Prakhar Mishra is a Full-time MS by Research student at WSL, IIIT-Bangalore. He holds a bachelor’s degree in CSE from The LNM Institute of Information Technology, Jaipur. He has a total industry work experience of 3 years in the field of Data Science, particularly in NLP and Text Analytics. His areas of interest include Unsupervised Learning, Natural Language Understanding, and Generation. He also owns a Blog and Youtube channel which you can find here and here respectively.
Aparna is a postdoctorate research fellow in Web Science Labs. She is working on social learning paradigm of Navigated Learning. Along with her research, she is working as research program manager for Mphasis CoE for Cognitive Computing. For a year she had also worked as a research project manager on Gooru project. Before joining Web Science labs, She was a postdoctorate research fellow at University of Haifa, Israel under the fellowship of Planning and Budgeting Commission of Israeli Higher Education.
She is a mathematician and educational technologist with PhD in Information Technology. For PhD she had proposed an ontology for teaching problem solving in mathematics. Her research interest include: application of Information Technology to Education specifically mathematics and science education, application of semantic web technology to education, ontological engineering and management, online assessment, automation of applications, educational technology and management.
She earned an MPhil in math education research from Cambridge University, UK and have received several academic fellowships and awards including HP Labs fellowship for PhD, DFID & CCT fellowship for MPhil.
She has wide range of teaching and work experience. She has taught to tribal students as well as intellectually gifted students. She has also taught graduate level and master’s level students. During PhD at IIITB, she has mentored MTech students for some projects.
She is also interested in social work, Indian culture and ancient Indian knowledge. She has worked as a Sevavrati for Vivekanand Kendra in the North Eastern region of India. She had worked as a joint secretary for Vivekanand Kendra Pune and during her association with VK, she had organized youth camps, personality development camps, conducted workshops and delivered lectures on life and work of Swami Vivekananda. She is a voracious reader in both Marathi and English and write regularly blog articles as well as articles in newspapers and magazines in Marathi and some times in English.
Publications: (Publications can be downloaded from my ResearchGate profile)
Journal Publications:
Aparna Lalingkar, Srinath Srinivasa, PrasadRam (2019), Characterization of Technology-based Mediations for Navigated Learning, Advanced Computing and Communications, Vol 3 (2), June 2019, ACCS Publications, pp. 33-47. (Paper Link)
Lalingkar, A. (2017). Applet Ontology as a Tool for Automatic Assessment of Applet-based Assessment Tasks, Journal of Computers in Education, Vol 5 (1), Dec 2017. (Cited by 2 as per GoogleScholar citation index) (Paper Link )
Lalingkar, A.; Chandrashekar, R. & Ramani, S. (2015). MONTO: Machine Readable Ontology for Teaching Word Problems in Mathematics, Journal of Educational Technology and Society, Vol 18 (3), July 2015, pp. 197-213. (SSCI indexed journal with 5-year impact factor of 1.34 as per Thomson Scientific Journal Citations Reports, and with Google Scholar h5-index of 39) (Cited by 6 as per GoogleScholar) (Paper Link )
Lalingkar, A.; Chandrashekar, R. & Ramani, S. (2014). Ontology-based Smart Learning Environment for Teaching Word Problems in Mathematics, Journal of Computers in Education, 1 (4), December 2014, Springer, pp. 313-334. (Cited by 11 as per GoogleScholar citation index) (Paper Link )
Lalingkar, A. (2007). Comprehensive Review of Research in Comparative Education, Perspectives in Education, Vol 23 (3), October 2007, PP. 249-257. (Paper Link)
Lalingkar, A. (2007). Comparison of geometry curricula with respect to objectives and content in India and England for the age group 14 to 16 years, Perspectives in Education, Vol 23 (2), April 2007, pp. 122-129. (Paper Link)
Conference Publications:
Lalingkar, A., Mishra, P., Mandyam, S., Pattanayk, J. and Srinivasa, S. (2020), Building a Model for Finding Quality of Affirmation in a Discussion Forum, In Proceedings of the 20th IEEE International Conference on Advanced Learning Technologies (ICALT), IEEE, 6th July to 9th July, Turtu, Estonia (Digital Conference). (Paper Link)
Lalingkar, A.; Srinivasa, S. & Ram, P. (2018). Deriving Semantics of Learning Mediations, In Proceedings of the 18th IEEE International Conference on Advanced Learning Technologies (ICALT), IEEE, pp. 54-55. (Cited by 1 as per GoogleScholar citation index) (Paper Link)
Lalingkar, A.; Chandrashekhar, R. & Ramani, S. (2014). Ontology-based Smart Learning Environment for Teaching Word Problems in Mathematics, In G. Chen, V. Kumar, Kinshuk, R. Huang & S. C. Kong (Eds) Emerging Issues in 3 Smart Learning, Lecture Notes In Educational Technology, Berlin Heidelberg, pp. 251-258. (Cited by 4 as per GoogleScholar citation index) This paper has won the best paper award!
Lalingkar, A.; Chandrashekhar, R. & Ramani, S. (2011). An Educational Resources Broker System for Collaborative Sharing of Knowledge-Centric Content, In the Proceedings of International Conference on Technology for Education, July 14-16, 2011, Chennai, India. (Cited by 1 as per GoogleScholar citation index) (Paper Link )
Lalingkar, A., & Ramani, S. (2010). A Web-based Study Facilitation System. In the Proceedings of ED-MEDIA 2010: World Conference on Educational Multimedia, Hypermedia and Telecommunications, June 28- July 2, 2010, Toronto, Canada. (Cited by 3 as per GoogleScholar citation index) (Paper Link )
Lalingkar, A., & Ramani, S. (2009). A Student’s Assistant for Open e-learning. In the Proceedings of T4E’09: International Conference on Technology for Education, August 4-6, 2009, Bangalore, India, 62-67. (Cited by 4 as per GoogleScholar citation index) (Paper Link )
Chaitali Diwan is a PhD student at Web Science Lab, IIIT Bangalore. She holds a MTech in Data Science from IIIT Bangalore and B.E in Computer Science from VTU. Her research interests are web science, education technologies, NLP, multi-agent systems, semantic and web mining.
She has around 10 years of software development experience and has worked in MNCs like Samsung India Research Centre, Qwest Telecom Software Services and Accenture Services. She has majorly worked on web technologies, data-centric applications, data workflows during her tenure in the software industry. For more, please visit her Linkedin Profile.
Niharika Parasa, Chaitali Diwan, Srinath Srinivasa. “Automatic Riddle Generation For Learning Resources”. In Proceedings of the 23rd International Conference on Artificial Intelligence in Education (AIED 2022), 27-31 July, Durham University, UK
Prakhar Mishra, Chaitali Diwan, Srinath Srinivasa, G.Srinivasaraghavan. “A Semi-automatic approach for Generating Video Trailers for Learning Pathways”. In Proceedings of the23rd International Conference on Artificial Intelligence in Education (AIED 2022), 27-31 July, Durham University, UK
Prakhar Mishra, Chaitali Diwan, Srinath Srinivasa, G.Srinivasaraghavan. Automatic Title Generation for Text with Pre-trained Transformer Language Model. 15th IEEE Interantional Conference on Semantic Computing, Virtual, January 27-29, 2021. [nominated for best paper award]
Chaitali Diwan, Srinath Srinivasa, and Prasad Ram. Computing Exposition Coherence of Learning Resources, In Proceedings of The 17th International Conference on Ontologies, Databases and Applications of Semantics (ODBASE 2018), Springer LNCS, Valletta, Malta, October 22-26, 2018.
Raksha P.S is a PhD Student at Web Science Lab. She has a Master’s degree in Web Technology from PES Institute Of Technology, Bangalore and Bachelor’s degree in Computer Science from K S Institute Of Technology, Bangalore. Prior to joining IIITB she has worked as a Big Data Engineer at Cogknit Semantics Pvt Ltd, Bangalore. Previously she has worked on Ontology Based Semantic Data Validation, Big Data, Data Visualization using D3.js, Web Crawlers and Developing Learning Management System. Currently she is working on Characterizing online social cognition as a marketplace of opinions. Her research interests are Web Science, Network Science, Data Mining and Social Cognition. For more, please visit her Linkedin Profile.
Raksha Pavagada Subbanarasimha, Srinath Srinivasa and Sridhar Mandyam, “Invisible Stories That Drive Online Social Cognition,” in IEEE Transactions on Computational Social Systems, vol. 7, no. 5, pp. 1264-1277, Oct. 2020, doi: 10.1109/TCSS.2020.3009474.
Raksha Pavagada Subbanarasimha. 2019. Designing the Cogno-Web Observatory: To Characterize the Dynamics of Online Social Cognition. In Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining (WSDM ’19). ACM, New York, NY, USA, 814-815. DOI: https://doi.org/10.1145/3289600.3291600.
Srinivasa S., Pavagada Subbanarasimha R. (2018) Design of the Cogno Web Observatory for Characterizing Online Social Cognition. In: Anirban Mondal, Himanshu Gupta, Jaideep Srivastava, P.Krishna Reddy, D.V.L.N. Somayajulu. (eds) Big Data Analytics. BDA 2018. Lecture Notes in Computer Science. Springer, Cham. (To appear)
Raksha Pavagada Subbanarasimha, Lokesh Todwal, Mamillapalli Rachana, Aditya Naidu, and Srinath Srinivasa. 2018. Mithya: A Framework For Identifying Opinion Drivers On Social Media. Demo at ACM IKDD Conference on Data Science and International Conference on Management of Data, Goa, India, Jan 2018 (CODS-COMAD 2018).
Anish Bhanushali, Raksha Pavagada Subbanarasimha, and Srinath Srinivasa. Identifying Opinion Drivers on Social Media. In Proceedings of ODBASE 2017, Rhodes, Greece, October 23-27, 2017, Springer International Publishing, Cham, 242–253.
Course work:
Web Information Retrieval (Reading elective – CS 902)
Abstract: With the rise of social media, a vast amount of new primary research material has become available to social scientists, but the sheer volume and variety of this make it difficult to access through the traditional approaches: close reading and nuanced interpretations of manual qualitative coding and analysis. This work sets out to bridge the gap by developing semi-automated replacements for manual coding through a mixture of crowdsourcing and machine learning, seeded by the development of a careful manual coding scheme from a small sample of data. To show the promise of this approach, we attempt to create a nuanced categorisation of responses on Twitter to several cases of extreme circumstances.
Bio of speaker:
Dima is a Senior Data Scientist at Skyscanner where his focus is on developing and optimizing the Skyscanner’s travel search engine. Prior to Skyscanner, Dima was with King’s College London where he worked on analysis of BBC iPlayer (a joint project with BBC) and various social media websites (Twitter, Pinterest, Foursquare, etc.). He contributes to the data mining (KDD, WWW, etc.) and computer networks communities (Infocom, ComMag, etc.) and have his works featured by New Scientist, BBC News and other media outlets. Dima has also co-founded and was a former CEO of Stanfy.com. More information – https://karamshuk.github.io/.
Sweety Agrawal. Presented a paper entitled “Integrity Management in a Trusted Utilitarian Data Exchange Framework” at ODBASE 2014, Amantea, Italy, October 29 2014.
Srinath Srinivasa. Presented WSL and CDS at Ericsson Research, Bangalore. Sep 23 2014.
Sumant Kulkarni. Successfully completed the comprehensive exam and thesis proposal seminar, qualifying him for candidature towards a PhD. September 18 2014.
Sumant Kulkarni, Srinath Srinivasa. Attended review meeting for the project on Intelligent Workflow Management. EMC Bangalore HQ, Mahadevapura. Aug 18 2014.
Srinath Srinivasa. Presented WSL and CDS at KayBus Bangalore office. August 14 2014.
Srinath Srinivasa. Delivered an invited talk entitled Towards a “Mindful” Web at Trinity College, Dublin, Ireland. July 28 2014.
Srinath Srinivasa. Invited by School of Computer Scinence and Statistics and School of Digital Humanities at Trinity College, Dublin for exploring research collaborations. July 27–31 2014.
Aastha Madaan joined WSL as post doctoral research faculty on 23 July 2014.
Srinath Srinivasa. Attended the second NRDMS review meeting for the Sandesh project at NSDI office, New Delhi. 22 July 2014.
Jayati Deshmukh. Successfully defended MTech thesis entitled, “Evolution of Cooperation with Entrenchment Effects.” 16 June 2014.
OSL members hosted CrossCurrents, an Indo-UK workshop on the use of digital technology for culture preservation. May 12-14 2014. Photos from the workshop.
Srinath Srinivasa. Presented a paper at IIWeb 2014 at Chicago, Illnois, USA. March 31 2014.
Chinmay Jog, Sweety Agrawal. Attended ACM CoDS 2014 at New Delhi to present a paper. March 21-23 2014.
OSL members hosted a talk, “Towards Intelligent Information Infrastructure” by Prof. Pete Edwards, University of Aberdeen, Scotland, 6 Feb 2014.
Srinath Srinivasa. Delivered an invited talk entitled: Utilitarian Aggregation of Open Data at the Social Media Workshop, organized by the British High Commission at IIIT Bangalore. Feb 5-6, 2014.
Nisha Bhasia, Tuli Kundu, Divya Maharshi. Organizational volunteers for Social Media Workshop, organized by the British High Commission at IIIT Bangalore. Feb 5-6, 2014.
OSL members hosted a talk, “From Big Data to Smart Data” by Prof. Amit Sheth, Wright University. 6 Jan 2014.
Narrative Arc is one of the research projects under the umbrella of Navigated Learning project at Gooru Labs, IIITB.
The Narrative Arc refers to presenting the sequence of learning activities as a narrative to the learner to make learning interesting and to help the learner navigate seamlessly through the learning space.
The project has two parts: First is creating the learning pathways automatically given a corpus of learning resources, such that the generated pathways are semantically coherent and pedagogically progressive. Second part is modelling an AI-based automatic conversational agent which makes the learning pathway interesting and adapts the learning pathways according to the users knowledge and preferences. Here, the learning pathway is first presented to the user according to her learning goal, then the conversation agent interacts with the learner to keep the user interested in the learning pathway and to augment her knowledge. The agent also gauges the knowledge of the learner and supports the learner by providing knowledge and if required re-route the learner through a different learning pathway.
Following link has the presentation for the project in RISE 2019 workshop held at IIITB on 14-16 Feb 2019. The title of the presentation is “Narrative Arc Computation towards Digital Empowerment”.
Narrative Arc Computation
Chaitali Diwan, Srinath Srinivasa, and Prasad Ram. Computing Exposition Coherence of Learning Resources, In Proceedings of The 17th International Conference on Ontologies, Databases and Applications of Semantics (ODBASE 2018), Valletta, Malta, October 22-26, 2018, Springer International Publishing.
Navigated Learning is a new paradigm of learning that aims to balance the three independent requirements: Scale, Personalization and Social Interactions. Please see figure 1 that shows parallels among the concepts that are technological solutions and the three requirements of learning.
This is achieved by representing learning as situated within an abstract “competency space,” and computing semantic embeddings of learning objects and learners into the competency map. The competency map is organized as a progression space– which is a metric space with a partial order. Here, not only is there a notion of “distance” between any two points, but also an element of “progress”. These embeddings can be computed for any semantic object like learning resources, activities, learners, etc. Each point in the space represents a “competency” or a demonstrable skill that can be acquired by the learner.
A primary element of research into Navigated Learning is to construct a competency map for a given subject area of study and to build semantic embedding models for different kinds of objects relevant to the learning process. Semantic embeddings may take different forms depending on the nature of the object. While some objects can be neatly represented as points in the logical space, other objects may be represented by regions, pathways or other contours in the space. In an organizational setting, objects that are embedded onto this space include not just learning resources and learners, but also departments, projects and other organizational elements that require or work with relevant skill sets represented in the competency map.
Navigated learning is manged by a “Learning Navigator” with which every learner interacts. The Learning Navigator (or just, navigator), continuously interacts with the learning map and the learner to perform the following:
Locate: Based on data about their activities and outcomes from formal assessments, the “Locate” module of the navigator embeds learners in the space, and continuously updates their location. Unlike a geographical space, a learner may have acquired several competencies in the competency space. Thus, their location is not identified by a point, but by a data structure called a Skyline, that is detailed in a later section.
Curate: Once a learner’s location is known, based on their stated goals or recently acquired competencies, a set of further candidate competencies are identified. Curating is based on competency modeling principles, that identifies complementary, supplementary and conflicting competencies.
Mediate: This is the logic by which the navigator navigates the learner by making suggestions. Mediation is based on computing an underlying “Narrative Arc” that computes a semantically coherent and meaningful learning sequence individualized for each learner. Mediation also involves suggesting connections with other learners as well as group learning activities.
Aparna Lalingkar, Srinath Srinivasa, PrasadRam (2019), Characterization of Technology-based Mediations for Navigated Learning, Advanced Computing and Communications, Vol 3 (2), June 2019, ACCS Publications, pp. 33-47. (Paper Link)
Praseeda, Srinath Srinivasa and Prasad Ram “Validating the Myth of Average through Evidences” In: The 12th International Conference on Educational Data Mining, Michel Desmarais, Collin F. Lynch, Agathe Merceron, & Roger Nkambou (eds.) 2019, pp. 631 – 634
Chaitali Diwan, Srinath Srinivasa, and Prasad Ram. Computing Exposition Coherence of Learning Resources, In Proceedings of The 17th International Conference on Ontologies, Databases and Applications of Semantics (ODBASE 2018), Valletta, Malta, October 22-26, 2018, Springer International Publishing.
Lalingkar, A.; Srinivasa, S. & Ram, P. (2018). Deriving Semantics of Learning Mediations, In Proceedings of the 18th IEEE International Conference on Advanced Learning Technologies (ICALT), IEEE, pp. 54-55. (Cited by 1 as per GoogleScholar citation index) (Paper Link)
