Research
Causal Inference in Policy Recommendation
People in Pandemic:
Factors Impacting Response to Interventions
Morteza Maleki
Graduate Research Assistant
Department of Industrial and Systems Engineering
Mohsen Bahrami
Postdoctoral Research Associate
MIT Media Lab
Monica Menendez
Associate Professor
NYU Abu Dhabi
Jose Balsa
Post Doctoral Associate
NYU Abu Dhabi
In this research, we were interested in analyzing whether people respond differently to governmental mandates during the time of pandemic and what factors are important determinants of such differentiation in response. Various statistical methods were used along with controlled multiple regression and instrumental variable regression to measure causality. This work resulted in a publication submitted in Journal of Sustainability. This work was performed in collaboration with researchers from MIT IDSS (Dr. Mohsen Bahrami), NYU (Prof. Monica Menendez & Dr. Jose Balsa)

Causal Inference in Vaccine Promotion
Intelligent Gamified Approach to Vaccine Promotion
Morteza Maleki
Graduate Research Assistant
Georgia Tech Social Dynamics & Wellbeing Lab
Mohammadali Javidian
Postdoctoral Researcher
Purdue University
Pooyan Jamshidi
Associate Professor of Computer Science
UofSC Artificial Intelligence & Systems Lab
Gregory Trevors
Assistant Professor of Education
UofSC
In this project, we are interested in gaining insights on various methods using which people can be encouraged to take up vaccination and disregard conspiracy theories regarding COVID-19 and vaccination. An intelligent has been developed and people from United States and Canada have participated, and their responses to knowledge and emotional questions in the context of this game has been used to draw conclusions and identify causal relationships among various variables and intent to take up vaccination. This work was performed in collaboration with social scientists in Education department at the UofSC (Prof. Greg Trevors), Computer Scientists from Purdue University (Dr. Mohammadali Javidian), and Computational Scientists from UofSC (Prof. Pooyan Jamshidi)
Deep Learning in Wellbeing Analysis
Impact of Gratitude on Wellbeing of Individuals on Twitter
Morteza Maleki
Graduate Research Assistant
Georgia Tech Social Dynamics & Wellbeing Lab
Abhirup Mondal
Graduate Research Assistant
MIT Media Lab
Munmun De Choudhury
Associate Professor
Georgia Tech Social Dynamics & Wellbeing Lab
Louis Tay
Associate Professor
Purdue University Wellbeing & Measurement Lab
Stuti Thapa Magar
Graduate Research Assistant
Purdue University Wellbeing & Measurement Lab
David Newman
Postdoctoral Researcher
University of California - San Francisco
In this project, annotated tweets from thousands of random individuals were analyzed to identify the difference between gratitude towards God vs inter-human relationship and the impact of such gratitude on online behavior of individuals. This work was performed under supervision of Prof. Munmun De Choudhry from Georgia Tech's Social Dynamics and Wellbeing Lab (SocWeB) and in collaboration with Psychologists from Purdue University (Prof. Louis Tay and Stuti Thapa Magar) and University of California - San Francisco (Dr. David Newman)
Causal Inference in Misinformation Identification
Misinformation on Mobile Instant Messengers
Morteza Maleki
Graduate Research Assistant
Department of Industrial and Systems Engineering
Eaman Jahani
Postdoctoral Research Associate
MIT Media Lab
In this project, under supervision of Dr. Eaman Jahani (MIT IDSS recent graduate), we were analyzed the Randomized Control Trial experiment carried out in Myanmar, as a follow up to a similar experiment in India, where misinformation and conspiracy theory propagation in networks is analyzed and causal relationship between perceived credibility of person spreading misinformation and whether it is believable is further analyzed.
Interactive Data Visualization for Policy Recommendation
Health Equity & Justice Dashboard
Morteza Maleki
Graduate Research Assistant
Department of Industrial and Systems Engineering
Mohsin Khan
Graduate Research Assistant
Northeastern University
Morteza Maleki
Graduate Research Assistant
University of California - Berkeley
The Population Reference Bureau (PRB) requested us to design a data visualization tool, that can help PRB and other relevant stakeholders to identify the negative impact of COVID19 pandemic which disproportionately affects the vulnerable segment of the population, particularly the seniors (age 65+) and the minority groups across United States. By combining dataset from PRB, and third-party Covid- 19 and public health data, we developed a Health Equity & Justice Dashboard, to ascertain the impact of pandemic on targeted population, and disaggregate useful information on various health (death rates, vaccination rate, obesity, hesitancy to vaccinations etc.) and demographic (i.e. race, ethnicity, age) related indicators, which can assist in informed decision making process.
This work was performed in collaboration with researchers and graduate students from Northeastern University (Mohsin Khan), Berkeley University (Xingyan Lin), University of Saint Petersburg (Maxim Sinelnikov), and TIAS school of Business (Teo Bais).

CH Bond Activation using Organometallic Clusters
Studies of CH Activation in Unsaturated Amides and Esters
Morteza Maleki
Graduate Research Assistant
UofSC Chemistry Department
Richard Adams
Carolina Distinguished Professor of Chemistry
UofSC Chemistry Department
The chemistry of the reaction of Os3(CO)10(NCCH3)2 with representatives of unsaturated amides and esters, RCOCHCH2 (R=(CH3)2N, CH3O) has been investigated. In these reactions, it has been observed that a CH bond on the β-carbon atom is readily activated by triosmium carbonyl clusters. The activation of β-carbon C-H bond in unsaturated amides and esters provides a robust platform for studying multicenter C-H bond transformations and for C-C bond formation via hydrogen shift and CO insertion processes. In this work, proposed mechanistic approaches have been taken in order to better understand and study the relationship between the characterized species. In addition, a few non-identified species have been predicted to exist. Furthermore, recommendations on how this work can be further studied and improved have been made.
