Leadership
Deepthi Welaratna (she)
Founder & CEO
Deepthi Welaratna has spent two decades building and launching new campaigns, products and services at venture-backed startups, creative agencies, and market research firms, often in the early days of a new industry or issue. She worked on startup teams in the early days of podcasting and online food delivery, and her work to educate the public about the diamond industry made its way into the Wikipedia entry on conflict diamonds. Other memorable experiences include helping launch California’s first statewide down-ballot progressive voter guide in 2020, documenting the first hackathon held in Haiti, and live tweeting a former president to an audience of millions.
Her work in print, interactive, and radio has been featured by San Francisco's KQED Public Media, Stanford Social Innovation Review, and Makeshift Magazine among others. Featured speaker and facilitation engagements include SXSW, Parsons School of Design, Magnum Foundation, and the National Academy of Medicine. She is a fellow of the Royal Society for the Encouragement of Arts, Manufactures and Commerce (RSA) and a member of AIGA-LA.
Deepthi releases music as a solo artist under the name Dark Spring Thunder and is also one half of Society of the Wing and Scale along with Disparition. Her sound and video design work for live performance has been shown at venues in the SF Bay Area and NYC.
Deepthi was born in England, raised in Silicon Valley, has lived in Paris and New York, and her family is from Sri Lanka. She speaks English fluently, French carefully, and Sinhalese colloquially. She currently makes her home with her husband in Los Angeles.
FELLOWSHIPS
Royal Society for the encouragement of Arts, Manufactures, and Commerce (2019 - present), Startup Leadership Program (2017), SOCAP Global (2017), Personal Democracy Forum (2016)
AWARDS
Wilmer Shields Rich Gold Medal for Public Policy Campaign (2005)
SELECTED PUBLIC SPEAKING AND FACILITATION
Panelist, “Making Change Equitable”, RSA, London, UK, 2021.
Panelist, “Design for Democracy - Defense Against Disinformation.” AIGA, Los Angeles, CA, 2020.
Panelist, “Sustainable Activism.” BRIC Summit, Los Angeles, CA, 2020.
Panelist, “Civics Disrupted: The Rise and Potential of Political Entrepreneurship”, Generation Citizen, New York, NY, 2017.
Panelist, “Tech and Disconnected Youth”, SXSW Interactive 2016, Austin, TX, 2016.
Panelist, Design Intelligence Conference, Parsons School of Design, New York, NY, 2016.
Presenter, “Complex Evaluations.” American Evaluation Association, Chicago, IL, 2015.
Facilitator, “Designing Evaluations for What Communities Value.” National Academy of Medicine, Washington, DC, 2014.
Facilitator, “The Story of Data.” #PhotoEx Symposium and Workshop, Magnum Foundation, New York, NY, 2014.
Presenter, “Designing New Pathways for Learning.” Digital Media and Learning Conference, Boston, MA, 2014.
Facilitator, G-Everyone Hackathon. The Design Gym, LRN, 92Y, the UN, and Mashable, New York, NY, 2013.
Vijay Mago, Ph.D. (he)
Technology Advisor
Dr. Vijay Mago is a distinguished expert in machine learning and healthcare informatics, bringing over a decade of experience in these fields to his role as Technology Advisor at Thicket Labs. With a PhD in Modeling & Simulation and extensive experience in computer science, Dr. Mago has established himself as a leader in data science, particularly at the intersection of AI, big data analytics, and healthcare.
Throughout his collaboration with Thicket Labs, Dr. Mago has provided strategic guidance that has been instrumental in shaping the company’s AI-driven products. His expertise in healthcare informatics has been particularly valuable in ensuring that Thicket’s technology remains cutting-edge and relevant to the evolving needs of the industry. Dr. Mago’s input has been vital in the early stages of product development, where he has helped shape core algorithms and data models, keeping Thicket ahead of trends in machine learning and data science.
In addition to his advisory role, Dr. Mago has led several collaborative product development initiatives with Thicket Labs. He has overseen and mentored his students in the development of AI and data science projects that have expanded Thicket’s capabilities, particularly in healthcare-related applications. His focus on innovation and research has kept both Thicket Labs and his academic lab at the forefront of technological advancements, exploring new avenues in AI and healthcare informatics.
Dr. Mago continues to contribute to Thicket Labs as a key collaborator, focusing on joint development projects and research initiatives that push the boundaries of what AI can achieve in healthcare and beyond.
SELECTED PUBLICATIONS
Fisher, A., Young, M. M., Payer, D., Pacheco, K., Dubeau, C., & Mago, V. (2023). Automating detection of drug-related harms on social media: machine learning framework. Journal of medical internet research, 25, e43630.
Liyanage, C. R., Mago, V., Schiff, R., Ranta, K., Park, A., Lovato-Day, K., ... & Gokani, R. (2023). Understanding Why Many People Experiencing Homelessness Reported Migrating to a Small Canadian City: Machine Learning Approach With Augmented Data. JMIR Formative Research, 7, e43511.
Singhal, A., & Mago, V. (2023, August). Exploring How Healthcare Organizations Use Twitter: A Discourse Analysis. In Informatics (Vol. 10, No. 3, p. 65). MDPI.
Randle, T., Garg, A., Mago, V., Choudhury, S., Ohle, R., Strasser, R., ... & Savage, D. W. (2023). Staffing rural emergency departments in Ontario: The who, what and where. Canadian Journal of Rural Medicine, 28(2), 73.
Shahbandegan, A., Mago, V., Alaref, A., van der Pol, C. B., & Savage, D. W. (2022). Developing a machine learning model to predict patient need for computed tomography imaging in the emergency department. Plos One, 17(12), e0278229.
Baxi, M. K., Sharma, R., & Mago, V. (2022). Studying topic engagement and synergy among candidates for 2020 US Elections. Social Network Analysis and Mining, 12(1), 136.
Rao, G., Mago, V., Lingras, P., & Savage, D. W. (2022). AEDNav: indoor navigation for locating automated external defibrillator. BMC Medical Informatics and Decision Making, 22(2), 1-17.
Phatak, A., Savage, D. W., Ohle, R., Smith, J., & Mago, V. (2022). Medical Text Simplification Using Reinforcement Learning (TESLEA): Deep Learning–Based Text Simplification Approach. JMIR Medical Informatics, 10(11), e38095.
Singhal, A., Baxi, M. K., & Mago, V. (2022). Synergy Between Public and Private Health Care Organizations During COVID-19 on Twitter: Sentiment and Engagement Analysis Using Forecasting Models. JMIR Medical Informatics, 10(8), e37829.
Fisher, A., Gajderowicz, B., Latimer, E., Aubry, T., & Mago, V. (2022). BEAUT: An ExplainaBle deep learning model for agent-based populations with poor data. Knowledge-Based Systems, 248, 108836.
Garg, M., Saxena, C., Saha, S., Krishnan, V., Joshi, R., & Mago, V. (2022, June). CAMS: An Annotated Corpus for Causal Analysis of Mental Health Issues in Social Media Posts. In Proceedings of the Thirteenth Language Resources and Evaluation Conference (pp. 6387-6396).
Chandrasekaran, D., & Mago, V. (2021). Comparative analysis of word embeddings in assessing semantic similarity of complex sentences. IEEE Access, 9, 166395-166408.
Emu, M., Chandrasekaran, D., Mago, V., & Choudhury, S. (2021, June). Validating optimal COVID-19 vaccine distribution models. In International Conference on Computational Science (pp. 352-366). Cham: Springer International Publishing.
Zainab, K., Srivastava, G., & Mago, V. (2021). Identifying health related occupations of Twitter users through word embedding and deep neural networks. BMC bioinformatics, 22(10), 1-16.
Garg, A., & Mago, V. (2021). Role of machine learning in medical research: A survey. Computer science review, 40, 100370.
Chandrasekaran, D., & Mago, V. (2021). Evolution of semantic similarity—a survey. ACM Computing Surveys (CSUR), 54(2), 1-37.
Tassone, Joseph, Peizhi Yan, Mackenzie Simpson, Chetan Mendhe, Vijay Mago, and Salimur Choudhury. "Utilizing deep learning and graph mining to identify drug use on Twitter data." BMC Medical Informatics and Decision Making 20, no. 11 (2020): 1-15.
Rao, G., Choudhury, S., Lingras, P., Savage, D., & Mago, V. (2020). SURF: identifying and allocating resources during out-of-hospital cardiac arrest. BMC Medical Informatics and Decision Making, 20(11), 1-15.
Mendhe, C. H., Henderson, N., Srivastava, G., & Mago, V. (2020). A scalable platform to collect, store, visualize, and analyze big data in real time. IEEE Transactions on Computational Social Systems, 8(1), 260-269.
Fisher, A., Mago, V., & Latimer, E. (2020). Simulating the evolution of homeless populations in canada using modified deep q-learning (mdql) and modified neural fitted q-iteration (mnfq) algorithms. IEEE Access, 8, 92954-92968.
Khanam, K. Z., Srivastava, G., & Mago, V. (2023). The homophily principle in social network analysis: A survey. Multimedia Tools and Applications, 82(6), 8811-8854.
Khayyatkhoshnevis, P., Choudhury, S., Latimer, E., & Mago, V. (2020). Smart city response to homelessness. IEEE Access, 8, 11380-11392.
Shah, N., Srivastava, G., Savage, D. W., & Mago, V. (2020). Assessing Canadians health activity and nutritional habits through social media. Frontiers in public health, 7, 400.
Sharma, G., Srivastava, G., & Mago, V. (2019). A framework for automatic categorization of social data into medical domains. IEEE Transactions on Computational Social Systems, 7(1), 129-140.
Janda, H. K., Pawar, A., Du, S., & Mago, V. (2019). Syntactic, semantic and sentiment analysis: The joint effect on automated essay evaluation. IEEE Access, 7, 108486-108503.
Heppner, A., Pawar, A., Kivi, D., & Mago, V. (2019). Automating articulation: Applying natural language processing to post-secondary credit transfer. IEEE Access, 7, 48295-48306.
Sandhu, M., Vinson, C. D., Mago, V. K., & Giabbanelli, P. J. (2019). From associations to sarcasm: mining the shift of opinions regarding the supreme court on twitter. Online Social Networks and Media, 14, 100054.
Pawar, A., & Mago, V. (2019). Challenging the boundaries of unsupervised learning for semantic similarity. IEEE Access, 7, 16291-16308.
Robinson, K., & Mago, V. (2018). Birds of prey: identifying lexical irregularities in spam on twitter. Wireless Networks, 1-8.
Shah, N., Willick, D., & Mago, V. (2018). A framework for social media data analytics using Elasticsearch and Kibana. Wireless networks, 1-9.