Mennatullah Siam

Our perspective on the potential of #liquidcrystals in #microrobotics can be found through a short story and snippet told by great researchers of my team Negar, Matthew, Cole, Ramon, and Azin University of Waterloo Faculty of Engineering https://lnkd.in/gteWyJEV

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Here, Remon Polus is presenting another paper (this time on cascaded ground-to-UAV-to-ground channels) at the IEEE WF on IoT in Ottawa.

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IEEE University of Toronto Student Branch is co-hosting Tiny Circuit Hacks - Fun Talk with Professor Dietz series with Prof. Paul Dietz, Distinguished Engineer in Residence and Director of Fabrication. Our third talk is on this Thursday, Oct. 10th, 6-7pm at BA2145. If you want to discover Prof. Dietz's exclusive fun tricks for circuits you should totally join! 😊 We will have snacks and drinks 😋 🗣️ Topic of this talk: Too Many LEDs!   💡 Abstract  It’s easy to connect LEDs to a microcontroller and make then blink. But what do you do when the number of LEDs you want to control is larger than the number of IO pins available? In this very practical edition of Tiny Circuit Hacks, we look at tricks that will let you easily connect lots of LEDs using a much smaller number of pins. 🤠 Event details: Date: Oct. 10th, Thursday Time: 6-7pm Location: BA2145 Sign up link: https://lnkd.in/g-tR4hXe

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Excited to present my work next week at the #MS2Discovery Interdisciplinary Research Institute at Wilfrid Laurier University in Waterloo. The seminar will focus on my papers: 'Finding a Needle in a Haystack: A Machine Learning Framework for Anomaly Detection in Payment Systems' (https://lnkd.in/e7ch4zeW) and 'Improving the Efficiency of Payments Systems Using Quantum Computing' (https://lnkd.in/d8e8zAu2). #Payments #AI #ML #Quantum #PaymentSystems

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[Deadline July 20, 2024 IoT World Forum Special Session, 10-13 Nov 2024, Ottawa, ON, Canada] Dear colleagues, We invite you to submit your work to the IoT World Forum Special Session (SS) on Energy Efficient Computing for IoT (SEEC-IoT) https://lnkd.in/dwmXytKQ Energy efficiency stands out as a primary focus for sustainable and eco-friendly IoT networks. As data traffic and network congestion continue to escalate, IoT devices equipped with restricted computational power and energy resources face obstacles in analyzing, processing, and storing data. In response to these challenges, computing technology has surfaced as a valuable solution for preserving energy in IoT devices, offering robust computing capabilities, and streamlined storage to facilitate data collection and processing. Consequently, energy-efficient (EE) computing, also known as "green computing," has emerged as a central area of interest for researchers looking to implement IoT solutions. The proposed SEEC-IoT special session aims to bring together researchers from academia and industry to explore and present their findings in Energy- Efficient Computing Solutions for IoT. Participants are encouraged to discuss the theories, systems, technologies, and approaches used to apply those findings in real-world applications. We look forward to receiving your contributions https://lnkd.in/d8-uq4Mp Special Session Co-Chairs: Zied Bouida Kuwait College of Science and Technology Mohamed Trabelsi Kuwait College of Science and Technology Ala Abu Alkheir Lytica Inc. Anis Ben Arfi Analog Devices

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[Call for Papers] The 3rd International Workshop on Responsible AI Engineering (RAIE 2025) - co-located with ICSE 2025 in Ottawa, Canada. Submission deadline: 11/Nov 2024 Workshop website link: https://lnkd.in/g_xcFwzk The rapid advancements in AI, particularly the release of large language models (LLMs) and their applications, have attracted significant global interest and raised substantial concerns on responsible AI and AI safety. While LLMs are impressive examples of AI models, it is the compound AI systems, which integrate these models with other key components for function and quality/risk control, that are ultimately deployed and have real-world impact. These AI systems, especially autonomous LLM agents and those involving multi-agent interacting, require careful system-level engineering to ensure responsible AI and AI safety. Topics of interests in this workshop include, but are not limited to: - Requirement engineering for responsible AI and AI safety - Responsible-AI-by-design and AI-safety-by-design software architecture - Verification and validation for responsible AI and AI safety - DevOps, MLOps, LLMOps, AgentOps for ensuring responsible AI and AI safety - Development processes for responsible and safe AI systems - Responsible AI and AI safety evaluation tools and techniques - Reproducibility and traceability of AI systems - Trust and trustworthiness of AI systems - Responsible AI and AI safety governance - Diversity and Inclusion in the Responsible AI ecosystem; humans, data, processes/algorithms, systems, governance - Operationalization of laws (e.g., EU AI Act) and standards - Human aspect of responsible AI and AI safety engineering - Responsible AI and AI safety engineering for next-generation foundation model-based AI systems (e.g., LLM-based agents) - Case studies from certain high-priority domains (e.g., financial services, scientific discovery, health, environment, energy) Foutse Khomh Apostol Vassilev Maximilian Poretschkin Muneera Bano #responsibleai #aisafety #aiengineering #softwareengineering

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🎉 Thrilled to share some great news stemming from an amazing example of collaboration between UK and Greece supported by ARCHIMEDES Research on AI, Data Science, and Algorithms which will soon reach new highs thans to our partnership via the CHAI Hub. Our paper, "Benchmarking Counterfactual Image Generation," has been accepted to NeurIPS 2024 in the Datasets & Benchmarks track! We’ll present it in Vancouver on December 11th, and I couldn’t be prouder of our incredible Greek dream team of students who led this effort— Thomas Melistas Nikos Spyrou and Nefeli Gkouti. We address a critical challenge: how do we rigorously evaluate counterfactual image generation, where causal constraints must be respected, and ground truths are elusive? Our team developed a benchmarking framework that highlights the strengths of Hierarchical VAEs across diverse datasets. We’ve even made it available as a user-friendly Python package to encourage community collaboration. 🚀 Interactive demo: https://lnkd.in/e9GA5Ebu 📄 Paper: https://lnkd.in/eR2ig3pY A huge thanks to co-authors: Pedro P. Sanchez, Yannis Panagakis, Giorgos Papanastasiou, PhD, and Dr Athanasios Vlontzos. Excited to share our work with the AI community at NeurIPS. Do go and see the work and talk to this wonderful team of students. #NeurIPS2024 #GenerativeAI #Counterfactuals #CausalInference #MachineLearning #AIResearch

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#QOTD: “Science will continue answering questions while sparking new ones in the process,” said A*STAR scholar Karthik Panicker 🔍 A recipient of the National Science Scholarship in 2023, Panicker is currently pursuing his PhD in Quantum Computing at the University of Toronto 🇨🇦, where he is designing quantum circuits to simulate the complexities of chemical reactions. In this interview with A*STAR Research, Panicker talks at length about his journey into quantum computing—citing the influence of mentors like Victor Leong, who introduced him to quantum optics during his research assistantship at the Institute of Materials Research and Engineering (IMRE). “[That] was my first hands-on research experience in quantum physics, and I got to explore and discuss new ideas in and around the subfield,” he recalled. “These insightful discussions helped me discover my true interest in quantum computing for chemistry, bringing my research full circle.” Full interview linked below ⬇️ --- #scicomm #science #technology #STEM #research #innovation #ASTAR #quantumcomputing #chemistry #physics #scholar #Singapore

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Honestly, nothing to add to this marvelous post, READ IT & consider SUBMITTING YOUR WORKS at our NeurIPS workshop! Many thanks to Cambridge University Press & Assessment and the Environmental Data Science journal for acknowledging our efforts at the Climate Change AI.

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Excited to share our latest work on "Robust Vehicle Localization and Tracking in Rain using Street Maps" to be presented at IEEE ITSC in Canada. Kudos to my PhD student Yu Xiang Tan for his hard work and dedication! In this work, we address the challenging task of vehicle localization and tracking in rain, a common scenario in Singapore. We leverage the road contextual information to correct drifting IMU and visual odometry estimates. We validated our results based on real-world trials on campus roads of Singapore University of Technology and Design (SUTD) and datasets from three geographically diverse cities: Oxford, Munich and Singapore. We have also open-sourced our code! Check out more details at the links below! Pre-print: https://lnkd.in/gJ8wDQnh Video: https://lnkd.in/gAeCySdU Github: https://lnkd.in/grmPTMqd #robotics #AI #EAI #autonomousdriving #sutd #research

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Congratulations to researchers from Max Planck Institute of Microstructure Physics, Max Planck – University of Toronto Centre for Neural Science and Technology, University of Toronto and Technische Universität Dresden for their recent publication!   The research group, led by Prof. Joyce Poon, exploited REGENHU’s melt electrowriting technology to fabricate titanium carbide-coated PCL scaffolds acting as bioactive interfaces to guide the growth of 3D neural circuits.   The fabricated structures were proven to have excellent biocompatibility and to enable optocapacitive neural stimulation, with spatially precise control over the photoinduced neural activity. As stated by the authors, the presented approach opens novel pathways for functional neural tissue engineering and the precise control and modulation of neural circuits in vitro and in vivo. Interested in more details? Reference article: https://lnkd.in/drAV3hsd   REGENHU bioprinting solutions: www.regenhu.com   #3DBioprinting #Bioprinting #MeltElectrowriting #BioInterfaces #NeuralCircuits #NeuralTissueEngineering #NeuronalStimulation #OpticalStimulation #Optocapacitance #TitaniumCarbide

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I’m happy to share our work on autonomous driving systems (ADS) testing, which we presented at the main research track of the 17th IEEE International Conference on Software Testing, Verification and Validation (ICST) in Toronto last week! 👉 Our work is titled “Assessing Quality Metrics for Neural Reality Gap Input Mitigation in Autonomous Driving Testing”. 🚗 Did you know that simulation-based testing is the go-to method for testing ADS? It’s safe, controlled, and cost-effective. But here’s the catch: simulations often don’t perfectly match real-world conditions, leading to ADS behavioural differences between testing in simulation and the real world. This is known as the sim2real gap. 🖼 To tackle this gap, we can use Image-to-Image (I2I) neural translation to make simulated environments look more realistic. In our study, we explore how well two popular I2I techniques, pix2pix and CycleGAN, close this gap for vehicle detection and lane-keeping tasks. 📊 We use a set of 13 well-established metrics from the literature to evaluate the quality of the generated images. However, are we sure that an image that appears more realistic makes the ADS behave as it would with real data? Therefore, we examine how the ADS’s behaviour changes when using the generated images. Our approach involves analyzing the correlation between the ADS behaviour and the perceived image quality of the generated images compared to real-world data. 🔍 Our findings: The success of these techniques can vary depending on the task. We also discovered that current evaluation metrics sometimes miss the mark. We found a stronger correlation with ADS behaviour by fine-tuning these metrics to be task-specific, leading to better ways to pick the right I2I technique for reliable testing. 📄 Interested? Here is the pre-print: https://lnkd.in/dtDbMyCx 💬 Want to learn more about what we do at the Automated Software Testing group (fortiss) and the Chair of Software Engineering for Data-intensive Applications (Technical University of Munich)? Feel free to contact me to know more or have a chat on #sim2real #realitygap mitigation! #generativeai #SoftwareEngeneering #Research #icst2024

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🚀 Diving into the World of AArch64 and x86_64 Assembly: More Adventures! 💻 I'm back with another post from my Software Portability and Optimization course (SPO600) at Seneca Polytechnic! In this post, I explore: - Complex loop implementations on AArch64(ARM) and x86_64(AMD) platforms - Number display and formatting challenges (sounds easy in C++ or Python, right? Assembly says hi! 😅) - Register handling and syscalls - Debugging with GDB (our saviour when Assembly decides to be Assembly 🔍) From printing simple messages to handling two-digit numbers - simple and easy, right? That's not exactly the case, but you'll need to check the post to find out why... So, if you are curious about assembly language or interested in the details, be sure to check out my full post here: https://wp.me/pg1A64-1z #AssemblyProgramming #AArch64 #x86_64 #LowLevelProgramming

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In this newly published paper, our team once again centred on human comfort and energy efficiency to identify the human centric problem and gather human-built environment interaction data for proving an innovative HVAC control mechanism. #humanbuiltenvironmentinteraction #Energyandbuildings

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🚨 Can AI System Quantify Misinformation in Real-Time? Groundbreaking Research Says Yes! 🚨 📊 Researchers at the University of Waterloo have developed a revolutionary system called U-MAS (UbiLab Misinformation Analysis System) to detect, analyze, and quantify health misinformation on social media as it happens. 🔑 Key features of U-MAS: • 🤖 Uses AI and machine learning to analyze Twitter data • 🧠 Performs topic modeling, sentiment analysis, and misinformation classification • 📈 Provides interactive dashboards with real-time misinformation percentages • ⏳ Enables monitoring of misinformation trends and volumes over time 🧪 The system was tested on fluoride-related misinformation, accurately quantifying the percentage of false information in the dataset. It's now being adapted for vaccine hesitancy and heat illness topics. 💡 U-MAS empowers public health officials and researchers to: • Measure the exact prevalence of misinformation on specific health topics • Identify emerging misinformation trends as a percentage of overall conversation • Develop data-driven, targeted interventions based on quantifiable metrics 🌟 This groundbreaking work puts a number on the spread of health misinformation online, potentially revolutionizing how we combat fake news. Read the full paper here: [Link to paper] #HealthMisinformation #AI #PublicHealth #DataAnalytics​​​​​​​​​​​​​​​​ #HealthMisinformation #AI #PublicHealth #DataAnalytics

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Building quantum hardware/software is not an easy task. The more collaboration we have, I believe the closer we get to achieving tangible results! Check out how at Open Quantum Design we are trying to build the world’s first open-source, full stack quantum computer to encourage more collaboration!

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Inventor of method that can "autonomously find properties in data and carry out tasks such as identifying specific elements in pictures", Geoffrey Hinton from the University of Toronto, together with colleague John Hopfield of Princeton University, were honoured with the 2024 Nobel Prize in Physics for discoveries and inventions that enable machine learning within artificial neural networks. Here is the official announcement: "This year’s laureates used tools from physics to construct methods that helped lay the foundation for today’s powerful machine learning. John Hopfield created a structure that can store and reconstruct information. Geoffrey Hinton invented a method that can independently discover properties in data and which has become important for the large artificial neural networks now in use." (https://lnkd.in/gq8THmzf) #nobelprize #physics #neuralnetworks #ai #data #images #machinelearning https://lnkd.in/g9k5a6tQ

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Join Jelle Hellings and me for Ontario Database Day (https://ondbd.ca/) – a one-day symposium on all things databases, hosted at the University of Waterloo! This event brings together researchers and practitioners to explore the latest advancements in the database field. It's a great platform to showcase your work—whether it’s published or still in progress. We welcome submissions from students, postdocs, academics, and professionals in industry. Present your work, exchange ideas, and network with fellow database enthusiasts. Don’t miss the opportunity—submit your abstract by October 13th! #OntarioDatabaseDay #DatabaseResearch #DataScience #DataPrivacy #DatabaseSymposium #DatabaseCommunity #DataManagement

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We have figured out a lot using mathematics, physics and chemistry to understand nature. We know how to predict electron flow in semiconductors, fluids in tubes, clouds in the sky, airflow over wings, space storms etc. Tools like computational fluid dynamics have remarkable applications in unexpected places. We also have ideas around PINN and we can use those insights to help us understand what happens in a foundational model. And I am sure there are lots more. None of these software artifacts should ever be said to be un-knowable or a "blackbox". That's intellectual laziness. These are all man made structures. We've figured out many parts of nature using math, physics and chemistry - we've mapped the Human Genome, so what's the excuse in not understanding foundational models? I look forward to people recognizing that there are existing human inventions (math, physics etc) whose insights can be used to remove/reduce the probabilistic nature of foundational models and thereby benefiting humanity as a whole. A press conference was held by University of Toronto with Geoffrey Hinton after the announcement that he was one of the two recipients of this year's Nobel Prize for Physics. Geoffrey is probably the only Turing Award winner to also have won a Nobel Prize. And the video - https://lnkd.in/gVHewNCd. Geoffrey is spot on where he says, at about 3:38: "I'm particularly proud of the fact that one of my students fired Sam Altman." Brilliant! #nobelprize #ai #opensource #turingaward

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