Post doctoral fellows




    Doctoral students



    (Research Intern :- July 2020 - Present)

    Affiliation: M.Tech in Statistical Computing (Data Science) from SCSS, JNU

    Research Interests: I'm passionate about improving lives using biomedical data, machine learning and deep learning techniques.

    Current Project: My current project focuses on analysis of biomedical time-series data specifically ECG data. 


    Ajay Arya

    (PhD; Jan 06, 2017 onwards- Submitted)

    Previous affiliation: Completed M. Tech. in Bioinformatics from University of Hyderabad

    Research Interests: I am interested in machine learning (classical and deep learning) techniques to predict DNA-protein interactions, drug resistance prevalence/pattern and binding/active sites of DNA or proteins. I am interested in applications of these methods to the development of new drugs/vaccines and disease diagnosis.

    Current Project: Transcription factors (TFs) have been known for long to bind to specific conserved motifs (TF binding sites TFBS), thereby initiating and regulating genes associated with those sequences. This is the key step or precursor to cell development and organization, to generate a functional unit of life. Most recently our lab has developed a novel method to study DNA shape viz. DynaSeq. In this approach, the scope of shape parameters has been broadened to look into the dynamics instead of static properties and into the other conformational features, which improve the insights earlier obtained by DNAshape. Our lab is working on novel sequence-based conformational ensemble prediction method(DynaSeq) and cell specific protein-DNA interactions. So I am currently working on improvement of methods to model protein-DNA complexes using DynaSeq-predicted DNA structures and investigating their specificity.


    Dana Mary Varghese

    (PhD; July 28, 2017 onwards)

    Previous affiliation: M.Tech. in Bioinformatics from Karunya University,Coimbatore; M.Sc. in Biotechnology from VIT University, Vellore; B.Sc. in Biotechnology from Dr.G.R.Damodaran College of Science, Bharatiar University, Coimbatore.

    Research Interests: My interest lies in applying machine learning approach to understand the condition specific functional regulation and interactions of protein and DNA.

    Current Project: In this post genomic era functional annotation of genomes is a challenging process, discovery of moonlighting proteins, nature's way of multitasking has lead to many compelling questions. A lot of proteomics studies are carried out to identify drug targets but the moonlighting ability of certain proteins further complicates the analysis of gene expression, protein-protein interaction and other such studies. Moonlighting properties of proteins have been implicated in several diseases, bacterial virulence .It may possibly play a role in side effects caused by drugs. I am currently working on function prediction of moonlighting proteins. In future I hope to study condition specific interactions of these proteins in systems level.


    Manisha Kalsan

    (PhD; July 30, 2017 onwards)

    Previous affiliation: M.Tech. in Bioinformatics from Delhi Technological University, Delhi; B.Tech. in Biotechnology from D C R University of Science & Technology, Murthal, Sonepat

    Research Interests: My interest lies in the applications of machine learning techniques to study the sequential and structural features of different transcription factors and their target sites, and to predict the different states of a genome on the basis of the conformational parameters of the DNA to annotate the genome for novel insights. I am also interested in developing predictors based on shape profiles for different types of target sites for a transcription factor, showing different temporal pattern.

    Current Project: Transcription factors (TFs) have been broadly divided into three different classes- pioneer, migrant and settler, on the basis of their ability to recognize different target chromatin. My work aims to apply machine learning techniques to learn the structural features of TFs and/or target sites to classify these TFs into the above mentioned classes. My work also aims to gain insights into the spatiotemporal dynamics of different TFs and the cellular specificity of their targets which hold great importance for the regulation of gene expression.


    Shruti Gupta

    (PhD; July 28, 2017 onwards)

    Previous affiliation: M.Sc. Computational and Integrative Sciences, School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi;B.Sc.(H) Biomedical Sciences, Acharya Narendra Dev College, University of Delhi, New Delhi

    Research Interests: I am interested in predictive analytics and re-purposing of biological data to address questions in systems biology and to develop computational tools which can aid in the application of these studies further.

    Current Project: I am currently working on protein complexes classification problem as an extension to the previously published tool PPiPP. Along with that, I am looking into profile based mining of gene expression datasets and effects of query partialisation on the overall data.



    Anuja Jain

    (PhD; July 22, 2018 onwards)

    Previous Affiliation: M.Sc. in Bioinformatics from Banasthali University, Rajasthan; B.Sc. in Biotechnology from Devi Ahilya Vishwavidyalaya, Indore, Madhya Pradesh.

    Research Interests: Focus of my research is to develop a computational method for uncovering the relationship between cell, gene and drugs. I am also very much passionate about drug repurposing of biological data to achieve this objective using Genomics and Immunoinformatics perspectives.

    Current Project: I am currently performing meta analysis of transcriptome profiles collected under different conditions for studying various pathways. And very much curious to know how these transcriptome profiles are enriched in these pathway associated gene sets. As an application of this analysis, I have been investigating prototype pathways involving TLRs. Meta analysis of hundreds of thousands of transcriptome profiles collected in GEO, arrayExpress and LINCS data sets are my primary source of information. This study might helpful to identify functional relationships among diseases, physiological processes and action of small molecules using gene expression profiles.


    Arfa Jabin 

    (PhD; July 22, 2018 onwards- de-Registered)

    Previous affiliation: M.Sc from SCIS, Jawaharlal Nehru University; Bachelor of Computer Application from Aligarh Muslim University, Aligarh

    Research Interests: Machine Learning, Neural Networks, Genome Analysis, Big Data Analytics, Computational Biology, Cloud Computing, Data Mining, Image Analysis, Transcriptome Analysis.

    Current Project: Data Compression is a technique to reduce the number of bits to store and transmit the data. There are various data compression techniques that are lossy as well as lossless. The project is about finding new and better algorithm for data compression by getting ideas from previous techniques like Huffman Coding, Burrows Wheeler Transform , gzip2 etc. with a primary focus on compressing DNA sequence data.


    Neha Vinayak

    (PhD: July, 2018 onwards)(Part-time)

    Previous affiliation: M.S. in Software Systems from BITS Pilani; B.Tech in Computer Science and Engineering from West Bengal University of Technology.

    Research Interests: Machine Learning, Artificial Neural Networks, Deep Learning, Machine Learning applications in clinical studies of Lymphedema.

    Current Project: I am working on benchmarking the performance of existing deep neural network training algorithms. Further, this will help in developing some novel strategies to improve the neural network training. I am also working on the applications of machine learning in clinical studies of Lymphedema treatment.


    Doctoral students (Co-supervised at SciWhyLab)



    Akash Ajay 

    Ph.D. since – August 2016, joined SciWhy Lab in May 2018

    Previous affiliation – University of Hyderabad, IMSc Sytems Biology (2016)

    Research Interests –I am interested in applying systems biology methods to answer questions in evolutionary theory and molecular evolution. Some of the problems which interest me in this field include - the mutation propensity, fitness landscapes associated with mutations, the interactome evolution at genome-scale, study of evolutionary trajectories and problems which relate the structure and evolution of the molecules in general. Understanding these kinds of problems can help in making the evolutionary theory more comprehensive, apart from enhancing our knowledge in more practical problems of disease genetics, host-pathogen interaction, resistance to the drugs and cancer development which can be explored in future.

    Current Project-We are trying to understand the role of DNA intrinsic factors in the evolution of mutational dynamics. Properties like DNA shape and supercoiling are being explored. 



    Junior Research Fellows and other Research Staff



    Saumya Priyadarshini

    (Junior Research Fellow; April 1, 2019 -September 30, 2019)

    (Collaborative Researcher; October 3, 2019 onwards)

    Previous affiliation: Research Assistant in SciWhyLab from Oct 01,2017-March 31,2019, M.Tech in Biomedical Engineering from Delhi Technological University; B.Tech in Electronics and Communication from Rajasthan Technical university.

    Research Interests: My research interests lies in the area of Signal Processing, Machine Learning, Data Analysis. I want to implement these tools for understanding brain dynamics and neural connectivity.

    Current Project: In SciWhyLab, my project concerns with the classification of Brain MRI Data using Machine Learning technique. I am interested in knowing the capabilities of neuroinformatic tools and brain simulation tools which are important for the analysis of increasingly large-volume, high-dimensional experimental data.

    Also working in the area of NIPT( Non Invasive Prenatal Testing). My objective is to develop a pipeline for early diagnosis of genetic abnormalities in a developing fetus.



    Seema Rani

    (Junior Research Fellow; April 09, 2019 onwards) Previous affiliation: M.Tech in Computer Science and Engineering from maharshi dayanand university Rohtak; Master in Computer Applications from Banasthali University,3.5 years work experience as a software Engineer in 9Dot9 Group . Current Project:I am currently working on "Dimensionality reduction of genomic and transcriptomic data sets” .This project involves meta-analysis of transcriptomic data sets emerging from biological data using machine learning and big data technologies.



    Akanksha Mishra

    (Junior Research Fellow; March 22, 2019 onwards) Previous affiliation: M.Tech in Biomedical Engineering from Indian Institute of Technology Bombay; B.Tech in Biotechnology from Vellore Institute of Technology.

    Current Project : I am currently working towards Identifying genome wide DNA conformation of Mycobacterium Tuberculosis as markers for disease prognosis.





    Nimmi Nelson
    (Research Intern:-December 2022-June 2023)

    Affiliation:Post Graduate Diploma in Big Data Analytics from School of Computational and Integrative Sciences,JNU, New Delhi;
    MSc. Statistics from Kannur University ;
    BSc. Mathematics from Govt. Arts and Science College, Kozhikode, Kerala.

    Research Interests:Machine Learning, Data Science, Statistics

    Project:The project is about finding the best performance metric in classifiers.The performance metrics considered for the study are accuracy score, f1 score and Matthews correlation coefficient. Imbalanced synthetic binary data is used for this research. Accuracy of prediction of the true data to the predicted data is found out at different class balances. And performance metrics are evaluated using scikit-learn library in python, which is a library used for machine learning.


    Avinash Kumar
    (Research Intern:-December 2022-Present)

    Affiliation:Post Graduate Diploma in Big Data Analytics from School of Computational and Integrative Sciences,JNU, New Delhi

    Research Interests:Data Science,Deep learning,Machine Learning.
    PROJECT :-Malaria Image Cell Classification using CNN


    Md Tarique Israr
    (Research Intern:-December 2022-Present)

    Affiliation:Post Graduate Diploma in Big Data Analytics from School of Computational and Integrative Sciences,JNU, New Delhi
    BSc-IT from Marwari College,Tilka Manjhi University Bhagalpur , Bihar

    Research Interests:Artificial intelligence,Machine Learning, Data Science,Big Data

    Project:1. Pubmed Articles Recommendation System, 2. Brain Tumor Classification using CNN



    Sourav Goswami

    (Research Intern :- September 2020 - Present)

    Affiliation: M.Sc in Computational and Integrative Sciences (Specialization in Computational Biology) from SCIS, JNU.
    B.Sc.(Hons.) in Chemistry from University of Calcutta.

    Research Interests: Genomic Data Science, Disease prediction, Personalized Medicine.

    Current Project: M.Sc. Dissertation Project titled "Investigation of a relationship between Co-expression and Co-location of genes"


    Paridhi Saxena

    (Master’s Fellow, Sep 2020- Present)

    Affiliation: MSc in Computational Biology from SCIS, JNU, BSc in Life Science from University of Delhi 

    Research Interests: Computational Biology and Bioinformatics, Genome Analysis 

    Current Project: Reanalysis of topological Hi-C derived data to study three dimensional structures of bacterial chromosomes and establish a structure-function relationship 


    Ritesh Yadav

    (Research Intern :- July 2021 - Present)

    Affiliation: Post Graduate Diploma in Big Data Analytics, SCIS, JNU

    Research Interests: Big Data, Machine Learning, Deep Learning.

    Current Project: Comparative analysis of X ray images, using deep learning Techniques.


    Harish Manoharan

    (Research Intern :- June-Aug 2021)

    Affiliation: Undergoing Dual degree(BS+MS) in Biological Sciences from IIT Madras

    Research Interests: Bioinformatics, Algorithms, Machine Learning

    Current Project: Deconvolution of bulk gene expression data to find individual cell populations in tumor microenvironment


    Kushal T

    (Research Intern :- June 2021 - Present)

    Affiliation: Biological Engineering (Dual Degree) from IIT Madras

    Research Interests: Machine Learning, Big Data Analytics

    Current Project: Tumor Deconvolution using bulk gene expression data



    (Research Volunteer)

    Affiliation: Ph.D. in Bioinformatics from Jamia Millia Islamia, New Delhi, India

    Research Interests: Artificial Intelligence and Machine Learning in Drug development, Precision Medicine, Biological Data Analytics, Microarray and Next Generation Sequencing (NGS) data analysis, Cancer research, Viral disease research, er Biology.



    Chandrima Barua

    (Research Volunteer :- March 2021 - Present)

    Affiliation: MS in Complex System from SCIS, JNU

    Research Interests: Machine Learning, Natural Language Processing, Data Science



    (Research Volunteer :- March 2021 - Present)

    Affiliation: M.Sc. Computational and Integrative Sciences with specialization in Bioinformatics

    Research Interests: Machine learning, Deep learning, Image Processing and Analysis


    Roquiya Tazeen Fatima

    (Research Intern: Sept. 2023 - Present)

    Affiliation: Post Graduate Diploma in Bioinformatics, Computational Biology and Drug Discovery, Dr. B.R. Ambedkar Centre for Biomedical Research, University of Delhi.

    Research Interests: Machine Learning, Drug Discovery, Deep Learning, Data Analysis.

    Current Project: The project I am currently working on focuses on the inter-species translatability. I am using drug toxicity based  gene expression data of rat and human to make a ML based predictive model to understand how much biological perturbation can be translated across species. This research could have significant implications for understanding the safety and efficacy of drugs across species and potentially improving drug development processes.


    Sakshi Taware

    (Research Intern: January 2023 - Present)

    Affiliation : B.Tech in Biotechnology from DPU, Pune

    Research Interests: Drug Discovery, Systems Biology, Machine Learning

    Current Project: Comparative analysis of data from multiple NGS techniques for TFs in K562 cell line.


    Pallavi Singh

    (Research intern: January 2023 - present)

    Affiliation : M.Sc in Bioinformatics from CUSB(Central University of South Bihar). B.Sc(Hons.) in Biotechnology from GLA University, Mathura.

    Research interests : Drug Discovery, Machine learning, Genomics


    Anjali Shahi

    (Research Intern: January 2023 - present)

    Affiliation: M.Sc. in biotechnology from IMS Ghaziabad, CCS university.

    Research Interest :  Computational genomics, Data analysis.

    Current Project - Critical Analysis of Topologically Associated Domains in Developmental cells.


    Abha Pandey

    (Research Intern: March 2023 - Present)

    Affiliation- M.Sc. in Bioinformatics from the University of Allahabad

    Research Interest - Structural biology, Network biology and Data analysis.


    Kushal Poddar

    (Research Intern :- Sep 2020 - Present)

    Affiliation: Integrated Btech & Mtech from SoE, JNU

    Research Interests: Software Development, Machine learning, Data Analytics

    Current Project: ASAView 2.0, Genome Snapshot Analysis


    Ritika Jha

    (Research Intern :- Sep 2020 - Present)

    Affiliation: Integrated Btech & Mtech from SoE, JNU

    Research Interests: Machine learning, Deep learning, Image processing, Data Analysis

    Current Project: ECG image digitization and classification, detection of apnea anomaly in given ECG sample


    Rohan Kumar

    (Research Intern :- Sep 2020 - Present)

    Affiliation: Integrated Btech & Mtech from SoE, JNU

    Research Interests: Data Analytics, Neural Nets, NLP

    Current Project: NLP based query and analysis of multi-platform gene expression data, Covid tweet sentimental analysis along with correlation between mortality rate and number of tweets for different countries


    Arya Dwivedi

    (Research Intern :- July 2021 - Present)

    Affiliation: Integrated Btech & Mtech from SoE, JNU

    Research Interests: Machine Learning, Deep Learning, Neural Networks , Data Analytics, Cloud Computing.

    Current Project: Currently working on fully automatic segmentation of sinonasal cavity and pharyngeal airway based on convolutional neural networks.


    Asad Nizami

    (Research Intern :- May-July 2021)

    Affiliation: Integrated Btech & Mtech from SoE, JNU

    Research Interests: Machine Learning, Deep Learning, Time Series Analysis

    Current Project: Covid data analysis - Demonstrate the relation between age and gender wise covid cases with geographical location in India


    Past Members


    Tina Begum

    Previous affiliation:- Postdoc in Computational Biology and Phylogenomics from University of Lausanne, Swiss Institute of Bioinformatics, Switzerland; Postdoc in Evolutionary Bioinformatics from Tripura University, Tripura, India; Ph.D. in Evolutionary Bioinformatics from Bose Institute, Kolkata, India; M.Tech. in Bioinformatics from West Bengal University of Technology, Kolkata, India; B.Tech. in Biotechnology from Bengal College of Engineering and Technology, Durgapur, India.

    Research Interests:- Phylogenomic data modeling to understand phenotypic evolution, Phylogenetic Comparative Methods (PCMs), gene and genome duplication mechanisms, molecular sequence evolution, Next Generation Sequencing (NGS) analysis, machine learning techniques. 

    Current Project :- Nucleic acid (NA) sensing proteins play important roles in pathogen-specific host responses. In this context, my current project aims to explore the sequence based, structural, gene-expression and functional features of pathogen specific NA sensors in a wide range of hosts. Such features can be used further to predict unknown NA sensor molecules with the aid of machine learning approaches.


    L Raghavendran

    (October 2019 -)

    Previous affiliation: Postdoc at Institute of Bioinformatics and Applied Biotechnology (IBAB), Bengaluru. PhD in Computational Biology from Max-Planck Institute for Bio-Physical Chemistry, Germany.

    Research Interests: Machine Learning in Medicine, Precision Oncology, Cancer Biology.

    Current Project: My current project focuses on evaluating a range of Machine Learning (ML) techniques for its ability to predict the tumor response to a treatment. For this purpose, these ML models will be trained on in vitro pharmacogenomics data from tumors with multiple molecular profiles.


    Ajay Kumar Verma

    (Ph.D. : July 31, 2013-2022 )

    Previous affiliation: M.Tech in Computer Science & Technology from Jawaharlal Nehru University; M.A. in Mathematics, B.A.(Hons) in Mathematics from Banaras Hindu University.

    Research Interests: My interests are in the area of Machine learning, Data mining, and Bioinformatics

    Current Project:I am currently working on denoising gene expression data for integrative meta analysis using deep learning.


    Shyam Kumar

    (July 2019 onwards)

    Previous affiliation: M.Sc. in Physics from IIT Gandhinagar, Gujarat;      B.Sc. (Hons) Physics, ANS College Nabinagar, Magadh University Bodh Gaya, Bihar.

    Research Interests: Machine learning, Neural Network, Complex networks, Nonlinear Dynamics

    Research Project: Machine learning and Biophysical approaches for genome-wide transcription factors dynamics.


    Anima kujur

    (PhD; July, 2019 onwards)

    Previous affiliation – M.Sc. in Mathematics, from University of Hyderabad; MCA from SC&SS, Jawaharlal Nehru University.

    Research Interests –Machine Learning, Deep Learning, Neural Networks, Machine Learning applications in Biomedical Image Data.

    Current Project-I am working on Neural Network Architecture Optimization in order to develop  the better understanding and the protocol  about why  a certain neural network architecture behaves,  the way it behaves with the biomedical image data.


    Samatha Kancharla

    (May - July 2021)

    Current Affiliation: Dual degree from the School of Engineering, JNU in Electronics and Communication Engineering.

    I worked on creating synthetic data concerning many ellipses into a pair wise distance matrix and to develop a prediction model that can reproduce the ratio of minor to the major axis in the original ellipse using neural networks.


    Nivedita Rai

    (October 2019 - January 2021)

    Previous affiliation: Ph.D. from Pondicherry University, Pondicherry; M.Sc. Bioinformatics and B.Sc. in Botany, Chemistry from the University of Allahabad, Uttar Pradesh, India.

    Research Interests: My research work lies in Understanding of structural Dynamics of Multimeric proteins like HtrA and their activation mechanism & identification of the novel therapeutic target. Along with this, I am also looking for Integrating the genomics sequences, and their functional annotation.

    Current Project: SNPs identification and Interval mapping in Seeded and Non-Seeded Banana by using a QTL-seq method, and a genome-wide NGS-based BSA mapping new mutations in Arabidopsis. Apart from this currently I am working on "Predictive modeling of nucleic acid recognition dynamics and Structured complex formation by disordered proteins”.



    Shikha Mittal

    (October 2019 - August 2020)

    Previous affiliation:- Ph.D. in Bioinformatics from Sam Higginbottom University of Agriculture,Technology and Sciences, Allahabad; M.Sc in Bioinformatics from Banasthali Vidyapith University, Rajasthan; B.Sc in Biotechnology from Sardar Bhagwan Singh University, Dehradun.

    Research Interests:- Next generation sequencing (NGS) analysis, Genome-wide association studies,genomic selection, computational biology and bioinformatics, comparative genomics.

    Current Project :-I am working on the project entitled “Data driven modeling of pathogen-specific host responses mediated by nucleic and sensing proteins”. Nucleic acid recognition in the host defense occurs in the endosomes and cytosol. Several NA-sensors are known but the detailed host-pathogen associations are poorly understood. Universal principles of pathogen recognition need to be understood in a data-driven manner spanning multiple studies. So, I am interested in analyzing cytosloic and endosomal Nucleic acid-sensing proteins in terms of their sequence, structure and gene-expression features. I will also identify unknown NA sensors using the computational analysis of known sensing molecules and their unknown specificity towards different pathogen types.


    Sucheta Chauhan

    (Ph.D. :-  Jan 2020)

    Previous affiliation: M.Tech. in Computer Science and Engineering from Mody Institute of Technology and Science, Lakshmangarh, Rajasthan; B.Tech. in Information Technology from Uttar Pradesh Technical University, Lucknow.

    Research Interests: Machine learning, Artificial neural network, Deep learning.

    Current Project: Deep learning have been successfully applied to a variety of applications, including image classification, prediction, segmentation and denoising. My aim is to develop an efficient computational model for disease diagnosis. Deep learning architectures like Convolutional Neural Network, Recurrent Neural Network, Long-short Term Memory etc. have been used for classification and prediction of time series sequences, biological annotated sequences, and image data. I am also interested in developing novel CNN-based model for predicting DNA-binding proteins from their whole sequence evolutionary profiles.


    Surender Kumar Sharma

    (Research Project: January-June, 2018)

    Post Graduate Diploma in Big Data Analytics, SCIS JNU
    Previous affiliation: Obtained Ph. D. in Physics from University of Delhi
    Research Project: I studied conformational ensembles of 5-mers in large sets of MD trajectories of DNA sequences and their genome-wide dictionaries using Data Science approaches. Optimum levels of coarse-graining conformational ensembles and Biological and technical trade-offs were investigated.

    koushiki Bhattacharya

    (Intern: January-June, 2019)

    Post Graduate Diploma in Big Data Analytics, SCIS JNU
    Previous Affiliation: M.Sc. in Physics from Jawaharlal Nehru University; B.Sc.(H) in Physics from University of Kalyani, West Bengal.
    Research Interest:
    Cosmology, High-enerfy Physics, Theoretical Condensed Matter Physics.
    "Bayesian Data Analysis for Cosmological Observations".

    I have explored the research area of Cosmology and the standard models used in this field during this project. I have learnt about Bayesian Statistics and its applications in the field. I have also explored and learnt about computational languages (Python mainly) and its packages during this project.

    Wasim Akram

    (Intern: January-June, 2019)

    Post Graduate Diploma in Big Data Analytics, SCIS JNU
    Previous Affiliation: M.Sc. in Computer Science from Maharshi Dayanand University, Rohtak; B.Sc.(H) in Electronics from University of Delhi.
    Research Interest: Big Data Analytics, Machine Learning, Data Engineering, Data mining, Natural Language Processing, Deep Learning.
    Project: "A priori best model selection using data summary features" 

    In this work, I have explored a choice between four machine learning models viz Linear regression, Logistic regression and Support vector classification and a Multilayer perceptron (MLP) and tried to estimate a priori which of these models is likely to better explain and hence predict the target features in each of the selected data sets.


    Vishwas Kukreti

     Master's' Fellow (Dec,2016 - July,2017)

    Previous affiliation: M.Sc. in Complex Systems from School of Computational & Integrative Sciences, Jawaharlal Nehru University, B.Sc. (Hons) in Physics from University of Delhi.
    Research Interest: Dynamics of complex systems, Data compression
    Project:“Re-implementation of Burrows-Wheeler Transformation for genome wide sequence data compression and identifying factors affecting its efficiency”. In this project, a FASTA file compressor was built and it was found that compression efficiency is not based on sequence features.

    Vineet Singh

    (Intern: June-July 2019)

    Affiliation: B.Tech student in ECE at IIIT Guahati.

    Research Interests: Machine Learning, Big Data Analytics.

    Project: Gene expression big data clustering



    (Intern: May-July 2019)

    Affiliation: B.Tech student in Biomedical Engineering at Amity University, Haryana.

    Research Interests: Machine Learning, Big Data Analytics.

    Project: To build a classifier to detect alcoholism in person using EEG Signal.


    Deepak Bharti

    (Postdoctoral Fellow; September, 2018-April 2019)

    Previous affiliation: Ph.D. from School of Computational and Integrative Sciences, JNU, New Delhi; M.Sc. Bioinformatics from Centre of Bioinformatics, IIDS, University of Allahabad, Allahabad; B.Sc. (Zoology, chemistry) from Deen Dayal Upadhyaya Gorakhpur University, Gorakhpur.

    Research Interests: My research interests include the application of machine learning and data mining for biological/chemical data analysis. I have developed a galaxy workflow system for virtual screening using predictive model building and also created a descriptor database for PubChem compounds. I have explored the of deep learning methods for cancer class classification using genomic mutational data.

    Current Project: Predictive modeling of nucleic acid recognition dynamics and structured complex formation by disordered proteins.


    Niccolò Rigi-Luperti

    (Research Intern; Feb 20 - Mar 22, 2019)

    Primary affiliation: B.Sc. in Physics at Heidelberg University, Germany

     Research Interest: Computational Optimization, Quantum Mechanics

    Current Project: A tool to predict Protein-DNA binding sites via Machine Learning. The inputs are the primary and secondary structure of a protein, as for many proteins readily available. Prediction is done via PSI-BLAST multi sequence alignment against a protein-database and then a 3-layer Neural Network.


    Sagarika Dey

    (Research Intern (Completed); Jan 3, 2018 - June 10, 2018)

    Previous affiliation: Completed M.Sc in Biotechnology from Vellore Institute of Technology, Vellore, Tamil Nadu; B.Sc Botany from BJB (Autonomous) College, Bhubaneswar, Odisha.

    Research Interests: My interest lies specifically in the field of plant biotechnology, particularly to investigate genetic determinants of plant responses to drought and salinity, role of small signaling molecules in plant responses to drought and salinity. My future aim is to improve genetic responses of plant tolerance to drought and salinity.

    Project Completed: I worked on the detectability of the transcription factor binding motifs from the meta analysis of the co expressed genes in Arabidopsis thaliana using gene expression data, bioinformatics tools and data analytics.


    Sheikh Nizamuddin

    (Postdoctoral Fellow (Completed); Oct 01, 2017 - May 31, 2018)

    Previous affiliation: Ph.D. from CSIR-Centre for Cellular and Molecular Biology, Hyderabad India.

    Research Interests: My interests lies in statistical methodology, data analysis and programming languages. Notably, (1) I have generated Indian specific haplotype reference panel for statistical imputation of missing genotype in Affymetrix array (6.0) data-sets, (2) identified Indian specific gene THSD7A in association with obesity, (3) explored genetics behind Indian traditional medicine Ayurveda, (4) identified novel marker rs2470102 (SLC24A5 ) in association with Skin pigmentation and (5) c.*84G>A in CETP associated with coronary artery disease.

    Project completed: The research work focus on the implication of DNA shape to understand genetic mechanism in various disorders including cancer and tuberculosis and to establish DNA shape as better predictor, comparative to DNA variations, in non-coding region of genome.


    Vinod Singh

    (Postdoctoral Fellow (Completed); June 1, 2017 - Jan 30, 2018)

    Previous affiliation: Ph.D and M.Tech from School of Computational and Integrative Sciences, JNU, New Delhi; B.Tech Biotechnology from Kurukshetra University, Kurukshetra.

    Research Interests: My research interests include the application of data mining and computational techniques for the genomics data analysis.

    Project Completed: I have developed an effective method to predict TAD boundaries from publicly available Hi-C data and topologically associated domains (TAD) information of the human genome.


    Saurabh Sugha

    (Research Volunteer (Completed); Sep 18, 2016 - Dec 15, 2017)

    Primary affiliation: Currently I am associated with Samsung India as a Business Analyst in Consumer Electronics Division. I have over 7-year work experience in Big Data Analytics, Data Visualization, Visual Basic Programming, Qlick View, Microsoft Dynamic AX - Business Intelligence System Automations, Database Management and Strategic Consulting. Past association was with Canon, Haier, Videocon Industries as a Business Operation Consultant.

    Research Interests: My interest lies in exploring the dynamics of Computational Biology, Machine learning, Neural networking, Deep learning, Text mining and Big data analytics. I am passionate about conducting an Integrative analysis of Biological data and developing an algorithm for Text mining to facilitate understanding of the Whole-Genome Sequencing and Molecular Epidemiology of infectious diseases. I am excited about the increasing role of Social Media and Mobile Technologies while taking a “Big data approach” to conduct Epidemiological disease modeling.

    Project Completed: The use of bioinformatics analytical tools and high level programing languages like Python/Java for streaming into the Application programming interface (API) of the social networking site (Twitter/Facebook). Idea was to extract epidemiologically relevant tweets or responses of the users and performing a comparative study of the medical symptoms or its side effects while developing a correlative mapping of diseases using unified medical language system (UMLS), SIDER (medical side effect) and other medical portals. The Project involved taking a Big data approach for performing disease modelling and sentiment analysis so as to developing an algorithm to expand the meta-thesaurus of the infectious diseases and its symptoms.


    Aditya Bajaj

    (Research Intern (Completed); June 25-October 30, 2016)

    Previous affiliation: Integrated M.Sc. – Ph.D. in Molecular Medicine at the Special Centre for Molecular Medicine, Jawaharlal Nehru University

    Research Interests: Broadly include Medical Microbiology- molecular basis of infectious diseases, host microbe relationships and human gut microbiome and its roles to modulate human physiological processes. In future I would like to emphasise on bacterial biofilms and quorum sensing in health and diseases and to study aspects of microbial antibiotic resistance and nosocomial infections.

    Project completed: To utilise Computational biology tools to study the Spoligotyping patterns in different members of Mycobacterium tuberculosis complex (MTBC). Spacer oligonucleotide typing, or spoligotyping, is a rapid, polymerase chain reaction (PCR)-based method for genotyping strains of the Mycobacterium tuberculosis complex. The project aims to decipher links between these spoligotyping patterns and the clinical and epidemiological characteristics of various Mycobacterial strains.


    Manasvini Markandey

    (Research Intern (Completed); June 25-October 30, 2016)

    Previous affiliation: Compeleted MSc in Biotechnology from Faculty of Life Sciences & Biotechnology, South Asian University, New Delhi

    Previous Qualification: BSc (H) Microbiology, Ram Lal Anand College, University of Delhi

    Research Interests: My interest lies in the field of medical microbiology. Particularly I wish to study the molecular basis of host-pathogen interactions and unravelling how the host physiology is altered as an infection ensues. Furthermore, I wish to develop on these mechanisms to design drugs that can possibly be used to cure the common, yet severe diseases. Another field of interest to me is the resident micro-flora of the human body and its effects on the host physiology. These microbes aren’t pathogenic, but can turn from friends to foes under certain circumstances. Studying the mechanisms by which this symbiotic relationship operates in its bidirectional fashion is a key area of research these days, since it’s now known that these micro-organisms may play substantial roles in altering the vulnerability of the human system towards various pathogenic infections.

    Project completed: To use bioinformatic tools to identify the genes and proteins in host system and the respective pathogenic molecules of Zika Virus interacting with these host molecules, so as to be able to define an outlining network of host-pathogen interactions underlying ZIKV infection in humans. We’d also like to extend it by carrying out co-infection analysis and identifying other pathogens that share similar molecular pathways during infection.



    © Prof Shandar Ahmad Research Group. | Developed by Sudhir Patwal