COVID-19 Research at IITs

Project Title : H+AI (Healthcare and Artificial Intelligence) Dataport and Factory.

Expected Outcome : 1. Dataport a. Submission of COVID-19 anonymized case reports including Clinical notes, rRT-PCR, Radiographs and observation annotations 2. Case Report browser for evidence based medicine a. Ever growing case and annotation registry, featuring RADS and clinical notes b. Semantic search for similar treatment and outcome retrieval for evidence based medicine 3. Reporting and Data Standards (RADS) Builder: AI assisted, knowledge graph based revision. 4. Factory for AI technology development to enabling features on Dataport, Case
Expected Timeline : Week -1 to Week 12
Remarks : Funding required Rs. 25 Lakh for 3 Weeks
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Additional Info
PI Details : Dr. Debdoot Sheet, [email protected]

Project Title : Local Home Delivery Networks

Expected Outcome : (a) Interactive Mobile App or Web GUI for placing orders (b) Algorithm for Resource Allocation (c) Logistics Planning and Activation of Delivery Network (d) Purchase Pattern Mining and Visualization (e) Algorithm for Hoarding detection
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PI Details : Dr. Prithwijit Guha, [email protected]

Project Title : Model the covid virus etiology using the tools of biophysics.

Expected Outcome : Use publicly available data both within India and outside to generate detailed models of how infections spread. Collaborate with hospitals to collect data about patients pre existing conditions and correlate with severity of infection.
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PI Details : Girish Sampath Setlur, [email protected]

Project Title : A team of faculty from the department of mechanical Engineering started to explore the use of shallow and deep learning technique to model the epidemic pattern and disease dynamics. These studies mainly focus on developing new techniques, which can give better efficiency and accuracy of its prediction using the datasets. However, an AI tool comprising of such techniques for diagnosis from the dataset is not available in the literature. The proposed AI tool will predict epidemic pattern of the disease.

Expected Outcome : AI model to predict epidemic pattern of a disease
Expected Timeline : 1 years
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PI Details : Prof. Deepak Sharma , 7896002571 , [email protected]

Project Title : An Inter-disciplinary approach towards predictive modeling of COVID-19 for Public Policy in Odisha.

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PI Details : Prof. Sujit Roy, [email protected]

Project Title : Developing apps that collect data about health conditions of the citizens to provide to local administration on a constant basis.

Expected Outcome : Ease of administration for Local Administration
Expected Timeline : 1 week
Remarks : NA
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PI Details : Dr. Sobhan, CSE dept. , (040) 2301 6081 (O) , [email protected]

Project Title : Working on Data analysis and modeling of Covid-19 disease spread.

Expected Outcome : Data Analytics to support ongoing & future work to contain Covid-19
Expected Timeline : On-going
Remarks : Study can be extended if further data from the administration is provided
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PI Details : Dr. Mohan and Dr. Kousik, BME dept. , (040) 23018452(O) , [email protected]

Project Title : Working on exploring working mothers' experiences, regarding housework, childcare and professional work during the lockdown through regular interviews.

Expected Outcome : Data Analytics to support ongoing & future work to contain Covid-19
Expected Timeline : 6-8 Weeks
Remarks : Need to study the pattern for at least 2 weeks once the lock-down period is over.
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PI Details : Dr. Mahati and Dr. Haripriya, LA dept. , (040) 2301 7045 (O) , [email protected]

Project Title : Working on the impact of COVID-19 on financial markets.

Expected Outcome : Data Analytics to support ongoing & future work to contain Covid-19
Expected Timeline : 2-3 Months
Remarks : NA
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PI Details : Dr. Prabheesh, LA dept. , (040) 2301 6013 (O) , [email protected]

Project Title : 1. Speech, text and video analytics applied to epidemic domain with special emphasis to COVID-19 (will be applied to COVID-19 domain) 2. A Platform for Cross-lingual and Multi-lingual Event Monitoring (with special emphasis on COVID-19) in Indian Languages

Expected Outcome : 1) Some automated tools to automatically extract information related to COVID-19 event from social media;
Expected Timeline : The models developed as a part of ongoing IMPRINT project will be extended for COVID-19 event.
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PI Details : Prof. Pushpak Bhattacharyya , 7541817400 , [email protected]

Project Title : In case of COVID19 like epidemics/pandemics we need to develop epidemic spreading models for supporting public health in real time decision-making and policy forming. We explore mathematical/mechanistic state-space models in Indian context. We use two types of models: a) Continuum models in form of differential equations with mean field approximation and b) Complex network models that are relaxing the hypothesis of the first type of models that the interactions between individuals are instantaneous and homogeneous.

Expected Outcome : (1) A data integration platfoem for integrating disease related data from diverse data sources. (2) Three models for epidemic forecasting: epidemic models, population models, and mobility models. (3) An epidemic simulation framework which can be used to simulate spatio-temporal dynamic of the epidemics using various models. Model forecast will be used to estimate the severity of the epidemic if left unchecked. The simulations will be done repetitively since models, data and underlying model parameters dynamically evolve over time. The framework will have the capability to manage the simulation ensembles and to analyze them.
Expected Timeline : 1 Year
Remarks : The most crucial part of the project would be to accumulate data related to population, mobility pattern and COVID19 with spatio-temporal information.
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PI Details : Abyayananda Maiti , 7070811668 , [email protected]

Project Title : TITLE: An automatic diagnostic system for COVID 19 based on CT Scan Image Analysis. ABSTRACT: In December 2019, a novel corona-virus has emerged in China, and it has turned into a global pandemic. The infection may have the first transmission from animal to human but has the property of communication from human to human transmission. A total of 203 countries and territories around the world have reported a total of 966,362 confirmed cases of the corona-virus COVID-19 that originated from Wuhan, China, and a death toll of 49,279 deaths. India is also affected by this disease, with 50+ deaths registered due to COVID 19. The virus affects the respiratory tract of the patient causing pneumonia. There is an attempt to understand the disease and its symptoms as the condition is at the early stage. In many cases, it is observed that the patient experiences fever, cold, and cough due to the disease as a first symptom. As the disease progress, the first sign is difficulty in breathing. Computed tomography (CT) scan of lungs had shown abnormality among COVID 19 patients. Patients have abnormal CT scan chest images. The ground-glass opacity was the most found abnormality among the patients. The other abnormalities are local patchy shadowing and interstitial abnormality. The research work aims to detect the anomaly in CT scan images of the chest and develop an algorithm for efficient automatic abnormality recognition.

Expected Outcome : Algorithm to detect chest CT scan abnormality pattern of the patient affected due to COVID 19 disease. An algorithm to increase the efficiency and speed of diagnosis of the disease.
Expected Timeline : One Year
Remarks : An automatic diagnostic system for COVID 19 based on CT Scan Image Analysis will be developed.
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PI Details : Dr. Maheshkumar H Kolekar, Associate Professor, EE Dept, IIT Patna , 8986184240 , [email protected]

Project Title : The project aims at building a multi-lingual and cross-lingual platform for Information Extraction in English and Indian Languages for monitoring health disaster, detecting actionable items and provding relevant information to the different stakeholders such as govt agencies, humanatarian organizations as well as the common people.

Expected Outcome : An End-to-End System will be built for multilingual event monitoring during health disaster. Some important components of this overall system are as follows: (i). Event Extraction System to extract events of interest from news and social media posts; (ii). Event Classification System to classify events into different categories; (iii). Event-Argument Linking; (iv). Sentiment Analysis from social media posts to understand public opinions; (v). Misinformation handling by linking social media posts to the actual news
Expected Timeline : One Year
Remarks : Months [1-3]: Event Extraction System in English; Months [4-6]: Event Classicfication, Argument Extraction, Event-Argument Linking and Event-Event Linking across the documents; Months[7-9]: Sentiment Analyzer; [Months 10-12]: Misinformation handling by generating news from tweets or social media posts and connecting to the actual newpaper reports
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PI Details : Dr. Asif Ekbal and Prof. Pushpak Bhattacharyya , 8521274830 , [email protected], [email protected]

Project Title : Blockchain-based Data collection and Prediction of Epidemic growth to develop an Early warning system

Expected Outcome : Trusted Data collection and validation, Developing a Global model to predict the spreading of disease, with preserving data privacy
Expected Timeline : 48 Months
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PI Details : Somanath Tripathy , 8084717331 , [email protected]

Project Title : Summarize the information available over social media related to COVID-19; The data available in different news-papers and social media can be categorized into two classes: relevant and irrelevant/fake. After checking the genuinity of the data, the relevant data can be selected judiciously to provide the reader a comprehensive summary. The images, videos available as the part of the news/social media posts will also be utilized in generating the summary. This summary will help different Govt. bodies in their decision making process.

Expected Outcome : A tool which will extract information from different online news websites, social media and will display the summary related to COVID-19 event. The images, videos will also be part of the summary. The summary will keep on updated in an online fashion with the availiability of the new information.
Expected Timeline : 0-3 months: data collection, 4-6 months: development of the preliminary text based model; 7-9 months: development of multimodal model; 10-12 months: development of online summarization model.
Remarks : The existing summarization works by the PIs will be extended for the COVID-19 domain.
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PI Details : Dr. Sriparna Saha, Prof. Pushpak Bhattacharyya , 8809559190;7541800000 , [email protected], [email protected]

Project Title : Project Title: COVID-19: Implying Gender Transformative Lens to address Gender Equity in Bihar and Jharkhand: Sustainable Development Goal 5 of the United Nations aims at achieving gender equality and empowers women and girls. However, during this phase of COVID 19, it is difficult for women to access health care, protect themselves against gender-based violence, and maintain financial stability. Women, who make up 70% of the health and social service workforce, are on the frontlines of the response effort to treat and stop the spread of the virus. However, when health care systems are forced to channel all of their resources to combat COVID 19, sexual and reproductive health care may be overlooked — despite the persistent need for adequate family planning, menstrual health resources, and maternal care. It is crucial to ensure the availability of sex-segregated data, where we not only look at differing rates of infection but the economic impacts, differential care burden, domestic violence rates, changing socio economic and cultural norms which are exacerbated by COVID- 19.

Expected Outcome : • Improved women's participation in their roles of surveillance and insights towards COVID-19 prevention activities within the community and ensuring their representation in local and national level COVID-19 response policy spaces. • Collection of accurate and complete sex disaggregated data and information to understand how COVID 19 impacts women in Bihar and Jharkhand especially in terms of prevalence, trends and other important information. • Strengthen the availability of evidence on the gender implications of COVID-19 pandemic to inform advocacy and programmatic interventions making it more gender-sensitive and responsive. • Integrating Gender Based Violence risk mitigation into all aspects of COVID-19 response and ensuring that Gender Based Violence mitigation response measures are included in the national contingency/preparedness and humanitarian response plans, including providing tools and methodologies for risk mitigation and prevention of GBV in any cash and voucher (CVA) based programming, especially related to food security; conducting safety audits; health and water, sanitation and hygiene (WASH) responses • Improved women's participation in their roles of surveillance and insights towards COVID-19 prevention activities within the community and ensuring their representation in local and national level COVID-19 response policy spaces. • Collection of accurate and complete sex disaggregated data and information to understand how COVID 19 impacts women in Bihar and Jharkhand especially in terms of prevalence, trends and other important information. • Strengthen the availability of evidence on the gender implications of COVID-19 pandemic to inform advocacy and programmatic interventions making it more gender-sensitive and responsive. • Integrating Gender Based Violence risk mitigation into all aspects of COVID-19 response and ensuring that Gender Based Violence mitigation response measures are included in the national contingency/preparedness and humanitarian response plans, including providing tools and methodologies for risk mitigation and prevention of GBV in any cash and voucher (CVA) based programming, especially related to food security; conducting safety audits; health and water, sanitation and hygiene (WASH) responses
Expected Timeline : 12 - 24 Months
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PI Details : Priyanka Tripathi, IIT Patna, Ashish Kumar, Gender Resource Centre, Government of Bihar , 9155147495, 9006795695 , [email protected] and [email protected]

Project Title : Decentralized Blockchain-based Platform Towards Achieving Fair and Transparent Distribution of Essential Commodities during Covid-19 Pandemic Situation We propose to develop a complete decentralized blockchain-based platform where any individual, group or organization can join as a 'donor' or 'distributor' and can help in distributing essential commodities during Covid-19 pandemic situation. The system facilitates a complete transparency in the distribution process, providing food traceability (from donors to multiple distributors to donatees) and eliminating the involvement of any un-useful untrusted third party. The proposed system supports not only cooked food or food grains, but also other essential commodities such as masks, medicines, etc.

Expected Outcome : A blockchain-based decentralized platform for fair and transparent distribution of all essential commodities (such as food grain, cooked food, masks, medicines, etc.) during Covid-19 pandemic situations, providing a complete traceability of commodities from donors to multiple distributors to donatees. For this purpose, a web based interface will be designed initially and later a mobile app will be developed.
Expected Timeline : 3 Months
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PI Details : Dr. Raju Halder and Dr. Samrat Mondal , 8678088635, 8292583635 , [email protected], [email protected]

Project Title : Investigation of host-pathogen interactions of SARS-CoV2 variants in the Indian population

Expected Outcome : A major challenge in tackling the current global COVID-19 pandemic is the diverse response (asymptomatic to severe respiratory distress and death) in infected human hosts which may be correlated with age, gender, ethnicity, comorbidities etc. We propose to investigate if the diverse host responses to pathogen infection can be attributed to specific DNA-based host biomarkers (host susceptibility or protective factors). Moreover, as the outbreak has spread globally, the novel SARS-CoV2 has diverged from the ancestral Wuhan strain. We also propose to analyse and compare pathogenicity of various viral isolates and investigate mutant variants of individual viral proteins to help design potential treatment and prevention options.
Expected Timeline : 1 year
Remarks : The work has been initiated, and submitted for funding.
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PI Details : Sharmistha Majumdar and Dr. Madhavi Joshi (GBRC)

Project Title : COVID Explorer

Expected Outcome : COVIDExplorer is an AI-based search and visualization platform to understand COVID-19 research papers. It helps in searching relevant research papers using biomedical terms like genes, proteins, RNAs, DNAs, Diseases, Molecular Formulae, etc. It presents details of India-specific infections, recovery, and death counts. It also displays the COVID-19 specific Twitter discussions, fact/myths in posts, and tries to automatically identify misinformed social-media messages.
Expected Timeline : 2-3 months
Remarks : The work is near completion
URL : covidexplorer.in
PI Details : Mayank Singh

Project Title : Artificial Intelligence based detection of COVID-19 from Chest X-ray images

Expected Outcome : The purpose of the project is to develop an AI tool for detection of COVID-19 from X- ray images. AI tools are widely used for medical image diagnosis. The primary requirement of such tools is big-data i.e. availability of large datasets. We report a simple machine learning architecture that can has been trained using deep learning algorithms and the pooled x-ray image datasets. The format of any test image of a new person will be automatically transformed and diagnosed using the AI tool. A similar web-interface can be setup for our tool using a simple desktop Linux server. It will also validate the input images before giving a result. Using our tool and web-interface anybody can upload a chest x-ray or CT-scan in standard image formats such as jpeg, png etc. and check whether it is COVID-19 positive or not.
Expected Timeline : 1 month
Remarks : The first phase of the work has been completed, the website based tool to be available in public domain soon
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PI Details : Krishna Miyapuram

Project Title : AI driven diagnostics using X-ray and CT-images of lungs

Expected Outcome : AI driven covid 19 detection
Expected Timeline : 1 TO 2 Months
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PI Details : Dr. Santanu Chaudhury, Dr. Mayank Vatsa, Dr. Richa Singh, Dr. Deepak Misra, Dr. Rajendra Rathore

Project Title : Detection of Coronavirus using advanced machine learning techniques

Expected Outcome : -
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Remarks : Project Initiated
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PI Details : Dr. M. Tanveer, [email protected]

Project Title : Working on the time dependent Mathematical Model based on the following parameters a)Total Population b)Susceptible Population c)Infected Population infected d)Undetected infected Population e)Expected recovery of quarantined population f)Recovered Population

Expected Outcome : The time dependent Mathematical Model
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PI Details : Dr,Shantanu Manna

Project Title : The Coronavirus (or Covid-19) outbreak is becoming a major worry for almost the entire world. According to World Health Organization (WHO), till recently, more that 900,000 cases of Covid-19 have been reported across the world. Also, as per WHO, there have been more than 45,000 deaths as a result of this pandemic. In India alone, there have been more than 2000 cases of Covid-19 till 2nd April 2020 and more than 55 deaths. Given these increasing numbers, one may want to predict people who are likely to get Covid-19, people who are likely to recover from it after getting it, and people who are likely to live no more due to it. These estimates may help the Government to better plan the country’s healthcare and other resources to fight this pandemic. In this write-up, we discuss how certain machine learning (ML) models could be used to predict Covid-19 recoveries across the world.

Expected Outcome : Model to predict Covid-19 recoveries across the world
Expected Timeline : 1 year
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PI Details : Dr. Varun Dutt, [email protected]

Project Title : The Coronavirus (or Covid-19) outbreak is becoming a major worry for almost the entire world. According to World Health Organization (WHO), till recently, more that 900,000 cases of Covid-19 have been reported across the world. Also, as per WHO, there have been more than 45,000 deaths as a result of this pandemic. In India alone, there have been more than 2000 cases of Covid-19 till 2nd April 2020 and more than 55 deaths. Given these increasing numbers, one may want to predict susceptible people who are diagnosed with Covid-19 (diagnoses), people who are likely to recover from Covid-19 after getting it (recoveries), and people who are likely to live no more after getting infected with Covid-19 (deaths). These estimates may help the Governments to better plan their country’s healthcare and other resources to fight the Covid-19 pandemic.

Expected Outcome : Model to predict Covid-19 susceptible population, recoveries, deaths, and data features that impact the susceptible population, recoveries, deaths. (from the second document).
Expected Timeline : 1 Year
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PI Details : Dr. Varun Dutt, [email protected]

Project Title : COVID-19 hotspots in Kerala will be identified based on the following data: population density, number of confirmed patients, patient’s travel history, climate (temperature), age, pre-existing conditions (diabetes, cancer patients, etc.). A GIS based analysis will be performed that will help identify the regions in Kerala vulnerable to COVID-19. It will lead to need based allocation of resources. A first round of this analysis was done for Thrissur district with the data that was available. Moreover, CORONA care centres and hospitals have also been mapped across Kerala. We are also in touch with the Health Department of Kerala regarding this.

Expected Outcome : The regions in Kerala vulnerable to COVID-19 will be identified.
Expected Timeline : Depends on data availability
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PI Details : Dr. Sarmistha Singh, [email protected]

Project Title : We are working in modeling Covid19 using variants of SEIR type compartment models. We are planning to use a detailed modeling considering India specific scenario to more accurately model the case in India. Our plan is to estimate the parameters from existing datasets to train the model, and then we will apply them for predicting the future possibilities. 

Expected Outcome : Forecasting the spread of Covid19, analysis of factors contributing to the spread of Covid19, policies to reduce the spread of Covid19 in India trading off with societal factors.
Expected Timeline : 2 months 
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PI Details : Sahely Bhadra, Deepak Rajendraprasad, Sarath Sasi, Mrinal Das, [email protected], [email protected], [email protected], [email protected]

Project Title : Currently, X-Ray / CT Scan are the commonly used diagnostic modalities for evaluating the lung condition of covid-19 patients in India – These are hazardous, costly and impractical for patients in ICUs/Hospital wards. Doctors and Researchers in Italy have demonstrated the usefulness of Lung Ultrasound Scans for monitoring covid-19 patients on daily basis, which is highly useful for frequent monitoring and timely medical intervention to reduce the mortality. IIT Palakkad intends to develop an automated analysis of ultrasound lung scans using machine learning techniques and conduct clinical trials in collaboration with Sree Chitra Institute of Medical Sciences and Technology (SCTIMST), Thiruvananthapuram. We will first develop automated analysis for the Italian Ultrasound Lung images available with support from the University of Trento and then validate it in Indian hospitals in clinical collaboration with SCTIMST.

Expected Outcome : An automated lung ultrasound workflow to detect anomalies in lung specifically related to Covid19. The research will be further expanded to identify any anomalies related to acute respiratory distress syndrome (ARDS)
Expected Timeline : 6 Months
Remarks : An MoU has been initiated between IIT Palakkad and Sree Chitra Institute of Medical Sciences and Technology (SCTIMST) for clinical evaluation of the approach
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PI Details : Dr. Mahesh Raveendranatha Panicker, Electrical Engineering, IIT Palakkad , +91-9008600663 , [email protected]

Project Title : A Rapid Large-scale Covid Detection Tool through Classification of Xrays using Deep Learning.

Expected Outcome : A tool that will classify xrays into covid19 positive or negative with more than 99% accuracy.
Expected Timeline : 2 months
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PI Details : Dr. Mrinal Kanti Das, Dr. Sahely Bhadra, {mrinal, sahely}@iitpkd.ac.in

Project Title : Chest X-Ray based Screening of COVID -19

Expected Outcome : Diagnosing or detecting patients infected with COVID19 using chest radiography images
Expected Timeline : Two months
Remarks : The objective of the project is to devlop a deep learning models with high recall for the classification of patients with (i) COVID X-rays, (ii) Viral infections, (iii) Bacterial infections and (iv) normal subjects based on the available Chest X-Ray data of COVID and non-COVID subjects. Currently with a hybrid deep learning model and effective cost function we could achieve a recall of 96% and precision of 96% on 25 COVID test samples, test accuracy of 94.4% on 600 samples. Vefification on Indian dataset is needed. Project is half way.
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PI Details : Dr. Rama Krishna Gorthi, [email protected]

Project Title : Project Title : Misinformation Detection for COVID-19

Expected Outcome : A website where one can enter fake/misinformation message in the form of text and URL if any, and the website will flag the truth score and security score of the website based on a machine learning classifier as well as use Natural Language Processing and search trend analysis at the backend and finally flags the message as spam or not.
Expected Timeline : Already live
Remarks : The work can be further improved by improving the accuracy of the model
URL : https://stop-corona-iittp.herokuapp.com/
PI Details : Dr. Sridhar Chimalakonda, Research in Intelligent Software & Human Analytics (RISHA) Lab, , [email protected]

Project Title : Project Title : SurviveCovid-19 -- A Game for Improving Awareness of Social Distancing and Health Measures for Covid-19 Pandemic

Expected Outcome : How do we bring awareness for Covid-19 pandemic in an innovative way? One of the most important tasks during a pandemic like Covid-19 is to bring awareness among people, more so when return to normal life is expected to be long. To address this challenge, we have designed and developed an innovative game called SurviveCovid-19. SurviveCovid-19 is developed as an educational game that helps people in understanding the importance of masks, sanitizers and social distancing to keep themselves and people in their surrounding safe from Covid-19 when they walk around the theme of a city. The game is inspired by a simple pixel-based top-down style design where people navigate the city with safety and health measures and accomplish tasks such as buying groceries and medicines. The game which is played 800 times till now is developed using a survivor style theme in which a player has to survive by performing predefined tasks and rules, which in this case are safety measures for Covid-19. The player gets immersed into the game to achieve the tasks of buying groceries and medicines while regularly using masks and sanitizers to survive in the game. We have given critical importance to “social distancing” in the game and the life of the player keeps reducing once the player comes in contact with Covid-19 infected persons until he/she visits a nearby hospital.
Expected Timeline : Already live
Remarks : The game is covered by The Hindu, NDTV, IndianExpress and we are currently working on improving the game with a fund from a foundation from USA
URL : :https://survivecovid-19.itch.io/game2020, https://arxiv.org/abs/2004.09759
PI Details : Dr. Sridhar Chimalakonda, Research in Intelligent Software & Human Analytics (RISHA) Lab,, [email protected]

Project Title : Mood of India During Covid-19 - An Interactive Web Portal Based on Emotion Analysis of Twitter Data

Expected Outcome : The severe outbreak of Covid-19 pandemic has affected many countries across the world. It has disrupted the day to day activities of many people across the world. During such outbreaks, understanding the emotional state of citizens of a country could be of interest to various public and private organizations to carry out various tasks and to take necessary measures. Several studies on data available on various social media platforms and websites have been carried out to understand the emotions of people against many events, inclusive of Covid-19, across the world. Twitter and other social media platforms have been bridging the gap between the citizens and government in various countries and are of more prominence in India. Sentiment Analysis of posts on twitter is observed to accurately reveal the sentiments. Analysing real time posts on twitter in India during Covid-19, could help in identifying the mood of the nation. However, most of the existing studies related to Covid-19, on twitter data and other social media platforms are performed on data posted during a specific interval. We are not aware of any research that identifies emotional state of India on a daily basis. Hence, we present a web portal that aims to display mood of India during Covid-19, based on real time twitter data. This portal also enables users to select date range, specific date and state in India to display mood of people belonging to the specified region, on the specified date or during the specified date range. Also, the number of Covid-19 cases and mood of people at specific cities and states on specific dates is visualized on the country map. As of May 6 2020, the web portal has about 194370 tweets, and each of these tweets are classified into seven categories that include six basic emotions and a neutral category. A list of Trigger Events are also specified, to allow users to view the mood of India on specific events happening in the country during Covid-19.
Expected Timeline : Live at https://moodofindia.herokuapp.com
Remarks : We are still working on improving the current version
URL : https://moodofindia.herokuapp.com/
PI Details : Dr. Sridhar Chimalakonda, Dept. of Computer Sci. & Engg, [email protected]

Project Title : COVID19 Mobility Data Network – Creation of Situation Reports and Mobility Pattern Predictions of Red Zones

Expected Outcome : (a) To perform scientific analyses on mobility patterns of COVID-19 pandemic in red zones using Facebook data; (b) To develop mobility data network pertinent to COVID19, accessing data and analysis, and roadmap to utilizing data streams in order to provide strategies for future disaster management; (c) To establish a framework for immediate discussion considering the research and implementation plan as a matter of national (and international) concern.
Expected Timeline : Until State Governments deem it important; started 15 March 2020; reports under production
Remarks : Currently, developing and sending daily situation reports for states of Andhra Pradesh and Odisha; anticipated to expand the framework to other states as well.
URL : under preparation; restricted data access only to Government bodies
PI Details : Krishna Prapoorna (Civil & Environmental Engineering),Kalidas (Computer Science & Engineering), [email protected],[email protected]

Project Title : YTCoder - Towards Turning YouTube to a Code Editor

Expected Outcome : Video Tutorials have become a most common method of learning various skills, from crafts and cooking to various educational concepts. Learning programming through online video tutorials is a common practice among programmers of multiple levels, novice to experienced. YouTube is one of the most popular and largest source that hosts many video tutorials that aim to teach concepts of various programming languages. Most of these tutorials include code snippets that are displayed and written by the tutor during the video. However, it is important that the viewers of video programming tutorials have a hands-on programming experience while learning various programming concepts. Providing a code editor along with the video tutorial could help learners in getting a better learning experience, as they have a scope to learn by practice. Existing solutions of accompanying video tutorials with code editors are either pre-programmed or require a separate web portal. We are not aware of any solutions in the literature that aim to support Youtube video tutorials. Hence, we are designing and developing YTCoder that aims to integrate videos related to various programming languages with code editor of respective programming languages.
Expected Timeline : : 2 to 4 weeks
Remarks : Currently, under development
URL :
PI Details : Dr. Sridhar Chimalakonda, Dept. of Computer Science and Engineering, [email protected]

Project Title : GeoCov19 Algorithm for Red-zone proximity monitoring for India

Expected Outcome : Red-zone areas are hot spots of confirmed cases of COVID19 inspection. Population movement in and around the regions during morning, evening and night time frames provides insights for law enforcement and health officials. The GeoCov19 algorithm combines red zone location information with Facebook mobility patterns from high resolution density maps and low resolution movement maps and generates diagnostic reports on a daily basis. The algorithm is already serving for AP and OR states and discussions are going on to include more state governments country-wide.
Expected Timeline : Already in production
Remarks : Discussions are in progress for country-wide deployment in collaboration with Facebook
URL : RESTRICTED ACCESS to deputed state government officials for the purpose.
PI Details : Dr. Kalidas Yeturu, Dept. of Computer Science and Engineering,, [email protected]

Project Title : Drug discovery for blockade of essential proteins for SARS-CoV-2 survival

Expected Outcome : Candidate ligand molecules are determined from naturally occurring sources against key SARS-CoV-2 proteins including spike, main protease and ACE2 receptors. The effectiveness of these ligands is determined using molecular docking studies. Analysis for side effects of these molecules is carried out using our recently developed deep learning based algorithm (site2vec). We have identified two key molecules and work is in progress to communicate the results.
Expected Timeline : Work is finished, publication is pending.
Remarks : Work is carried out in collaboration with IISER Tirupati.
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PI Details : Dr. Kalidas Yeturu, Dept. of Computer Science and Engineering, [email protected]

Project Title : Mathematical model and statistical simulations of CoVID19 spread

Expected Outcome : • The vulnerable area or areas facing high risk of spreading of diseases. • Numbers of positive cases to be expected in a district in given time frame • Doubling time prediction for different scenario that might arise. • Identification of factor that might be altered to reduce the spread by aid of administration • Predict the effect of administrative steps that has been or might be taken to curb the spread of the disease.
Expected Timeline : One Year
Remarks : Submitted under MATRICS CoVID 19 Scheme
URL :
PI Details : Dr. Vipin Kumar, Associate Professor, Env. Sc. & Engg. , 9471191352 , [email protected]

Project Title : Bayesian Hierarchical space and time statistical modeling of COVID-19 pandemic Objective: Corona virus COVID-19 further transmitted to several states of India. The status of the infected cases can be determined base on the treatment process along with several other factors. This research aims to build a prediction model to predict the number of cases, death due to corona virus COVID-19 patients in India.

Expected Outcome : Currently, the outbreak of COVID-19 is rapidly spreading especially in the capital cities of India and threatens 1.5 billion people in India. In this proposed study we planned to apply Hierarchical space and time statistical model to show that COVID-19 infection is spatially dependent and mainly spread from capital cities like Mumbai, Delhi to neighbouring areas. The statistical model will be employed according to the trend of available data, which shows the difference between capital cities and outside of it. The measures will reduce or prevent the virus spread should be implemented, and we expect our modeling analysis providing some insights to identify and prepare for future virus control.
Expected Timeline : I have submitted this project under MATRICS Short-term special call on COVID-19 to DST-SERB for financial support. The duration of this project is one year but we may able to give better and efficient prediction model within two months.
Remarks : Summary: The entire world is in crisis, due to the rapid spread of deadly infectious disease virus COVID-19. Typically this virus spreads by contact of susceptible and infected individuals. It is relatively very difficult to trace small-scale movements and find a linkage between peoples that are not recorded. The available data becomes aggregations in space and time, provides small-area counts of the number infected during successive and regular time intervals. In this project, we will develop and apply a spatially descriptive, and dynamic model to the COVID-19 data. The multivariate disease count autoregressive model will be considered is work. The relative risk of infection will be defined as a spacetime dynamic. Now the Bayesian approach using Markov chain Monte Carlo method will be used to obtain the posterior estimates of the parameter of interest for COVID-19 pandemic data.
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PI Details : Dr. Gajendra Kumar Vishwakarma (PI: Dept of Mathematics & Computing, IIT(ISM), Dhanbad) Dr. Atanu Bhattacharjee (Co-PI: Centre for Cancer Epidemiology, Tata Memorial Centre, Mumbai) Dr. Sharvari Rahul Shukla (Co-PI: Director, Symbiosis Statistical Institute, Pune) , +91-9471191338 , [email protected]

Project Title : Development of Deep Learning based Model for the Automatic Identification of COVID-19 disease using CT image history

Expected Outcome : A deep learning models based on CNN and SVM, are proposed to be developed to extract visual features from volumetric chest CT exams for the detection of COVID-19
Expected Timeline : One Year
Remarks : The project proposal is submitted to SERB(DST) under the scheme MATRICS short term special call COVID-19
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PI Details : Prof. TANMOY MAITY , 9471191126 , [email protected]

Project Title : Data Analytics, AI to model epidemic patterns and disease dynamics

Expected Outcome : 1. Clear characterization/definition of clusters 2. Multi-cluster model for spread of epidemic and impact of preventive measures/interventions 3. Data-driven estimation of the parameters of the studied models 4. Identification of parameters for different strains and a model for predicting the extent of mutation 5. Packaging the solution in a usable software form and make it available for ready use by Government of India on need basis (with emphasis on ease of use)
Expected Timeline : One year
Remarks : Approved by SERB under Short-term MATRICS special call on Mathematical Modeling and Computations for COVID-19 Infections. Total project cost Rs. 5,00,000/-
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Additional Info
PI Details : Arzad Alam Kherani, Co-PI: Rishi Ranjan Singh (IIT Bhilai), D. Manjunath (IIT Bombay) , 9741987453 , [email protected]

Project Title : Data Science and Epidemic models to tackle COVID-19 pandemic : To analyze the infection, disease background, death, and recovery data to generate insights. Using epidemic models, we plan to build predictive tools for designing effective mitigation strategies.

Expected Outcome : An efficient testing strategy and real-time epidemic control strategy
Expected Timeline : Depends on data availability
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PI Details : Dr. Sreenath Balakrishnan, Dr. Thaseem Thajudeen, Dr. Sreejith A. V., Dr. Clint P. George, [email protected], [email protected], [email protected], [email protected]