Dr. CHANDRA MOHAN D

Dr. CHANDRA MOHAN D, PhD

Assistant Professor,

Department of Computer Science & Engineering,
Email: chandramohan.d[at] iiitk.ac.in | Contact Number: 08518-289100 - 141(E)

Academic Qualifications: • Ph.D. in Computer Science and Engineering, NIT Warangal, Telangana, India. • M.E. in Computer Science and Engineering, Jadavpur University, Kolkata, India. • B.Tech. in Computer Science and Engineering, University College of Engineering (Kakatiya University), Warangal, Telangana, India.

Areas of Interest: • Bioinformatics • Machine and Deep Learning • Natural Language Processing

Professional / Teaching Experience: • Assistant Professor (Grade-I) in the department of CSE at IIITDM Kurnool (3rd June 2026- Present). • Assistant Professor (Grade-II) in the department of CSE at IIITDM Kurnool (10th December 2025 – 2nd June 2026). • Assistant Professor (Grade-II) in the department of CSE at IIIT Raichur (21st May 2025 – 9th December 2025). • Assistant Professor (Grade-II) in the CSE group at IIIT Sri City (18th April 2022 – 20th May 2025). • Assistant Professor (Sr. Grade-I) in the school of CSE at VIT-AP University (18th March 2021–17th April 2022). • Assistant Professor in the department of CSE at GITAM University (13th August 2013- 22nd July 2017). • Assistant Systems Engineer at TCS Pvt. Ltd (11th July 2012- 6th August 2013).

Publication Profile: • Google Scholar: https://scholar.google.com/citations?user=8BeZ6aoAAAAJ&hl=en&oi=ao • Scopus: https://www.scopus.com/authid/detail.uri?authorId=57217857652 • ORCID : https://orcid.org/0000-0002-0515-4979

Funded Projects: • Project Title: Graph GAN based Novel Molecular Generation and Synthesis for Blood–Brain Barrier Permeability in Neurological and Psychiatric Disorder Treatment, Funded by IIITDM Kurnool under the Scheme Institute Seed Research Grant (iSRG) in February, 2026 of total budget: Rs.15 Lakhs, Duration: 2 years, Role: Principal Investigator, Status: Ongoing. • Project Title: DrCMDs Predictor: A novel system for Disease prediction, Mutated patterns discovery, and Drug Candidates generation to combat viral diseases in Indian population, Funded by SERB under the Scheme SRG in October, 2023, Govt. of India, with Sanction No. SRG/2023/000941of total budget outlay: Rs.13 Lakhs, Duration: 2 years, Role: Principal Investigator, Status: Completed.

FDP/Workshop/Hackathon(s) Organized: 1. I organized a 36-hour continuous National Hackathon, “NETRIK 2026,” as part of the Decennial Celebrations of the Indian Institute of Information Technology Design and Manufacturing Kurnool, through the Department of Computer Science and Engineering, on 28 February and 1 March 2026. 2. I organized a one-week online Faculty Development Programme (FDP) titled “Advanced Computational Methods in Genomics and Drug Discovery: Bridging AI and Biomedical Science,” sanctioned by ATAL, from 08 to 13 September 2025. 3. I organized a five-day online Faculty Development Programme (FDP) on “Current Trends of Deep Learning in Various Research Domains” at VIP-AP University, in collaboration with the Centre for Continuing Education (CCE), NIT Warangal, from 20 to 24 September 2021.

Research Guidance: • Ph.D - 03 (Ongoing) • M.Tech – 01 (Completed) • B.Tech- 17 (Completed)

International Journal Publications:

  1. Sandhya G, Santhosh Amilpur, Chandra Mohan Dasari. “Leakage-controlled benchmarking of multi-omics patient graph construction for pan-cancer tumor-type classification and survival modeling”. Computational Biology and Chemistry. August, 2026. (SCIE-Q1, Elsiever, Impact Factor: 3.1).(Accepted)
  2. Amodini A.P, Chandra Mohan Dasari, Santhosh Amilpur. “Novel Molecules Generation Using Graph Generative Adversarial Networks”. Molecular Informatics, March, 2026. 45(5), p.e70031 (SCI-Q1, Wiley, Impact Factor: 3.1) https://doi.org/10.1002/minf.70031
  3. Sandhya G, Santhosh Amilpur, Chandra Mohan Dasari. “Dynamic Bernstein GCN for Pan-Cancer Subtype Classification using RNA-seq and CNV Data”. IEEE Transactions on Computational Biology and Bioinformatics. Jan, 2026. (SCI-Q1, IEEE, Impact Factor: 3.4) https://doi.org/10.1109/TCBBIO.2026.3651305
  4. Dheeraj Kodati, Chandra Mohan Dasari. “Detecting critical diseases associated with higher mortality in electronic health records using a hybrid attention-based transformer”. Engineering Applications of Artificial Intelligence. Nov, 2024. 139, p.109649 (SCI-Q1, Elsevier, Impact Factor: 8.0) https://doi.org/10.1016/j.engappai.2024.109649
  5. Dheeraj Kodati, Chandra Mohan Dasari. “Negative emotion detection on social media during the peak time of COVID-19 through deep learning with an auto-regressive transformer”. Engineering Applications of Artificial Intelligence. 2024 Jan 1;127:107361. (SCI-Q1, Elsevier, Impact Factor: 8.0) https://doi.org/10.1016/j.engappai.2023.107361
  6. Kaushik Bhargav Sivangi, Santhosh Amilpur, Chandra Mohan Dasari. “ReGen-DTI: A novel drug target interaction model for predicting potential drug candidates induced by generative network against SARS-COV2”. Computational Biology and Chemistry. Volume 106, October 2023, 107927. (SCIE-Q1, Elsiever, Impact Factor: 3.1). https://doi.org/10.1016/j.compbiolchem.2023.107927
  7. L V S K B Kasyap Varanasi and Chandra Mohan Dasari. “ Deep Learning based techniques for Neuro-degenerative disorders detection”. 2023 Engineering Applications of Artificial Intelligence. Volume 122, June 2023, 106103. (SCI-Q1, Elsevier, Impact Factor: 8). https://doi.org/10.1016/j.engappai.2023.106103
  8. Raju Bhukya, Archana K, Chandra Mohan Dasari, Santhosh A. “An attention based hybrid deep neural networks for accurate identification of transcription factor binding sites”. Neural Computing and Applications. 2022 Nov;34(21):19051-60.(Scopus, Springer, Impact Factor: 4.5). https://doi.org/10.1007/s00521-022-07502-z
  9. Kaushik Bhargav Sivangi, Chandra Mohan Dasari, Santhosh Amilpur and Raju Bhukya. “NoAS-DS: Neural Optimal Architecture Search for detection of diverse DNA Signals”. Neural Networks. Volume 147, March 2022, 63-71. ( SCI-Q1, Elsiever, Impact Factor: 6.3). https://doi.org/10.1016/j.neunet.2021.12.009
  10. Raju Bhukya, Archana Kumari, Santhosh Amilpur, Chandra Mohan Dasari. “PPred-PCKSM: A multi-layer promoter predictor for determining promoter and its variants using position based features”. Computational Biology and Chemistry. Volume 97, April 2022, 107623. (SCIE-Q1, Elsiever, Impact Factor: 3.1). https://doi.org/10.1016/j.compbiolchem.2022.107623.
  11. Chandra Mohan Dasari, Santhosh Amilpur and Raju Bhukya. “Exploring variable-length features (motifs) for predicting binding sites through interpretable deep neural networks”. Engineering Applications of Artificial Intelligence. Volume 106, 15 Nov-2021,104485. (SCI-Q1, Elsevier, Impact Factor: 8). https://doi.org/10.1016/j.engappai.2021.104485
  12. Chandra Mohan Dasari, and Raju Bhukya. “Explainable deep neural networks for novel viral genome prediction”. Applied Intelligence. Volume 52, 24 May-2021, 3002–3017. (SCI-Q2, Springer, Impact Factor: 3.5). https://doi.org/10.1007/s10489-021-02572-3
  13. Chandra Mohan Dasari, and Raju Bhukya. “MapReduce Paradigm: DNA Sequence Clustering based on Repeats as Features”. Expert Systems. Volume 39, 12827, 12 August, 2021 (SCIE-Q2, Wiley, Impact Factor:2.3). https://doi.org/10.1111/exsy.12827
  14. Chandra Mohan Dasari, and Raju Bhukya. “InterSSPP: Investigating patterns through interpretable deep neural networks for accurate splice signal prediction”. Chemometrics and Intelligent Laboratory Systems. Volume 206, 15 Nov-2020,104144. (SCIE-Q1, Elsevier, Impact Factor: 3.8). https://doi.org/10.1016/j.chemolab.2020. 104144
  15. Chandra Mohan Dasari, and Raju Bhukya. “Comparative analysis of protein synthesis rate in COVID-19 with other human coronaviruses”. Infection Genetics and Evolution. Volume 85, Nov-2020, 104432. (SCIE-Q2, Elsevier, Impact Factor: 2.6). https://doi.org/10.1016/j.meegid.2020.104432

International Conference Papers:

  1. Sandhya G, Santhosh Amilpur, Chandra Mohan Dasari, Pooja Chandragiri. “Interpretable Graph Attention Network with Feature Ranking for Multi-omics Pan-Cancer Subtyping”. 14th International Conference on Big Data Analytics and Artificial Intelligence (BDA). August, 2026. (Accepted)
  2. NV Harshith, Venkatesh Bandaru, Chandra Mohan Dasari, Santhosh Amilpur. “GeoXP-Explainer: An Interpretable Graph Neural Network Framework for Blood-Brain Barrier Permeability Prediction”. 14th International Conference on Big Data Analytics and Artificial Intelligence (BDA). August, 2026. (Accepted)
  3. Varshitha Bammidi, Chandra Mohan Dasari, Santhosh Amilpur. “Explainable Deep Neural Networks for Predicting Mutated Patterns in SARS-CoV-2 Variants with Geographic Analysis”. IEEE International Conference on ETAACT, March, 2026. (Best Paper Award)
  4. Sravya Sri Mallampalli, Chandra Mohan Dasari. “Genomic Variant Classification for MECP2 Mutation Pathogenicity”, PM4B 2025 workshop of the PAKDD 2025 conference which held on June 10, 2025. https://doi.org/10.1007/978-981-96-8197-6_19
  5. Chandra Mohan Dasari, Dheeraj Kodati, Nivesh Mittapally, Srinivas Reddy A, Krishna Reddy P. “Graph Neural Networks Based Explainability of Drug-Target Interactions”, 17th International Conference on Bioinformatics and Computational Biology (BICOB 2025) which held on March 17-18, 2025. https://doi.org/10.1007/978-3-031-94039-2_12
  6. Prasad S, Dhrupad S, Dheeraj K and Chandra Mohan Dasari. “Kmer-Based DNA Sequence Image Representation for Viral Disease, Translation and Mutated Pattern Prediction”, 15th International Conference on Bioscience, Biochemistry and Bioinformatics (ICBBB 2025) which will be held on January 16-19, 2025, Bangkok. https://doi.org/10.1051/bioconf/202516301008
  7. Santansu Mohanty and Chandra Mohan Dasari. "Explainable Graph Neural Networks to identify potential atoms and chemical bonds of drug candidates from drug target interactions", 12th International Conference on Big data and Artificial Intelligence which will be held on December 17-20, 2024. https://doi.org/10.1007/978-3-031-81821-9_19
  8. Naman Bhatia, Kasyap Varanasi, Parth Raghuwanshi, Avinash Saroj, and Chandra Mohan Dasari. "Neurodegenerative disorder prediction using curated short mutated genome sequences through hybrid deep neural networks", 12th International Conference on Bioinformatics and Computational Biology, Mar, 2024. https://doi.org/10.1109/ICBCB61507.2024.11011955
  9. L V S K B Kasyap Varanasi and Chandra Mohan Dasari. “ PsychNet: Explainable Deep Neural Networks for Psychiatric Disorders and Mental Illess”. 2022 6th IEEE Conference on Information and Communication Technology (CICT-2022). Nov 18-20, 2022. (pp. 1-6). IEEE. https://doi.org/10.1109/cict56698.2022.9997832
  10. L V S K B Kasyap Varanasi and Chandra Mohan Dasari. “A Novel Deep Learning Framework for Diabetic Retinopathy Detection ”. 2022 6th IEEE Conference on Information and Communication Technology (CICT-2022), Nov 18-20, 2022. (pp. 1-5). IEEE. https://doi.org/10.1109/CICT56698.2022.9997826
  11. Chandra Mohan Dasari, and Raju Bhukya. “Disease Diagnosis based on Various Pattern Frequency from Extracted Exons”. 2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT) Bangalore, India. Oct 7-9, 2022. (pp. 1-7). https://doi.org/10.1109/GCAT55367.2022.9972173
  12. Krishna Siva Prasad M, and Chandra Mohan Dasari, Nilesh Chandra K Pikle, Dr. Snehal B. “Path and Information content based Semantic Similarity Measure to Estimate Word-Pair Similarity”. The International Conference on “Applied Mechanics, Machine Learning and Advanced Computation (AMMLAC 2022)”. vol. 2745, no. 1. AIP Publishing, 2022. https://doi.org/10.1063/5.0143216
  13. Chandra Mohan Dasari, Dipankar Das and Prof. Sivaji Bandyopadhyay. “Emotion Argumentation”. IEEE 2nd International Conference on Recent Trends in Information Systems (ReTIS). 2015. https://doi.org/10.1109/ReTIS.2015.7232900.
  14. Chandra Mohan Dasari, Dipankar Das and Prof. Sivaji Bandyopadhyay. “Topic Identification from Blog Documents: Roles of Bigram, Named Entity and Sentiment”. LREC workshop on Information Access Technologies for Online Reputation Management. pp.19-24. 2012.
  15. Dipankar Das, Soujanya Poria, Chandra Mohan Dasari and Sivaji Bandyopadhyay. “Building Resources for Multilingual Affect Analysis – A Case Study on Hindi, Bengali and Telugu”. LREC ES3 4th International workshop on Corpora for Research on Emotion Sentiment. pp.54-61. 2012.

Book Chapters: 1. Santhosh Amilpur and Chandra Mohan Dasari. “Deep network based drug target interaction model to identify potential drug molecules against COVID-19”. AMHM-2023: Handbook of AI-Based Models in Healthcare and Medicine: Approaches, Theories, and Applications. Taylor and Francis, CRC press, Scopus.

Courses Handled: • Programming Languages: C, C++, Java, Python • Data Structures, Advanced Data Structures • Design and Analysis of Algorithms • Machine Learning, Deep Learning • Data Science, Data Mining • Bioinformatics • Digital Electronics • Full Stack Development: HTML, CSS, JavaScript, React, Node.js, MySQL, MongoDB

Accolades: • PhD Fellowship from MHRD, Govt. of India (July, 2017 – January, 2021) • Qualified GATE-2017, 2014, and 2010. • Qualified UGC–NET for Lectureship in Dec-2018, June-2014, Dec-2013. • Qualified State Eligibility Test–2014 (SET TS & AP) for Lectureship in 2014. • Won Three Silver Medals for Securing high scores in SSC, B.Tech. and M.E.