Get all the information you need about the M.Tech. (Computational and Data Science) course structure, duration, core courses, soft core courses, dissertation, and electives.

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Universal two-qubit computational register for trapped ion quantum processors, including state preparation, gates, and benchmarking. The experimental setup and results are discussed.

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The basic structure of MPICH and its features in Computational Physics Lecture 18. Understand how MPI functions are used and linked with a static library provided by the software package. Explore how P4 offers functionality and supports parallel computer systems. Discover the concept of clusters in

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This lecture explores the connection between computational complexity and cryptography, focusing on topics like pseudorandom functions, public-key cryptography, and learning from Gaussians. It delves into the implications of cryptographic reductions, lower bounds for learning MLPs, and the existence

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Dive into the world of signed integers, extensions, truncations, and addition in computer science with a focus on how negative values are represented and operated on. Explore concepts like sign-magnitude and two's complement representations, uncovering the intricacies of handling integers in computa

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OBPMark and OBPMark-ML are computational benchmarks developed by ESA and BSC/UPC for on-board data processing and machine learning in space applications. These benchmarks aim to standardize performance comparison across different processing devices, identify key parameters, and provide recommendatio

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Computational thinking is a critical skill for the digital age, involving problem-solving techniques that enable computers to process information effectively. It precedes programming and requires breaking down complex problems into manageable steps. Educators emphasize computational thinking exercis

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Voronoi diagrams, a key concept in computational geometry, involve partitioning a space based on points sites. They have diverse applications like nearest neighbor queries and facility location. The diagrams consist of Voronoi cells, edges, and vertices, forming a connected graph. Properties include

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This Master's program offers a comprehensive curriculum focusing on Artificial Intelligence, Computational Drug Discovery, and Development. With a blend of cutting-edge technologies and practical applications, students delve into techniques, AI/ML, big data mining, modeling, and more. Through intens

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Explore the fascinating fields of Computational Linguistics and Natural Language Processing (NLP), delving into their development, applications, and significance. Learn about the study of human languages in computational models, the importance of corpora in linguistic research, and the various types

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Pattern recognition is a vital skill in computational thinking, enabling the identification of similarities and differences between concepts and objects. By recognizing patterns, individuals can efficiently solve complex problems, create shortcuts, and avoid duplications in problem-solving processes

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Implementing paper-based problem-solving activities using puzzles, riddles, and pattern recognition can effectively introduce computational thinking without the need for complex technology or terminology. Through real-life scenarios like transporting a fox, chicken, and corn across a river or encodi

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Exploring the challenges in proving major lower bounds for computational complexity, focusing on the Hardness Magnification and Minimum Circuit Size Problem (MCSP). Discusses the difficulties in proving weak and strong LBs, highlighting recent theorems and barriers that impact progress in the field.

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Explore the latest developments in computational modeling of Doppler radar data, focusing on error estimation, dual vs. single pol radars comparison, uncertainty quantification, and methodology for analyzing Doppler radar predictions against gauge measurements. The study involves data from multiple

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Dive into the world of High Dynamic Range (HDR) sensors in computational photography with topics covering sensor architectures, CMOS sensing techniques, dynamic range evaluation, and basic concepts related to image sensors and pixel integrators. Explore the importance of dynamic range in capturing a

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Delve into the world of texture synthesis and hole-filling in computational photography, exploring the challenges, goals, and techniques involved in creating new textures and filling in image gaps. Learn about building probability distributions, modeling textures, and the intricacies of synthesizing

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Explore the techniques and concepts of image-based lighting in computational photography through slides covering topics such as rendering objects in images, using environment maps and light probes, mirrored spheres, and dealing with light sources like the sun. Learn about capturing and utilizing lig

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This unit covers key concepts in computational thinking, including decomposition, abstraction, and algorithmic thinking. Decomposition involves breaking down complex problems, abstraction focuses on identifying essential elements, and algorithmic thinking is about defining clear instructions to solv

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MatFlow is an open-source Python code designed for computational materials science, running on HPC systems like CSF at Manchester. Users specify tasks to run in a workflow, with the main output being a workflow HDF5 file. The tool aims to make reproducibility and transparency easier, connect dispara

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This resource provides insights into the segregated solver approach in computational fluid dynamics (CFD) simulations, specifically focusing on the sweeping direction and its impact on computational efficiency and convergence rates. It discusses the benefits of employing the XY plane for 2D cases to

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Dive into a world of computational complexity and theory with a focus on topics such as NP, P, PH, PSPACE, NL, L, random vs. deterministic algorithms, and the interplay of time and space complexity. Discover insights on lower bounds, randomness, expanders, noise removal, and the intriguing question

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In the age of vast data growth, tackling complex computational problems is crucial. Statistical physics can provide insights into handling the new challenges arising from the exponential increase in data. As we delve into understanding the complexity of computational tasks, it becomes evident that e

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This lecture outlines the structure and query process of Priority Search Trees (PST) in computational geometry. It covers heap-based point queries, range trees for windowing queries, handling query ranges in 1D and 2D spaces, and using heaps to efficiently handle query ranges. The content discusses

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In today's discussion, we delved into computational complexity and the challenges faced in finding efficient algorithms for various problems. We explored how some problems defy easy categorization and resist polynomial-time solutions. The concept of NP-complete problems was also introduced, highligh

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Irina Tezaur leads the Quantitative Modeling & Analysis Department, focusing on computational modeling and simulation of complex multi-scale, multi-physics problems. Her work benefits DOE nuclear weapons, national security, and climate missions. By employing innovative techniques like model order re

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Decision problems play a crucial role in computational complexity theory, especially in the context of P and NP classes. These problems involve questions with yes or no answers, where the input describes specific instances. By focusing on polynomial-time algorithms, we explore the distinction betwee

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Computational Biology combines computational methods with molecular biology to solve biological problems. Explore topics like proteins, DNA, RNA, and genetics, learning about amino acids, nucleotides, and the genetic code. Understand the evolutionary processes of mutation and natural selection.

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Plane sweep algorithms are a powerful technique in computational geometry for solving various problems efficiently. By simulating the sweep of a vertical line across the plane and maintaining a cleanliness property, these algorithms can process events at discrete points in time to update the status

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In dynamic environments, tasks may face unknown workloads and deadlines, leading to system overload and missed deadlines. This research focuses on adapting task workloads to provide results before the deadline by adjusting computational parameters. It explores how to minimize degradation of result u

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Practical private-key cryptography can be done without advanced math, but understanding computational number theory is essential for public-key encryption. This field focuses on the computational difficulty of problems, analyzing algorithms' running times, classifying problems as easy or hard based

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Delve into the fundamentals of Computer Science and Computational Thinking through chapters discussing the nature of science, predictions in physics, and the distinction between Computer Science and Computer Information Systems. Explore the relationships between Math, Physics, and Computer Science i

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Our project for The Cadenza Challenge 2023 focused on improving audio for headphone users with hearing loss by integrating Spleeter's deep learning capabilities. We utilized N-ALR prescriptions, Butterworth bandpass filters, and Dynamic Range Compression to enhance audio quality. By leveraging advan

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The North American Computational Linguistics Olympiad (NACLO) is a competition for high school students interested in linguistics, languages, and computation. It consists of an Open Round in January and an Invitational Round in March, with no prerequisites needed. Participants tackle easy problems i

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The Mississippi Center for Supercomputing Research (MCSR) supports computational research in various fields like Chemistry, Bioinformatics, Physics, Engineering, and Computer Science for Mississippi IHLs. They provide training to optimize computational resources, offer classes for computational trai

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This work delves into the intricate world of complexity measures for Boolean functions, exploring concepts such as certificate complexity, decision tree depth, sensitivity, block sensitivity, PRAM complexity, and more. It sheds light on the relationships among different complexity measures and provi

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In this series of images and text snippets, the discussion revolves around the emerging field of computational theories of brain function. Various aspects such as symbolic memories, the relationship between the brain and computation, the emergence of the mind from the brain, and computational thinki

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Explore the world of Computational Earth Science with Bill Menke as the instructor and Emily Glazer as the teaching assistant. The course aims to help you become proficient in applying Python-based computational methods to understand dynamic Earth Science phenomena. Through modeling, you will gain i

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The workshop at the 8th EAI International Conference on Design, Learning & Innovation (DLI 2023) in Aalborg aims to delve into the application of computational play with mathematics in early childhood education. Through live sessions and discussions, opportunities and challenges in utilizing computa

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Algorithm analysis is a methodology used to predict the computational resources an algorithm requires, focusing on computational time rather than memory. It involves assessing the efficiency of different algorithms in solving a single problem. The analysis covers functions like Constant, Logarithm,

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The Trust Metric Estimator project aims to create a computational model to estimate user trust levels towards system performance over time. It considers social and technical factors, integrating trust, trustworthiness, and economic aspects to aid decision-making. Research includes surveys to identif

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