I have been awarded Junior Faculty Excellence in Research Award at IST, Penn State! I consider this a collective effort and am very grateful to all my students, collaborators, and mentors! Read more details here.

Role: PI
Funding agency: College of IST, Penn State
Value: $33,000

Democratic Metaverse: Recovering Truth from Ranking Data.

Thank you, IST!

Role: Lead PI
Funding agency: National Science Foundation
Value: $552,417

Collaborative Research: RI: Medium: Transparent Fair Division of Indivisble Items.

Thank you, NSF!

Role: PI
Funding agency: College of IST, Penn State
Value: $55,000

Robust and Fair Matching Markets: From Rideshare to Kidney Exchange.

Thank you, IST!

Role: PI
Funding agency: Center for Socially Responsible AI, Penn State
Value: $5,000

Diversity and Fairness in Gig Economies..

Thank you, CSRAI!

Role: PI
Funding agency: National Science Foundation
Value: $16,000

NSF Research Experiences for Undergraduates: strategic aspects or fair and stable resource allocation.

Thank you, NSF!

Role: PI
Funding agency: National Science Foundation
Value: $173,656

Title: CRII: RI: Fair, Efficient, and Truthful Resource Allocation in Dynamic Environments

More information: National Science Foundation

Role: co-PI, with Carlos Rivero and Zack Butler
Funding agency: National Science Foundation
Value: $292,868

Title: IUSE: EHR: Using Program Dependence Graphs to Propagate Feedback to Students on Programming Assignments and Promote Responsive Teaching

More information: National Science Foundation

Role: PI
Funding agency: GCCIS, Rochester Institute of Technology
Value: $7,500

Title: Modeling Malicious Agents in Cyber Systems

Role: PI
Funding agency: Rochester Institute of Technology (Provost's Learning Innovation Grants)
Value: $4,864

Title: An Interactive Online Platform for Artificial Intelligence Education

Abstract: The main objective of this proposal is to design, implement, and assess new interactive tools for teaching various concepts in Artificial Intelligence (AI) with the goal of improving students’ cognitive ability for critical thinking. Artificial Intelligence techniques have had ubiquitous influence on all aspects of decision making from simple everyday tasks such as searching a term in search engines and pricing items on online platforms (e.g. eBay, Amazon) to sophisticated algorithms that guide autonomous self-driving vehicles. We plan to develop an online platform consisting of a series of interactive tools that enable learners and educators to experiment with AI-inspired algorithms, particularly in the subfield of AI called Multiagent Systems.

More information: Innovative Learning Insititute

Role: PI
Funding agency: Rochester Institute of Technology (Provost's Learning Innovation Grants)
Value: $4,860

Title: Enhancing Active Learning in Computer Science Education Through Gameplay

Abstract: The primary objective of this proposal is to design, implement, and evaluate new instructional development opportunities using game-based learning. Integrating games in higher education pedagogy will provide the opportunity for students to develop problem-solving and analytical skills through gameplay in a participatory and engaging approach. We plan to demonstrate the effectiveness of game-based teaching by enhancing students’ in-class learning experience at RIT.

More information: Innovative Learning Insititute

Role: PI
Funding agency: Rochester Institute of Technology
Value: $5,000

Title: Efficiency and Truthfulness in Matching Under Uncertainty

Abstract: Resource allocation problems have generated an interestingly rich interplay at the intersection of artificial intelligence, economics, and computer science. These problems are particularly important in the presence of multiple self-interested agents, where market design approaches such as matching and auctions are often applied to ensure fairness, efficiency, and truthfulness. The advent of online platforms gives rise to novel algorithmic and computational challenges in designing efficient and fair allocations, which require subtle practical, applicable, and scalable mechanisms. The proposed research aims to study two interconnected problems at the interaction of AI and economics in the following areas: (i) Dynamic allocation mechanisms, which investigates various efficiency and fairness measures of matching mechanism in dynamic and uncertain settings, (ii) Matching with uncertain population, which studies incentives and efficiency of matching decisions in sequential settings when agents arrive and depart dynamically over time.

More information: Sponsored Research Office

Role: co-PI
Funding agency: University of Waterloo (Centre for Teaching Excellence)
Value: $5,000

Title: Enhancing Learning Through Game-Based Learning

More information: Centre for Teaching Excellence, University of Waterloo

International Conference on Autonomous Agents and Multiagent Systems (AAMAS)

More information: AAMAS Awards

Natural Sciences and Engineering Research Council, Canada

More information: NSERC Fellowships

University of Waterloo

More information: Center for Teaching Excellence

University of Waterloo

More information: Graduate Studies

University of Waterloo

More information: Cheriton School of Computer Science

University of Waterloo

More information: Cheriton Symposium

University of Waterloo

More information: Distiniguished Teaching Assistantship Award

University of Waterloo

More information: Cheriton School of Computer Science

University of New Brunswick

More information: Outstanding Graduate Student