Nishant Malik Headshot

Nishant Malik

Assistant Professor

School of Mathematics and Statistics
College of Science

585-475-5439
Office Hours
Mon 2:00-4:00pm, Wed 2:00-4:00pm
Office Location

Nishant Malik

Assistant Professor

School of Mathematics and Statistics
College of Science

Education

BS, MS, University of Delhi (India), M.Tech, University of Hyderabad (India), Ph.D., University of Potsdam (Germany)

Bio

Dr. Malik did his Ph.D. at the Potsdam Institute for Climate Impact Research in Germany under the supervision of renowned mathematical physicist Juergen Kurths. Subsequently, the Physical Society of Berlin awarded him the Carl Ramsauer Prize in 2012 for his Ph.D. work. Before joining RIT, he worked as a postdoc at Dartmouth College and UNC-Chapel Hill. Dr. Malik has a wide range of research interests in data-driven analysis and modeling of complex systems. In his research, he employs tools from network science, the theory of nonlinear and stochastic dynamical systems, and applied statistics and enjoys working on mathematical problems across disciplines in natural and social sciences. For more information, please visit Dr. Malik's personal webpage and the Complexity Lab @RIT his research group page. 

585-475-5439

Areas of Expertise

Select Scholarship

Journal Paper
James, Alexander, et al. "Detecting Paleoclimate Transitions With Laplacian Eigenmaps of Recurrence Matrices (LERM)." Paleoceanography and Paleoclimatology 39. (2024): e2023PA004700. Print.
Giammarese, Adam, Jacob Brown, and Nishant Malik. "Reconfiguration of Amazon’s connectivity in the climate system." Chaos: An Interdisciplinary Journal of Nonlinear Science 34. (2024): 13134. Print.
Bhuyan, K, et al. "Landslide topology uncovers failure movements." Nature Communications 15. 1 (2024): 2633. Print.
John, Nicholas and Nishant Malik. "Automated discovery of analytical models for epidemic dynamics on coevolving networks." Elsevier Journal of Computational Science 67. 101968 (2023): 1877-7503. Print.
McDanold, Jenna S and Nishant Malik. "Spatially extended radiant heat fire model." Physical Review E 107. 3 (2023): 34133. Print.
Jacobs, Ivan, et al. "In silico Antibody-Peptide Epitope prediction for Personalized cancer therapy." Frontiers in Applied Mathematics and Statistics 9. (2023): 1-12. Print.
Rana, Kamal, Nishant Malik, and Ugur Ozturk. "Landsifier v1.0: a Python library to estimate likely triggers of mapped landslides." Natural Hazards and Earth System Sciences 22. (2022): 3751–3764. Print.
Malik, Nishant, David Spencer, and Quang Neo Bui. "Power in the U.S. political economy: A network analysis." J Associate Inf Sci Technol.. (2021): 1-13. Print.
Rana, Kamal, Ugur Ozturk, and Nishant Malik. "Landslide Geometry Reveals its Trigger." Geophysical Research Letters. (2021): e2020GL090848. Print.
Malik, Nishant. "Uncovering Transitions in Paleoclimate Time Series and the Climate Driven Demise of an Ancient Civilization." Chaos: An Interdisciplinary Journal of Nonlinear Science 30. (2020): 83108. Print.
Malik, Nishant and Ugur Ozturk. "Rare Events in Complex Ssystems: Understandingand Prediction." Chaos: An Interdisciplinary Journal of Nonlinear Science 30 (9), 090401 30. (2020): 90401. Print.
Lee, Hsuan-Wei, et al. "Social clustering in epidemic spread on coevolving networks." Physical Review E 99. 62301 (2019): 1-14. Print.
Ozturk, Ugur, et al. "A Network‐based Comparative Study of Extreme Tropical and Frontal Storm Rainfall Over Japan." Climate Dynamics 53. (2019): 521–532. Print.
Barnett, Ian, et al. "EndNote: Feature-based classification of networks." Network Science. (2019): 1-7. Print.
Invited Keynote/Presentation
Malik, Nishant. "Data-Driven Modeling of Complex Systems." Frontiers in Geosciences. Los Alamos National Lab. Los Alamos, NM. 21 Nov. 2022. Lecture.
Malik, Nishant, et al. "Understanding and Prediction of RegionalClimate Phenomena using Climate Network Analysis." SIAM Conference on Application of Dynamical Systems, Minisymposium on Dynamical Systems on Networks: Stability and Applications. SIAM. Online, Virtual Conference. 27 May 2021. Conference Presentation.
Malik, Nishant. "Network Classification and Applications to Climate Forecasting." SIAM Conference on Discrete Mathematics (Minisymposium on Graph Theory and Machine Learning). SIAM. Online, US. 21 Jul. 2021. Conference Presentation.
Malik, Nishant. "Uncovering Dynamical Transitions in Paleoclimate Time Series." Third Northeast Regional Conference on Complex Systems. Department of Mathematics, University at Buffalo, SUNY. Buffalo, NY (ONLINE), NY. 3 Apr. 2020. Conference Presentation.
Malik, Nishant. "Integrating Methods of Network Science, Dynamical Systems, and Machine Learning for Data Analysis." Chapman Chair Lecture Series: Complex Systems Meet Machine Learning:From Basics to Real Applications,. CNSM, University of Alaska, Fairbanks. Fairbanks, Alaska. 28 May 2019. Lecture.

Currently Teaching

IMGS-699
0 Credits
This course is a cooperative education experience for graduate imaging science students.
IMGS-740
3 Credits
The analysis and solution of imaging science systems problems for students enrolled in the MS Project capstone paper option.
IMGS-790
1 - 6 Credits
Masters-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.
IMGS-890
1 - 6 Credits
Doctoral-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.
IMGS-891
0 Credits
Continuation of Thesis
MATH-182
4 Credits
This is the second in a two-course sequence. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers techniques of integration including integration by parts, partial fractions, improper integrals, applications of integration, representing functions by infinite series, convergence and divergence of series, parametric curves, and polar coordinates.
MATH-251
3 Credits
This course introduces sample spaces and events, axioms of probability, counting techniques, conditional probability and independence, distributions of discrete and continuous random variables, joint distributions (discrete and continuous), the central limit theorem, descriptive statistics, interval estimation, and applications of probability and statistics to real-world problems. A statistical package such as Minitab or R is used for data analysis and statistical applications.
MATH-495
1 - 3 Credits
This course is a faculty-directed project that could be considered original in nature. The level of work is appropriate for students in their final two years of undergraduate study.
MATH-498
1 - 3 Credits
This course is a faculty-guided investigation into appropriate topics that are not part of the curriculum.
MATH-689
1 - 4 Credits
Special Topics courses cover content that is not represented in the main curriculum on an experimental or trial basis.
MATH-709
3 Credits
In this course, students will explore complex networks: the mathematical objects used in the modeling and analysis of various complex systems in nature and society. This course will introduce students to basic network models, methods for the classification of networks, mechanisms that generate multiple classes of networks, measures and algorithms for quantifying local and global network structures, and frameworks used in modeling dynamical processes involving networks, including the diffusion of social and biological contagions on networks. Students will also learn Python-based software packages, including visualization techniques used in network analysis.
MATH-790
0 - 9 Credits
Masters-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.
MATH-791
0 Credits
Continuation of Thesis

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