Akash Choudhuri
PhD student in Computer Science at the University of Iowa

I am a PhD student of Computer Science at The University of Iowa advised by Dr. Bijaya Adhikari. I also am a part of the Computational Epidemiology Research Group and the AlgoEpi Reading Group that discusses techniques and methods about algorithms, data mining, and Machine Learning that can be applied to problems related to the spread of infections.

• Updated Resume

My primary interests lie in the intersection of Machine Learning and Deep Learning with applications in Healthcare. I have been trying to construct predictive models that accurately estimate patient risk for different scenarios like CDI incidence and MICU Transfer. I have been using various data mining methods and developing some of my own methods to extract knowledge to aid that task. My primary programming language is Python and I have good knowledge of Tensorflow and PySpark. I also have a fair bit of experience in model risk validation for Financial Institutions during my stint as a Consultant at Solytics Partners LTD

Akash Choudhuri, Philip M. Polgreen, Alberto M. Segre, Bijaya Adhikari. (2024). Summarizing Clinical Notes using LLMs for ICU Bounceback and Length-of-Stay Prediction. In The 12th Data Mining in Biomedical Informatics and Healthcare (DMBIH’24) Workshop at ICDM 2024 (Paper) [Supplementary].

Akash Choudhuri, Hankyu Jang, Alberto M. Segre, Philip M. Polgreen, Kishlay Jha, Bijaya Adhikari. (2023). Continually-Adaptive Representation Learning Framework for Time-Sensitive Healthcare Applications. In ACM CIKM23 [Paper] [Code] [Slides].

Akash Choudhuri. (2023). A Hybrid Machine Learning Model for Estimation of Obesity Levels. In: Goswami, S., Barara, I.S., Goje, A., Mohan, C., Bruckstein, A.M. (eds) Data Management, Analytics and Innovation. ICDMAI 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 137. Springer, Singapore. [Paper] [Code].

Spring 2024: Conformal Prediction (intro) (domain).

Fall 2023: XAI + Hypergraphs (slides).

Spring 2023: Epidemics on Hypergraphs (slides).

Fall 2022: NLP+Domain (slides).

Spring 2022: PINNs (slides).

Fall 2021: Variational Autoencoder for Flu Forecasting (slides).

29th October 2023: Jeff will be presenting our work on Designing Near-Optimal Spatial Vaccine Allocation Strategies at the MIDAS Annual Meeting. All the best Jeff!

4th August 2023: Our work titled "Continually-Adaptive Representation Learning Framework for Time-Sensitive Healthcare Applications" got accepted in the Applied Track of 32nd ACM International Conference on Information and Knowledge Management . Acceptance Rate 24% overall. Yayy!

17th May, 2023: Starting my internship at the DSSI at the Lawrence Livermore National Lab, California. Whohoo!

22nd September 2022: I passed my Qualifier Examination! My Report and Presentation is located here.

January 2022: Finally started a new journey as a PhD Student and a Graduate Research Assistant at the University of Iowa.

August-December, 2021: Data Scientist at Data Sutram.

May-August, 2021: Data Scientist (Consultant) at Solytics Partners LTD.

February-April, 2021: Research Analyst at Counterpoint Research.

January 2020- February 2021: Intern at Solytics Partners LTD.

September 2021: Graduated with First Class (2nd in class) with M.Sc in Mathematics with Data Science from Institute of Mathematics and Applications Bhubaneswar, India.

June 2019: Graduated with First Class with Distinction with B.Sc in Mathematics and Computing from Birla Institute of Technology Mesra, India.

May-June, 2019: Selected for the Summer School in Quantitative Finance at Chennai Mathematical Institute, India.

May-August, 2018: Awarded the prestigious Summer Research Fellowship by the Indian Science Academies to work at Indian Statistical Institute, Kolkata, India.

June 2016: Finished schooling at St. Xavier's Collegiate School, Kolkata, India.

I was a serious Scrabble player as a kid but now play it for fun. I am an avid reader of the non-fiction genre, with Jefferey Archer, Amitav Ghosh, and Saradindu Gangopadhyay being some of my favourite authors. I love to sing and used to have an acoustic music band called Tritiyo Purush back while I was pursuing my undergraduate degree. I also love to play table tennis and badminton (although I am not good at them).

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