Bhargob Deka | Bayesian machine learning | Best Researcher Award

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🌟Dr. Bhargob Deka, Bayesian machine learning, Best Researcher Award🏆

Doctorate at Polytechnique Montreal, Canada

Professional Profiles:

Bio Summary

AI Research Scientist and Data Scientist with over 4 years of experience in applied probability, statistics, and machine learning. Specialized in Bayesian neural networks, time series modeling, and industrial research. Enthusiastic about AI and continuous learning. Proven track record in developing innovative ML models, leading projects, and collaborating with R&D teams.

Education

Polytechnique Montréal | Sep 2018-Dec 2022

  • Ph.D. in Civil Engineering: Machine Learning Specialization – GPA 4/4.3
  • Research Grant: Hydro Québec, NSERC

McGill University | Sep 2015-Mar 2018

  • M. Eng. in Civil Engineering: Structural Engineering – GPA 3.88/4
  • Research Grant: Graduate Research Assistantship

Assam Engineering College | Aug 2010-June 2014

  • B. Eng. in Civil Engineering: First-Class Honours with 75.78%
  • Research Grant: North-Eastern Council Merit Scholarship

Research Focus

Advanced Machine Learning Research

  • Bayesian Neural Networks, Regression, Classification, Time Series

Industrial Research Leadership

  • End-to-end ML solutions, process automation, software training

Machine Learning Research Scholarship

  • Neurocomputing, Adaptive Control, Signal Processing

AI Enthusiast

  • Diverse end-to-end deep learning projects in CV, NLP, Generative AI

Professional Journey

Machine Learning Researcher | Polytechnique Montréal | Sep 2018 – Present

  • Developed AGVI for uncertainty quantification in Bayesian neural networks.
  • Improved training time significantly, applied in regression, classification, and time series.
  • Published AGVI in the International Journal of Adaptive Control and Signal Processing.

Research Consultant | Polytechnique Montréal | Sep 2018 – Present

  • Developed ML approach for nonlinear dependencies in time series.
  • Collaborated with dam engineers for real-time anomaly detection, winning competitions.

Honors & Awards

Eliminated hyper-parameter tuning and sped up Bayesian neural network training.

First and fourth rankings in predictive modeling competition at ICOLD-BW2022.

Author Metrics

Number of publications: 4

Conferences and Talks: 2

First-author publications: 2

Research Timeline

2018-2022: Ph.D. in Civil Engineering with a focus on Machine Learning.

2018-Present: Machine Learning Researcher at Polytechnique Montréal.

2018-Present: Research Consultant for industrial projects in collaboration with Hydro Québec.

2022: Published AGVI in the International Journal of Adaptive Control and Signal Processing.

2022: First and fourth rankings in predictive modeling competition at ICOLD-BW2022.

Publications & Contributions

Journals:
  • Tractable Uncertainty Quantification in Bayesian Neural Networks (Neurocomputing, 2023).
  • Gaussian Variance Inference for State-Space Models (IJACSP, 2023).
  • Inspector’s Uncertainty Inference Using Network-Scale Visual Inspections (J. Computing in Civil Engineering, 2023).
  • Gaussian Multiplicative Approximation for State-Space Models (Structural Control and Health Monitoring, 2022).
Conferences and Talks:
  • Online aleatory uncertainty quantification for probabilistic time series (ICASP14, 2023).
  • Dam Behavior Prediction Using Bayesian Models (Benchmark Workshop on Numerical Analysis of Dams, 2022).
Publications Top Noted

1. Building Classification Scheme and Vulnerability Model for the City of Guwahati, Assam

  • Authors: J Pathak, R Bharali, B Deka, S Pathak, IJ Ahmed, DH Lang, A Meslem
  • Published in: EQRisk Project Report
  • Year: 2015
  • Cited By: 6

2. The Gaussian Multiplicative Approximation for State-Space Models

  • Authors: B Deka, L Ha Nguyen, S Amiri, JA Goulet
  • Published in: Structural Control and Health Monitoring
  • Volume: 29 (3)
  • Page: e2904
  • Year: 2022
  • Cited By: 5

3. Damage Assessment of RC Frame Structures under Long Duration Aftershock Ground Motion

  • Authors: B Deka, SN Rahman, P Tamuly
  • Published in: International Journal of Innovative Research in Science, Engineering, and Technology
  • Volume: 3 (9)
  • Pages: 16144-16149
  • Year: 2014
  • Cited By: 5

4. Analytical Bayesian Parameter Inference for Probabilistic Models with Engineering Applications

  • Author: B Deka
  • Published at: Polytechnique Montréal
  • Year: 2022
  • Cited By: 3

5. Analytically Tractable Heteroscedastic Uncertainty Quantification in Bayesian Neural Networks for Regression Tasks

  • Authors: B Deka, LH Nguyen, JA Goulet
  • Published in: Neurocomputing
  • Pages: 127183

Sepideh Khoee | Polymer Chemistry | Best Researcher Award

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🌟 Prof Dr. Sepideh Khoee, University of Tehran, Iran: Polymer Chemistry🏆

Professional Profiles:

Bio Summary:

Dr. Sepideh Khoee is a highly accomplished polymer chemist and professor at the University of Tehran, Iran. She earned her Ph.D. in polymer chemistry from Isfahan University of Technology in 2002, following an M.Sc. in organic chemistry and a B.Sc. in chemistry from Isfahan University. With a focus on nanotechnology and drug delivery, Dr. Khoee has made substantial contributions to her field, earning her international recognition and several prestigious awards.

Education:

  • Ph.D. in Polymer Chemistry, Isfahan University of Technology, 2002
  • M.Sc. in Organic Chemistry, Isfahan University, 1994
  • B.Sc. in Chemistry, Isfahan University, 1990

Research Focus:

  • Synthesis of micro/nanomotors
  • Synthesis of linear and branched copolymers
  • Synthesis of drug-loaded nanopolymers for drug delivery investigations

Professional Journey:

  • Professor, Department of Polymer Chemistry, University of Tehran (2013-present)
  • Visiting Associate Professor, Department of Materials Science and Engineering, Lehigh University, USA (2009-2010)
  • Associate Professor, Department of Polymer Chemistry, University of Tehran (2008-2013)
  • Assistant Professor, Department of Polymer Chemistry, University of Tehran (2003-2008)

Honors & Awards:

  • Maryam Mirzakhani Award at the 4th National Festival of Women and Science (2021)
  • COMSTECH Patent Award (2019)
  • Distinguished Researcher of Chemistry, University of Tehran Research Week (2018, 2015)
  • Outstanding Researcher, 7th Iran Nano Festival (NanoMatch, 2013)

Publications Top Noted & Contributions:

  • Author of several book chapters on nanotechnology and drug delivery
  • Notable works include chapters on medicinal plant-based terpenoids, reversible core–shell crosslinked micelles, and Janus nanoparticles in drug delivery

Title: “Use of NIR/NaBH4 Combinatorial Techniques for Simultaneous and High-Efficient Adsorption of Heavy Metal Ions from Contaminated Water by Chitosan/Au Janus Microdisks”

  • Journal: Surfaces and Interfaces
  • Publication Date: December 2023
  • DOI: 10.1016/j.surfin.2023.103801
  • Source: Crossref
  • Summary: This study explores the application of NIR (Near-Infrared) and NaBH4 combinatorial techniques for the simultaneous and efficient adsorption of heavy metal ions from contaminated water. The adsorption is facilitated by Chitosan/Au Janus Microdisks.

Title: “Magnetite‐Based Janus Nanoparticles, Their Synthesis and Biomedical Applications”

  • Journal: WIREs Nanomedicine and Nanobiotechnology
  • Publication Date: November 2023
  • DOI: 10.1002/wnan.1908
  • Source: Crossref
  • Summary: This article focuses on the synthesis of Magnetite-based Janus Nanoparticles and explores their potential biomedical applications.

Title: “Tuning the Motion Velocity of Enzyme-Driven Dextran/Polyacrylamide Janus Nanomotors by Incorporating the Thermo-Switchable PNIPAM Moieties in Their Structure”

  • Journal: European Polymer Journal
  • Publication Date: July 2023
  • DOI: 10.1016/j.eurpolymj.2023.112113
  • Source: Crossref
  • Summary: This research investigates the modulation of motion velocity in enzyme-driven Dextran/Polyacrylamide Janus Nanomotors through the incorporation of thermo-switchable PNIPAM moieties.

Title: “Dual-Drug Delivery by Anisotropic and Uniform Hybrid Nanostructures: A Comparative Study of the Function and Substrate–Drug Interaction Properties”

  • Journal: Pharmaceutics
  • Publication Date: April 11, 2023
  • DOI: 10.3390/pharmaceutics15041214
  • Source: Crossref
  • Summary: This study presents a comparative analysis of dual-drug delivery using anisotropic and uniform hybrid nanostructures, exploring their function and substrate-drug interaction properties.

Title: “The Simultaneous Role of Porphyrins’ H- and J- Aggregates and Host–Guest Chemistry on the Fabrication of Reversible Dextran-PMMA Polymersome”

  • Journal: Scientific Reports
  • Publication Date: December 2021
  • DOI: 10.1038/s41598-021-82256-7
  • Source: Crossref
  • Summary: This article explores the simultaneous roles of porphyrins’ H- and J-aggregates and host–guest chemistry in the fabrication of reversible Dextran-PMMA polymersomes.

These publications showcase Dr. Sepideh Khoee’s diverse research interests, spanning from environmental applications to biomedical nanotechnology and drug delivery. Her work reflects a multidisciplinary approach with a focus on innovative materials and techniques.

Author Metrics:

  • Holds a patent: “Synthesizing Nanocapsules Containing Reactive Amine” (US Patent 20,150,307,649)
  • Recognized for significant contributions to the field with awards such as the COMSTECH Patent Award and the Maryam Mirzakhani Award
  • Citations: 3,332 citations across 2,636 documents
  • Documents: 143
  • h-index: 36

Research Timeline:

  • 1996-2002: Ph.D. in polymer chemistry
  • 2003-2008: Assistant Professor, Department of Polymer Chemistry, University of Tehran
  • 2008-2013: Associate Professor, Department of Polymer Chemistry, University of Tehran
  • 2009-2010: Visiting Associate Professor, Lehigh University, USA
  • 2013-present: Professor, Department of Polymer Chemistry, University of Tehran

Dr. Khoee’s research journey reflects a commitment to advancing polymer chemistry, nanotechnology, and drug delivery, earning her accolades and recognition both nationally and internationally.