Virtually … <\/p>\n","protected":false},"author":78,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[34],"tags":[],"class_list":["post-2389","post","type-post","status-publish","format-standard","hentry","category-conferences"],"_links":{"self":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts\/2389","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/users\/78"}],"replies":[{"embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/comments?post=2389"}],"version-history":[{"count":0,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts\/2389\/revisions"}],"wp:attachment":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/media?parent=2389"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/categories?post=2389"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/tags?post=2389"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":2386,"date":"2024-07-23T18:29:19","date_gmt":"2024-07-24T01:29:19","guid":{"rendered":"https:\/\/r6.ieee.org\/scv-cs\/?p=2386"},"modified":"2024-07-27T18:46:53","modified_gmt":"2024-07-28T01:46:53","slug":"ieee-newera","status":"publish","type":"post","link":"https:\/\/r6.ieee.org\/scv-cs\/ieee-newera\/","title":{"rendered":"IEEE New Era World Leaders AI Summit"},"content":{"rendered":"

Sponsored by Seattle Section, IEEE Industrial Engagement Committee, IEEE-USA, Region 6, SCV-CS chapter<\/em>
\nAffected by tech layoffs?<\/em><\/strong> Don’t miss this AI Summit!
\nDOWNLOAD the SUMMIT FLYER<\/strong><\/a><\/p>\n

<\/a> Keynote Speakers: Senator Maria Cantwell<\/strong> (State of WA); Dr. Bill Dally<\/strong> (Chief Scientist, Nvidia Research); Dr. Stefano Soatto<\/strong> (VP AWS, Amazon AI Labs); Dr. Peter Lee<\/strong> (Pres, Microsoft Research); Dr. Blaise Ag\u00fcera Arcas<\/strong> (Vice Pres\/Fellow & CTO, Google); Dr. Juan LaVista Ferres<\/strong> (Corp VP & Chief Data Scientist, AI for Good); Dr. Kristin Luter<\/strong> (Sr Director, FAIR Labs, Meta); Rish Tandon<\/strong> (VP, Meta); Tom Coughlin<\/strong> (IEEE President); and many more.
\n… plus Lightning talks<\/strong> and workshops<\/strong><\/a> to teach the fundamentals of AI, to redirect mid-career SW\/CS engineers, across a wide range of the newest AI applications in industry, science, and medicine.
\n <\/p>\n

Event Dates:<\/strong> Sat-Sun, August 24-25, 2024
\nLocation:<\/strong> Huskies Student Union, Univ of Washington (in-person); and via MS Teams (for all talks on Saturday)
\nCost:<\/strong> $20 for IEEE Members, $60 for non-members (by Aug 9th); 25% more after Aug 9th.
\nInformation and Reservations:<\/strong> attend.ieee.org\/newera <\/a>
\nSummary:<\/strong> This is a major IEEE event with top-level leaders from all the major AI companies. Plus, for those coming to Seattle, a second full day of Workshops<\/a>, including a LLM\/RAG hands-on class<\/strong> from Nvidia<\/a> (WTL), Generative AI Applications<\/strong> from Amazon AWS<\/a> (WTE), Data Engineering and GenAI<\/strong> from Netflix<\/a> (WTF), and Unlocking the Power of LLMs<\/strong> from Meta<\/a> (WTI), and more, aimed at helping new and current CS engineers and programmers to evaluate moving into this exciting new field. <\/p>\n

The latest McKinsey Global Survey on AI<\/strong> in May of 2024 concludes that 2023 was the year the world discovered generative AI (GenAI), and 2024 is the year organizations truly began using — and deriving business value<\/strong> — from this new technology. An incredible 65 percent of respondents report that their organizations are regularly using GenAI, which is nearly double the percentage from the previous survey just ten months before. Respondents’ expectations for gen AI’s impact remain as high, with three-quarters predicting that gen AI will lead to significant or disruptive change<\/strong> in their industries in the years ahead. Oracle<\/strong> is laying off 4,250 current employees — but plans to hire 4,000 AI specialists. <\/strong> <\/p>\n

Mastering AI tools and techniques is not just about keeping pace with technology — it’s also about leveraging these advanced resources to fill in knowledge gaps, enhance decision-making, and drive productivity in the next phase of your career. <\/strong> Learning to utilize AI at our Seattle Workshops<\/strong> can significantly boosts your capacity to deliver increased business outcomes, making you more valuable and a strategic asset to your organization. See especially the in-depth hands-on sessions from Nvidia and AMD.<\/p>\n

Get details from the New Era AI Summit<\/strong>‘s website.<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

— two-day opportunity to check out this new technology, and potentially re-focus your SW\/CS career …<\/p>\n","protected":false},"author":78,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[69,34,2,31],"tags":[],"class_list":["post-2386","post","type-post","status-publish","format-standard","hentry","category-2024-events","category-conferences","category-upcoming-events","category-webinar"],"_links":{"self":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts\/2386","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/users\/78"}],"replies":[{"embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/comments?post=2386"}],"version-history":[{"count":0,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts\/2386\/revisions"}],"wp:attachment":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/media?parent=2386"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/categories?post=2386"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/tags?post=2386"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":2374,"date":"2024-06-15T09:06:19","date_gmt":"2024-06-15T16:06:19","guid":{"rendered":"https:\/\/r6.ieee.org\/scv-cs\/?p=2374"},"modified":"2024-09-19T19:10:59","modified_gmt":"2024-09-20T02:10:59","slug":"about-us-2360-2","status":"publish","type":"post","link":"https:\/\/r6.ieee.org\/scv-cs\/about-us-2360-2\/","title":{"rendered":"Third International Conference on Applied Data Science (ICADS) 2024"},"content":{"rendered":"

\"\"<\/a><\/p>\n

Date: Sept 13, 2024<\/strong><\/span><\/h1>\n

Join us for the Third International Conference on Applied Data Science (ICADS 2024), organized by the IEEE Computer Society of Santa Clara Valley. This virtual event brings together global innovators in data science to share cutting-edge research and practical applications.<\/p>\n

With keynote sessions, interactive workshops, and panel discussions covering topics related to GenAI and its application. ICASDS 2024 offers a dynamic platform for innovation and collaboration. Don’t miss this opportunity to connect with experts and advance the field of data science from the comfort of your own home.<\/p>\n

Registration<\/a><\/strong><\/span><\/p>\n

Schedule<\/strong><\/span><\/p>\n\n\n\n\n\n\n\n\n
Time<\/td>\nSession<\/td>\n<\/tr>\n
09:00 to 10:00 am<\/td>\nQuantum Gate Neural Networks<\/td>\n<\/tr>\n
10:00 am to 11:00 am<\/td>\nPanel Discussion: AI and Social Media<\/td>\n<\/tr>\n
11:00 to 12:00 pm<\/td>\nAccelerating Code Contribution with CodeBaseBuddy’s Intelligent Semantic Search System<\/span><\/td>\n<\/tr>\n
12:00 to 01:00 pm<\/td>\nRevolutionizing Aerospace Supply Chains with Machine Learning-Powered Digital Twins<\/td>\n<\/tr>\n
01:00 to 2:00 pm<\/td>\nEnabling Performance-Efficient GenAI at the Edge Through Quantization<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n
02:00 to 3:00 pm<\/td>\nThe Power and Perils of Generative AI: A Realistic Perspective<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Speakers<\/strong><\/span><\/p>\n\n\n\n\n\n\n\n
\"\"<\/a><\/td>\n\n

Title:\u00a0 Quantum Gate Neural Networks\u00a0<\/strong><\/p>\n

Dr. Siddhartha Bhattacharyya<\/strong> earned his Bachelor in Physics, Bachelor in Optics and Optoelectronics, and Master in Optics and Optoelectronics from the University of Calcutta, India, in 1995, 1998, and 2000, respectively. He completed his PhD in Computer Science and Engineering from Jadavpur University, India, in 2008. He is the recipient of the University Gold Medal from the University of Calcutta for his Masters. He is the recipient of several coveted awards, including the Distinguished HoD Award and Distinguished Professor Award conferred by the Computer Society of India, Mumbai Chapter, India, in 2017, the Honorary Doctorate Award (D. Litt.) from The University of South America, and the South East Asian Regional Computing Confederation (SEARCC) International Digital Award ICT Educator of the Year in 2017. He has been appointed as the ACM Distinguished Speaker for 2018-2020. He was inducted into the People of ACM Hall of Fame by ACM, the USA, in 2020. He has been appointed as the IEEE Computer Society Distinguished Visitor for 2021-2024. He has been elected as a full foreign member of the Russian Academy of Natural Sciences (RANS) and the\u00a0 Russian Academy of Engineering (REA). He has been elected a full fellow of The Royal Society for Arts, Manufacturers and Commerce (RSA), London, UK.<\/p>\n<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\nTitle: The Power and Perils of Generative AI: A Realistic Perspective<\/strong><\/p>\n

Dr. San Murugesan<\/strong> is the Director of BRITE Professional Services in Sydney, Australia. and Editor in Chief of IEEE Intelligent Systems. He is also an adjunct professor at the School of Computing at Western Sydney University and an honorary professor at Amity University. Murugesan has an extensive background in academia and industry, having previously worked as a Senior Research Fellow at NASA Ames Research Center and held senior positions at Southern Cross University and the Indian Space Research Organization (ISRO). Murugesan’s expertise covers a broad spectrum of areas in information technology, including smart systems, sustainability, artificial intelligence, autonomous systems, green computing, cloud computing, and the Internet of Things (IoT). He has authored and co-edited several books, including “Encyclopedia of Cloud Computing” and “Harnessing Green IT: Principles and Practices.” Murugesan is a distinguished speaker of the ACM and IEEE and has been recognized with numerous awards, such as the IEEE Computer Society’s Distinguished Service Certificate, for his significant contributions to the field. He is a Life Senior Member of IEEE and Golden Core Member of the IEEE Computer Society. In addition to his academic and research contributions, Murugesan has been actively involved in organizing conferences, delivering keynotes, and providing consultancy services. He holds a PhD from the Indian Institute of Science, an MTech from the Indian Institute of Technology Madras, and a BE (Honours) from PSG College of Technology.<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\nTitle: Revolutionizing Aerospace Supply Chains with Machine Learning-Powered Digital Twins<\/strong><\/p>\n

Mr. Amit Dubey<\/strong> is a seasoned technology leader with over two decades of experience in the software, data science industry. As the Chief Technology Officer at Dataflux.ai and Data science manager at Agilent technologies, he has demonstrated expertise in digital transformation, cloud computing, and emerging data science technologies. Amit’s career spans roles at prestigious organizations like Agilent Technologies, Boeing, Fiserv, Accenture, Egon Zehnder, Airbus GMBH, where he honed his skills in data Science, solution architecture and technology consulting. Beyond his technical prowess, Amit is passionate about mentoring and developing talent, actively participating in various technology communities. He is a frequent speaker at industry events and has contributed to publications on digital innovation. In his spare time, Amit enjoys outdoor activities and is an avid photographer. His unique blend of technical depth, leadership experience, and diverse interests makes him well-suited to engage with the IEEE workshop audience, offering insights that bridge the gap between cutting-edge technology and practical business applications.<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\nTitle: Enabling Performance-Efficient GenAI at the Edge Through Quantization<\/strong><\/p>\n

Mr. Dwith Chenna<\/strong> is working as Member of Technical Staff, Product Development, AI Inference at AMD. He is a highly experienced research and development professional with a focus on algorithm development and optimization in computer vision, deep learning, and Edge AI. Over the past decade, he has honed his expertise in creating state-of-the-art, performance-critical perception systems, particularly on resource-constrained hardware like Digital Signal Processors (DSPs). His work is centered on optimizing deep learning models to enhance efficiency and accuracy, while also addressing key performance metrics such as latency, memory usage, bandwidth, and power consumption. Dwith\u2019s career includes significant roles at prestigious organizations such as Magic Leap, the FDA\u2019s Center of Devices and Radiology Health, and AMD. His contributions, including advancements in augmented reality and non-contact fever screening, have been instrumental in solving complex real-world challenges. Beyond his technical prowess, Dwith is a recognized leader in the technology community, serving as a technical committee member, reviewer for leading conferences, judge for AI excellence awards, and a speaker at major technology summits.<\/td>\n<\/tr>\n

\"\"<\/a><\/td>\nTitle: Accelerating Code Contribution with CodeBaseBuddy’s Intelligent Semantic Search System<\/strong><\/p>\n

Mr. Raghavan Muthuregunathan<\/strong> is a senior engineering manager, leading the Linkedin Search AI team. Earlier, he worked at Microsoft Bing. He is also a volunteer and contributor to Open Source initiatives by Linux Foundation’s LF AI + Data , specifically to GenAICommons.org and Apache Solr. He is also an active hackathon participant on lablab.ai and have won multiple hackathons on the lablab.ai platform.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 <\/p>\n

Panel Discussion<\/strong><\/span><\/p>\n

Topic: Artificial Intelligence and Social Media\u00a0<\/strong><\/p>\n

The convergence of artificial intelligence (AI) and social media has revolutionized the way businesses engage with their audience. By leveraging AI, companies can perform advanced audience analysis and optimize their content to maximize engagement. However, the same technology has also accelerated the spread of misinformation, highlighting the need for a balanced approach that weighs both the benefits and ethical risks.The panel will address critical questions around the benefits and impact of AI integration, the challenges of implementation, the opportunities for innovative applications, and the future trends shaping this rapidly evolving field. By bringing together experts from academia and industry, this discussion aims to shed light on strategic decision-making and policy development, offering valuable insights into the far-reaching implications of AI and social media convergence.<\/span><\/p>\n\n\n\n\n
\"\"<\/a><\/td>\n\"\"<\/a><\/td>\n\"\"<\/a><\/td>\n\"\"<\/a><\/td>\n\"\"<\/a><\/td>\n<\/tr>\n
Prof. Anupam Mukherjee<\/strong><\/td>\nVipul Bharat Marlecha<\/strong><\/td>\nAqsa Fulara<\/strong><\/td>\nMeenal Nalwaya<\/strong><\/td>\n\u00a0Sreyashi Das (Moderator)<\/strong><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

Previous Events<\/strong><\/span><\/p>\n

First International Conference on Applied Data Science (ICADS’22<\/a>)<\/p>\n

Second International Conference on Applied Data Science (ICADS’23<\/a>)<\/p>\n

Contact Us<\/strong><\/span><\/p>\n

If you have any questions, please reach out to us at: link<\/a><\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

— GenAI, keynotes, panels, workshops …<\/p>\n","protected":false},"author":78,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[34],"tags":[],"class_list":["post-2374","post","type-post","status-publish","format-standard","hentry","category-conferences"],"_links":{"self":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts\/2374","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/users\/78"}],"replies":[{"embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/comments?post=2374"}],"version-history":[{"count":0,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts\/2374\/revisions"}],"wp:attachment":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/media?parent=2374"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/categories?post=2374"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/tags?post=2374"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}},{"id":2353,"date":"2024-05-30T15:33:57","date_gmt":"2024-05-30T22:33:57","guid":{"rendered":"https:\/\/r6.ieee.org\/scv-cs\/?p=2353"},"modified":"2024-06-11T08:15:30","modified_gmt":"2024-06-11T15:15:30","slug":"blockchain-innovations-ai-integration-security-trust","status":"publish","type":"post","link":"https:\/\/r6.ieee.org\/scv-cs\/blockchain-innovations-ai-integration-security-trust\/","title":{"rendered":"Blockchain Innovations: AI Integration and Security Trust"},"content":{"rendered":"

Two Presentations:<\/em> “Blockchain and AI for Industrial Applications”<\/strong> at 4 PM and “Facilitating Security and Trust among Multiple Parties through Blockchain Techniques”<\/strong> at 5 PM
\nOrganized by the Blockchain Chapter<\/em><\/p>\n

Speakers: Prof. Daswin De Silva, Centre for Data Analytics and Cognition, LaTrobe University, Australia; and Prof. Yuhong Liu, Santa Clara University
\n <\/a>
\nMeeting Date: Tuesday, June 11, 2024
\nTime: 6:00 PM – 8:00 PM (PDT); Checkin via WebEx for presentation at 6:00 PM (PDT)
\nLocation: ActionSpot, 453 W San Carlos St, San Jose in person (or on the Web at 6:30 PM)
\nCost: none
\nReservations: events.vtools.ieee.org\/m\/422199 <\/a>
\nTalk at 4:00 PM by Prof. deSilva: Blockchain and AI for Industrial Applications
\nSummary:<\/strong> The fusion of Blockchain and Artificial Intelligence (AI) heralds a new era of industrial innovation with opportunities for transparency, efficiency, and autonomy. Blockchain is a decentralized digital ledger that can be significantly augmented using conventional and generative AI capabilities This lecture will delve into the synergistic potential of Blockchain and AI, aiming to equip participants with the knowledge and tools to leverage these technologies, their individual capabilities, and how their integration can create robust solutions for industrial challenges. Participants will learn to design, implement, and manage Blockchain-AI integrated systems for energy and manufacturing applications. For instance, grid management and energy trading where Blockchain enables secure, transparent transactions for energy trading, allowing for decentralized energy markets with AI being leveraged to predict energy demand and supply, optimizing grid operations and enabling dynamic pricing models based on real-time data. Also, \u00a0automated compliance and quality control where smart contracts can automatically enforce agreements based on predefined rules and conditions. The workshop will conclude with best practices for the design and development of AI Blockchain applications for industrial innovation.
\n Bio: Daswin De Silva <\/strong> is a Full-time Professor and Deputy Director of the Centre for Data Analytics and Cognition (CDAC) at La Trobe University, Australia. He specializes in AI, Data Analytics, Automation, and the Ethics of AI. Professor De Silva has received numerous awards for teaching excellence and has published over 100 research articles. He also holds several key positions within IEEE, contributing significantly to the fields of AI and blockchain.<\/p>\n

Talk at 5:00 PM by Prof. Liu: Facilitating Security and Trust among Multiple Parties through Blockchain Techniques
\nSummary:<\/strong> With the increasing computation and communication capabilities at the edge of the network, how to enable trustworthy interactions among multiple parties in decentralized systems becomes an essential issue. Blockchain has been widely adopted as an approach to facilitate decentralized trustworthy computing with non-repudiated information records. Multi-signature, on the other hand, enables multiple parties to approve each transaction in a secure and efficient way. This talk will discuss our latest studies on the adoption of multi-signature schemes in blockchain, including a secure and efficient multi-signature scheme to facilitate multi-party approval process on Hyperledger Fabric, an enterprise blockchain platform; and a group-oriented multi- signature supporting monotonic endorse policies in Hyperledger Fabric.
\nBio: Yuhong Liu <\/strong> is currently an Associate Professor at Department of Computer Science and Engineering, Santa Clara University. Her research interests include trustworthy computing and cyber security of emerging applications, such as online social media, Internet-of-things and Blockchain. She is currently serving as an IEEE Computer Society Distinguish Visitor (2022-2023) and an APSIPA Distinguished Lecturer (2021-2022). She is serving as an Associate Editor on IEEE Transactions of Service Computing, Associate Editor for the Multimedia Applications and Tools Journal, a Youth EBM Editor of the Blockchain: Research and Applications Journal, and an Associate Editor of the APSIPA Transactions on Signal and Information Processing.<\/p>\n","protected":false},"excerpt":{"rendered":"

— blockchain, artificial intelligence, AI, security, decentralization, trust, smart contracts, bitcoin …<\/p>\n","protected":false},"author":78,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[69,2,31],"tags":[],"class_list":["post-2353","post","type-post","status-publish","format-standard","hentry","category-2024-events","category-upcoming-events","category-webinar"],"_links":{"self":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts\/2353","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/users\/78"}],"replies":[{"embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/comments?post=2353"}],"version-history":[{"count":0,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/posts\/2353\/revisions"}],"wp:attachment":[{"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/media?parent=2353"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/categories?post=2353"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/r6.ieee.org\/scv-cs\/wp-json\/wp\/v2\/tags?post=2353"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}]