Exploring Space Through Astrophysics and AI
Astrophysics, AI, and space policy research. Explore projects, publications, and leadership in advancing science and technology.
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Key projects
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Academic Recognitions
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Leadership roles
Astrophysics, AI, and space policy research. Explore projects, publications, and leadership in advancing science and technology.
"My research journey has taken me from local beginnings to international recognition, proving that passion has no fixed horizon. I used to look up and see limits. Now I see directions."
Malaika Malik is a Pakistani student who grew up in Dubai and now studies astrophysics and cognitive science at the University of Toronto. She discovered her passion for astrophysics near the end of high school, though her curiosity for computation and analytical thinking began much earlier. Over time, she has built that passion into an intersection between astrophysics and artificial intelligence, exploring how data and algorithms can uncover new insights about the universe. Beyond her research, Malaika leads and contributes to several interdisciplinary initiatives that connect space, technology, and policy to make science and innovation more accessible worldwide.
Showcasing leadership in astrophysics, cognitive science, and space policy. Explore recent projects and ongoing research.
Presented at IAC 2025, this initiative expands satellite access and practical skills worldwide.
Analyzed Rosetta mission data to deepen knowledge of comet geology and surface activity.
Peer-reviewed research advancing understanding of stellar variability and data analysis.
Led multidisciplinary projects at University of Toronto, encouraging innovation and teamwork.
Recognized with scholarships for research excellence and leadership in science and policy at the University of Toronto (e.g Dean's List Scholar), doing an Astrophysics Thesis Course (AST425Y1).
Active in global collaborations shaping the future of space exploration and policy.
As the Research Lead for the University of Toronto’s Aerospace Team (UTAT), Malaika leads a major multi-country project developing a capacity building roadmap for emerging and non-spacefaring nations.
The project is grounded in novel, internationally scaled work, built from a large comparative study that gathered surveys and interviews from CubeSat experts across 13 countries. This cross-continental dataset is one of the most globally diverse and original collections created in student-led CubeSat capacity research.
Through this work, Malaika identified key global patterns that explain why early CubeSat programs either succeed, stall, or collapse. These include persistent issues with student continuity and turnover, limited financial literacy and budgeting structures, the uneven availability of infrastructure and testing facilities, and the long-term impact of institutional support, mentorship, and knowledge retention. By mapping these findings across national ecosystems, she showed how emerging space actors face systemic challenges that repeat across borders, regardless of region or resources.The significance of this research was recognized when it was accepted for an oral presentation at the International Astronautical Congress (IAC) 2025.
Malaika presented the project in Sydney, Australia, where the work received strong validation from capacity building experts, policy leaders, and international collaborators. This reception confirmed the novelty and global relevance of the research and sparked the continuation of the project on an expanded international scale.
Building on this momentum, Malaika is now working toward a practical, evidence-based framework designed to help emerging nations build sustainable CubeSat programs. This roadmap integrates the project’s findings into actionable guidance for developing training pipelines, improving program management, strengthening knowledge transfer, planning infrastructure development, and building long-term national capacity. The work aims to support governments, universities, and emerging space nations seeking accessible pathways into space.
The current plan is to refine and expand this roadmap through ongoing collaboration with international stakeholders, with the long-term vision of advancing global equity in space access and helping nations establish the foundations needed for meaningful participation in the space sector.
Co-Author with Professor John R. Percy (University of Toronto)
Published in the Journal of the American Association of Variable Star Observers (JAAVSO)
Malaika co-authored a peer-reviewed research paper with Professor John R. Percy, one of Canada’s leading experts in variable star astronomy, as part of a University of Toronto–based project on the complex variability of pulsating red giants. The study examined long-term observational data from the AAVSO and revealed a range of previously overlooked or poorly characterized behaviours in these stars.
These behaviours included unusual changes in pulsation period, the presence of multiple pulsation periods that vary in amplitude over time, non-sinusoidal and sometimes double-peaked light curves, very slow cyclic variations not explained by standard models, and long-term changes in average brightness.The research showed that many pulsating red giants display extreme extensions of normal variability, challenging existing assumptions about their evolution and internal structure. By identifying and characterizing these patterns, the work opened new directions for understanding the underlying physical mechanisms in late-stage stellar evolution.
The research was published in JAAVSO Volume 53, Number 2 (2025), and an accompanying conference proceeding was presented at the 114th Annual Meeting of the American Association of Variable Star Observers in Portland, Oregon (remote oral paper presented by Prof. Percy), where the results were shared with the international variable-star community.
Malaika is conducting a computational imaging study of Comet 67P using data collected by the European Space Agency’s Rosetta mission.
Through a collaboration with NYU Abu Dhabi, she works with 2048×2048 high resolution frames and applies a SAM2 based segmentation workflow specifically adapted for comet imaging. She designed a sliding window inference system that processes each frame in 512×512 tiles and reconstructs high fidelity, stable segmentation masks across the entire dataset.Her analysis focuses on how different preprocessing pipelines affect the recovery of dust jets, surface texture, and low intensity features, along with the broader morphological patterns that appear across the image slices.
By running segmentation under multiple conditions and comparing the resulting masks, she identifies subtle structural variations that are difficult to see through manual inspection alone. This approach provides new insight into how machine learning tools can reveal fine scale comet morphology from legacy space mission data.
The project contributes to ongoing efforts to integrate computer vision, astrophysical imaging, and data driven morphology studies. It also supports future work on developing automated pipelines for small body analysis, showing how modern segmentation models can extend the scientific value of missions like Rosetta and guide new methodologies for studying comets.
Find quick answers about my research focus, publications, leadership experience, and ways to connect or collaborate.
See projectsI specialize in astrophysics, cognitive science, and space policy. My projects include CubeSat development, comet imaging, and variable star research.
Links to my peer-reviewed articles and conference talks are available in the Projects and Publications sections.
I have led teams at the University of Toronto Aerospace Team and participated in international space research networks.
To connect or discuss collaboration, please use the contact form or email listed on this site.
Contact for project info or academic collaboration.
