Kanchan Sarkar

Biography

⚫ *𝒑𝒅𝒇 𝒗𝒆𝒓𝒔𝒊𝒐𝒏 𝒐𝒇 𝒂𝒄𝒂𝒅𝒆𝒎𝒊𝒄 𝒑𝒓𝒐𝒇𝒊𝒍𝒆 (𝙘𝙫​​​​​): https://www.academia.edu/33424265/CV_KANCHANSARKAR_pdf

⚫ 𝑪𝑨𝑹𝑬𝑬𝑹 𝑺𝑼𝑴𝑴𝑨𝑹𝒀
⦿ 𝑼𝒏𝒊𝒗𝒆𝒓𝒔𝒊𝒕𝒂̈𝒕 𝑼𝒍𝒎 (Institut für Theoretische) - Research Scientist (Dec 2020 – Dec 2023)
⦿ 𝑽𝒊𝒔𝒗𝒂-𝑩𝒉𝒂𝒓𝒂𝒕𝒊 𝑼𝒏𝒊𝒗𝒆𝒓𝒔𝒊𝒕𝒚​​​​​ - Voluntary association (Sept. 2019 – Dec 2020)
⦿ 𝑪𝒐𝒍𝒖𝒎𝒃𝒊𝒂 𝑼𝒏𝒊𝒗𝒆𝒓𝒔𝒊𝒕𝒚 (Applied Physics & Applied Mathematics) - Associate Research Scientist (Aug. 2017 – Aug. 2019)
⦿ 𝑾𝒂𝒌𝒆 𝑭𝒐𝒓𝒆𝒔𝒕 𝑼𝒏𝒊𝒗𝒆𝒓𝒔𝒊𝒕𝒚 (Dept. of Physics) - Visiting Scientist (July 2016)
⦿ 𝑼𝒏𝒊𝒗𝒆𝒓𝒔𝒊𝒕𝒚 𝒐𝒇 𝑴𝒊𝒏𝒏𝒆𝒔𝒐𝒕𝒂 (Chemical Engineering and Materials Science) - Post-Doctoral Assistant (Sept. 2014 - Aug. 2017)
⦿𝑰𝒏𝒅𝒊𝒂𝒏 𝑨𝒔𝒔𝒐𝒄𝒊𝒂𝒕𝒊𝒐𝒏 𝒇𝒐𝒓 𝒕𝒉𝒆 𝑪𝒖𝒍𝒕𝒊𝒗𝒂𝒕𝒊𝒐𝒏 𝒐𝒇 𝑺𝒄𝒊𝒆𝒏𝒄𝒆 - Research Associate-I (March 2014 - August 2014)

⚫ 𝑬𝑫𝑼𝑪𝑨𝑻𝑰𝑶𝑵
⦿ 𝑰𝒏𝒅𝒊𝒂𝒏 𝑨𝒔𝒔𝒐𝒄𝒊𝒂𝒕𝒊𝒐𝒏 𝒇𝒐𝒓 𝒕𝒉𝒆 𝑪𝒖𝒍𝒕𝒊𝒗𝒂𝒕𝒊𝒐𝒏 𝒐𝒇 𝑺𝒄𝒊𝒆𝒏𝒄𝒆 (Department of Physical Chemistry) 𝟮𝟬𝟬𝟴-𝟮𝟬𝟭𝟰
𝑷𝒉.𝑫. 𝑻𝒉𝒆𝒔𝒊𝒔: 𝑺𝒐𝒇𝒕-𝑪𝒐𝒎𝒑𝒖𝒕𝒊𝒏𝒈 𝒂𝒍𝒈𝒐𝒓𝒊𝒕𝒉𝒎𝒔 𝒇𝒐𝒓 𝒔𝒐𝒍𝒗𝒊𝒏𝒈 𝒔𝒐𝒎𝒆 𝒑𝒓𝒐𝒃𝒍𝒆𝒎𝒔 𝒐𝒇 𝑸𝒖𝒂𝒏𝒕𝒖𝒎 𝑪𝒉𝒆𝒎𝒊𝒔𝒕𝒓𝒚
𝕮𝖔𝖒𝖒𝖎𝖙𝖙𝖊𝖊: Prof. S.P. Bhattacharyya, Prof. Satrajit Adhikari, Prof. Kamal Bhattacharyya, Prof. S.C. Bhattacharyya(Chair).

⦿ 𝑰𝒏𝒅𝒊𝒂𝒏 𝑺𝒕𝒂𝒕𝒊𝒔𝒕𝒊𝒄𝒂𝒍 𝑰𝒏𝒔𝒕𝒊𝒕𝒖𝒕𝒆 – 𝑲𝒐𝒍𝒌𝒂𝒕𝒂 (Center for Soft Computing Research and Machine Intelligence Unit) 𝟮𝟬𝟬𝟴-𝟮𝟬𝟬𝟵
Certificate course on Machine Intelligence & Soft Computing
𝐂𝐨𝐮𝐫𝐬𝐞𝐬: Genetic Algorithms, Fuzzy Sets, Rough Sets, Artificial Neural Networks, Digital Image Processing, Pattern Recognition, Data Mining. Course Coordinator: Professor S. K. Pal
𝑷𝒓𝒐𝒋𝒆𝒄𝒕𝒔 𝒄𝒐𝒎𝒑𝒍𝒆𝒕𝒆𝒅: Determination of transition temperature in Ising model system by using Genetic Algorithm (supervisor: Professor C. A. Murthy).
Simulation of a Single Layer Perceptron for Pattern Classification of IRIS data set (supervisor: Dr Ashish Ghosh).

⦿ 𝑽𝒊𝒔𝒗𝒂-𝑩𝒉𝒂𝒓𝒂𝒕𝒊 𝑼𝒏𝒊𝒗𝒆𝒓𝒔𝒊𝒕𝒚 (Department of Chemistry) 𝟮𝟬𝟬𝟮-𝟮𝟬𝟬𝟳
𝑩𝒂𝒄𝒉𝒆𝒍𝒐𝒓 𝒐𝒇 𝑺𝒄𝒊𝒆𝒏𝒄𝒆 (𝑩.𝑺𝒄.) & 𝑴𝒂𝒔𝒕𝒆𝒓 𝒐𝒇 𝑺𝒄𝒊𝒆𝒏𝒄𝒆 (𝑴.𝑺𝒄.)
𝑪𝒍𝒂𝒔𝒔/𝑫𝒊𝒗𝒊𝒔𝒊𝒐𝒏: First Class with Distinction (B. Sc.) & First Class (M. Sc.; Specialization: Physical Chemistry)
𝑴𝒂𝒔𝒕𝒆𝒓𝒔 𝑷𝒓𝒐𝒋𝒆𝒄𝒕𝒔: Interplay between size and impurity position of doped quantum dot

⚫ 𝑺𝑲𝑰𝑳𝑳𝑺
⦿ 𝑶𝑺: Open source GNU/Linux distros, Red Hat, Sun Solaris, OS X and Windows.
⦿ 𝑪𝒐𝒅𝒊𝒏𝒈: Fortran, Python, bash/zsh, MatLab/Octave, C, LATEX, HTML, CSS, Java-script
⦿ 𝑺𝒐𝒇𝒕𝒘𝒂𝒓𝒆: ATOMPAW, Quantum-Espresso, VASP, WIEN2k & GAUSSIAN
⦿ 𝑬𝒙𝒑𝒆𝒓𝒕𝒊𝒔𝒆: Evolutionary and Nature-inspired computing, Classical optimization, Fuzzy logic.
Working proficiency in Machine learning, Deep learning and Data mining.
⦿ 𝑳𝒂𝒏𝒈𝒖𝒂𝒈𝒆: English (fluent), Bengali (native), Hindi (native), German (A1).


⚫ 𝑨𝑾𝑨𝑹𝑫𝑺 𝑨𝑵𝑫 𝑯𝑶𝑵𝑶𝑹𝑺
▪ Division of Computational Physics Travel Award 2019, 𝑨𝒎𝒆𝒓𝒊𝒄𝒂𝒏 𝑷𝒉𝒚𝒔𝒊𝒄𝒂𝒍 𝑺𝒐𝒄𝒊𝒆𝒕𝒚.
▪ Program Committee Member and Reviewer: International Conference on Information Society
and Smart Cities (𝑰𝑺𝑪 2018), Oxford city, United Kingdom, 06-07 June 2018.
▪ One of the active developers of the online software “Virtual Laboratory of Earth and Planetary
Materials” (𝑽𝑳𝒂𝒃) for high temperature and high-pressure elasticity calculations.
▪ Member of American Physical Society (2014-2019).
▪ Member of American Geophysical Union (2014-2019).
▪ Awarded on “Changing Paradigms in Theoretical and Computational Chemistry: From Atoms to Molecular Clusters”. (December 18-20, 2009), at University of Pune.
▪ Fellowship by Council of Scientific and Industrial Research (𝑵𝑬𝑻 𝑪𝑺𝑰𝑹-2007, India).
▪ Rank in the West Bengal Joint Entrance examination (𝑴𝒆𝒅𝒊𝒄𝒂𝒍): 713 (2002).

Currently, KS traverses across the first-principles electronic structure upshots to commentary on the adsorption of chlorine and the formation of a surface chloride on Li(001) and Mg(0001). KS et al. anticipate that these theoretical outcomes within the framework of density functional theory are relevant for 𝗰𝗵𝗹𝗼𝗿𝗶𝗱𝗲-𝗶𝗼𝗻 𝗯𝗮𝘁𝘁𝗲𝗿𝗶𝗲𝘀 in which lithium and magnesium are potential anode materials. Besides, it is also of fundamental interest, as halide adsorption on metal electrodes is an inevitable process in electrochemistry. He is studying the adsorption properties and determining the stable adsorption structures, both with respect to the free chlorine molecule and as a function of the electrode potential. He will also address the process of chloride formation on the surface.
Besides, KS is one of the active developers of the database software 𝑴𝑶𝑮𝑨𝑫𝑶𝑪 (MOlecular GAsphase DOCumentation), produced and distributed by the Chemieinformationssysteme (formerly Sektion für Spektren- und Strukturdokumentation) at the University of Ulm.  𝑴𝑶𝑮𝑨𝑫𝑶𝑪 has been a powerful tool for scientists worldwide to retrieve information about gas phase investigations.

KS got his formal training in soft computing and machine intelligence methods from the Center for Soft Computing Research and Machine Intelligence Unit, 𝑰𝒏𝒅𝒊𝒂𝒏 𝑺𝒕𝒂𝒕𝒊𝒔𝒕𝒊𝒄𝒂𝒍 𝑰𝒏𝒔𝒕𝒊𝒕𝒖𝒕𝒆 - 𝑲𝒐𝒍𝒌𝒂𝒕𝒂. During doctoral training in the 𝑰𝒏𝒅𝒊𝒂𝒏 𝑨𝒔𝒔𝒐𝒄𝒊𝒂𝒕𝒊𝒐𝒏 𝒇𝒐𝒓 𝒕𝒉𝒆 𝑪𝒖𝒍𝒕𝒊𝒗𝒂𝒕𝒊𝒐𝒏 𝒐𝒇 𝑺𝒄𝒊𝒆𝒏𝒄𝒆 - 𝑲𝒐𝒍𝒌𝒂𝒕𝒂, he experimented with 𝒔𝒆𝒗𝒆𝒓𝒂𝒍 𝒑𝒖𝒓𝒆 𝒂𝒏𝒅 𝒉𝒚𝒃𝒓𝒊𝒅 𝒔𝒐𝒇𝒕-𝒄𝒐𝒎𝒑𝒖𝒕𝒊𝒏𝒈 𝒕𝒆𝒄𝒉𝒏𝒊𝒒𝒖𝒆𝒔 in the general context of computing global minimum energy structures of oligomers and homogeneous or heterogeneous aggregates of atoms or molecules. In his postdoctoral studies in the USA (𝑪𝑬𝑴𝑺, 𝑼𝑴𝑵; 𝑨𝑷𝑨𝑴, 𝑪𝑼; 𝑾𝑭𝑼), he explored the possibilities that evolutionary computing techniques can offer a 𝒄𝒐𝒏𝒔𝒊𝒔𝒕𝒆𝒏𝒕 𝒑𝒓𝒐𝒄𝒆𝒅𝒖𝒓𝒆 𝒐𝒇 𝒈𝒆𝒏𝒆𝒓𝒂𝒕𝒊𝒏𝒈 𝒑𝒓𝒐𝒋𝒆𝒄𝒕𝒐𝒓 𝒂𝒖𝒈𝒎𝒆𝒏𝒕𝒆𝒅 𝒘𝒂𝒗𝒆 (𝑷𝑨𝑾) 𝒅𝒂𝒕𝒂𝒔𝒆𝒕𝒔. These evolutionary optimized PAW (𝑬𝑷𝑨𝑾) 𝒅𝒂𝒕𝒂𝒔𝒆𝒕𝒔 maintain the 𝒔𝒂𝒎𝒆 𝒍𝒆𝒗𝒆𝒍 𝒐𝒇 𝒂𝒄𝒄𝒖𝒓𝒂𝒄𝒚 as all-electron full-potential linearized augmented plane wave (𝑨𝑬-𝑭𝑳𝑨𝑷𝑾) 𝒄𝒂𝒍𝒄𝒖𝒍𝒂𝒕𝒊𝒐𝒏𝒔 up to very high pressure. He had also introduced a 𝒏𝒆𝒘 𝒎𝒆𝒂𝒔𝒖𝒓𝒆 𝒐𝒇 𝒂𝒕𝒐𝒎𝒊𝒄 𝒅𝒂𝒕𝒂𝒔𝒆𝒕 𝒒𝒖𝒂𝒍𝒊𝒕𝒚 by considering performance uniformity over an extended pressure range. His other projects involved computing ab initio 𝒕𝒉𝒆𝒓𝒎𝒐𝒆𝒍𝒂𝒔𝒕𝒊𝒄 𝒑𝒓𝒐𝒑𝒆𝒓𝒕𝒊𝒆𝒔 𝒐𝒇 𝒎𝒂𝒕𝒆𝒓𝒊𝒂𝒍𝒔 under extremely high temperature and pressure conditions and designing atomic datasets for 𝒍𝒐𝒘𝒆𝒓 𝒎𝒂𝒏𝒕𝒍𝒆 𝒄𝒐𝒏𝒅𝒊𝒕𝒊𝒐𝒏𝒔 to understand 𝒅𝒆𝒆𝒑-𝒆𝒂𝒓𝒕𝒉 𝒑𝒓𝒐𝒄𝒆𝒔𝒔𝒆𝒔. He was also an active software developer for the Virtual Laboratory of Earth and Planetary Materials (𝙑𝙇𝙖𝙗) for high temperature and high-pressure elasticity calculations.

Education

Post-Doctorate, APAM, Columbia University, NYC, 2017-
Post-Doctorate, CEMS, University of Minnesota, 2014-2017
Research Scientist-I, IACS, Kolkata, 2014
PhD, IACS, Kolkata, 2014
Post Doctoral Scientist, Institut für Theoretische Chemie, U

Areas of Research / Professional Expertise

⦿ Uniform goodness measure for density functional theory potentials; evolutionary optimized transferable projector augmented-wave atomic files for use in a number of electronic structure codes.
⦿ Materials properties prediction through zero to ultra-high pressure, at the scalar relativistic level; computing ab initio thermoelastic properties and effect of spin transitions in some perovskite, post-perovskite materials at high temperature and pressure.
⦿ Machine Intelligence-based computing paradigm: Stochastic global optimization procedures: simulated annealing, evolutionary computing: evolutionary strategies, genetic algorithms, differential evolution; particle swarm optimization, ant colony algorithm.
⦿ Applications in Exploration of Clusters: Lennard-Jones, Morse, ionic and metal clusters; nanoalloys; crystal structure.
⦿ Applications in energy extremalization; Hamiltonian diagonalization; eigenvalues, eigenvectors computing; locating first-order saddle points; reaction paths.
⦿ Application of artificial neural networks, fuzzy logic theory in problems of chemical physics.
⦿ Deep learning, machine learning.
⦿ Blending density functional theory based open-source codes with soft computing methodologies.
⦿ Computer Programming: stochastic and classical optimization using Fortran, Python, bash/zsh, MatLab/Octave, C, and their combinations.

Personal Interests

⚫ Writing short and attractive codes to bypass repetitive customary jobs.
⚫ Identify knowledge gaps perceived by single scientific disciplines.
⚫ Transactional interactions with people from experimental, theoretical, computational and engineering research for communicating multifaceted problems.
⚫ Comprehensive intercultural and international experiences.
⚫ Organising beneficial events such as "Science Week" and "Science in 1st hand" for school students as well as the general public.
⚫ New artificial intelligence-based spin-out software company for the prediction of chemical and pharmaceutical materials on demand.

Websites

• 𝑳𝒊𝒏𝒌𝒆𝒅𝑰𝒏

• 𝑷𝒆𝒓𝒔𝒐𝒏𝒂𝒍

• 𝑹𝒆𝒔𝒆𝒂𝒓𝒄𝒉𝑮𝒂𝒕𝒆

• 𝑹𝒆𝒔𝒆𝒂𝒓𝒄𝒉𝒆𝒓𝑰𝑫: 𝑨-4133-2010

• 𝑨𝒄𝒂𝒅𝒆𝒎𝒊𝒂 (𝑪𝑽.𝒑𝒅𝒇)

• 𝑮𝒐𝒐𝒈𝒍𝒆 𝑺𝒄𝒉𝒐𝒍𝒂𝒓

• 𝑺𝒄𝒐𝒑𝒖𝒔 𝑨𝒖𝒕𝒉𝒐𝒓 𝑰𝑫: 55412942000

• 𝑶𝒓𝒄𝒊𝒅 𝟎𝟎𝟎𝟎-𝟎𝟎𝟎𝟐-𝟎𝟎𝟐𝟓-𝟕𝟎𝟓𝟓

• 𝑷𝒉.𝑫. 𝑻𝒉𝒆𝒔𝒊𝒔 (.𝒑𝒅𝒇)

• github

Books

Articles