Winter Research Internship 2020 under Center for Cognitive Computing (CCC)

Data science for IoT is a multidisciplinary area that uses scientific methods, algorithms and systems to extract hidden knowledge and insights from data (Structured and Unstructured). It is the study of where information comes from, what it represents and how it can be transformed into a valuable resource in the creation of business and IT strategies. Data Science is a confluence of mathematics, statistics and computer science disciplines, and incorporates techniques like machine learning, cluster analysis, data mining and visualization. Hence, it is important to bring awareness among researchers & academicians and train manpower on data sciences for IoT to do innovative research work, projects, and create knowledge base. Therefore, there is both a great need and an exciting opportunity for the fraternity to develop theory, models, and algorithms in the domain of data science for IoT. The AICTE Training And Learning (ATAL) Academy sponsored 5-day FDP will bring awareness among researchers & academicians to discuss existing key progress and promising new directions.

Nanomedicine is a branch of medicine that applies the knowledge and tools of nanotechnology to the prevention and treatment of diseases. Nanomedicine involves the use of nanoscale materials, such as biocompatible nanoparticles and nanorobots, for diagnosis, delivery, sensing or actuation purposes in living organism. This workshop is an introduction to the world of nano research for beginners. The idea is to attract students, young researchers to the area of nanotechnology. Link for registration: https://docs.google.com/forms/d/1WjbN5XN0sXi9eZqjWSMLhL3V5p1GXQOXv6doq8Vprxo/edit

To provide an interactive platform for exchange of ideas and latest research findings on topics related to MEMS, NEMS, Nano robotics, 3D printing in tissue engineering, microfluidic cell culture and interdisciplinary research involving Bio-MEMS, Nanotechnology, Robotics, Microbiology and cutting edge characterization modalities like

Creative problem solving and critical thinking has been considered as potent tool to solve Complex problems in the industry as well as the academic circle. In this FDP & Workshop we will use established methods of Creative problem solving and critical thinking to approach the problem and move towards a solution which not only satisfies the constraints but also transcends the current boundaries created due to constrained viewpoint at prospective of agents involved in: The envisaging Analysis Assessment and Resolution of the problem.

The program is webbed around the idea of helping the faculties across the nation gain some significant skills from some highly qualified and experienced faculty. The faculty will guide you all to prosper in this field and develop a good foundation for their career in this domain. The concept of Emotional Quotient has seen some drastic improvisation in research of the past few years. Emotional intelligence (otherwise known as emotional quotient or EQ) is the ability to understand, use, and manage your own emotions in positive ways to relieve stress, communicate effectively, empathize with others and defuse conflict. It is the ability of individuals to recognize their own emotions and those of others, discern between different feelings and label them appropriately, use emotional information to guide thinking and behavior, and manage and/or adjust emotions to adapt to environments or achieve one's goal.

15th Convocation of the Institute has been scheduled on September 12, 2020 at 10:45 a.m. at its Jhalwa Campus, Allahabad in online mode. Hon’ble Dr. K. Sivan, Secretary, Department of Space and Chairman, Space Commission will be the Chief Guest and has kindly consented to deliver the convocation address in e-mode. Hon’ble Chairman (Officiating), Board of Governors and Director of IIIT-Allahabad Prof. P. Nagabhushan will preside over the ceremony.

Time-dependent sequential data emerge in many key real-world problems, including areas such as climate, robotics, economics, entertainment, healthcare and transportation. The increasing volume and complexity of time series data in modern applications highlight the importance of scalable and flexible time series learning techniques. Predominant methods in machine learning often assume i.i.d. observations, which is generally not appropriate for time series data. Therefore, there is both a great need and an exciting opportunity for the machine learning community to develop theory, models, and algorithms for processing and analyzing large-scale complex time series data. This Workshop will bring awareness among researchers & academicians at the forefront of time series analysis and algorithms to discuss existing key progress and promising new directions.