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Indian Institute of Information Technology, Lucknow
भारतीय सूचना प्रौद्योगिकी संस्थान, लखनऊ
(An Institute of National Importance by the Act of Parliament)

Dr. Rohit Gupta

Dr. Rohit Gupta

Adjunct Faculty


  • Ph.D (University of Minnesota)
  • M.S (University of Minnesota)
  • B.Tech (IIT Roorkee)


  • Machine Learning
  • Data Mining
  • Computational Biology


  • Bengaluru, Karnataka, India

NeuranceAI is a deep-tech company focusing on building intelligent machines inspired by concepts from neuroscience that learn and solve critical healthcare problems globally

Founder and Director
DeepKnomics is a data-driven technology company with a strong vision to build products in clinical diagnostics and immuno-oncology space and provide customized solutions for bioinformatics workflows and genomics data analysis.
  • 6 yrs 2 mos
Taught a graduate level course to MTech and PhD students on “Data Science for Genomics”. Explored research collaborations in areas of mutual interest.


BuddhiMed is an innovative HealthTech start-up that converges AI and Modern Medicine by developing machine learning tools and solutions using very large health data sets. These tools are aimed at improving decision making in healthcare delivery systems and clinical medicine. We aim to improve the health and wellness of millions of people by helping their doctors, hospitals, insurers and themselves to make more informed and better decisions about their health and wellness
  • Bengaluru Area, India
Managed all major functions and activities within bioinformatics, software and IT for all aspects of company’s business catering to explosive growth in genomics, clinical diagnostics and research market.
  • 3 yrs 9 mos
  • , India
Research and Product Development in Computational Biology, Next Generation Sequencing data analysis, and Clinical Applications of Genomics
– Data mining for discovering genetic markers of complex diseases using next-generation sequencing and microarray expression and methylation data. – Hidden Markov Modeling based approach for copy number analysis in cancer using SNP array and illumina data. – Pathway and network based approaches for integration and analysis of large number of “omic” data sets to guide clinical decision-making. – Analysis of The Cancer Genome Atlas (TCGA) data with focus on DNA Methylation, Copy Number, RNASeq.
– Characterization of missed neoplasia during Colonoscopy – Understanding physician-, patient-, and environment-related risk factors through statistical analysis of large medical data sets containing historical information about colonoscopy and cancer pathology. – Identification and characteristics of patients with idiosyncratic drug-induced liver injury (IDILI) [Pfizer funded project]. – Application of KNN and SVM based classification techniques on structured and unstructured Mayo Clinic life sciences data for the early prediction of liver cirrhosis and hepatocellular cancer. – Explored association rule mining and hyperclique pattern discovery techniques for discovery of patterns based on patients’ diagnosis history in a large clinical database from Mayo Clinic Life Sciences System (MCLSS). – Studied Computer Pathology (CoPath) system of Mayo Clinic and explored techniques to analyze pathology reports and their integration with MCLSS system. Various data mining techniques for prediction of liver cirrhosis and hepatocellular cancer at an early stage were also explored.
– Integrated analysis of microarray gene expression and protein-protein interaction data for the discovery of active sub-network based biomarkers. – Association mining framework for discovering error-tolerant patterns/biclusters. – Data mining techniques for identifying novel connections between diseases and genomic or medical characteristics.
Developed and implemented expectation-maximization algorithm based scale-recursive estimation methodology for validation and blending of multi-sensor precipitation estimates available at multiple scales from radars and satellites [NASA and NSF Funded Project]
Collaborated with a team of experts at SNRA (Swedish National Road Administration) and KTH and developed artificial intelligence based strategy selection, prioritization and decision making modules for Swedish infrastructure management system. Developed framework can be used to assist planners, road managers and decision makers to make efficient and more economically viable decisions at both strategic and project level.
Developed and implemented an algorithm based on Genetic Learning Artificial Neural Network (GLANN) for preparing Landslide Hazard Zonation (LHZ) map of Bhagirathi valley area in Himalayan region using spatial data from sensors on IRS-1B satellite and GIS maps from other sources.
  •  (RRCAT)
Studied design, construction and safety aspects of radiation shielding structures for electron accelerator buildings (Indus I & II) at CAT. Also performed experiments with a Cobalt-60 source (most common radioactive isotope of cobalt) to study shielding effects of soil.


Department of Information Technology,
Indian Institute of Information Technology,
Lucknow, India.

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