Prediction of Indian Tiger population increase/decrease in future using Machine Learning techniques. pdf
I am a PhD student in University of Texas at Dallas (UTD) advised by Prof. Sriraam Natarajan as a part of the Statistical Relational Learning (StARLinG) group. I completed my MS degree from Indiana University Bloomington in 2015 with a GPA of 3.84/4 with my master's thesis
focused on creating novel features from galaxy images for spiral shape detection under Prof. David Crandall. My Bachelors was completed from Sir MVIT in Visvesvaraya Technological University with an aggregate of 79.82% along with a gold medal and an academic excellence award. I work in the general area of Machine learning and artificial intelligence and I am especially interested in
development and application of Machine Learning algorithms for medical domain. I am currently working on predicting drug-drug interactions and adverse drug events from SMILES strings and structural properties of the drugs themselves. I am also looking at machine learning methods for early detection of Alzheimer's and Parkinson's disease. Here is my current
I also write short stories as a hobby and am also an avid reader. I am currently reading Understanding Machine Learning: From Theory to Algorithms by Shai Ben-David and Shai Shalev-Shwartz. I am also reading A Pale Blue Dot by Carl Sagan.
A Few of my works
Devendra Singh Dhami. Morphological Classification of Galaxies into Spirals and Non-Spirals. pdf
1. Mayukh Das, Devendra Singh Dhami, Gautam Kunapuli, Kristian Kersting and Sriraam Natarajan. Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs , AAAI Conference on Artificial Intelligence (AAAI) 2019. pdf
2. Mayukh Das, Devendra Singh Dhami, Gautam Kunapuli, Kristian Kersting and Sriraam Natarajan. Approximate Counting for Fast Inference and Learning in Probabilistic Programming , The International Conference on Probabilistic Programming (PROBPROG) 2018. [2-page Abstract] pdf
3. Devendra Singh Dhami, Gautam Kunapuli, Mayukh Das, David Page and Sriraam Natarajan. Drug-Drug Interaction Discovery: Kernel Learning from Heterogeneous Similarities , The IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) 2018. pdf
4. Devendra Singh Dhami, Ameet Soni, David Page and Sriraam Natarajan. Identifying Parkinson's Patients : A Functional Gradient Boosting Approach , AI in Medicine (AIME) 2017. pdf
1. Devendra Singh Dhami, David Leake and Sriraam Natarajan. Knowledge-based Morphological Classification of Galaxies from Vision Features , KnowPros workshop AAAI 2017. pdf
1. John M Billings, Maxwell Eder, William C Flood, Devendra Singh Dhami, Sriraam Natarajan and Christopher T Whitlow. Machine Learning Applications to Resting-State Functional MR Imaging Analysis , Neuroimaging Clinics of North America, Volume 27, Issue 4, November 2017.
You can also find me on Facebook, Linkedin and Twitter using icons on the right and on Research Gate .