Faculty

Photo of Dr. Md Tamjidul Hoque

Dr. Md Tamjidul Hoque

Associate Professor

  • Ph.D., Monash University, Australia
  • Math 333
  • 504-280-2406
  • thoque@uno.edu

Dr. Hoque’s research interests include Protein Structure Prediction (PSP), focusing on disorder protein prediction, development of sampling algorithms, energy function, fold-recognition, binding-region prediction and Optimized Metabolic Network based Biofuel Production in Algae.

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Dr. Christopher Summa

Associate Professor

Dr. Summa’s interests include Protein Structure/Function Relationships, Protein Structure Prediction, and Protein Design and Engineering. His research focuses on technique development and applications in the fields of computational biology and bioinformatics, specifically: Macromolecular Structure Prediction and Refinement Large Scale Analysis of Known Macromolecule Structures De Novo Protein Design.


Graduate Research Assistants

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Md Kauser Ahmmed

Algorithm development for next generation gene‐protein regulatory network.

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Syvia Charchut

I work at the Naval Research Lab in the Geospatial Science and Technology branch. I am also enrolled at the University of New Orleans working on a Master’s in Computer Science and subsequently a PhD in Engineering and Applied Sciences. Currently my research is focused on applying machine‐learning techniques to interpolate bathymetry data using classification with various interpolation methods, supervised by Dr Hoque. Bathymetric data varies in density, collection, resolution etc… Therefore becoming difficult to apply a single “best” interpolation algorithm. The goal is to determine the best interpolation algorithm for a given area of interest using classification.

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Lijing Cui

Graduate Student, Lijing Cui is designing and developing a protein carbohydrate binding predictor under the supervision of Dr Hoque.

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Michael Anthony Flot

Michael Anthony Flot is a graduate student, working at Hoque Lab under the supervision of Dr Hoque. He is currently working on stacking approach based super secondary structure predictor.

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Suraj Gattani

Suraj Gattani is a graduate assistant, working at Hoque Lab under the supervision of Dr. Hoque. He is currently designing and developing a peptide-protein binding residue predictor.

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Corey Maryan

Corey Maryan is a Graduate Research Assistant working under Dr. Tamjidul Hoque. Corey is currently working on a project in collaboration with Naval Research Labs on the effects of machine learning with rip currents. The overall goal of the project is to find ways to identify and predict rip currents using techniques similar to facial recognition.

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Aaron Maus

Aaron is a Ph.D. student in the DENAS program at the University of New Orleans.

His previous work includes the analysis of energy functions, specifically exploring possible improvements for knowledge based Potentials of Mean Force. His current work focuses the structural determination of large protein complexes, in particular the gp160 envelope of HIV-1.

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Avdesh Mishra

Avdesh Mishra is a Ph.D. candidate for the Department of Computer Science at The University of New Orleans (UNO). He is a recipient of the Doctoral Award Scholarship by UNO. He currently researchers under the supervision of Dr. Tamjidul Hoque in the BioMaLL Lab. Prior to joining the lab, he worked as a software engineer for BitsCrafters an offshore software company. He completed his Bachelors of Science in Computer Engineering from the Advanced College of Engineering and Management affiliated to Tribhuvan University.

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Manisha Panta

Manisha Panta is a Graduate Computer Science Student at UNO, working under the supervision of Dr Hoque. Her concentration is Bioinformatics and Machine Learning. Her research focus is on applying machine-learning technique for hierarchical classification of Transposable Elements (TEs). TEs are the jumping genes or sequence of DNAs capable of moving within a host genome from one chromosome or plasmid location to another. It is important to identify and classify TEs to understand their effects on target genes and their role in the evolution of different genomes.

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Denson Smith

Denson Smith is a graduate research assistant working under Dr. Hoque’s Lab. His reasearch focus is using machine learning to detect seamounts.


Undergraduate Research Assistants

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Joel Andrepont

Joel Andrepont is an undergraduate student, working at Bioinformatics and Machine Learning Lab (BMLL) under the supervision of Dr. Hoque. He has been involved in design and development of the Lab’s website and web service that allows users to remotely run lab’s software over the cloud.

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Reecha Khanal

Reecha Khanal is an undergraduate Research Assistant at Hoque lab, working under the supervision of Dr Hoque. She is working on RNA binding protein rediction using machine-learning approaches.

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Pujan Pokhrel

Pujan Pokhrel is an undergrad Computer Science student at UNO with a concentration in Machine Learning and Bioinformatics. His field of interest is the use of various machine learning techniques for practical applications. His current field of research is the use of neural networks for protein structure prediction.

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Nishan Rayamajhee

Nishan Rayamajhee is an undergraduate student, working at Bioinformatics and Machine Learning Lab (BMLL) under the supervision of Dr. Hoque. He has been involved in design and development of the Lab’s website and web service that allows users to remotely run lab’s software over the cloud.


Past Lab Members

Photo of Chaitanya Anne

Chaitanya Anne

Chaitanya Anne is a Graduate Research Assistant working under Dr. Tamjidul Hoque. He is currently working on NASA project: “Data Analysis and Decision Support Using Advanced Text Analytics and Machine Learning” under the guidance of Dr Hoque. The objective of this project is to develop a set of automated tools that can assist NASA to manage and market NASA portfolio of intellectual properties (IP), and to enable easier discovery of relevant IP by users.

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Sumaiya Iqbal

Sumaiya Iqbal is a Ph.D. candidate in the department of Computer Science at the University of New Orleans (UNO). She obtained her B.Sc. and M.Sc. degree in Computer Science and Engineering from Bangladesh University of Engineering and Technology (BUET). Before starting this Ph.D. program, she worked as a faculty of the Computer Science and Engineering department at BUET. She is currently working as a doctoral research assistant in the Bioinformatics and Machine Learning lab. Her prior research works include algorithms in bioinformatics, development, analysis and application of evolutionary algorithms, etc. Her current research work focuses on protein structure prediction, identification of protein disorder and its critical correspondence with human diseases, development of machine learning based predictive tools and efficient sampling algorithms to find optimal solutions of complex problems.

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Md Nasrul Islan

ResearchSummaryofGraduateStudentofHoque‐Lab:MdNasrulIslamI am Md Nasrul Islam, a graduate student of computer science in the University of New Orleans. I am pursuing the MS in Computer Science degree with research option. My research area is Bioinformatics and I am working under the supervision of Dr. Hoque in Hoque lab. In my research I use machine learning tools such as neural network, random forest, support vector machine etc. or statistical methods, such as least square, along with highly efficient heuristic approach such as genetic algorithm. Any significant success in my research may help to identify the causes of many critical diseases such as cancer, type2 diabetes, Parkinson’s disease, Alzheimer’s disease and many more. It will also contribute to the development of current state of machine learning approaches

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Christian Winkler

I am Christian Winkler, a graduate student of Information Technology and Systems Management at Salzburg University of Applied Sciences. During my exchange semester at the University of New Orleans, I am working on my master’s thesis in the field of bioinformatics under the supervision of Dr. Hoque. My research focus aims to improve accuracy of profile‐Hidden Markov models in protein family prediction, by extending the scoring‐algorithm with predicted secondary structure.