Scientific Presentations and Talks

Talk1

  1. (Keynote) AI+HPC for Accelerating Science and Engineering, 14th International Conference on Cloud Computing, Data Science & Engineering (CONFLUENCE) 2024, January 19, 2024, Amity University, Noida, Delhi NCR, India.

  2. (Invited) Artificial Intelligence and High-Performance Data Mining for Accelerating Science and Engineering, Computers, Materials & Continua (CMC) Webinar, December 21, 2023 (Virtual).

  3. A Deep Learning Framework for Time-Series Processing-Microstructure-Property Prediction, 22nd IEEE International Conference on Machine Learning and Applications (ICMLA) 2023, December 15, 2023, Jacksonville, FL, USA.

  4. (Keynote) Artificial Intelligence and High-Performance Data Mining for Accelerating Science and Engineering, 7th International Conference on Image Information Processing (ICIIP) 2023, November 23, 2023, Jaypee University of Information Technology, Solan, HP, India.

  5. Physics-based Data-Augmented Deep Learning for Enhanced Autogenous Shrinkage Prediction on Experimental Dataset, International Conference on Contemporary Computing (IC3 2023), August 04, 2023, Noida, Delhi NCR, India.

  6. (Invited) Artificial Intelligence and High-Performance Data Mining for Accelerating Materials Discovery and Design, Freudenberg Visit, July 11, 2023, Evanston, IL, USA.

  7. (Keynote) Artificial Intelligence and High-Performance Data Mining for Accelerating Materials Discovery and Design, JARVIS School and CHiMaD Training, June 15, 2023, Lemont, IL, USA.

  8. (Keynote) Artificial Intelligence and High-Performance Data Mining for Accelerating Materials Discovery and Design, JARVIS School and CHiMaD Training, June 14, 2023, Evanston, IL, USA.

  9. (Invited) Artificial Intelligence and High-Performance Data Mining for Accelerating Materials Discovery and Design, 7th World Congress on Integrated Computational Materials Engineering (ICME 2023), May 22, 2023, Orlando, FL, USA.

  10. (Keynote) Artificial Intelligence and High-Performance Data Mining for Accelerating Materials Discovery and Design, 6th Forum of Materials Genome Engineering (ForMGE), February 18, 2023, Hangzhou City, Zhejiang Province, China.

  11. (Keynote) Artificial Intelligence and High-Performance Data Mining for Accelerating Science and Engineering, 13th International Conference on Cloud Computing, Data Science & Engineering (CONFLUENCE) 2023, January 20, 2023, Amity University, Noida, Delhi NCR, India.

  12. (Keynote) Artificial Intelligence and High-Performance Data Mining for Accelerating Materials Science and Engineering, Accelerated Materials Design and Additive Manufacturing: Scientific and Technological Perspectives (AMDAM), 76th Annual Technical Meeting of The Indian Institute of Metals, November 13, 2022, Hyderabad, Telangana, India.

  13. Artificial Intelligence and High-Performance Data Mining: Overview and Updates, CHiMaD Annual Meeting, November 08, 2022, University of Chicago, Chicago, IL, USA.

  14. (Keynote) Artificial Intelligence and High-Performance Data Mining for Accelerating Scientific Discovery, 3rd International Conference on Advances and Applications of Artificial Intelligence & Machine Learning (ICAAAIML 2022), September 16, 2022, Sharda University, Greater Noida, Delhi NCR, India.

  15. (Keynote) Artificial Intelligence and High-Performance Data Mining for Accelerating Scientific Discovery, 9th International Conference Signal Processing and Integrated Networks(SPIN 2022), August 26, 2022, Amity University, Noida, Delhi NCR, India (Virtual).

  16. Machine Learning for Materials Science (MLMS), 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022), August 15, 2022, Washington DC, USA.

  17. (Keynote) Artificial Intelligence and High-Performance Data Mining for Accelerating Materials Discovery and Design, 3rd Biennial International Conference on Future Learning Aspects of Mechanical Engineering (FLAME 2022), August 04, 2022, Amity University, Noida, Delhi NCR, India.

  18. AI/ML/DL for Forward and Inverse Problems in Science and Engineering, International Conference on Dynamical Systems, Control and their Applications (ICDSCA 2022), July 01, 2022, Indian Institute of Technology Roorkee (IITR), Roorkee, Uttarakhand, India.

  19. (Keynote) AI + HPC for Accelerating Science, IEEE International Conference on Machine Learning, Big Data, Cloud and Parallel Computing: Trends, Perspectives and Prospects (Com-IT-Con 2022), May 26, 2022, Manav Rachna International Institute of Research and Studies, Faridabad, Delhi NCR, India.

  20. (Keynote) Artificial Intelligence and High-Performance Data Mining for Accelerating Materials Discovery and Design, Workshop on Data-driven Modeling and Optimization, May 19, 2022, Fraunhofer Institute for Mechanics of Materials, IWM, Germany (Virtual).

  21. (Invited) AI/ML/DL Approaches for Accelerating Materials Discovery and Design, TMS 2022: AI/Data Informatics, February 28, 2022, Anaheim, CA, USA.

  22. (Invited) Harnessing the Power of FAIR Materials Data, MaRDA Annual Meeting, February 23, 2022 (Virtual).

  23. (Invited) AI-Driven Learning of the Science and Engineering of Materials from Simulations, NAFEMS Seminar on AI, Data Driven Models & Machine Learning, February 23, 2022 (Virtual).

  24. (Keynote) AI + HPC for Accelerating Science, 12th International Conference on Cloud Computing, Data Science & Engineering (CONFLUENCE) 2022, January 28, 2022, Amity University, Noida, Delhi NCR, India (Virtual).

  25. (Invited) Artificial Intelligence and High-Performance Data Mining for Accelerating Scientific Discovery, AI for Interdisciplinary Scientific Discovery, January 27, 2022, Institute of Advanced Studies, Loughborough University, England, UK.

  26. Artificial Intelligence and High-Performance Data Mining: Overview and Updates, CHiMaD Annual Meeting, January 24, 2022, Northwestern University, USA (Virtual).

  27. (Invited) Artificial Intelligence and High-Performance Data Mining for Accelerating Scientific Discovery, US Army DEVCOM CBC Seminar on AI/ML Applications, November 10, 2021 (Virtual).

  28. (Invited) Introduction to Machine Learning and Deep Learning for Materials Science, TMS Online Course: Artificial Intelligence in Materials Science and Engineering, November 02, 2021 (Virtual).

  29. (Invited) Artificial Intelligence and High-Performance Data Mining for Accelerating Scientific Discovery, BiGmax Summer School on Harnessing Big Data in Materials Science from Theory to Experiment, September 15, 2021, Max Plank Institute, Germany (Virtual).

  30. (Invited) AI for Accelerating Materials Discovery and Design, Nanocombinatorics Workshop on Science of AI, August 19, 2021, Northwestern University, USA (Virtual).

  31. (Invited) Artificial Intelligence and High-Performance Data Mining for Accelerating Scientific Discovery, ULTRA DOE-EFRC Seminar, June 28, 2021, Arizona State University, USA (Virtual).

  32. (Invited) Artificial Intelligence and High-Performance Data Mining for Accelerating Scientific Discovery, NSF Workshop on Accelerating Materials Discovery, Design, and Synthesis: A Grand Challenge for Artificial Intelligence (AIMS): AI Panel, April 09, 2021, Pennsylvania State University, USA (Virtual).

  33. CHiMaD AI and High Performance Data Mining: Tool Group Updates, CHiMaD Executive Meeting, February 12, 2021, Northwestern University, USA (Virtual).

  34. (Invited) Deep Materials Informatics: Illustrative Applications of Deep Learning in Materials Science, TMS Webinar Series: Artificial Intelligence in Materials: Research, Design, and Manufacturing, February 04, 2021, Virtual.

  35. (Keynote) Artificial Intelligence and High-Performance Data Mining for Accelerating Scientific Discovery, 11th International Conference on Cloud Computing, Data Science & Engineering (CONFLUENCE) 2021, January 29, 2021, Amity University, Noida, Delhi NCR, India (Virtual).

  36. (Invited) AI and High-Performance Data Mining: Illustrative Applications in Materials Science, Indian Symposium on Machine Learning (IndoML), December 16, 2020, Indian Institute of Technology (IIT) Gandhinagar, India (Virtual).

  37. (Invited) Deep Materials Informatics: Illustrative Applications of Deep Learning in Materials Science, MS&T 2020: Materials Design through AI Composition and Process Optimization, November 02, 2020 (Virtual).

  38. Data-Driven Analytics on Navy Hull Steels Data, DLA/SFSA Naval Structural Steels Review, July 24, 2020 (Virtual).

  39. Artificial Intelligence and High-Performance Data Mining, CHiMaD Annual Meeting, June 09, 2020, Northwestern University, USA (Virtual).

  40. (Invited) Deep Materials Informatics: Illustrative Applications of Deep Learning in Materials Science, CHiMaD Phase Field Workshop 2020, April 21, 2020, Northwestern University, USA (Virtual).

  41. (Invited) Deep Materials Informatics: Illustrative Applications of Deep Learning in Materials Science, TMS 2020: ICME Gap Analysis in Materials Informatics, February 26, 2020, San Diego, CA, USA.

  42. (Keynote) High Performance Data Mining: An Essential Paradigm for AI and Big Data Analytics, 10th International Conference on Cloud Computing, Data Science & Engineering (CONFLUENCE) 2020, January 29, 2020, Amity University, Noida, Delhi NCR, India.

  43. Data-driven Analytics for Understanding Materials Properties, Toyota Visit, Toyota Motor Corporation, January 23, 2020, Nagoya, Aichi, Japan.

  44. A Real-time Iterative Machine Learning Approach for Temperature Profile Prediction in Additive Manufacturing Processes, 6th IEEE International Conference on Data Science and Advanced Analytics (DSAA) 2019, October 07, 2019, Washington DC, USA.

  45. Martensite Start Temperature Predictor for Steels Using Ensemble Data Mining, 6th IEEE International Conference on Data Science and Advanced Analytics (DSAA) 2019, October 07, 2019, Washington DC, USA.

  46. CHiMaD Data Mining and Analytics, CHiMaD Annual Meeting and Phase II Kickoff, September 24, 2019, Chicago, IL, USA.

  47. (Keynote) Materials Image Informatics Using Deep Learning: Challenges and Opportunities, LANL Workshop on Advanced Probes and Materials for Enabling 3-D Imaging, , Los Alamos National Laboratory, August 27, 2019, Santa Fe, NM, USA.

  48. (Keynote) High Performance Data Mining: An Essential Paradigm for Big Data Analytics and AI, 5th International Conference on Artificial Intelligence and Security (ICAIS) 2019, July 27, 2019, Brooklyn, NY, USA.

  49. (Invited) Deep Materials Informatics: Illustrative Applications of Deep Learning in Materials Science, CHiMaD Materials Design & Data Informatics Workshop, July 26, 2019, Evanston, IL, USA.

  50. Deep Materials Informatics: Illustrative Applications of Deep Learning in Materials Science, 5th World Congress on Integrated Computational Materials Engineering (ICME 2019), July 22, 2019, Indianapolis, IN, USA.

  51. (Invited) Materials Informatics and Big Data: Realization of “Fourth Paradigm” of Science in Materials Science, KAIST Faculty Visit, May 16, 2019, Evanston, IL, USA.

  52. (Invited) Illustrative Microstructure Analytics @CHiMaD, NIST/NSF Microstructures Workshop, May 14, 2019, National Cybersecurity Center of Excellence, Rockville, MD, USA.

  53. (Invited) CHiMaD Data Analytics, SRG 2019, March 25, 2019, Evanston, IL, USA.

  54. (Invited) Materials Informatics and Big Data: Realization of “Fourth Paradigm” of Science in Materials Science, TMS 2019: Computational Approaches for Big Data, Artificial Intelligence and Uncertainty Quantification in Computational Materials Science - Big Data, March 13, 2019, San Antonio, TX, USA.

  55. (Invited) High Performance Data Mining: An Essential Paradigm for Applied Mathematics and Interdisciplinary Big Data Analytics, RAMSA 2019, January 18, 2019, Noida, Delhi NCR, India.

  56. Materials Informatics and Big Data: Realization of “Fourth Paradigm” of Science in Materials Science, ACS Midwest Regional Meeting (MWRM 2018), October 23, 2018, Ames, IA, USA.

  57. (Invited) Materials Informatics and Big Data: Realization of “Fourth Paradigm” of Science in Materials Science, XXVII International Materials Research Congress (MRS-Mexico), August 20, 2018, Cancun, Mexico.

  58. (Invited) Materials Informatics and Big Data: Realization of “Fourth Paradigm” of Science in Materials Science, Artificial Intelligence for Materials Science Workshop (AIMS), National Institute of Standards and Technology, August 07, 2018, Gaithersburg, MD, USA.

  59. (Invited) Materials Informatics and Big Data: Realization of “Fourth Paradigm” of Science in Materials Science, 13th World Congress on Computational Mechanics (WCCM), July 25, 2018, New York City, NY, USA.

  60. (Invited) High Performance Data Mining: An Essential Paradigm for Interdisciplinary Big Data Analytics, Tata Consultancy Services Visit, TRDDC/TCS, July 18, 2018, Pune, Maharashtra, India.

  61. (Invited) Materials Informatics and Big Data: Realization of “Fourth Paradigm” of Science in Materials Science, Toyota Visit, Toyota Motor Corporation, June 13, 2018, Toyota-shi, Japan.

  62. The investigation of machine learning for material development, Toyota Visit, Toyota Motor Corporation, June 13, 2018, Toyota-shi, Japan.

  63. (Invited) Materials Informatics and Big Data: Realization of “Fourth Paradigm” of Science in Materials Science, Machine Learning in Science & Engineering, Carnegie Mellon University, June 08, 2018, Pittsburgh, PA, USA.

  64. Deep Transfer Learning Based Pavement and Structural Health Monitoring , Machine Learning in Science & Engineering, Carnegie Mellon University, June 08, 2018, Pittsburgh, PA, USA.

  65. Big Data Analytics in Medicine and Healthcare: Analyzing Electronic Healthcare Records, Sequence Data, Social Media, and More, Machine Learning in Science & Engineering, Carnegie Mellon University, June 07, 2018, Pittsburgh, PA, USA.

  66. CHiMaD Data Mining, CHiMaD Site-Visit, April 16, 2018, Evanston, IL, USA.

  67. (Invited) Materials Informatics and Big Data: Realization of “Fourth Paradigm” of Science in Materials Science, Machine Learning in Materials Science Workshop, University of Utah, April 06, 2018, Salt Lake City, UT, USA.

  68. Materials Informatics and Big Data: Realization of “Fourth Paradigm” of Science in Materials Science, MRS Spring Meeting & Exhibit, April 04, 2018, Phoenix, AZ, USA.

  69. (Invited) Materials Informatics and Big Data: Realization of “Fourth Paradigm” of Science in Materials Science, 6th NU-NIMS Materials Genome Workshop, March 28, 2018, Evanston, IL, USA.

  70. (Invited) CHiMaD Data Mining, SRG 2018, March 27, 2018, Evanston, IL, USA.

  71. (Invited) Data-Driven Approaches for Steel Fatigue Strength Prediction, TMS 2018: Fatigue in Materials: Fundamentals, Multiscale Modeling and Prevention - Data-driven Investigations of Fatigue, March 12, 2018, Phoenix, AZ, USA.

  72. (Invited) Materials Informatics and Big Data: Realization of “Fourth Paradigm” of Science in Materials Science, Materials Science Division Colloquium, Argonne National Lab, February 15, 2018, Lemont, IL, USA.

  73. Deep Learning Models for Structure-Property Linkages in High Contrast Composites, MURI Final Review, December 18, 2017, Arlington, VA, USA.

  74. Learning Crystal Orientations of Polycrystalline Materials from Electron Backscatter Diffraction Experiments using Convolutional Neural Networks, MURI Final Review, December 18, 2017, Arlington, VA, USA.

  75. (Invited) Materials Informatics and Big Data: Realization of “Fourth Paradigm” of Science in Materials Science, International Conference on Nano and Functional Materials (NFM 2017), November 17, 2017, BITS Pilani, Rajasthan, India.

  76. (Invited) Materials Informatics on Images: Structure Characterization, Crack Detection, Localization, and More, Machine Learning Applied to Materials Imaging Workshop, Northwestern-Argonne Institute of Science and Engineering, October 30, 2017, Evanston, IL, USA.

  77. (Invited) High Performance Data Mining: An Essential Paradigm for Interdisciplinary Big Data Analytics, 2017 IEEE Region 4 Workshop on Big Data, October 25, 2017, Evanston, IL, USA.

  78. Materials Informatics and Big Data: Realization of “Fourth Paradigm” of Science in Materials Science, MS&T 2017: Data and Tools for Materials Discovery and Design: Data Science Methods in Materials Discovery and Development, October 11, 2017, Pittsburgh, PA, USA.

  79. Data-Driven Approaches for Predicting Thermoelectric Properties, MS&T 2017: In-situ Characterization of Energy Materials, October 10, 2017, Pittsburgh, PA, USA.

  80. Classification of Scientific Journal Articles to Support Automated Data Extraction and Curation, MS&T 2017: Recent Advances in Computer-aided Materials Design: Emerging Approaches of Material Design, October 10, 2017, Pittsburgh, PA, USA.

  81. Data-Driven Approaches for Predicting Fatigue Strength of Steels, MS&T 2017: Shaping & Forming of Advanced High Strength Steels: Performance, October 10, 2017, Pittsburgh, PA, USA.

  82. Materials Informatics and Big Data: Realization of 4th Paradigm of Science in Materials Science, Materials Research and Data Science Conference, September 25, 2017, Rockville, MD, USA.

  83. (Invited) Materials Informatics and Big Data: Realization of 4th Paradigm of Science in Materials Science, MAPEX Symposium 2017, University of Bremen, September 15, 2017, Bremen, Germany.

  84. (Keynote) Materials Informatics and Big Data: Realization of 4th Paradigm of Science in Materials Science, Materials Genome Symposium, Chinese Materials Conference (CMC 2017), Chinese Materials Research Society (C-MRS), July 11, 2017, Yinchuan, Ningxia, China.

  85. Materials Informatics and Big Data: Realization of 4th Paradigm of Science in Materials Science, 4th World Congress on Integrated Computational Materials Engineering (ICME 2017), ICME Success Stories and Applications, May 24, 2017, Ypsilanti, MI, USA.

  86. (Invited) Materials Informatics and Big Data: Realization of 4th Paradigm of Science in Materials Science, SJTU/MaGIC Faculty Visit, April 27, 2017, Evanston, IL, USA.

  87. (Invited) Materials Informatics and Big Data: Realization of 4th Paradigm of Science in Materials Science: Steel Fatigue Strength Predictor, 5th NU-NIMS Materials Genome Workshop, March 28, 2017, Evanston, IL, USA.

  88. CHiMaD Data Mining, CHiMaD Annual Meeting, March 27, 2017, Evanston, IL, USA.

  89. (Invited) CHiMaD Data Mining: Fatigue, SRG 2017, March 23, 2017, Evanston, IL, USA.

  90. Data Science Approaches for Predicting Fatigue Strength of Steels, TMS 2017, February 27, 2017, San Diego, CA, USA.

  91. Data Science Approaches for Predicting Thermoelectric Properties, TMS 2017, February 27, 2017, San Diego, CA, USA.

  92. Parallel Implementation of Lossy Data Compression for Temporal Data Sets, 23rd Annual International Conference on High Performance Computing, Data, and Analytics (HiPC), December 20, 2016, Hyderabad, India.

  93. Five Year Life Expectancy Calculator for Older Adults, IEEE International Conference on Data Mining (ICDM), December 13, 2016, Barcelona, Spain.

  94. A Formation Energy Predictor for Crystalline Materials Using Ensemble Data Mining, IEEE International Conference on Data Mining (ICDM), December 13, 2016, Barcelona, Spain.

  95. Predicting the Outcome of Startups: Less Failure, More Success, IEEE ICDM Workshop on Data Market for Co-evolution of Sciences and Business (MoDAT), December 12, 2016, Barcelona, Spain.

  96. (Invited) Materials Informatics and Big Data: Realization of the “Fourth Paradigm” of Science in Materials Science, CHiMaD Summit on Data & Analytics for Materials Research, November 02, 2016, Evanston, IL, USA.

  97. A Fatigue Strength Predictor for Steels Using Ensemble Data Mining, 25th ACM International Conference on Information and Knowledge Management (CIKM), October 26, 2016, Indianapolis, IN, USA.

  98. (Invited) High Performance Data Mining: An Essential Paradigm for Big Data Analytics and Knowledge Discovery, 3M Visit, October 19, 2016, Evanston, IL, USA.

  99. Identifying HotSpots in Five Year Survival Electronic Health Records of Older Adults, 6th IEEE International Conference on Computational Advances in Bio and Medical Sciences (ICCABS), October 13, 2016, Atlanta, GA, USA.

  100. Software tools for sequence comparison, sequence mapping, and patient-specific healthcare outcome prediction, 7th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), October 05, 2016, Seattle, WA, USA.

  101. Materials Informatics and Big Data: Realization of 4th Paradigm of Science in Materials Science, International Conference on Fatigue Damage of Structural Materials (FATD), September 22, 2016, Hyannis, MA, USA.

  102. CHiMaD Data Mining: An Update, CHiMaD Executive Meeting, September 12, 2016, Evanston, IL, USA.

  103. Materials Informatics and Big Data: Realization of 4th Paradigm of Science in Materials Science, Theory and Applications of Computational Chemistry (TACC), August 30, 2016, University of Washington, Seattle, WA, USA.

  104. Deep Learning Based Big Data Analytics in Materials Science, MURI Annual Meeting, August 22, 2016, Caltech, Pasadena, CA, USA.

  105. (Invited) Data-driven materials science enabling large-scale property prediction and optimization, APS/CNM Users Meeting 2016, May 10, 2016, Argonne National Lab, Chicago, IL, USA.

  106. (Invited) High Performance Data Mining: An Essential Paradigm for Big Data Analytics and Knowledge Discovery, Invited seminar, May 05, 2016, Golden, CO, USA.

  107. (Invited) Big data analytics in medicine and healthcare: Analyzing electronic healthcare records, sequence data, social media, and more, Outcomes Research Workshop, April 27, 2016, University of Chicago, Chicago, IL, USA.

  108. CHiMaD Data Mining, CHiMaD Annual Meeting, March 23, 2016, Evanston, IL, USA.

  109. (Invited) CHiMaD Data Mining: Fatigue, SRG 2016, March 21, 2016, Evanston, IL, USA.

  110. (Invited) High Performance Data Mining: An Essential Paradigm for Big Data Analytics and Knowledge Discovery, Invited seminar, March 02, 2016, Auburn, AL, USA.

  111. (Invited) Towards Better Efficiency and Accuracy: Data Mining for Prediction and Optimization in Materials System Design, TMS 2016, February 16, 2016, Nashville, TN, USA.

  112. CHiMaD Data Mining: An Update, CHiMaD Executive Meeting, October 19, 2015, Evanston, IL, USA.

  113. Parallel Distributed-Memory Based Community Detection for Large Graphs, DARPA GRAPHS / SIMPLEX Workshop: Data, Algorithms and Problems on Graphs (DAPG) 2015, September 28, 2015, New York, NY, USA. [video]

  114. (Invited) Big Data Analytics and Discovery in Medicine and Healthcare, NUS Surgical Faculty Visit, September 18, 2015, Chicago Innovation Exchange, Chicago, IL, USA.

  115. Pruned Search: A Machine Learning Based Meta-Heuristic Approach for Constrained Continuous Optimization, 8th International Conference on Contemporary Computing (IC3) 2015, August 20, 2015, Noida, Delhi NCR, India.

  116. All Your Google and Facebook Logins are Belong to Us: A Case for Single Sign-off, 8th International Conference on Contemporary Computing (IC3) 2015, August 20, 2015, Noida, Delhi NCR, India.

  117. (Invited) Towards an Infrastructure for Materials Data Analytics: An Overview of Tools and Platforms for Code Development, Collaboration, and Data Analytics, Materials Research Collaboration Environment Workshop, August 13, 2015, Dayton, OH, USA.

  118. Application of Machine Learning to Materials Discovery and Development, MURI 3-Year Review, June 23, 2015, Arlington, VA, USA.

  119. Optimization of Microstructures in Magnetoelastic Alloys, MURI 3-Year Review, June 23, 2015, Arlington, VA, USA.

  120. Mining of Process-Structure-Property Linkages Using Data Science Tools, MURI 3-Year Review, June 23, 2015, Arlington, VA, USA.

  121. Towards Better Efficiency and Accuracy: Data Mining for Optimization and Prediction in Materials System Design, AFOSR Program Review, May 21, 2015, Arlington, VA, USA.

  122. CHiMaD Data Mining, CHiMaD Annual Meeting, May 01, 2015, Evanston, IL, USA.

  123. Data-driven Analytics for Materials Science: Realization of the Fourth Paradigm of Science, DARPA SIMPLEX Pre-Kickoff Meeting, April 14, 2015, Evanston, IL, USA.

  124. (Invited) CHiMaD Data Mining: Fatigue, SRG 2015, March 23, 2015, Evanston, IL, USA.

  125. (Invited) High Performance Data Mining: An Essential Paradigm for Big Data Analytics and Knowledge Discovery, Invited seminar, March 09, 2015, Lawrence, KS, USA.

  126. CHiMaD Data Mining, CHiMaD Executive Meeting, December 01, 2014, Evanston, IL, USA.

  127. (Invited) High Performance Big Data Analytics for Data-Driven Discovery in Natural Sciences, GBMF Symposium, July 29, 2014, Palo Alto, CA, USA.

  128. (Invited) CHiMaD Data Mining, MTL/SRG 2014, March 24, 2014, Evanston, IL, USA.

  129. High Performance Big Data Clustering, SDAV All-Hands Meeting, February 25, 2013, Atlanta, GA, USA.

  130. (Invited) An Overview of Essential Concepts in Data Mining, MURI Program Review, January 21, 2014, Dayton, OH, USA.

  131. Multi-objective Optimization and Multimodal Prediction in the Design of Materials System, MURI Program Review, January 21, 2014, Dayton, OH, USA.

  132. (Invited) Data-Driven Analytics and Discovery in Medicine and Healthcare, Research Mela, November 23, 2013, Rush Hospital, Chicago, IL, USA.

  133. An Analysis of Variation in Hospital Billing Using Medicare Data, KDD Workshop on Data Mining for Healthcare (DMH), August 11, 2013, Chicago, IL, USA.

  134. Heart Transplant Outcome Prediction using UNOS Data, KDD Workshop on Data Mining for Healthcare (DMH), August 11, 2013, Chicago, IL, USA.

  135. Colon Surgery Outcome Prediction Using ACS NSQIP Data, KDD Workshop on Data Mining for Healthcare (DMH), August 11, 2013, Chicago, IL, USA.

  136. High Performance Big Data Clustering, SDAV All-Hands Meeting, February 20, 2013, San Fransisco, CA, USA.

  137. Parallel Hierarchical Clustering on Shared Memory Platforms, International Conference on High Performance Computing (HiPC), December 19, 2012, Pune, Maharashtra, India.

  138. Data-driven Analytics and Applications - Realization of the Fourth Paradigm of Science, MURI Kickoff Meeting, October 19, 2012, Carnegie Mellon University, Pittsburgh, PA, USA.

  139. Supporting Computational Data Model Representation with High-performance I/O in Parallel netCDF, International Conference on High Performance Computing (HiPC), December 19, 2011, Bangalore, Karnataka, India.

  140. Enhancing Parallelism of Pairwise Statistical Significance Estimation for Local Sequence Alignment, 2nd HiPC Workshop on Hybrid Multi-Core Computing, December 18, 2011, Bangalore, Karnataka, India.

  141. Identifying HotSpots in Lung Cancer Data Using Association Rule Mining, 2nd IEEE ICDM Workshop on Biological Data Mining and its Applications in Healthcare, BioDM 2011, December 11, 2011, Vancouver, Canada.

  142. Community Dynamics and Analysis of Decadal Trends in Climate Data, 3rd IEEE ICDM Workshop on Knowledge Discovery from Climate Data, ClimKD 2011, December 11, 2011, Vancouver, Canada.

  143. Derived Distribution Points Heuristic for Fast Pairwise Statistical Significance Estimation, ACM International Conference on Bioinformatics and Computational Biology (ACM-BCB) 2010, August 03, 2010, Niagara, NY, USA.

  144. MPIPairwiseStatSig: Parallel Pairwise Statistical Significance Estimation of Local Sequence Alignment, HPDC ECMLS 2010, June 22, 2010, Chicago, IL, USA.

  145. Pairwise Statistical Significance of Local Sequence Alignment Using Substitution Matrices with Sequence-Pair-Specific Distance, IEEE International Conference on Information Technology (ICIT 2008), December 20, 2008, Bhubaneswar, Orissa, India.

  146. Pairwise DNA Alignment with Sequence Specific Transition-Transversion Ratio Using Multiple Parameter Sets, IEEE International Conference on Information Technology (ICIT 2008), December 20, 2008, Bhubaneswar, Orissa, India.

  147. Conservative, Non-Conservative and Average Pairwise Statistical Significance of Local Sequence Alignment, IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2008), November 5, 2008, Philadelphia, PA, USA.

  148. Pairwise Statistical Significance of Local Sequence Alignment Using Multiple Parameter Sets, 2nd International Workshop on Data and Text Mining in Bioinformatics (DTMBIO 2008), October 30, 2008, Napa Valley, CA, USA.

  149. DNAlignTT: Pairwise DNA Alignment with Sequence Specific Transition-Transversion Ratio, IEEE International Conference on EIT 2008, May 21, 2008, Ames, IA, USA.

  150. Pairwise Statistical Significance Versus Database Statistical Significance for Local Alignment of Protein Sequences, International Symposium on Bioinformatics Research and Applications (ISBRA 2008), May 7, 2008, Atlanta, GA, USA.

  151. Estimating Pairwise Statistical Significance of Protein Local Alignments Using a Clustering-Classification Approach Based on Amino Acid Composition, International Symposium on Bioinformatics Research and Applications (ISBRA 2008), May 7, 2008, Atlanta, GA, USA.

  152. Identifying Temporal Gene Networks Using Signal Processing Metrics on Time-Series Gene Expression Data, IEEE Third International Conference on Intelligent Sensing and Information Processing, December 14, 2005, Bangalore, Karnataka, India.

  153. Identifying Temporal Gene Networks by Mining Gene Expression Data, IEEE 12th International Conference on Advanced Computing and Communications (ADCOM) 2004, December 17, 2004, Ahmedabad, Gujarat, India.