Education

Emory University, Atlanta GA | Expected May 2023
PhD, Theoretical Biophysics | Advisor: Dr. Gordon Berman
Research Focus: Exploring predictive dynamics between hippocampus, visual cortex and behavior using tools from physics and machine learning. Learn more here.

Indian Institute of Science Education and Research, Mohali, India | 2012 – 2017
BS MS (Physics) | MS Thesis Advisor: Dr. Sudeshna Sinha
MS Thesis title: Synchronized populations resist persistent infection.

Publications

Jain, Kanishk; Berman, Gordon; (2019); Opening the black box of social behavior. Nature Neuroscience 22 (12), 1947-1948. link
Moitra, Promit; Jain, Kanishk; Sinha, Sudeshna; (2018); Anticipating persistent infection. EPL (Europhysics Letters) 121 (6). link
Kovach, Kristin; Davis-Fields, Megan; Irie, Yasuhiko; 8Jain, Kanishk**; Doorwar, Shashvat; Vuong, Katherine; Dhamani, Numa; Mohanty, Kishore; Touhami, Ahmed; Gordon, Vernita; (2016); *Evolutionary adaptations of biofilms infecting cystic fibrosis lungs promote mechanical toughness by adjusting polysaccharide production. Nature Partner Journal Biofilms and Microbiomes. link

Presentations

Jain, Kanishk; Menichini, Elena; Muzzu, Tomaso; Macke Jakob; Saleem, Aman; Berman, Gordon; Integrated tools for Behavioral and Neural dynamics. Simons Motor Consortium, August 13, 2020 | Talk
Jain, Kanishk; Menichini, Elena; Muzzu, Tomaso; Macke Jakob; Saleem, Aman; Berman, Gordon; Mapping long timescale dynamics of rat behavior. Physics of Living Systems Annual Meeting, June 8-11, 2020 | Talk Youtube
Jain, Kanishk; Menichini, Elena; Muzzu, Tomaso; Macke Jakob; Saleem, Aman; Berman, Gordon; Representing rat behavioral dynamics. FENS Forum of Neuroscience, July 11-15, 2020 | Poster Presentation

Fellowships

Simons-Emory International Motor Control Consortium Fellow | 2020
Innovation in Science Pursuit and Inspired Research (INSPIRE) Fellow | 2012 – 2017
Department of Science and Technology, Government of India

Skills

Coding : Advanced Python and MATLAB with focus on deep learning, libraries related to cleaning and exploring substantial time-series data using Machine Learning and making useful UIs. Quick learner with computational languages.
Mathematics : Advanced linear algebra, differential equations. Familiarity with topological topics in ML.

Research Projects

Modelling predictive dynamics between hippocampus, visual cortex and behavior
2018 – Present | Advisor: Dr. Gordon Berman, Emory University
We aim to characterize multi-timescale predictive dynamics between the hippocampus (‘memory’), visual cortex (‘visual perception’) and postural dynamics (‘behavior’) in unrestrained animals. Challenges overcome until now are extracting animal pose data from videos using deep learning markerless tracking tools, creating rich and concise multi-timescale mathematical description of ‘behavior‘ from animal pose time series using wavelet transformation, unsupervised machine learning and clustering techniques, and creating a multi-timescale representation of the behavioral dynamics using Recurrent Neural Networks. Long term aim is to create low-dimensional state space representation of behavioral and neural dynamics and explore causal dynamics between the memory, visual and behavioral processes.

Synchronization and persistence of infectious diseases
2016 – 2017 | Advisor: Dr. Sudeshna Sinha, IISER Mohali
Simulated infection dynamics on a finite lattice population model using SIRS model. Formulated and used a synchronization order parameter to investigate the dependence of global and local synchronization on the long-term persistence of infection in the population. We find a strong dependence between population synchronization at transient times to the persistence of infection at long timescales. Work resulted in publication.

Characterizing biofilm separation forces with Atomic Force Microscope data
Summer 2015 | Advisor: Dr. Vernita Gordon, UT Austin
Tackled the task of sorting and cleaning AFM data for various biofilm variants and identified peak forces that characterize the mechanical underpinnings of biofilm extracellular material. Created self-motivated GUIs that helped sort through overwhelming datasets which resulted in accelerated analysis and lead to publication.