Cognitive Space’s Post

📢 Shoutout to all #postdocs and recent #phds I would like to support postdoctoral applications for Marie Skłodowska-Curie Actions (#MSCA) at TU Chemnitz at our chair of #ScientificComputing 🎓 I would welcome applications in the area of numerical linear algebra for data science, complex networks or large scale (PDE-constrained) optimization or related topics. If interested, contact me as soon as possible to discuss options https://lnkd.in/eX8uuEw4 #NumericalLinearAlgebra #DataScience #ComputationalScience

Pragmatic solutions are built on allowing the curious to be curious. It is allowing for the space to make discoveries that we do not yet know how to profit from. It is in studying fireflies which lead to a better understanding of pulse-coupled oscillators which lead to advances in computing. Throughout my career I have been a pragmatist, but I sometimes have forgotten that I got here by exploration. Build stuff that matters, but remain curious. We know less than we think.

On New Year's Eve, I am delighted to announce the publication of my research paper on "Rough Set Theory Applied to Finite Dimensional Vector Spaces" in Information Sciences. Vector spaces, crucial in the representation of data entities, play a pivotal role in organizing and understanding complex information. The vector space associated with data is commonly referred to as the feature space. In data analysis, granular computing in the feature space takes center stage. Rough set theory emerges as a powerful tool, providing a framework for granulation on data and offering tools for the reduction of data dimensionality. The synergy between vector spaces, granular computing, and rough set theory opens up new avenues for impactful applications in the field of data science and machine learning. From enhancing data representation to efficient dimensionality reduction, this research contributes significantly to advancing the methodology of the field. I extend my heartfelt gratitude to my co-author Imran Javaid, who also happens to be my supervisor, for his invaluable guidance throughout this research journey. His expertise and support have been instrumental in shaping the depth and direction of our work. #research #informationsciences #vectorspaces #datascience #roughsettheory #granularcomputing #dimensionalityreduction #featurespace #datarepresentation #machinelearning

👇 👇Very much looking forward to collaborating with Takahiro Yabe and Alex 'Sandy' Pentland on our #NSF project "Fostering Collective Disaster Resilience via Cross-city Learning of Post-disaster Mobility Dynamics and Collaborative Data Governance"! ➡️ Focused on leveraging language models and new computational methods to address existing data gaps in crisis zones to improve forecasting toward enhancing disaster preparedness and response strategies. ➡️ Will contribute to the need for innovation beyond traditional data sources to enhance disaster resilience and climate change adaptation. ➡️ In association with this project we will also look to develop a data governance mechanism - a data commons platform - that offers inclusive access to and transparent re-usage of synthetic human behavior data under various disaster scenarios. 💻More details at NSF website: https://lnkd.in/enYeTYvA 🤔 Want to learn more 👉 Takahiro Yabe at NYU Center for Urban Science + Progress #data #syntheticdata #humanitarian #disaster #climate

"🔍 Day 5 of my array sorting odyssey! 🌟 Hello, LinkedIn community! Today marks another exciting chapter in my exploration of array sorting algorithms. With each passing day, I delve deeper into the intricate methods and efficiencies of sorting arrays. In this ongoing series, I'm dedicated to unraveling the beauty and significance of array sorting, refining my problem-solving skills, and fostering a deeper appreciation for the elegance of algorithms. As I embark on Day 5 of this journey, I'm thrilled to tackle new challenges and deepen my understanding of sorting techniques. With each algorithm mastered, I am reminded of the immense power and efficiency inherent in the world of computer science. Join me as I continue this quest to unravel the mysteries of array sorting, one step at a time. Together, we'll embark on a journey of exploration and discovery that promises to sharpen our programming prowess and ignite our passion for problem-solving. Stay tuned for more updates and insights as we venture further into the realm of array sorting! 💻✨ #ArraySortingOdyssey #ComputerScience #Exploration"

Please register from one of the followings: https://lnkd.in/e8RnBcgu or https://lnkd.in/eGVtYies or https://lnkd.in/eWDZ7zsn Speaker: Ed Younis of Berkeley Lab Moderators: Paweł Gora Sebastian Zając QPoland OrionX.net Cambridge Quantum Quantum AI Foundation QB Net Inc. Quantum Computing and Data Science #quantumcomputing #physics #research #softwaredevelopment #pythonprogramming #algorithms

Excited to announce that I have successfully completed the "Introduction to Quantum Computing" course by Qubit by Qubit, along with a capstone project! This comprehensive two-semester program (September 2023-April 2024) provided me with an in-depth understanding of quantum computing, covering a wide array of topics including: 🔸 Foundational Quantum Mechanics: Delving into qubits, superposition, and entanglement   🔸Mathematics for Quantum Computing: Essential mathematical concepts for quantum computation   🔸 Quantum Coding: Hands-on experience with Cirq, Stim, and Qualtran, open-source programming languages developed by the Google Quantum AI team   🔸 Quantum Algorithms and Protocols: Implementing quantum key distribution (QKD), Grover's algorithm, and running a Variational Quantum Eigensolver (VQE) to simulate molecules   🔸 Applications of Quantum Computing: Exploring real-world applications in Quantum Finance, Quantum Chemistry, and beyond  For my capstone project, I developed an encryption and decryption system in Python using quantum algorithms, specifically implementing Quantum Key Distribution (QKD). This project allowed me to apply the theoretical knowledge and practical skills gained throughout the course. I'm grateful for the opportunity to learn from such an innovative program and excited to apply these skills in the field of quantum computing. Thank you to the Qubit by Qubit,The Coding School team and all my fellow classmates for an incredible journey. Here’s to the future of quantum technology! 🌌🔭 #QuantumComputing #QuantumMechanics #Cirq #QuantumAI #QuantumAlgorithms #QuantumFinance #QuantumChemistry #QubitbyQubit

Yesterday was full of big news and I needed some rest at the end of the day. Now, I can share. First, the long-awaited piece of news, I have defended my thesis after submitting it months ago and after having spent already a year in my new post-doc position. Better late than never! It was an enjoyable and smooth experience and ended up with minor typos to fix, very happy! Second, the first of a series of quantum topological data analysis works came out yesterday on the arXiv! This is a piece of work done with Chukwudubem and Oleksandr. In the paper, we approach the problem of #QTDA from an unusual point of view that is, shifting some of the problem complexity towards circuit optimization, readout, and post-processing. The result is a solid protocol that we run on real IBM hardware, but "the protocol does not know" and showed impressive noise resilience! Check it out here: https://lnkd.in/dXggszZk Lastly, a few acknowledgments. These last four years have been very intense for so many reasons, the pandemic, meeting with my dad after ten years, moving four houses, having our little smily (and chatty) daughter, and starting a post-doc while finishing the PhD. In this period, 9 papers came out of which 5 first author. I could NOT have done this without the help from the people around me. First, no doubt, Samantha, there are no words to describe how lucky I am to share every day with you. The strength that you gave me during this time, at any time, has halved my effort. Then, my supervisors Janet and Simon, always supportive allowing me to express and work on my ideas while being academic and life role models. Then, all my colleagues who made this journey extremely cheerful and have repeatedly given some help when I would get stuck (I am referring to you Federico :)), Charlie, Annie, Joe, Jonas, Kok Wee, Jesús, Salvatore, Marco, Sonal, Luis, Luca, Rick, Kishan, Marie, William, Matt...I apologize for inevitably missing some of you, I believe you all know I am grateful for your help. Pics: the first picture is the QTDA schematic of the protocol, while the middle row is the moment I accidentally left my mark on the ceiling of the 6th floor of the physics building. I repeat, University of Exeter, accidentally. The last are some of these special people. Merry Christmas if I do not see you around! 🎄

Data science has become a powerful — and profitable — tool for understanding the world and making decisions. #CSSW Prof. Courtney Cogburn joined Chris Wiggins, a professor at the Applied Physics & Applied Mathematics Department of Columbia University (and New York Times chief data scientist), for a conversation about the promise and peril of this new reality. Check out this feature video in the latest issue of Columbia Engineering Magazine: columbiaeng.com/data

#GeospatialRevolution #Day2 #learningjourney #learningtogether 🌎🔍 Have you ever wondered how high-resolution mapping of global surface water is done? 📊 I recently came across a fascinating paper that shed light on this! 🛰️ This paper utilized a whopping 3 million Landsat imageries to quantify changes in global surface water over the past 32 years, making it an incredible dataset. 💡 Curiosity piqued, I delved deeper into the resources they used for processing and analysis, and here's what I found: 1️⃣ They harnessed the power of Google's Earth Engine, a computational structure optimized for parallel processing of geospatial data, coupled with a dedicated application programming interface. 2️⃣ Just imagine, running the expert system on a single computer CPU would have taken a staggering 1,212 years! 😲 3️⃣ However, they employed a network of 10,000 computers in Earth Engine, and the processing was completed in around 45 days. Impressive, right? 🚀 📖 If you're as intrigued as I am and want to dive into the details, you can access the full paper here [https://lnkd.in/gMC5GBVh]. Let's keep exploring the incredible world of geospatial data together! 💫 #GeospatialData #EarthScience #Innovation #geospatialtechnology #revolutionarytechnology #cuttingedgesolutions