Abhishek Jha| Pharmacology | Best Researcher Award

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Mr. Abhishek Jha|Pharmacology|Best Researcher Award

Mr. Abhishek Jha, Dr. D. Y. Patil Institute of Pharmaceutical Sciences and Research, India.

Abhishek Jha is a final-year doctoral candidate at the Indian Institute of Technology (BHU), Varanasi, specializing in Pharmaceutical Engineering and Technology. His research focuses on developing nanomedicine-based therapeutic strategies, particularly for breast and lung cancer treatments. Abhishek has hands-on experience with a range of sophisticated instruments, including HPLC, SEM, and fluorescence microscopy, and is proficient in various software used for data analysis and drug formulation. He has contributed to multiple high-impact publications in areas such as targeted drug delivery, nanofiber-based wound healing, and tuberculosis therapy. His projects involve innovative approaches, including redox-responsive nanocarriers and pulmonary nanocrystals, aimed at improving the efficacy and specificity of cancer treatments. With a passion for research and mentoring, Abhishek has guided several undergraduate and postgraduate students. His work, recognized in peer-reviewed journals, reflects his commitment to advancing pharmaceutical sciences, making him a strong contender for research excellence awards.

Profile

Education

Abhishek Jha is a dedicated scholar with a robust educational background in pharmaceutical sciences. He is currently pursuing a Ph.D. in Pharmaceutical Engineering and Technology at the prestigious Indian Institute of Technology (IIT-BHU), Varanasi. His doctoral research, initiated in July 2019, focuses on innovative strategies for nanomedicine-based treatments for breast cancer, with a particular emphasis on tumor-targeted drug delivery systems. Prior to this, Abhishek earned his Master of Pharmacy (M.Pharm) from the same institution in June 2019, specializing in Pharmaceutics. During his postgraduate studies, he achieved an impressive C.G.P.A. of 9.43, showcasing his academic excellence. His foundation in the field was laid during his Bachelor of Pharmacy (B.Pharm) studies at KIET School of Pharmacy, affiliated with AKTU, Ghaziabad, where he graduated with a strong 85.8% in 2017. Abhishek’s education reflects his deep commitment to pharmaceutical research and innovation, laying the groundwork for his promising career in academia and industry.

Professional Experience

Abhishek Jha is a Senior Research Fellow at the Indian Institute of Technology (BHU), Varanasi, where he has been working since July 2019. He is currently pursuing his doctoral degree under the supervision of Prof. Brahmeshwar Mishra, focusing on developing nanomedicine-based strategies for breast cancer therapy. His research includes creating redox-responsive, self-assembled systems for targeted drug delivery and localized breast cancer treatments using dissolving microneedles. Abhishek has extensive experience in the development of nanofibrous matrices for wound healing and tissue regeneration, and has mentored over 20 M. Tech and B. Tech students. Prior to his doctoral research, he worked as a Post-graduate Research Scholar at IIT (BHU) from January 2018 to June 2019, where he gained expertise in fabricating polymeric nanoparticles, micelles, liposomes, and hydrogels, and optimized various disease models for lung and breast cancer, diabetes, and infections in rats, applying QbD approaches for formulation optimization.

Research Interest

Abhishek Jha’s research interests lie at the intersection of pharmaceutical sciences and nanomedicine, focusing on innovative drug delivery systems for targeted cancer therapies. His work emphasizes the development of nanocarriers that enhance the selective accumulation of therapeutics in tumor sites, particularly in the treatment of breast and lung cancers. Jha is particularly skilled in designing redox-responsive self-assembled systems and microneedle technologies to facilitate localized drug delivery. Additionally, he investigates nanofibrous scaffolds with wound healing and anti-infective properties, aiming to improve patient outcomes in chronic diabetic wounds. His extensive experience in formulating various nanomedicines, including polymeric nanoparticles, liposomes, and hydrogels, showcases his commitment to advancing drug delivery approaches. Through his research, Jha aims to contribute significantly to the fields of pharmaceutics and biomedical engineering, ultimately improving therapeutic efficacy and patient care in complex disease management.

Research Skills

Abhishek Jha possesses a robust set of research skills that significantly contribute to his expertise in pharmaceutical engineering and technology. His hands-on experience with sophisticated instruments such as High-Performance Liquid Chromatography, Electron Microscopes, and Atomic Force Microscopes demonstrates his proficiency in advanced analytical techniques. Abhishek’s adeptness in interpreting various spectra for drug characterization, including Differential Scanning Calorimetry and Nuclear Magnetic Resonance spectroscopy, showcases his comprehensive understanding of pharmaceutical formulations. He has successfully developed nanomedicine-based strategies for cancer treatment, exhibiting strong problem-solving skills and innovative thinking. His involvement in mentoring over 20 M. Tech and B. Tech students highlights his leadership abilities and commitment to collaborative research. Additionally, Abhishek’s proficiency in software tools like JMP and Minitab enhances his capacity for data analysis and interpretation. Overall, his combination of technical expertise, mentoring experience, and analytical skills positions him as a valuable asset in the field of pharmaceutical research.

Award and Recognition

Abhishek Jha, a promising final-year doctoral candidate at the Indian Institute of Technology (BHU), Varanasi, has garnered notable recognition for his innovative research in pharmaceutical engineering and drug delivery systems. His work on developing nanomedicine-based strategies for breast cancer treatment has been published in prestigious journals, earning him accolades in the scientific community. Abhishek’s contributions include developing targeted therapies and biomaterials for chronic wound healing, showcasing his commitment to addressing complex medical challenges. He has actively engaged in mentoring over 20 undergraduate and graduate students, reflecting his dedication to fostering the next generation of researchers. His publications in high-impact journals, alongside collaborations with esteemed institutions, further underscore his reputation as a rising star in pharmaceutical sciences. Abhishek’s achievements have not only positioned him as a thought leader in his field but also earned him recognition within academic circles for his innovative approach to drug delivery and cancer therapy.

Conclusion

Abhishek Jha is a highly capable researcher with exceptional skills in nanomedicine and drug delivery systems. His academic excellence, technical proficiency, and extensive publication record position him as a strong contender for the Best Researcher Award. By broadening his research scope and further engaging with industry and public platforms, he could reach new heights in his career, making him a well-deserved candidate for recognition in his field.

Publication Top Notes

  • Electrospun nanofiber-based drug delivery platform: advances in diabetic foot ulcer management
    DR Madhukiran, A Jha, M Kumar, G Ajmal, GV Bonde, B Mishra
    Expert Opinion on Drug Delivery 18 (1), 25-42, 2021.
  • Targeted drug nanocrystals for pulmonary delivery: a potential strategy for lung cancer therapy
    M Kumar, A Jha, M Dr, B Mishra
    Expert Opinion on Drug Delivery 17 (10), 1459-1472, 2020.
  • Mannose receptor targeted bioadhesive chitosan nanoparticles of clofazimine for effective therapy of tuberculosis
    DM Pawde, MK Viswanadh, AK Mehata, R Sonkar, S Poddar, AS Burande, …
    Saudi Pharmaceutical Journal 28 (12), 1616-1625, 2020.
  • DNA biodots based targeted theranostic nanomedicine for the imaging and treatment of non-small cell lung cancer
    A Jha, MK Viswanadh, AS Burande, AK Mehata, S Poddar, K Yadav, …
    International Journal of Biological Macromolecules 150, 413-425, 2020.
  • Gold liposomes for brain-targeted drug delivery: Formulation and brain distribution kinetics
    R Sonkar, A Jha, MK Viswanadh, AS Burande, DM Pawde, KK Patel, …
    Materials Science and Engineering: C 120, 111652, 2021.
  • Novel redox-sensitive thiolated TPGS based nanoparticles for EGFR targeted lung cancer therapy
    MK Viswanadh, N Agrawal, S Azad, A Jha, S Poddar, SK Mahto, …
    International Journal of Pharmaceutics 602, 120652, 2021.
  • Formulation and In Vivo Efficacy Study of Cetuximab Decorated Targeted Bioadhesive Nanomedicine for Non-Small-Cell Lung Cancer Therapy
    MK Viswanadh, Vikas, A Jha, SK Reddy Adena, AK Mehata, V Priya, …
    Nanomedicine 15 (24), 2345-2367, 2020.
  • Treatment of H. pylori infection and gastric ulcer: Need for novel Pharmaceutical formulation
    A Gupta, S Shetty, S Mutalik, K Nandakumar, EM Mathew, A Jha, B Mishra, …
    Heliyon 9 (10), 2023.
  • Nanocarriers for tuberculosis therapy: design of safe and effective drug delivery strategies to overcome the therapeutic challenges
    K Sarkar, M Kumar, A Jha, K Bharti, M Das, B Mishra
    Journal of Drug Delivery Science and Technology 67, 102850, 2022.
  • Advances in lipid-based pulmonary nanomedicine for the management of inflammatory lung disorders
    M Kumar, A Jha, K Bharti, G Parmar, B Mishra
    Nanomedicine 17 (12), 913-934, 2022.
  • Myricetin encapsulated chitosan nanoformulation for management of type 2 diabetes: preparation, optimization, characterization and in vivo activity
    M Upadhyay, RV Hosur, A Jha, K Bharti, PS Mali, AK Jha, B Mishra, …
    Biomaterials Advances 153, 213542, 2023.
  • DNA-Based Nanostructured Platforms as Drug Delivery Systems
    M Kumar, A Jha, B Mishra
    Chem & Bio Engineering 1 (3), 179-198, 2024.
  • Enhanced in vitro therapeutic efficacy of triphenyltin (IV) loaded vitamin E TPGS against breast cancer therapy
    M Singh, NK Rana, MS Muthu, A Jha, TSB Baul, B Koch
    Materials Today Communications 31, 103256, 2022.
  • Biopolymer-based tumor microenvironment-responsive nanomedicine for targeted cancer therapy
    A Jha, M Kumar, K Bharti, M Manjit, B Mishra
    Nanomedicine 19 (7), 633-651, 2024.
  • Fabrication of gelatin coated polycaprolactone nanofiber scaffolds co-loaded with luliconazole and naringenin for treatment of Candida infected diabetic wounds
    M Manjit, K Kumar, M Kumar, A Jha, K Bharti, P Tiwari, R Tilak, V Singh, …
    International Journal of Biological Macromolecules 261, 129621, 2024.
  • Formulation and characterization of polyvinyl alcohol/chitosan composite nanofiber co-loaded with silver nanoparticle & luliconazole encapsulated poly lactic-co-glycolic acid …
    M Manjit, M Kumar, A Jha, K Bharti, K Kumar, P Tiwari, R Tilak, V Singh, …
    International Journal of Biological Macromolecules 258, 128978, 2024.
  • Marine biopolymers for transdermal drug delivery
    M Kumar, A Jha, B Mishra
    Marine Biomaterials: Drug Delivery and Therapeutic Applications, 157-207, 2022.
  • Marine Biopolymer-Based Anticancer Drug Delivery Systems
    A Jha, M Kumar, B Mishra
    Marine Biomaterials: Drug Delivery and Therapeutic Applications, 351-401, 2022.
  • Metronidazole Loaded Polycaprolactone-Carbopol Blends Based Biodegradable Intrapocket Dental Film for Local Treatment of Periodontitis
    N Dhedage, G Khan, G Ajmal, M Kumar, A Jha, B Mishra
    Drug Delivery Letters 11 (1), 34-43, 2021.
  • Lipid-coated nanocrystals of paclitaxel as dry powder for inhalation: Characterization, in-vitro performance, and pharmacokinetic assessment
    M Kumar, A Jha, K Bharti, M Manjit, P Kumbhar, V Dhapte-Pawar, …
    Colloids and Surfaces B: Biointerfaces 237, 113865, 2021.

Tamal Pramanick | Scientific Computing |Best Researcher Award

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Assist Prof Dr. Tamal Pramanick | Scientific Computing |Best Researcher Award

Assist Prof Dr/Tamal Pramanick, National Institute of Technology (NIT) Calicut, India.

Dr. Tamal Pramanick is an Assistant Professor in the Department of Mathematics at NIT Calicut, specializing in numerical methods for partial differential equations, particularly finite element methods. He holds a PhD from IIT Guwahati, where his research focused on the development of two-scale composite finite element methods for parabolic problems in convex and nonconvex polygonal domains. Dr. Pramanick has received several prestigious fellowships, including the NBHM Post-Doctoral Fellowship at IISc Bangalore. His research has been published in numerous SCI-indexed journals, and he has been an invited speaker at international conferences. Dr. Pramanick is actively involved in guiding postgraduate dissertations and organizing academic events such as workshops and webinars. He has also secured research grants for projects on fractional order diffusion equations and nonlinear thermistor equations. His contributions to applied mathematics and his role in fostering academic collaboration make him a distinguished scholar in his field.

Profile

Education

The educational journey began with a Secondary education from the West Bengal Board of Secondary Education in 2006, achieving a percentage of 71.38%. Following that, Higher Secondary education was completed from the West Bengal Council of Higher Secondary Education in 2008, with a percentage of 70.29%. The pursuit of higher education continued with a B.Sc. in Mathematics from the University of Kalyani, West Bengal, from 2008 to 2011, securing a percentage of 70.75%. This was followed by an M.Sc. in Mathematics & Computing from the Indian Institute of Technology (IIT) Guwahati, where the candidate achieved a CPI of 8.23 from 2011 to 2013. The academic path culminated in a Ph.D. from IIT Guwahati, awarded on February 25, 2019, with a CPI of 8.25 for the coursework, focusing on “Two-Scale Composite Finite Element Method for Parabolic Problems in Convex and Nonconvex Polygonal Domains.”

Professional Experience

Dr. Tamal Pramanick is an accomplished Assistant Professor in the Department of Mathematics at NIT Calicut, serving since March 2020. He has a rich background in applied mathematics, with expertise in finite element methods and their applications in solving complex mathematical problems. Dr. Pramanick completed his PhD from the Indian Institute of Technology Guwahati in 2019, focusing on two-scale composite finite element methods for parabolic problems in convex and nonconvex domains. He has held a prestigious post-doctoral fellowship from the National Board of Higher Mathematics (NBHM) at IISc Bangalore. His professional contributions include serving as a reviewer, PhD selection committee member, course coordinator, and departmental seminar coordinator at NIT Calicut. Dr. Pramanick has led several research projects sponsored by national agencies and organized numerous conferences, workshops, and faculty development programs. His work is published in reputed journals, and he regularly delivers invited talks at international conferences and workshops.

Research Interest

Dr. Tamal Pramanick’s research interests lie in the field of applied mathematics, with a focus on numerical methods for solving partial differential equations, particularly the Finite Element Method (FEM) and its applications. His work explores the development and analysis of two-scale composite finite element methods for complex parabolic and elliptic problems in convex and nonconvex polygonal domains. Dr. Pramanick is particularly interested in improving the accuracy and efficiency of numerical solutions for nonlinear and semilinear parabolic equations, with applications spanning diverse fields such as thermistor equations, heat transfer, and diffusion processes. His research also extends to fractional order diffusion equations and mathematical modeling of physical systems. Through his interdisciplinary approach, Dr. Pramanick aims to contribute to advancements in computational mathematics and its practical applications in engineering, physics, and other sciences, making his work highly relevant to both academic research and industrial problem-solving.

Research Skills

Dr. Tamal Pramanick is a proficient researcher specializing in applied mathematics, particularly in the finite element method for complex problems in nonconvex polygonal domains. His expertise spans numerical analysis, mathematical modeling, and the development of error estimates for nonlinear parabolic equations. Dr. Pramanick has demonstrated advanced skills in multi-scale composite finite element methods, with significant contributions to solving fractional-order diffusion equations and semilinear parabolic problems. His research includes high-level computational simulations and analytical techniques for addressing real-world mathematical challenges. He has successfully secured research funding for multiple projects, including Faculty Research Seed Grants and prestigious National Board of Higher Mathematics (NBHM) projects. Additionally, Dr. Pramanick’s experience extends to guiding postgraduate dissertations on topics like heat equations and delay differential equations, while his prolific publications in SCI-indexed journals further attest to his research caliber. His role as an invited speaker and coordinator for various academic events reflects his strong leadership and collaborative research capabilities

Award and Recognition

Dr. Tamal Pramanick, an accomplished Assistant Professor at NIT Calicut, has received multiple awards and recognition for his outstanding contributions to mathematics and computational science. He qualified the prestigious Joint Admission Test for M.Sc. (JAM) in 2011 and the Graduate Aptitude Test in Engineering (GATE) in 2013, both in Mathematics. During his academic journey at IIT Guwahati, he was a recipient of the Merit cum Means Scholarship and awarded Junior and Senior Research Fellowships (JRF and SRF) from 2013 to 2018. In 2019, Dr. Pramanick achieved the National Eligibility Test (NET) for Lectureship and was selected for the National Board of Higher Mathematics (NBHM) Postdoctoral Fellowship. His innovative research has earned him prestigious grants, including a Faculty Research Seed Grant and NBHM-funded projects, advancing his work in finite element methods and nonlinear equations. His invited talks at international conferences further highlight his scholarly impact on the global stage.

Conclusion

 Dr. Tamal Pramanick is a highly qualified candidate with a solid track record of research, teaching, and leadership. His achievements in securing grants, organizing academic programs, and contributing to mathematical research through high-impact publications position him as a strong contender for the Best Researcher Award. With minor improvements in international collaboration and interdisciplinary research, his candidacy would be even stronger.

Publication Top Notes

  • Error estimates for two-scale composite finite element approximations of parabolic equations with measure data in time for convex and nonconvex polygonal domains

Authors: T. Pramanick, R.K. Sinha

Citation: Applied Numerical Mathematics, 143, 112-132

Year: 2019

  • Two-scale composite finite element method for parabolic problems with smooth and nonsmooth initial data

Authors: T. Pramanick, R.K. Sinha

Citation: Journal of Applied Mathematics and Computing, 58, 469-501

Year: 2018

  • A hybrid high-order method for quasilinear elliptic problems of nonmonotone type

Authors: T. Gudi, G. Mallik, T. Pramanick

Citation: SIAM Journal on Numerical Analysis, 60(4), 2318-2344

Year: 2022

  • Composite Finite Element Approximation for Parabolic Problems in Nonconvex Polygonal Domains

Authors: T. Pramanick, R.K. Sinha

Citation: Computational Methods in Applied Mathematics, 20(2), 361-378

Year: 2020

  • Composite finite element approximation for nonlinear parabolic problems in nonconvex polygonal domains

Authors: T. Pramanick, R.K. Sinha

Citation: Numerical Methods for Partial Differential Equations, 34(6), 2316-2335

Year: 2018

  • Adaptation of the composite finite element framework for semilinear parabolic problems

Authors: A. Anand, T. Pramanick

Citation: Journal of Numerical Analysis and Approximation Theory, 53(1), 26-53

Year: 2024

  • Error estimates for finite element approximations of nonlinear parabolic problems in nonconvex polygonal domains

Authors: T. Pramanick, S. Mahata, R.K. Sinha

Citation: Advances in Mathematics: Scientific Journal, 9(9), 6513-6524

Year: 2020

  • Two scale composite finite element method for parabolic problems in convex and nonconvex polygonal domains

Authors: T. Pramanick

Citation: Guwahati

Year: 2019

  • Managing error estimates for semidiscrete finite element approximations of semilinear parabolic equations in a nonconvex polygon

Authors: T. Pramanick

Year: 2018

  • Adaptation of a variant of finite element method for the evolution equation in nonconvex domain

Authors: A. Anand, T. Pramanick

Event: 2025 Joint Mathematics Meetings (JMM 2025)

  • Composite finite element method implementation for nonlinear parabolic problems in nonconvex domains

Authors: T. Pramanick, R.K. Sinha

Year: Not specified in your list

  • Fully discrete finite element approximations of semilinear parabolic equations in a nonconvex polygon

Authors: T. Pramanick, R.K. Sinha

Year: Not specified in your list

Dr. Cong Guo | Computer Science | Best Researcher Award

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Dr. Cong Guo | Computer Science | Best Researcher Award

Nurse Practitioner at UNC Blue Ridge, United States.

Cong Guo, who earned his master’s degree in 2024 from the School of Computer and Information Engineering at Henan University, is currently pursuing a PhD in Computer Science and Technology at Zhejiang Normal University. His research specializes in machine learning and pattern recognition, fields that are increasingly relevant in today’s data-driven landscape. Guo has made significant contributions to the field, as evidenced by his publications, including a novel feature selection framework for incomplete data and a method for iterative missing value imputation based on feature importance. These works demonstrate his innovative approach to addressing common challenges in data science. While his academic background and publication record are impressive, expanding his publication scope and enhancing networking opportunities could further elevate his research impact. With his solid foundation and commitment to advancing knowledge in machine learning, Cong Guo is a promising candidate for recognition as a leading researcher.

Profile:

Education

Cong Guo received his master’s degree in 2024 from the School of Computer and Information Engineering at Henan University, where he laid a strong foundation in computer science principles and research methodologies. His academic journey has been characterized by a focus on machine learning and pattern recognition, reflecting his passion for harnessing data to solve complex problems. Currently, Cong is pursuing his Ph.D. at the School of Computer Science and Technology at Zhejiang Normal University, further enhancing his expertise in these cutting-edge fields. His educational experiences have equipped him with essential skills in data analysis, algorithm development, and statistical modeling, which are critical for his research. Throughout his studies, Cong has demonstrated a commitment to academic excellence and innovation, making significant strides in understanding and improving feature selection and data imputation techniques. His educational background positions him as a promising researcher in the rapidly evolving landscape of computer science.

Professional Experiences 

Cong Guo has demonstrated significant commitment to his academic and professional development in the field of computer science. He obtained his master’s degree from the School of Computer and Information Engineering at Henan University in 2024, where he developed a solid foundation in computer science principles and applications. Currently, he is pursuing his PhD at the School of Computer Science and Technology at Zhejiang Normal University, focusing on machine learning and pattern recognition. During his studies, Guo has engaged in research projects that involve innovative approaches to data analysis, particularly in handling incomplete datasets and missing value imputation. His publications in reputable journals reflect his dedication to advancing knowledge in his field. Additionally, his collaborative work with fellow researchers highlights his ability to contribute effectively to team-oriented projects, enhancing his experience and understanding of complex computational problems. This combination of academic rigor and research experience positions Guo as a promising researcher in computer science.

Research Interests

Cong Guo’s research interests lie primarily in the fields of machine learning and pattern recognition, where he aims to develop innovative algorithms and frameworks to address real-world challenges in data analysis. His work focuses on enhancing feature selection and imputation techniques, particularly in the context of incomplete datasets, which are common in many applications. By investigating novel approaches to handle missing data, Cong seeks to improve the accuracy and efficiency of machine learning models. Additionally, he is interested in exploring the broader implications of machine learning across various domains, such as healthcare, finance, and environmental science. Cong’s passion for advancing knowledge in these areas drives his commitment to research that not only contributes to theoretical advancements but also has practical applications that can benefit society. Through his ongoing doctoral studies and collaborative projects, he aims to further explore the intersections of machine learning and real-world problem-solving.

Research Skills 

Cong Guo possesses a robust set of research skills that enhance his capabilities in machine learning and pattern recognition. His proficiency in feature selection and data imputation techniques demonstrates a strong analytical mindset, enabling him to address complex challenges in handling incomplete datasets effectively. Guo is adept at employing various machine learning algorithms and tools, which allows him to develop innovative frameworks that optimize data analysis processes. His experience in collaborative research, evidenced by his co-authored publications, showcases his ability to work effectively in teams, share ideas, and contribute to collective goals. Additionally, Guo’s familiarity with statistical methods and computational techniques underpins his research, ensuring that his findings are both rigorous and applicable. His commitment to continuous learning and adaptation to emerging trends in technology further solidifies his expertise, making him a valuable asset in advancing the field of computer science and information engineering.

Award and Recognition 

Cong Guo has distinguished himself in the field of machine learning and pattern recognition, earning recognition for his innovative research contributions. He completed his master’s degree in 2024 at the School of Computer and Information Engineering, Henan University, where he developed a strong foundation in computational methodologies. Currently pursuing his PhD at Zhejiang Normal University, Cong has co-authored impactful publications, including “A novel feature selection framework for incomplete data” and “Iterative missing value imputation based on feature importance,” which have been well-received in reputable journals. His research not only addresses critical challenges in data science but also demonstrates his potential to influence future advancements in the field. Cong’s commitment to academic excellence and his collaborative spirit have garnered him respect among peers and mentors alike, positioning him as a promising candidate for the Best Researcher Award. His ongoing efforts are indicative of a bright future in research and innovation.

Conclusion

Cong Guo exhibits a promising trajectory in research, with a strong academic foundation and relevant publications in machine learning and pattern recognition. His commitment to advancing the field is evident in his current work. By broadening his publication efforts and enhancing his professional network, he can significantly improve his contributions to research. Given his strengths and potential for growth, Cong Guo is a suitable candidate for the Best Researcher Award.

Publication Top Notes
  1. A novel feature selection framework for incomplete data
  2. Iterative missing value imputation based on feature importance
  3. KNCFS: Feature selection for high-dimensional datasets based on improved random multi-subspace learning