diff --git a/_includes/sections/team.html b/_includes/sections/team.html index 7698489..4eb58fc 100644 --- a/_includes/sections/team.html +++ b/_includes/sections/team.html @@ -11,7 +11,7 @@ Team Members {% for member in site.members %} - + @@ -21,7 +21,7 @@ {{ member.name }} {% for s in member.social%} - + {% endfor %} diff --git a/_layouts/default.html b/_layouts/default.html index 026a9af..8088013 100644 --- a/_layouts/default.html +++ b/_layouts/default.html @@ -16,6 +16,8 @@ + + @@ -33,6 +35,24 @@ {{content}} + diff --git a/_layouts/member.html b/_layouts/member.html index 763d5d0..720792e 100644 --- a/_layouts/member.html +++ b/_layouts/member.html @@ -1,5 +1,5 @@ --- -layout: default +layout: pm_default --- @@ -22,7 +22,7 @@ {{page.name}} {% for s in page.social%} - + {% endfor %} diff --git a/_layouts/pm_default.html b/_layouts/pm_default.html new file mode 100644 index 0000000..49f341b --- /dev/null +++ b/_layouts/pm_default.html @@ -0,0 +1,74 @@ + + + + + + + MIND LAB + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + {{site.name}} + + + + + + {% for item in site.data.navigation %} + {{item.name}} + {% endfor %} + + + + + + + + {{content}} + + + + + + + + + + + + + + + + + + + + diff --git a/_layouts/post.html b/_layouts/post.html index 7d5777d..0c59b8a 100644 --- a/_layouts/post.html +++ b/_layouts/post.html @@ -1,5 +1,5 @@ --- -layout: default +layout: pm_default --- diff --git a/_members/Akram_Karimi.md b/_members/Akram_Karimi.md new file mode 100644 index 0000000..c8d97b4 --- /dev/null +++ b/_members/Akram_Karimi.md @@ -0,0 +1,11 @@ +--- +layout: member +name: Akram Karimi +avatar: /assets/img/membersimg/images.png +title: Member +social: +--- + +Master student in financial mathematics + +###### Email : akram.karimi @aut.ac.ir diff --git a/_members/Atefeh_Sadeghi.md b/_members/Atefeh_Sadeghi.md new file mode 100644 index 0000000..0d79515 --- /dev/null +++ b/_members/Atefeh_Sadeghi.md @@ -0,0 +1,11 @@ +--- +layout: member +name: Atefeh Sadeghi +avatar: /assets/img/membersimg/images.png +title: Member +social: +--- + +Atefeh Sadeghi is a Ph.D. student at Amirkabir University of Technology. Her research focuses on numerical solutions of partial differential equations and integral-differential equations. She holds her Master's degree in Financial Mathematics from Kharazmi University. Her Master's thesis was dedicated to Optimal trading strategy considering the stochastic price impact and incorporating signals. She is interested in developing numerial methods to solve problems related to engineering, biology and finance. + +###### Email : atef.sadeghi@aut.ac.ir diff --git a/_members/Baharak_Hooshyar_Farzin.md b/_members/Baharak_Hooshyar_Farzin.md new file mode 100644 index 0000000..a65350b --- /dev/null +++ b/_members/Baharak_Hooshyar_Farzin.md @@ -0,0 +1,13 @@ +--- +layout: member +name: Baharak Hooshyar Farzin +avatar: /assets/img/membersimg/images.png +title: Member +social: + - link: https://scholar.google.com/citations?user=WA5zYxUAAAAJ&hl=en + icon: bi-mortarboard +--- + +Baharak Hooshyar Farzin is a Ph.D. student at Amirkabir University of Technology. Her research focuses on enhanced finite element methods for the numerical solutions of partial differential equations. She holds her Master's degree from Amirkabir University of Technology. Her Master's thesis was dedicated to the proper orthogonal decomposition idea and finite element method for numerical solution of the solute transport equation. She is interested in developing numerical approaches based on weak Galerkin finite, isoparametric, and virtual element methods to solve practical engineering problems. + +###### Email : baharak.farzin74@aut.ac.ir diff --git a/_members/Elnaz_Ramezani .md b/_members/Elnaz_Ramezani .md new file mode 100644 index 0000000..64cd668 --- /dev/null +++ b/_members/Elnaz_Ramezani .md @@ -0,0 +1,13 @@ +--- +layout: member +name: Elnaz Ramezani +avatar: /assets/img/membersimg/images.png +title: Member +social: + - link: https://www.linkedin.com/in/elnazramezani + icon: bi-linkedin +--- + +Elnaz Ramezani is a master's student in Financial Mathematics. My project focuses on default prediction using explainable machine learning models. Additionally, I am interested in data science and work as a data analyst, utilizing Power BI, SQL, and Python. + +###### Email : elnaz.rmzn@aut.ac.ir diff --git a/_members/Fatemeh_Moaven.md b/_members/Fatemeh_Moaven.md new file mode 100644 index 0000000..2c804fa --- /dev/null +++ b/_members/Fatemeh_Moaven.md @@ -0,0 +1,17 @@ +--- +layout: member +name: Fatemeh Moaven +# avatar: /assets/img/membersimg/Fatemehmoaven.jpg +avatar: /assets/img/membersimg/images.png +title: Member +social: + - link: https://www.linkedin.com/in/fatemeh-moaven-1151b2231/ + icon: bi-linkedin + + - link: https://github.com/Fm1540440 + icon: bi-github +--- + +Fatemeh Moaven is a PhD student in Applied Mathematics with a focus on Numerical Analysis at Amirkabir University of Technology. She holds a master's degree in Numerical Analysis from Iran University of Science and Technology. Her master's thesis was dedicated to the analysis of cardiac signals using neural networks, and her doctoral dissertation focuses on discovering mathematical models based on data. She is interested in research in the fields of data mining and machine learning and is seeking to advance in these areas. + +###### Email : fatemeh.moaven@aut.ac.ir diff --git a/_members/M.Amin_Ghoreyshi.md b/_members/M.Amin_Ghoreyshi.md new file mode 100644 index 0000000..4608d04 --- /dev/null +++ b/_members/M.Amin_Ghoreyshi.md @@ -0,0 +1,13 @@ +--- +layout: member +name: M.Amin Ghoreyshi +avatar: /assets/img/membersimg/images.png +title: Member +social: + - link: https://www.linkedin.com/in/aminghoreyshi/ + icon: bi-linkedin +--- + +Amin Ghoreyshi is a master’s student in applied mathematics at Amirkabir University of Technology (Tehran Polytechnic). He holds a Bachelor's degree in mathematics and its applications from Shahid Chamran University of Ahvaz. His master’s thesis centers on numerical methods for solving fractional partial differential equations (FPDEs). Ghoreyshi has worked on various numerical methods and models involving distributed-order FPDEs. His research interests include mathematical modeling, fractional calculus, mathematical analysis, numerical linear algebra and numerical methods for partial integro-differential equations. Amin has some experience with Python and regularly uses MATLAB. + +###### Email : amin.ghoreyshi7@gmail.com, aminghoreyshi@aut.ac.ir diff --git a/_members/M.Soroush_Ghafari.md b/_members/M.Soroush_Ghafari.md new file mode 100644 index 0000000..3f023d9 --- /dev/null +++ b/_members/M.Soroush_Ghafari.md @@ -0,0 +1,13 @@ +--- +layout: member +name: M.Soroush Ghafari +avatar: /assets/img/membersimg/images.png +title: Member +social: + - link: https://www.linkedin.com/in/soroushghafari + icon: bi-linkedin +--- + +M. Soroush Ghafari graduated with a Master's degree in Applied Mathematics, specializing in solving equations related to fluid dynamics using numerical methods. His thesis focused on the simulation and numerical solution of the Navier-Stokes-Cahn-Hilliard equation using local meshless methods. He has a strong interest in fluid dynamics, particularly in the context of climate change and geophysics. Ghafari is proficient in programming languages such as MATLAB and Python. He is currently exploring integrating numerical methods with machine learning and data science to develop more accurate models for fluid dynamics. + +###### Email : m.soroush.g@gmail.com diff --git a/_members/Maedeh_Nemati.md b/_members/Maedeh_Nemati.md new file mode 100644 index 0000000..37995da --- /dev/null +++ b/_members/Maedeh_Nemati.md @@ -0,0 +1,11 @@ +--- +layout: member +name: Maedeh Nemati +avatar: /assets/img/membersimg/images.png +title: Member +social: +--- + +Maedeh Nemati is a master’ student in in applied mathematics at Amirkabir University of Technology (Tehran Polytechnic). His thesis is about the numerical solution of Schrödinger-Poisson equation with application in cosmology and nonlinear optics. + +###### Email : maede.nemati@aut.ac.ir diff --git a/_members/Mahya_Pashapour.md b/_members/Mahya_Pashapour.md new file mode 100644 index 0000000..bc080a1 --- /dev/null +++ b/_members/Mahya_Pashapour.md @@ -0,0 +1,16 @@ +--- +layout: member +name: Mahya Pashapour +avatar: /assets/img/membersimg/images.png +title: Member +social: + - link: https://www.linkedin.com/in/mahya-pashapour-18a939264 + icon: bi-linkedin + + - link: https://github.com/mahyapashapour + icon: bi-github +--- + +Mahya Pashapour is a master's student in Applied Mathematics, Numerical Analysis, at Amirkabir University of Technology (Tehran Polytechnic). Her research focuses on solving partial differential equations (PDEs) and parameter estimation for these equations using Physics-Informed Neural Networks (PINNs). She is working on the Fisher-KPP reaction-diffusion equation, which is used to model cell invasion. Pashapour is proficient in Python and MATLAB for numerical methods in solving PDEs. She holds a bachelor's degree in Applied Mathematics from Amirkabir University of Technology (Tehran Polytechnic). + +###### Email : mahyapashapour@aut.ac.ir diff --git a/_members/Masood_Farahani.md b/_members/Masood_Farahani.md new file mode 100644 index 0000000..1dfb914 --- /dev/null +++ b/_members/Masood_Farahani.md @@ -0,0 +1,19 @@ +--- +layout: member +name: Masood Farahani +avatar: /assets/img/membersimg/images.png +title: Member +social: + - link: linkedin.com/in/masood-farahani-a31a65167 + icon: bi-linkedin + + - link: https://github.com/masoodfarahani + icon: bi-github + + - link: https://scholar.google.com/citations?hl=en&view_op=list_works&gmla=ALUCkoUA1L5NxPW1a-Aon8TSTDYNCKA1ynTyO9GkanSaOJ5hDUDT8cpffqcdJ0CmSANvyOpppYsaPv74CUgTHxVepyYt6sJXHIc14hzoN-I&user=NN3D0CwAAAAJ + icon: bi-mortarboard +--- + +Masood Farahani, Ph.D. student of Amirkabir University of Technology, conducting research on numerical methods for solving partial differential equations (PDEs) and numerical methods for solving fractional partial differential equations (FPDEs). He completed his master's degree at Amirkabir University of Technology, where he researched numerical methods in financial mathematical models. He is also proficient in MATLAB and Python and is interested in developing mathematical techniques in engineering and biology and some other physical fields. + +###### Email : masoodfarahani@aut.ac.ir diff --git a/_members/Mohaddese_Heydari.md b/_members/Mohaddese_Heydari.md new file mode 100644 index 0000000..c568b30 --- /dev/null +++ b/_members/Mohaddese_Heydari.md @@ -0,0 +1,13 @@ +--- +layout: member +name: Mohaddeseh Heidari +avatar: /assets/img/membersimg/images.png +title: Member +social: + - link: https://www.linkedin.com/in/mohaddeseheydari + icon: bi-linkedin +--- + +Mohaddeseh Heidari is a Master's student in Applied Mathematics, specializing in Numerical Analysis at Amirkabir University. Her thesis is focused on predicting cryptocurrency prices using machine learning methods. Her interests include machine learning, data mining, the application of mathematics in finance, and areas related to numerical analysis. + +###### Email : mohaddese.heydari@aut.ac.ir diff --git a/_members/MohammadReza_Ahmadi.md b/_members/MohammadReza_Ahmadi.md new file mode 100644 index 0000000..da26db5 --- /dev/null +++ b/_members/MohammadReza_Ahmadi.md @@ -0,0 +1,13 @@ +--- +layout: member +name: MohammadReza Ahmadi +avatar: /assets/img/membersimg/images.png +title: Member +social: + - link: https://github.com/Mohammad-Reza-Ahmadi + icon: bi-github +--- + +Mohammad Reza Ahmadi is a Ph.D. candidate in Applied Mathematics with a focus on Financial Mathematics at Amirkabir University of Technology. He earned his Master's degree in Financial Mathematics from the University of Isfahan. His primary research interests lie in the mathematical modeling of financial markets and the study of stochastic differential equations associated with these models for option pricing. He employs a wide range of stochastic processes in his work, including Brownian motion, fractional Brownian motion, and various types of Lévy processes, such as pure jump and jump-diffusion processes. He is also interested in solving fractional partial differential equations (FPDEs) derived from financial mathematics models, along with their numerical solutions. Driven by a strong passion for applying mathematical models to financial markets, Mohammad Reza is actively exploring and validating his models in real-world financial settings. + +###### Email : mohammadreza.ahmadi@aut.ac.ir diff --git a/_members/Mohammad_mahdi-hajiabbasi.md b/_members/Mohammad_mahdi-hajiabbasi.md new file mode 100644 index 0000000..46312c8 --- /dev/null +++ b/_members/Mohammad_mahdi-hajiabbasi.md @@ -0,0 +1,17 @@ +--- +layout: member +name: Mohammad Mahdi Hajiabbasi +# avatar: /assets/img/membersimg/mohammadmahdihajiabasi.jpg +avatar: /assets/img/membersimg/images.png +title: Member +social: + - link: https://www.linkedin.com/in/mohammad-mahdi-hajiabbasi-87824020b/ + icon: bi-linkedin + + - link: https://github.com/hajiabbasi + icon: bi-github +--- + +Mohammad Mahdi Haji Abbasi is a graduate student in the Artificial Intelligence Master's program at Amirkabir University of Technology, currently in his third semester with an outstanding GPA of 19. He earned his bachelor's degree in mathematics with a GPA of 18.19 and was directly admitted to the master's program without an entrance exam. His primary research focuses on portfolio optimization using neural networks, particularly transformers and graph neural networks. Additionally, he is exploring numerical solutions of differential equations through neural networks. Mohammad is dedicated to applying advanced mathematical and computational techniques to address complex challenges in finance and science. + +###### Email : hajiabbasi@aut.ac.ir diff --git a/_members/mostafa_abbaszadeh.md b/_members/Mostafa_abbaszadeh.md similarity index 77% rename from _members/mostafa_abbaszadeh.md rename to _members/Mostafa_abbaszadeh.md index 41a9339..ebba30a 100644 --- a/_members/mostafa_abbaszadeh.md +++ b/_members/Mostafa_abbaszadeh.md @@ -1,14 +1,20 @@ --- layout: member name: Mostafa Abbaszadeh -avatar: /assets/img/speakers/download (1).jpg -title: Professor +# avatar: /assets/img/membersimg/download (1).jpg +avatar: /assets/img/membersimg/images.png +title: Professor/Team lead social: - link: https://www.linkedin.com/in/mostafa-abbaszadeh-81493b248/ icon: bi-linkedin - link: https://github.com/MAbbaszadeh1988 icon: bi-github + + - link: https://scholar.google.com/citations?hl=en&user=9nuBcAIAAAAJ&view_op=list_works&sortby=pubdate + icon: bi-mortarboard --- Mostafa Abbaszadeh is an Associate Professor of Applied Mathematics at Amirkabir University of Technology in Tehran, Iran. His research primarily focuses on numerical methods for partial differential equations, computational mechanics, and mathematical modeling. He has contributed significantly to the field through various publications, including studies on the proper orthogonal decomposition method and meshless methods for numerical simulations. Abbaszadeh has collaborated with researchers internationally and has presented his work at numerous conferences. His contributions have been recognized in several academic journals, where he has served as a reviewer. He is dedicated to advancing the understanding and application of mathematical techniques in engineering and physical sciences. + +###### Email : mabbaszadeh.aut@gmail.com \ No newline at end of file diff --git a/_members/Nima_Mohamadi.md b/_members/Nima_Mohamadi.md new file mode 100644 index 0000000..8d5b543 --- /dev/null +++ b/_members/Nima_Mohamadi.md @@ -0,0 +1,16 @@ +--- +layout: member +name: Nima Mohamadi +avatar: /assets/img/membersimg/images.png +title: Member +social: + - link: https://www.linkedin.com/in/nima-mohammadi-764a9a228 + icon: bi-linkedin + + - link: https://github.com/NMohammadi76 + icon: bi-github +--- + +Nima Mohammadi is a Ph.D. student at Amirkabir University of Technology, conducting research on numerical methods and computational physics, utilizing machine learning techniques for the analysis of psychological models. He completed his master's degree at Amirkabir University of Technology, where he researched mesh-free numerical methods in financial mathematical models. He is also proficient in MATLAB and Python and is interested in applying data science algorithms in various fields. + +###### Email : nima_mohammadi@aut.ac.ir diff --git a/_members/Reza _Masoumzadeh.md b/_members/Reza _Masoumzadeh.md new file mode 100644 index 0000000..783a465 --- /dev/null +++ b/_members/Reza _Masoumzadeh.md @@ -0,0 +1,17 @@ +--- +layout: member +name: Reza Masoumzadeh +# avatar: /assets/img/membersimg/RezaMasoumzadeh.jpg +avatar: /assets/img/membersimg/images.png +title: Member +social: + - link: https://www.linkedin.com/in/reza-masoumzadeh-10a09b225?utm_source=share&utm_campaign=share_via&utm_content=profile&utm_medium=android_app + icon: bi-linkedin + + - link: https://github.com/RezaMz77 + icon: bi-github +--- + +Reza Masoumzadeh is a Master's graduate in Numerical Analysis from Amirkabir University of Technology. He is a Bachelor's graduate in Mathematics and Applications from Isfahan University of Technology. His Master's thesis was dedicated to the simulation of two-phase flows based on the incompressible Cahn-Hilliard-Navier-Stokes (CHNS) equations using the isogeometric analysis (IGA) method. Accordingly, his research primarily focuses on numerical methods for solving partial differential equations. Masoumzadeh is interested in researching and working in the fields of machine learning and data mining, especially for combining such algorithms with numerical methods. Reza is proficient in programming with MATLAB, Maple and Python. + +###### Email : reza.masoumzade@aut.ac.ir diff --git a/_members/Shila_Rezvani.md b/_members/Shila_Rezvani.md new file mode 100644 index 0000000..f1ff270 --- /dev/null +++ b/_members/Shila_Rezvani.md @@ -0,0 +1,16 @@ +--- +layout: member +name: Shila Rezvani +avatar: /assets/img/membersimg/images.png +title: Member +social: + - link: linkedin.com/in/shila-rezvani-416853331 + icon: bi-linkedin + + - link: https://github.com/shilarez + icon: bi-github +--- + +Shila Rezvani is a master's student in applied mathematics in the field of numerical analysis at Amirkabir University of Technology. She has also completed her bachelor's degree in applied mathematics in the same university. Her research is in the field of various diseases such as the Corona virus and Alzheimer's disease and the numerical solution of their equations and machine learning methods, including Physics-informed neural networks (PINNs). She is interested in working on partial differential equations and ordinary differential equations with numerical methods and deep learning , parameter estimation and Physics-informed neural networks. She has programming skills in MATLAB and Python. Her senior project is in the field of Alzheimer's disease and discovering new equations for this disease. + +###### Email : shilarezvani1380@aut.ac.ir diff --git a/_members/Zahra_Ghobadi.md b/_members/Zahra_Ghobadi.md new file mode 100644 index 0000000..c34a29e --- /dev/null +++ b/_members/Zahra_Ghobadi.md @@ -0,0 +1,16 @@ +--- +layout: member +name: Zahra Ghobadi +avatar: /assets/img/membersimg/images.png +title: Member +social: + - link: https://www.linkedin.com/in/nghz/ + icon: bi-linkedin + + - link: https://github.com/nghz + icon: bi-github +--- + +Zahra Ghobadi is a Master student at Amirkabir University of Technology, working on financial data analysis and machine/deep learning algorithms. + +###### Email : vadod@aut.ac.ir diff --git a/_members/Zeynab_Baralak.md b/_members/Zeynab_Baralak.md new file mode 100644 index 0000000..04d67a2 --- /dev/null +++ b/_members/Zeynab_Baralak.md @@ -0,0 +1,12 @@ +--- +layout: member +name: Zeynab Baralak +avatar: /assets/img/membersimg/images.png +title: Member +social: +--- + +Zeynab Baralak is a PhD student in Applied Mathematics at Amirkabir University of Technology. Her research centers on numerical methods for solving partial differential equations (PDEs), specifically utilizing the Discontinuous Galerkin (DG) method to model acoustic waves and analyze noise generated by turbulent fluids. She is proficient in both MATLAB and Python. +Zeynab holds a master’s degree in Financial Mathematics from Allameh Tabataba'i University, where her main area of expertise was financial modeling for option pricing. During her studies, she also gained experience in accounting and worked as an accountant. + +###### Email : zeynab.baralak@aut.ac.ir diff --git a/_posts/2024-07-31-Nima Noii.md b/_posts/2024-07-31-Nima Noii.md new file mode 100644 index 0000000..2468a87 --- /dev/null +++ b/_posts/2024-07-31-Nima Noii.md @@ -0,0 +1,19 @@ +--- +layout: post +speaker: Nima Noii +position: Senior Research Associate +avatar: /assets/img/posts/31-07-2024/Nimanoii.jpeg +date: 31-07-2024 +title: > + Fatigue failure theory for lithium diffusion induced fracture in lithium-ion battery electrode particles +abstract: > + To gain better insights into the structural reliability of lithium-ion battery electrodes and the nucleation as well as propagation of cracks during the charge and discharge cycles, it is crucial to enhance our understanding of the degradation mechanisms of electrode particles. This work presents a rigorous mathematical formulation for a fatigue failure theory for lithium-ion battery electrode particles for lithium diffusion induced fracture. The prediction of fatigue cracking for lithium-ion battery during the charge and discharge steps is an particularly challenging task and plays an crucial role in various electronic- based applications. Here, to simulate fatigue cracking, we rely on the phase-field approach for fracture which is a widely adopted framework for modeling and computing fracture failure phenomena in solids. The primary goal is to describe a variationally consistent energetic formulation for gradient-extended dissipative solids, which is rooted in incremental energy minimization. The formulation has been derived as a coupled system of partial differential equations (PDEs) that governs the gradient-extended elastic-chemo damage response. Additionally, since the damage mechanisms of the lithium-ion battery electrode particles result from swelling and shrinkage, an additive decomposition of the strain tensor is performed. + +poster: /assets/img/posts/31-07-2024/poster.jpg +social: + - link: https://meet.google.com/xfu-vsxs-uzj + icon: bi-google + + - link: https://youtube.com + icon: bi-youtube +--- diff --git a/_posts/2024-08-15-Mobina Golmohammadi.md b/_posts/2024-08-15-Mobina Golmohammadi.md new file mode 100644 index 0000000..e90cec0 --- /dev/null +++ b/_posts/2024-08-15-Mobina Golmohammadi.md @@ -0,0 +1,23 @@ +--- +layout: post +speaker: Mobina Golmohammadi +position: Doctor of Philosophy +avatar: /assets/img/posts/15-08-2024/mobina.jpg +date: 15-08-2024 +title: > + Comprehensive Assessment of Adverse Event Profiles Associated with + Bispecific Antibodies in Multiple Myeloma +abstract: > + Multiple myeloma (MM) is a cancer involving uncontrolled plasma cell growth in the bone marrow. Research is exploring Bispecific T Cell engagers (BITES) as a treatment for relapsed/refractory MM, showing promising initial results. + Methods: A comprehensive review of biomedical literature from PubMed, Scopus, and Nature databases was conducted until early 2023. BITES were categorized into BCMA and non-BCMA targeting groups. Data from 23 trials, including 1,899 MM patients, were analyzed for adverse event (AE) frequencies. A pooled analysis using Welch's t-test and clustering with t-distributed stochastic neighbor embedding (t-SNE) was performed to compare the safety profiles of BCMA and non-BCMA BITES. + Results: The study involved 1,094 patients treated with BCMA inhibitors, 677 with non-BCMA inhibitors, 65 with Teclistamab and Talquetamab,and 63 with Talquetamab and Daratumumab. Median follow-up was 12.6 months. Common all-grade hematological AEs included neutropenia (43.87%), anemia (43.96%), infections (44.05%), CRS (64.16%), and lymphopenia (40.33%). Grade 3/4 AEs included neutropenia (40.03%), infections (18.18%), CRS (1.84%), anemia (28.48%), and lymphopenia (45.09%). Subtle differences between BCMA and non-BCMA BITES were found, with more CRS and CRS with Tocilizumab in BCMA BITES (P<0.024). Significant differences were noted in overall and severe grade 3/4 AEs (p<0.0001). t-SNE analysis showed similar clustering patterns for all grades and grade 3/4 AEs, except for two agents. + Conclusion: BITES show efficacy in MM treatment but have distinct AE profiles. Non-BCMA BITES had less hematotoxicity, while BCMA BITES had lower CRS rates. These findings are crucial for treatment selection and developing mitigation strategies to improve patient outcomes. + +poster: /assets/img/posts/15-08-2024/mobinaposter.jpg +social: + - link: https://meet.google.com/xfu-vsxs-uzj + icon: bi-google + + - link: https://youtube.com + icon: bi-youtube +--- diff --git a/_posts/2024-09-11-SeyedAdel Moravveji.md b/_posts/2024-09-11-SeyedAdel Moravveji.md new file mode 100644 index 0000000..9206d62 --- /dev/null +++ b/_posts/2024-09-11-SeyedAdel Moravveji.md @@ -0,0 +1,24 @@ +--- +layout: post +speaker: SeyedAdel Moravveji +position: Postdoctoral Researcher +avatar: /assets/img/posts/11-09-2024/adel.jpeg +date: 11-09-2024 +title: > + A Comprehensive Computational Model of Alzheimer's Disease: + From Nano to Micro Scale +abstract: > + While many individual hypotheses about the causes of Alzheimer's Disease (AD) have been studied, large-scale efforts to integrate these factors are rare due to the complexity involved. Experimentally testing such comprehensive theories is challenging because of the numerous variables. However, computational neuroscience allows for the simultaneous study of multiple factors, prediction generation, and validation with real data. + + Method: The computational model uses 19 ordinary differential equations to describe the dynamics of proteins at the nanoscale (e.g., Aẞ monomers, oligomers, plaques, tau filaments, tangles, anti-inflammatory cytokines, insulin) and cell populations at the microscale (e.g... neurons, astrocytes, macrophages, microglia). These equations are parameterized by sex and APOE status, with initial conditions taken from existing literature. The main outcomes measured are the accumulation of pathological markers of AD (such as Aẞ monomers or plaques and tau filaments or tangles) and neuronal death. The model simulates these processes in daily increments over a 50-year lifespan. + + Results: The model shows that the progression of various forms of amyloid is similar for both APOE4-negative and APOE4-positive individuals, with some variations between groups. Neuronal loss occurs earlier in those with an APOE4 allele, regardless of sex. Specifically, neuronal losses were 10.9% for APOE4 women, 11.7% for APOE4+ women, 10.9% for APOE4 men, and 12.1% for APOE4+ men, aligning with existing literature. + Conclusion: Computational models are a crucial first step in developing a complex, predictive framework for AD and hold significant promise for identifying effective therapeutic targets in the fight against the disease. +poster: /assets/img/posts/11-09-2024/Adelmorovajiposter.jpg +social: + - link: https://meet.google.com/xfu-vsxs-uzj + icon: bi-google + + - link: https://youtube.com + icon: bi-youtube +--- diff --git a/_posts/2024-10-09-Mahya pashapour.md b/_posts/2024-10-09-Mahya pashapour.md new file mode 100644 index 0000000..e621120 --- /dev/null +++ b/_posts/2024-10-09-Mahya pashapour.md @@ -0,0 +1,21 @@ +--- +layout: post +speaker: Mahya Pashapour +position: Reshearcher +avatar: /assets/img/posts/09-10-2024/mahyapashapour.jpg +date: 09-10-2024 +title: > + Parameter identifiability and model selection for + partial differential equation models of cell invasion +abstract: > + In modeling phenomena, achieving a balance between the complexity of a model and its output is a key + consideration. A model's parameters play a critical role in shaping its predictions. When phenomena are formulated using partial differential equations (PDES) or ordinary differential equations (ODES), accurate parameter estimation is essential to improve the precision of the solution. Additionally, when multiple models with different levels of complexity exist for a given phenomenon, parameter estimation helps in identifying the optimal model. In this presentation, we introduce the Fisher-KPP (developed by Ronald Fisher, Andrey Kolmogorov, Ivan Petrovsky,and Nikolai Piskunov) reaction-diffusion model and its various forms to study cell invasion. We also examine parameter estimation results using the profile likelihood method and discuss model selection based on the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). + +poster: /assets/img/posts/09-10-2024/mahyaposter.jpg +social: + - link: https://meet.google.com/xfu-vsxs-uzj + icon: bi-google + + - link: https://youtube.com + icon: bi-youtube +--- diff --git a/_posts/2024-10-23-Amirreza Khodadadian.md b/_posts/2024-10-23-Amirreza Khodadadian.md index 45ddfc0..f2c844e 100644 --- a/_posts/2024-10-23-Amirreza Khodadadian.md +++ b/_posts/2024-10-23-Amirreza Khodadadian.md @@ -1,8 +1,9 @@ --- layout: post speaker: Amirreza Khodadadian -position: Faculty Member -avatar: /assets/img/speakers/speaker-2.jpg +position: Assistant Professor (Lecturer) +avatar: /assets/img/posts/23-10-2024/amirezza-300.jpg +date: 23-10-2024 title: > Advanced Numerical Modeling of Fracture Mechanisms in Lithium-Ion Batteries During Charge/Discharge Cycles: Implementation Using FEniCS abstract: > diff --git a/_sass/main.scss b/_sass/main.scss index 6ea434b..c3160be 100644 --- a/_sass/main.scss +++ b/_sass/main.scss @@ -288,6 +288,14 @@ h6 { background: color-mix(in srgb, var(--accent-color), transparent 15%); 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