{"id":441,"date":"2013-08-09T08:34:47","date_gmt":"2013-08-09T13:34:47","guid":{"rendered":"http:\/\/hachmannlab.cbe.buffalo.edu\/?page_id=441"},"modified":"2021-12-09T13:07:35","modified_gmt":"2021-12-09T18:07:35","slug":"group-meetings","status":"publish","type":"page","link":"https:\/\/hachmannlab.cbe.buffalo.edu\/index.php\/events\/group-meetings\/","title":{"rendered":"Group Meetings"},"content":{"rendered":"

Group Meetings<\/h3>\n

\nOur group meetings take place weekly and cover reports on progress in the group, presentations of codes and other tools, as well as literature reviews and discussions of interesting scientific developments. Our regular meeting slot is currently Thursdays, 5:00–6:30pm in 207 Furnas Hall<\/b>. In addition to the regular meetings, we occasionally have special group meetings as well as joint sessions with the other theory groups at UB.\n<\/p>\n

\nHere is the schedule for all upcoming meetings.\n<\/p>\n\n\n\n\n\n\n\n
Date<\/th>\nSpeaker<\/th>\nTopic<\/th>\n<\/tr>\n
TBD<\/td>\nGaurav<\/td>\nTBD<\/td>\n<\/tr>\n
TBD<\/td>\nArpit<\/td>\nTBD<\/td>\n<\/tr>\n
TBD<\/td>\nAditya<\/td>\nTBD<\/td>\n<\/tr>\n
TBD<\/td>\nNitin<\/td>\nTBD<\/td>\n<\/tr>\n
TBD<\/td>\nAatish<\/td>\nTBD<\/td>\n<\/tr>\n<\/table>\n

  <\/p>\n

(Last update: 2021-12-09)<\/p>\n

\n

  <\/p>\n

Past Group Meetings<\/h3>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Date<\/th>\nSpeaker<\/th>\nTopic<\/th>\n<\/tr>\n
2021-12-09<\/td>\nAatish<\/td>\nTailor-Made Materials: Second-Generation Libraries using Evolutionary Algorithms and
\nPredicting Synthesizability of Compounds<\/td>\n<\/tr>\n
2021-10-08<\/td>\nJohannes<\/td>\nModeling in Chemical Engineering: From Physics to Machine Learning and back (new graduate student presentation)<\/td>\n<\/tr>\n
2021-08-10<\/td>\nNitin<\/td>\nSynthetic Accessibility Scoring and its Potential Applications in Chemical Library Generation<\/td>\n<\/tr>\n
2021-02-26<\/td>\nJohannes<\/td>\nMolecular and Materials Modeling: From Physics to Machine Learning and back (new graduate student presentation)<\/td>\n<\/tr>\n
2020-09-28<\/td>\nJohannes<\/td>\nThe Machine Learning and Quantum Chemistry Route to Molecular and Materials Modeling (new graduate student presentation)<\/td>\n<\/tr>\n
2020-07-22<\/td>\nAatish<\/td>\nTailor-Made Materials: Inverse Engieneering Compounds Using Feature Correlation<\/td>\n<\/tr>\n
2020-05-08<\/td>\nKrutika<\/td>\nPredicting Spin Contamination in Organic Photovoltaic Compounds Using Data Mining<\/td>\n<\/tr>\n
2019-11-26<\/td>\nYudhajit, Aditya,
Gaurav, Aatish,
Krutika<\/td>\n		Project updates<\/td>\n<\/tr>\n
2019-10-31<\/td>\nDhairya<\/td>\nHypergeometric Distribution Analysis for Target Properties of Polyimides<\/td>\n<\/tr>\n
2019-10-24<\/td>\nYudhajit, Aditya,
Gaurav, Aatish,
Krutika<\/td>\n		UB CBE Graduate Research Symposium Poster Presentation Trial Run<\/td>\n<\/tr>\n
2019-10-17<\/td>\nKrutika<\/td>\nClassifying Organic Photovoltaics Based on the Existence of Spin Contamination<\/td>\n<\/tr>\n
2019-10-10<\/td>\nAatish<\/td>\nHypergeometric Distribution Analysis for Properties of Small Organic Molecules and Polyimides\n<\/td>\n<\/tr>\n
2019-09-23<\/td>\nJohannes<\/td>\nThe Machine Learning and Big Data Route to Molecular and Materials Modeling (new graduate student presentation)<\/td>\n<\/tr>\n
2019-08-16<\/td>\nAditya<\/td>\nA Demo of the Current Version of ChemBDDB<\/i><\/td>\n<\/tr>\n
2019-08-16<\/td>\nYudhajit<\/td>\nAn Update on Deep Eutectic Solvent Work<\/i><\/td>\n<\/tr>\n
2019-06-03<\/td>\nKrishnendu<\/td>\nAdvanced Computational Modeling of Carboxylic-Based Organic Molecules for Li-Ion Battery Anode Materials<\/td>\n<\/tr>\n
2019-05-10<\/td>\nJanhavi<\/td>\nVirtual Molecular and Material Library Generation via<\/i> a Graphical Interface<\/td>\n<\/tr>\n
2019-05-07<\/td>\nKrishnendu<\/td>\nComputational Modeling of Carboxylic-Based Organic Molecules for Li-Ion Battery Anode Materials (revisited)<\/td>\n<\/tr>\n2019-05-03<\/td>\nKrishnendu<\/td>\nComputational Modeling of Carboxylic-Based Organic Molecules for Li-Ion Battery Anode Materials<\/td>\n<\/tr>\n
2019-04-26<\/td>\nN\/A<\/td>\nIndividual Research Updates<\/td>\n<\/tr>\n
2019-03-22<\/td>\nArpit<\/td>\nComputational Cluster-Integral Methods for Solutions<\/td>\n<\/tr>\n
2019-03-15<\/td>\nAditya<\/td>\nCost-Benefit Analysis of Using Different Feature Sets in Machine Learning Models for Predicting Solubility Parameters<\/td>\n<\/tr>\n
2019-02-22<\/td>\nKrishnendu<\/td>\nComputational Methods for the Study of Li-Ion Battery Anode Materials and an Intro to OpenMM<\/td>\n<\/tr>\n
2019-02-15<\/td>\nJanhavi<\/td>\nAn Intro to Jupyter Notebooks and an Update on the ChemLG<\/i> GUI<\/td>\n<\/tr>\n
2019-02-01<\/td>\nMojtaba<\/td>\nRedesigning Machine Learning Training Sets Based on Chemical Intuition<\/td>\n<\/tr>\n
2019-01-18<\/td>\nAmol<\/td>\nComputational Modeling of Liquid Organic Hydrogen Carriers<\/td>\n<\/tr>\n
2018-12-17<\/td>\nYudhajit<\/td>\nVirtual High-Throughput Screening for Energy Conversion Technologies (annual PhD committee presentation)<\/td>\n<\/tr>\n
2018-12-14<\/td>\nGaurav<\/td>\nChemLG<\/i> – An Update and Demonstration<\/td>\n<\/tr>\n
2018-12-07<\/td>\nJohannes<\/td>\nMachine Learning in Chemical Research (for DARPA visitor)<\/td>\n<\/tr>\n
2018-12-05<\/td>\nAditya<\/td>\nPredicting Melting Points of Deep Eutectic Solvents (DES), High-Throughput Screening of DES Candidates for Specific Applications, and ChemBDDB<\/i> (PhD proposal presentation)<\/td>\n<\/tr>\n
2018-12-05<\/td>\nArpit<\/td>\nComputational Cluster-Integral Methods for Solutions (PhD proposal presentation)<\/td>\n<\/tr>\n
2018-11-27<\/td>\nYudhajit<\/td>\nOverview and Demonstration of ChemHTPS<\/i>: A High-Throughput Quantum Chemistry Infrastructure<\/td>\n<\/tr>\n
2018-11-20<\/td>\nJohannes<\/td>\nHachmann Group Quantum Research Profile (for UB Quantum Research Group)<\/td>\n<\/tr>\n
2018-11-06<\/td>\nKrishnendu<\/td>\nA Density Functional Theory Study of NTCDA and its Derivatives for Use as Anode Material in Li-Ion Batteries<\/td>\n<\/tr>\n
2018-10-19<\/td>\nJohannes<\/td>\nFrom Molecular and Materials Modeling to Data-Driven Discovery and Rational Design (new graduate student presentation)<\/td>\n<\/tr>\n
2018-10-04<\/td>\nAditya<\/td>\nJSON, JSON Schema, and MolSSI’s QC JSON Schema<\/td>\n<\/tr>\n
2018-10-04<\/td>\nYudhajit<\/td>\nHigh-Throughput Search for Deep Eutectic Solvent Systems<\/td>\n<\/tr>\n
2018-09-13<\/td>\nArpit<\/td>\nComputing Second and Third Osmotic Virial Coefficients for Additive Hard Sphere Mixtures<\/td>\n<\/tr>\n
2018-09-06<\/td>\nAmol<\/td>\nComputational Modeling of Liquid Organic Hydrogen Carriers (LOHCs)<\/td>\n<\/tr>\n
2018-08-30<\/td>\nMojtaba<\/td>\nHands-on Session: MolSSI\u2019s Best Practice Standards for Software Development<\/td>\n<\/tr>\n
2018-08-23<\/td>\nMojtaba<\/td>\nChemML<\/i>: A Machine Learning and Informatics Program Suite for the Chemical and Materials Sciences (annual PhD committee presentation)<\/td>\n<\/tr>\n
2018-08-16<\/td>\nAditya<\/td>\nPredicting Melting Points of Deep Eutectic Solvents<\/td>\n<\/tr>\n
2018-08-09<\/td>\nJanhavi<\/td>\nA GUI for ChemLG<\/i><\/td>\n<\/tr>\n
2018-07-26<\/td>\nPo-Han<\/td>\nUsing Concepts from Active Learning and Applicability Domain to Enhance Predictive Modeling<\/td>\n<\/tr>\n
2018-07-26<\/td>\nGaurav<\/td>\nMachine Learning Model Selection for Predicting Properties of Organic Polymers<\/td>\n<\/tr>\n
2018-07-12<\/td>\nKrishnendu<\/td>\nA Density Functional Theory Approach for the Feasibility of NTCDA and its Derivatives as an Anode in Li-Ion Batteries<\/td>\n<\/tr>\n
2018-07-05<\/td>\nMojtaba<\/td>\nAddressing Functional Dependence in Density Functional Theory via<\/i> Machine Learning Design Methodologies<\/td>\n<\/tr>\n
2018-06-28<\/td>\nYudhajit<\/td>\nComputationally Mapping the Adsorption and Diffusion Pathways of Li on Single Layer Graphene Structures<\/td>\n<\/tr>\n
2018-06-19<\/td>\nAtif<\/td>\nThe Effect of Tacticity and Side Chain Structure on the Coil Dimensions of Polyolefins<\/td>\n<\/tr>\n
2018-05-15<\/td>\nShirish<\/td>\nChemBDDB<\/i>: A Software-Assisted Database Infrastructure for the Exploration of Chemical and Materials Space<\/td>\n<\/tr>\n
2018-05-09<\/td>\nShirish<\/td>\nChemBDDB<\/i> – Modern Database Technology for Chemical and Materials Research<\/td>\n<\/tr>\n
2018-04-25<\/td>\nMojtaba<\/td>\nAdvancing Deep Learning Methodologies for Predicting Optical Properties of Organic Molecules<\/td>\n<\/tr>\n
2018-04-18<\/td>\nPo-Han<\/td>\nDetermining Applicability Domains to Enhance Predictive Modeling<\/td>\n<\/tr>\n
2018-03-14<\/td>\nGaurav<\/td>\nSearch Algorithms for Machine Learning Model Selection<\/td>\n<\/tr>\n
2018-03-07<\/td>\nAmol<\/td>\nComputational Modeling and Virtual High-Throughput Screening of LOHCs<\/td>\n<\/tr>\n
2018-02-21<\/td>\nAditya<\/td>\nA Data-Driven Approach to Calculating the Melting Point of Deep Eutectic Solvents<\/td>\n<\/tr>\n
2018-02-14<\/td>\nYudhajit<\/td>\nHigh-Throughput Screening of Materials for Application in Battery Technologies<\/td>\n<\/tr>\n
2018-01-16<\/td>\nVigneshwar<\/td>\nModeling of Polymers with Controlled Degradation Using First-Principles<\/i> and Virtual High-Throughput Screening<\/td>\n<\/tr>\n
2017-12-12<\/td>\nVigneshwar<\/td>\nComputational Modeling and Virtual High-Throughput Screening of Degradable Polymers<\/td>\n<\/tr>\n
2017-11-16<\/td>\nMojtaba<\/td>\nDemo of ChemML<\/i> Pre-Release <\/td>\n<\/tr>\n
2017-11-09<\/td>\nPo-Han<\/td>\nDetermining the Applicability Domains of QSPR Models<\/td>\n<\/tr>\n
2017-10-26<\/td>\nGaurav<\/td>\nGenetic Algorithm for Machine Learning Model Selection<\/td>\n<\/tr>\n
2017-10-05<\/td>\nAditya<\/td>\nA Molecular Dynamics Approach to Calculating the Melting Points of Deep Eutectic Solvents<\/td>\n<\/tr>\n
2017-09-29<\/td>\nJohannes<\/td>\nFrom Molecular and Materials Modeling to Data-Driven Discovery and Rational Design (new graduate student presentation)<\/td>\n<\/tr>\n
2017-09-21<\/td>\nShirish<\/td>\nChemBDDB<\/i> – a Database Infrastructure for the Software-Assisted Exploration of Chemical and Materials Space<\/td>\n<\/tr>\n
2017-08-17<\/td>\nMojtaba<\/td>\nDeep Learning of Optical Properties of Small Organic Molecules<\/td>\n<\/tr>\n
2017-08-10<\/td>\nAmol<\/td>\nComputational Modeling and Virtual High-Throughput Screening of Liquid Organic Hydrogen Carriers<\/td>\n<\/tr>\n
2017-08-03<\/td>\nYudhajit<\/td>\nRoadmap to Material Discovery for Photoelectrochemical and Electrochemical Applications<\/td>\n<\/tr>\n
2017-07-27<\/td>\nVigneshwar<\/td>\nModeling Thermal Degradation of Polymers<\/td>\n<\/tr>\n
2017-07-06<\/td>\nAtif<\/td>\nAccelerating Molecular Property Predictions Using Neural Networks<\/td>\n<\/tr>\n
2017-06-29<\/td>\nPo-Han<\/td>\nDevelopment of a GUI Web Application for ChemML<\/i><\/td>\n<\/tr>\n
2017-06-22<\/td>\nGaurav<\/td>\nDimensionality Reduction<\/td>\n<\/tr>\n
2017-06-07<\/td>\nAditya<\/td>\nChemBDDB<\/i> and More<\/td>\n<\/tr>\n
2017-05-26<\/td>\nShirish<\/td>\nChemBDDB<\/i> – a Database Infrastructure for the Software-Assisted Exploration of Chemical and Materials Space<\/td>\n<\/tr>\n
2017-05-17<\/td>\nSai <\/td>\nHow do Geometry Differences of Isomers Affect the Polarizability of Organic Polymers? (BSc thesis defense)<\/td>\n<\/tr>\n
2017-05-12<\/td>\nChris <\/td>\nData Storage Methods for High-Throughput Library Screening in Computational Chemistry (CE 408 presentation)<\/td>\n<\/tr>\n
2017-05-05<\/td>\nMojtaba <\/td>\nMachine Learning for the Prediction of Optical Properties of Small Organic Molecules<\/td>\n<\/tr>\n
2017-03-31<\/td>\nVigneshwar <\/td>\nModeling Thermal Degradation of Polymers<\/td>\n<\/tr>\n
2017-03-29<\/td>\nAtif <\/td>\nA GROMACS Tutorial to Perform Simple MD Simulations<\/td>\n<\/tr>\n
2017-03-10<\/td>\nYudhajit <\/td>\nHigh-Throughput Computations on N-Doped Graphene: Fuel Cell Reactions and Metal-Air Batteries<\/td>\n<\/tr>\n
2017-02-15<\/td>\nJohannes<\/td>\nA Software Ecosystem for the Data-Driven Design of Chemical Systems and the Exploration of Chemical Space (for Govindaraju Group)<\/td>\n<\/tr>\n
2017-02-10<\/td>\nAtif <\/td>\nNeural Networks for the Prediction of Number Density Values<\/td>\n<\/tr>\n
2017-01-27<\/td>\nMojtaba <\/td>\nHands-on Intro to ChemML<\/i><\/td>\n<\/tr>\n
2017-01-26<\/td>\nSupriya <\/td>\nHands-on Intro to ChemBDDB<\/i> and Django<\/td>\n<\/tr>\n
2017-01-20<\/td>\nShirish <\/td>\nDjango: The Web Framework for Perfectionists with Deadlines<\/td>\n<\/tr>\n
2017-01-13<\/td>\nSupriya <\/td>\nChemBDDB<\/i>: A Database Infrastructure for the Software-Assisted Exploration of Chemical and Materials Space<\/td>\n<\/tr>\n
2017-01-06<\/td>\nVigneshwar <\/td>\nModeling the Degradation of Polymers<\/td>\n<\/tr>\n
2016-09-29<\/td>\nJohannes<\/td>\nResearch in the Hachmann Group: Computational Catalysis, Materials, Big Data, & More… (new graduate student presentation)<\/td>\n<\/tr>\n
2016-08-19<\/td>\nAtif <\/td>\nChemLG<\/i>: A Smart and Massively Parallel Molecular Library Generator<\/td>\n<\/tr>\n
2016-08-19<\/td>\nMojtaba <\/td>\nFrom Structural Analysis to Fingerprints for Molecular Property Predictions<\/td>\n<\/tr>\n
2016-08-05<\/td>\nYujie <\/td>\nInheritance of Molecular Orbital Energies from Monomer Building Blocks to Larger Copolymers in Organic Semiconductors<\/td>\n<\/tr>\n
2016-06-24<\/td>\nBill <\/td>\nA Review of the Latest ChemHTPS<\/i> Version<\/td>\n<\/tr>\n
2016-06-02<\/td>\nBill<\/td>\nAn Intro to Sphinx: Auto-Documentation for Python<\/td>\n<\/tr>\n
2016-05-20<\/td>\nYudhajit <\/td>\nReaction Modeling of Solar Water Splitting: Playing with Quantum Mechanical Tools<\/td>\n<\/tr>\n
2016-05-13<\/td>\nMojtaba<\/td>\nChemML<\/i>: A Machine Learning and Informatics Program Suite for the Chemical and Materials Sciences<\/td>\n<\/tr>\n
2016-05-02<\/td>\nSai<\/td>\nHow do Geometry Differences between Isomers Affect the Polarizability of Organic Polymers?<\/td>\n<\/tr>\n
2016-05-02<\/td>\nAtif<\/td>\nAccelerated Discovery of Organic Polymers for Optical Applications<\/td>\n<\/tr>\n
2016-04-29<\/td>\nSai<\/td>\nAnalysis of Energy, Polarizability, and Refractive Index Value Differences between Diastereomers<\/td>\n<\/tr>\n
2016-04-04<\/td>\nYujie<\/td>\nInheritance of HOMO Energies from Individual Building Blocks to Copolymers<\/td>\n<\/tr>\n
2016-03-11<\/td>\nEd<\/td>\nUsing Regular Expressions in Python<\/td>\n<\/tr>\n
2016-02-26<\/td>\nAtif<\/td>\nChemLG<\/i>: A Molecular Library Generator Package<\/td>\n<\/tr>\n
2016-02-12<\/td>\nBill<\/td>\nOverview and Demonstration of ChemHTPS<\/i>: a High-Throughput Quantum Chemistry Infrastructure<\/td>\n<\/tr>\n
2016-02-01<\/td>\nJohannes<\/td>\nComputational and Data-Driven Discovery of Chemical and Materials Systems (for faculty meeting)<\/td>\n<\/tr>\n
2015-12-10<\/td>\nYudhajit<\/td>\nComputational Chemistry Investigations into Energy Conversion Technologies (PhD proposal presentation)<\/td>\n<\/tr>\n
2015-12-01<\/td>\nYudhajit<\/td>\nComputational Generation of Candidate N-Doped Graphene Sheets for Energy Conversion<\/td>\n<\/tr>\n
2015-11-24<\/td>\nAtif<\/td>\nAccurate Prediction of the Refractive Index of Polymers Using First-Principles<\/i> and Data Modeling<\/td>\n<\/tr>\n
2015-11-17<\/td>\nMojtaba<\/td>\nFrom Structural Analysis to Fingerprints that Guide Predictions<\/td>\n<\/tr>\n
2015-10-27<\/td>\nSai<\/td>\nAccurate Prediction of Refractive Index Values of Organic Polymers and Analysis of Low-Energy Conformer Impact<\/td>\n<\/tr>\n
2015-10-26<\/td>\nYudhajit, Shawn<\/td>\nGraphene Catalysts for Oxygen Reduction Reactions<\/td>\n<\/tr>\n
2015-10-13<\/td>\nYujie<\/td>\nPattern Recognition and its Application in Computational Research<\/td>\n<\/tr>\n
2015-10-13<\/td>\nMojtaba<\/td>\nIdentifing Substructure Sequences in Molecular Structures<\/td>\n<\/tr>\n
2015-10-06<\/td>\nMikhail<\/td>\nSimilarity Screening of Molecular Fingerprints<\/td>\n<\/tr>\n
2015-09-24<\/td>\nJohannes<\/td>\nResearch in the Hachmann Group: Computational Catalysis, Materials, Big Data, & More… (new graduate student presentation)<\/td>\n<\/tr>\n
2015-06-23<\/td>\nBill<\/td>\nGetting Started with Git on your Machine and on the Cluster<\/td>\n<\/tr>\n
2015-04-21<\/td>\nYudhajit<\/td>\nComputational Studies on Solar Water Splitting<\/td>\n<\/tr>\n
2015-04-14<\/td>\nJun<\/td>\nCalculating van der Waals Radii and Volumes<\/td>\n<\/tr>\n
2015-03-31<\/td>\nAndrew<\/td>\nModeling Tandem Organic Solar Cells<\/td>\n<\/tr>\n
2015-03-17<\/td>\nChing-Yen<\/td>\nImplementation of Substructure Searching with SMARTS via<\/i> Pybel and Identifying Chemical Patterns in Outliers<\/td>\n<\/tr>\n
2015-03-10<\/td>\nBryan<\/td>\nDiscovering\u00a0Trends in Data from Different Quantum Chemical Models<\/td>\n<\/tr>\n
2015-03-03<\/td>\nAtif<\/td>\nRapid Discovery of High-Refractive-Index Polymers<\/td>\n<\/tr>\n
2015-02-20<\/td>\nYudhajit<\/td>\nSolar Water Splitting: A High-Throughput Computational Study on Catalysts<\/td>\n<\/tr>\n
2015-02-19<\/td>\nAtif<\/td>\nAn Intro to Emacs<\/td>\n<\/tr>\n
2015-02-17<\/td>\nMojtaba<\/td>\nMachine Learning for the Prediction of Organic Semiconductor HOMO Energies<\/td>\n<\/tr>\n
2014-12-10<\/td>\nAtif<\/td>\nOptimizing Optical Properties of Organic Polymers: High-Throughput Screening and Big Data Mining (PhD proposal presentation)<\/td>\n<\/tr>\n
2014-12-09<\/td>\nMojtaba<\/td>\nMachine Learning for Accelerated Materials Discovery (PhD proposal presentation)<\/td>\n<\/tr>\n
2014-10-13<\/td>\nAtif<\/td>\nComputational Approach to Discovering Novel Monomers for High-Refractive-Index Organic Materials<\/td>\n<\/tr>\n
2014-09-25<\/td>\nJohannes<\/td>\nResearch in the Hachmann Group: Computational Catalysis, Materials, Big Data, & More… (new graduate student presentation)<\/td>\n<\/tr>\n
2014-09-22<\/td>\nArti<\/td>\nStatistic Relational Learning<\/td>\n<\/tr>\n
2014-09-15<\/td>\nJohannes<\/td>\nFellowship and Funding Opportunities<\/td>\n<\/tr>\n
2014-09-08<\/td>\nCynthia Cornelius (CCR)<\/td>\nIntro to the Resources of CCR II<\/td>\n<\/tr>\n
2014-08-21<\/td>\nBryan<\/td>\nIntro to Matplotlib<\/td>\n<\/tr>\n
2014-08-18<\/td>\nMojtaba<\/td>\nIntro to LAMMPS<\/td>\n<\/tr>\n
2014-07-31<\/td>\nJohannes<\/td>\nA Beginner’s Guide to Writing Research Papers<\/td>\n<\/tr>\n
2014-07-11<\/td>\nJohannes<\/td>\nResearch in the Hachmann Group: Computational Materials, Catalysis, Big Data, & More… (for Samsung visitors)<\/td>\n<\/tr>\n
2014-07-10<\/td>\nJohannes<\/td>\nStudy-Session on Computational Quantum Chemistry IX: ORCA Outputs<\/td>\n<\/tr>\n
2014-07-07<\/td>\nJohannes<\/td>\nStudy-Session on Computational Quantum Chemistry VIII: DFT<\/td>\n<\/tr>\n
2014-07-03<\/td>\nAtif<\/td>\nHands-on Intro to Avogadro<\/td>\n<\/tr>\n
2014-06-30<\/td>\nJohannes<\/td>\nStudy-Session on Computational Quantum Chemistry VII: Open-Shell Problems, Post-HF Methods<\/td>\n<\/tr>\n
2014-06-26<\/td>\nJohannes<\/td>\nHands-on Intro to Redmine<\/td>\n<\/tr>\n
2014-06-23<\/td>\nJohannes<\/td>\nStudy-Session on Computational Quantum Chemistry VI: Recap<\/td>\n<\/tr>\n
2014-05-15<\/td>\nChing-Yen<\/td>\nIntro to the Pariser-Parr-Pople Model and the ppp.x Code<\/td>\n<\/tr>\n
2014-05-08<\/td>\nJohannes<\/td>\nStudy-Session on Computational Quantum Chemistry V: Molecular Properties from QM, Semiempirics<\/td>\n<\/tr>\n
2014-05-01<\/td>\nJohannes<\/td>\nStudy-session on Computational Quantum Chemistry IV: Roothaan-Hall Equations, Basis Sets<\/td>\n<\/tr>\n
2014-04-24<\/td>\nMojtaba<\/td>\nAn Overview on Machine Learning II<\/td>\n<\/tr>\n
2014-04-21<\/td>\nJohannes<\/td>\nStudy-Session on Computational Quantum Chemistry III: MO Calculations, HF Equations<\/td>\n<\/tr>\n
2014-04-17<\/td>\nMojtaba<\/td>\nAn Overview on Machine Learning I<\/td>\n<\/tr>\n
2014-04-14<\/td>\nJohannes<\/td>\nStudy-Session on Computational Quantum Chemistry II: QM Basics, BO Approximation, 1e-Systems<\/td>\n<\/tr>\n
2014-04-08<\/td>\nJohannes<\/td>\nStudy-Session on Computational Quantum Chemistry I: Concepts in Molecular Modeling, Mathematical Basics<\/td>\n<\/tr>\n
2014-04-03<\/td>\nJohannes<\/td>\nFrom Big Data to New Materials: Virtual High-Throughput Screening and the Rational Design of Organic Semiconductors (for Govindaraju Group)<\/td>\n<\/tr>\n
2014-03-27<\/td>\nMojtaba<\/td>\nHands-on Intro to Mendeley<\/td>\n<\/tr>\n
2014-03-13<\/td>\nBryan, Johannes<\/td>\nIntro to Bash Tools; RSS Feed Readers in Science <\/td>\n<\/tr>\n
2014-03-12<\/td>\nJohannes<\/td>\nHachmann Group Research Program (new graduate student presentation)<\/td>\n<\/tr>\n
2014-02-27<\/td>\nJun, Ching-Yen<\/td>\nIntro to the Linux Shell and Bash Tools<\/td>\n<\/tr>\n
2014-02-20<\/td>\nShawn<\/td>\nIntro to Git and Bitbucket<\/td>\n<\/tr>\n
2014-02-18<\/td>\nJohannes<\/td>\nGroup Business: Some Thoughts on Research, Organization, and Being Successful as a Team<\/td>\n<\/tr>\n
2014-02-06<\/td>\nJohannes<\/td>\nHigh-Throughput Quantum Chemistry and Big Data Techniques for the Rational Design of Organic Semiconductors (jointly with Autschbach and Zurek groups)<\/td>\n<\/tr>\n
2014-02-05<\/td>\nCynthia Cornelius (CCR)<\/td>\nIntro to the Resources of CCR I<\/td>\n<\/tr>\n
2013-10-04<\/td>\nJohannes<\/td>\nResearch in the Hachmann Group: Computational Catalysis, Materials, Big Data, & More… (new graduate student presentation)<\/td>\n<\/tr>\n<\/table>\n","protected":false},"excerpt":{"rendered":"

Group Meetings Our group meetings take place weekly and cover reports on progress in the group, presentations of codes and other tools, as well as literature reviews and discussions of interesting scientific developments. Our regular meeting slot is currently Thursdays, 5:00–6:30pm in 207 Furnas Hall. In addition to the regular meetings, we occasionally have special group meetings as well as joint sessions with the other theory groups at UB. Here is the schedule for all upcoming meetings. Date Speaker Topic TBD Gaurav TBD TBD Arpit TBD TBD Aditya TBD TBD Nitin TBD TBD Aatish TBD   (Last update: 2021-12-09)   Past Group Meetings Date Speaker Topic 2021-12-09 Aatish Tailor-Made Materials: Second-Generation Libraries using Evolutionary Algorithms and Predicting Synthesizability of Compounds 2021-10-08 Johannes Modeling in Chemical Engineering: From Physics to Machine Learning and back (new graduate student presentation) 2021-08-10 Nitin Synthetic Accessibility Scoring and its Potential Applications in Chemical Library Generation 2021-02-26 Johannes Molecular and Materials Modeling: From Physics to Machine Learning and back (new graduate student presentation) 2020-09-28 Johannes The Machine Learning and Quantum Chemistry Route to Molecular and Materials Modeling (new graduate student presentation) 2020-07-22 Aatish Tailor-Made Materials: Inverse Engieneering Compounds Using Feature Correlation 2020-05-08 Krutika Predicting Spin Contamination in Organic Photovoltaic Compounds Using Data Mining 2019-11-26 Yudhajit, Aditya, Gaurav, Aatish, Krutika Project updates 2019-10-31 Dhairya Hypergeometric Distribution Analysis for Target Properties of Polyimides 2019-10-24 Yudhajit, Aditya, Gaurav, Aatish, Krutika UB CBE Graduate Research Symposium Poster Presentation Trial Run 2019-10-17 Krutika Classifying Organic Photovoltaics Based on the Existence of Spin Contamination 2019-10-10 Aatish Hypergeometric Distribution Analysis for Properties of Small Organic Molecules and Polyimides 2019-09-23 Johannes The Machine Learning and Big Data Route to Molecular and Materials Modeling (new graduate student presentation) 2019-08-16 Aditya A Demo of the Current Version of ChemBDDB 2019-08-16 Yudhajit An Update on Deep Eutectic Solvent Work 2019-06-03 Krishnendu Advanced Computational Modeling of Carboxylic-Based Organic Molecules for Li-Ion Battery Anode Materials 2019-05-10 Janhavi Virtual Molecular and Material Library Generation via a Graphical Interface 2019-05-07 Krishnendu Computational Modeling of Carboxylic-Based Organic Molecules for Li-Ion Battery Anode Materials (revisited) 2019-05-03 Krishnendu Computational Modeling of Carboxylic-Based Organic Molecules for Li-Ion Battery Anode Materials 2019-04-26 N\/A Individual Research Updates 2019-03-22 Arpit Computational Cluster-Integral Methods for Solutions 2019-03-15 Aditya Cost-Benefit Analysis of Using Different Feature Sets in Machine Learning Models for Predicting Solubility Parameters 2019-02-22 Krishnendu Computational Methods for the Study of Li-Ion Battery Anode Materials and an Intro to OpenMM 2019-02-15 Janhavi An Intro to Jupyter Notebooks and an Update on the ChemLG GUI 2019-02-01 Mojtaba Redesigning Machine Learning Training Sets Based on Chemical Intuition 2019-01-18 Amol Computational Modeling of Liquid Organic Hydrogen Carriers 2018-12-17 Yudhajit Virtual High-Throughput Screening for Energy Conversion Technologies (annual PhD committee presentation) 2018-12-14 Gaurav ChemLG – An Update and Demonstration 2018-12-07 Johannes Machine Learning in Chemical Research (for DARPA visitor) 2018-12-05 Aditya Predicting Melting Points of Deep Eutectic Solvents (DES), High-Throughput Screening of DES Candidates for Specific Applications, and ChemBDDB (PhD proposal presentation) 2018-12-05 Arpit Computational Cluster-Integral Methods for Solutions (PhD proposal presentation) 2018-11-27 Yudhajit Overview and Demonstration of ChemHTPS: A High-Throughput Quantum Chemistry Infrastructure 2018-11-20 Johannes Hachmann Group Quantum Research Profile (for UB Quantum Research Group) 2018-11-06 Krishnendu A Density Functional Theory Study of NTCDA and its Derivatives for Use as Anode Material in Li-Ion Batteries 2018-10-19 Johannes From Molecular and Materials Modeling to Data-Driven Discovery and Rational Design (new graduate student presentation) 2018-10-04 Aditya JSON, JSON Schema, and MolSSI’s QC JSON Schema 2018-10-04 Yudhajit High-Throughput Search for Deep Eutectic Solvent Systems 2018-09-13 Arpit Computing Second and Third Osmotic Virial Coefficients for Additive Hard Sphere Mixtures 2018-09-06 Amol Computational Modeling of Liquid Organic Hydrogen Carriers (LOHCs) 2018-08-30 Mojtaba Hands-on Session: MolSSI\u2019s Best Practice Standards for Software Development 2018-08-23 Mojtaba ChemML: A Machine Learning and Informatics Program Suite for the Chemical and Materials Sciences (annual PhD committee presentation) 2018-08-16 Aditya Predicting Melting Points of Deep Eutectic Solvents 2018-08-09 Janhavi A GUI for ChemLG 2018-07-26 Po-Han Using Concepts from Active Learning and Applicability Domain to Enhance Predictive Modeling 2018-07-26 Gaurav Machine Learning Model Selection for Predicting Properties of Organic Polymers 2018-07-12 Krishnendu A Density Functional Theory Approach for the Feasibility of NTCDA and its Derivatives as an Anode in Li-Ion Batteries 2018-07-05 Mojtaba Addressing Functional Dependence in Density Functional Theory via Machine Learning Design Methodologies 2018-06-28 Yudhajit Computationally Mapping the Adsorption and Diffusion Pathways of Li on Single Layer Graphene Structures 2018-06-19 Atif The Effect of Tacticity and Side Chain Structure on the Coil Dimensions of Polyolefins 2018-05-15 Shirish ChemBDDB: A Software-Assisted Database Infrastructure for the Exploration of Chemical and Materials Space 2018-05-09 Shirish ChemBDDB – Modern Database Technology for Chemical and Materials Research 2018-04-25 Mojtaba Advancing Deep Learning Methodologies for Predicting Optical Properties of Organic Molecules 2018-04-18 Po-Han Determining Applicability Domains to Enhance Predictive Modeling 2018-03-14 Gaurav Search Algorithms for Machine Learning Model Selection 2018-03-07 Amol Computational Modeling and Virtual High-Throughput Screening of LOHCs 2018-02-21 Aditya A Data-Driven Approach to Calculating the Melting Point of Deep Eutectic Solvents 2018-02-14 Yudhajit High-Throughput Screening of Materials for Application in Battery Technologies 2018-01-16 Vigneshwar Modeling of Polymers with Controlled Degradation Using First-Principles and Virtual High-Throughput Screening 2017-12-12 Vigneshwar Computational Modeling and Virtual High-Throughput Screening of Degradable Polymers 2017-11-16 Mojtaba Demo of ChemML Pre-Release 2017-11-09 Po-Han Determining the Applicability Domains of QSPR Models 2017-10-26 Gaurav Genetic Algorithm for Machine Learning Model Selection 2017-10-05 Aditya A Molecular Dynamics Approach to Calculating the Melting Points of Deep Eutectic Solvents 2017-09-29 Johannes From Molecular and Materials Modeling to Data-Driven Discovery and Rational Design (new graduate student presentation) 2017-09-21 Shirish ChemBDDB – a Database Infrastructure for the Software-Assisted Exploration of Chemical and Materials Space 2017-08-17 Mojtaba Deep Learning of Optical Properties of Small Organic Molecules 2017-08-10 Amol Computational Modeling and Virtual High-Throughput Screening of Liquid Organic Hydrogen Carriers 2017-08-03 Yudhajit Roadmap to Material Discovery for Photoelectrochemical and Electrochemical Applications 2017-07-27 Vigneshwar Modeling Thermal Degradation of Polymers 2017-07-06 Atif Accelerating Molecular Property Predictions Using Neural Networks 2017-06-29 Po-Han Development of a GUI Web Application for ChemML 2017-06-22 Gaurav Dimensionality Reduction 2017-06-07 Aditya ChemBDDB<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":1778,"menu_order":0,"comment_status":"open","ping_status":"open","template":"","meta":{"footnotes":""},"class_list":["post-441","page","type-page","status-publish","hentry","entry","post-inner"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/hachmannlab.cbe.buffalo.edu\/index.php\/wp-json\/wp\/v2\/pages\/441","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hachmannlab.cbe.buffalo.edu\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/hachmannlab.cbe.buffalo.edu\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/hachmannlab.cbe.buffalo.edu\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/hachmannlab.cbe.buffalo.edu\/index.php\/wp-json\/wp\/v2\/comments?post=441"}],"version-history":[{"count":0,"href":"https:\/\/hachmannlab.cbe.buffalo.edu\/index.php\/wp-json\/wp\/v2\/pages\/441\/revisions"}],"up":[{"embeddable":true,"href":"https:\/\/hachmannlab.cbe.buffalo.edu\/index.php\/wp-json\/wp\/v2\/pages\/1778"}],"wp:attachment":[{"href":"https:\/\/hachmannlab.cbe.buffalo.edu\/index.php\/wp-json\/wp\/v2\/media?parent=441"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}